Particle surface modification using isothermal dry coating to deliver biologics through the buccal route

Particle surface modification using isothermal dry coating to deliver biologics through the buccal route | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Particle surface modification using isothermal dry coating to deliver biologics through the buccal route Anthony Rajabi, Mohamad Anas Al Tahan, Affiong Iyire, David Wyatt, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8957044/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Buccal delivery offers a non-invasive route for biologics but is limited by poor permeation and susceptibility to processing-induced structural disruption. This challenge is compounded for the delivery of biologics particularly where co-localisation of excipients is required. This study evaluated the application of a solvent-free isothermal dry particle coating (iDPC) technology for buccal permeation of ovalbumin (OVA) by co-localisation of OVA with functional excipients on a polymer carrier. Polyvinyl alcohol (PVA) was used as the host carrier and pre-coated with gelatine to modify surface properties and improve retention, before coating with OVA alongside L-lysine and α-tocopherol. iDPC coated particles were characterised by confocal microscopy, confocal Raman mapping, and inverse gas chromatography (IGC). Raman mapping confirmed surface co-localisation of OVA, L-lysine and α-tocopherol on PVA–gelatine, and IGC indicated that gelatine reduced PVA surface area (1.7471 to 0.7344 m²/g) and altered surface energetics towards a more uniform profile. Buccal permeation was assessed across TR146 cell layers over 120 minutes (OVA 1 mg/mL). To facilitate comparison and mitigate ceiling effects, permeation was expressed relative to the OVA control (F1 = 100%). Under this normalisation, the gelatine-containing iDPC formulation (F3) demonstrated sustained enhancement across all time points, peaking at approximately 151% of control at 30 minutes and remaining elevated at 120 minutes (approximately 114% of control). In contrast, the physically mixed formulation (F4) consistently reduced permeation relative to control, reaching approximately 65% of control at 120 minutes, while the PVA iDPC formulation (F2) remained broadly comparable to control but decreased to approximately 90% of control at 120 minutes. TEER remained stable post-study, supporting model integrity. Overall, these findings confirm iDPC combined with gelatine surface modification is an effective strategy to enhance buccal delivery of protein therapeutics through altered particle surface properties and excipient co-localisation. Biological sciences/Biotechnology Physical sciences/Chemistry Physical sciences/Materials science buccal delivery biologic ovalbumin gelatine coating TR146 permeation large molecule Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Biologics are crucial for the treatment and management of a wide range of diseases, including cancer, autoimmune disorders, and genetic conditions [ 1 ]. However, their delivery is often limited by the reliance on the parenteral route that require trained personnel, cold-chain logistics, and may lead to poor patient compliance [ 2 ]. Due to these limitations there is a need for alternative delivery strategies that are non-invasive, patient friendly, and accessible across varied healthcare settings [ 3 ]. Buccal delivery targets the inner cheek and oral mucosa, and presents several advantages including ease of administration [ 4 ]. The buccal route bypasses the first-pass effect of hepatic metabolism, avoids degradation by gastric enzymes, facilitates drug absorption through its moderately permeable epithelium, and offers a patient-friendly administration without needles [ 2 , 5 ]. Despite these advantages, buccal delivery of biologics is underutilised due to challenges such as susceptibility to degradation during manufacturing and storage, necessitating cold-chain logistics to maintain stability. Upon administration, biologics may further degrade due to salivary enzymes, have limited residence time due to salivary flow, and exhibit poor permeation without appropriate excipients or delivery systems [ 2 , 5 , 6 ]. Addressing these challenges requires innovative formulation strategies to improve stability, retention, and absorption of biologics. Ovalbumin (OVA) is widely utilised as a model biologic in drug delivery research due to its well-characterised structure and cost-effectiveness [ 7 ]. As a glycoprotein derived from chicken egg whites, OVA has been utilised in various studies to evaluate novel delivery systems. For example, Osswald and Kang-Mieler (2015) used OVA to investigate the release profiles of a protein within a microsphere delivery system [ 8 ]. In addition, Di Francesco et al. (2024) utilised OVA as a model biologic to investigate minimally invasive delivery through the nasal route [ 9 ]. In this study, OVA served as a convenient, well-characterised biologic to assess the efficacy of a novel buccal formulation. The primary objective of this study was to evaluate the feasibility of the buccal route for biologic administration, specifically focussing on optimising the co-localisation of the model biologic compound with excipients designed to enhance permeation and stability. To achieve this, a carrier polymer was selected and coated with gelatine to modify surface properties, followed by coating with OVA, L-lysine, and α-tocopherol, to produce the formulation depicted in Fig. 1 . A critical consideration was maintaining the stability and structural integrity of OVA during the formulation process. To achieve this, isothermal dry particle coating (iDPC), a technology that allows the controlled deposition of fine particles onto larger particles without the use of heat, solvents, or physical mixing was used. The iDPC mechanism utilises a high-speed rotating vessel combined with a fluidising nitrogen gas blade, creating a unique thin-layer fluidisation process that operates in a dry, ambient state [ 10 ]. This coating technique ensured the stability of the formulation, preserving the structural properties of OVA and enhancing the overall efficacy of the buccal delivery system. Results and discussion Formulation development The formulation strategy was to generate a particulate “host–guest” system using isothermal dry particle coating (iDPC), enabling co-localisation of the model biologic (OVA) with excipients intended to support stability and buccal permeation while avoiding heat and solvents that can compromise protein integrity. Specifically, the approach was to use polyvinyl acetate (PVA) as a carrier (“host”) and apply a gelatine pre-coat to modify the carrier surface and promote adhesion/retention, before coating OVA with additional functional excipients, L-lysine and α-tocopherol. PVA was selected as the carrier polymer due to its film-forming capability, mechanical robustness and biocompatibility, and because its predominantly neutral character supports mucoadhesion largely via hydrogen bonding and physical entanglement rather than strongly pH-dependent electrostatics [ 11 , 12 ]. Gelatine was selected as the primary surface-modifying coating component because of its well-characterised adhesive and film-forming properties, with the aim of enhancing carrier adhesiveness and promoting co-localisation of OVA and excipients at the mucosal interface to support transport across buccal cell layers [ 13 , 14 ]. In parallel, L-lysine was incorporated on the basis that it is positively charged at physiological pH and may promote electrostatic association/ion-pairing with negatively charged OVA, potentially increasing effective permeation while also contributing to protein stability [ 15 ]. α-tocopherol was selected as an antioxidant stabiliser and as a candidate membrane-modulating excipient reported to influence barrier properties and macromolecular transport in mucosal models [ 16 ]. In accordance with iDPC requirements, the “guest” component should be at least two to three times smaller than the “host” component to enable efficient deposition [ 10 ]. PVA was therefore carried forward as the host material; however, initial laser diffraction measurements indicated that the volume mean diameter (VMD) of PVA was 163.33 µm while gelatine was 97.44 µm. As a consequence, gelatine size reduction was required to satisfy the host–guest criterion. The target was to reduce gelatine to a VMD ≤ 32 µm (approximately three-fold smaller than PVA). Several particle-size reduction approaches were evaluated (homogenisation, ultrasonication, and cryogenic milling), but none achieved the required VMD threshold. A practical size-classification method was then developed in which gelatine was placed on a 32 µm sieve and agitated using a vortex mixer rather than a conventional sieve shaker. This vortex-assisted approach reduced powder bridging and cohesive clumping, increasing the fraction of particles passing the sieve (≤ 32 µm), as summarised in Table 1 [ 35 ]. In contrast to the standard sieve shaker (≈ 5% yield below 32 µm), the vortex-mixer method produced ≈ 40% yield and exceeded the original size target, giving a gelatine VMD of 12.74 µm. This size-reduced gelatine was therefore suitable for subsequent iDPC coating onto PVA under the host–guest size constraint. Table 1 Particle size analysis of unprocessed and vortex-mixer method gelatine powder determined by laser diffractometry. Each sample, approximately 100 mg, was dispersed at 3 bar of pressure and measurements were performed in triplicate (mean ± SD, n = 3). Properties (µm) Unprocessed gelatine Vortex-mixer method gelatine D10 42.12 ± 1.86 5.48 ± 0.74 D50 96.06 ± 2.78 13.36 ± 1.99 D90 153.21 ± 3.77 18.94 ± 2.62 VMD 97.44 ± 2.60 12.74 ± 1.96 Confocal laser scanning microscopy Confocal laser scanning microscopy (CLSM) was employed to evaluate whether the inclusion of gelatine influenced the adherence of fluorescently labelled ovalbumin (FITC-OVA) to PVA particles. Both PVA and PVA-gelatine particles were coated with 1% FITC-OVA under identical iDPC processing conditions (20-minute run time, 25 L/min nitrogen gas flow, 1800 rpm). CLSM images are presented in Fig. 2 . Figures 2 A and 2 B show FITC-OVA coated PVA particles, and Figs. 2 C and Fig. 2 D are FITC-OVA coated PVA-gelatine particles. Visual analysis indicated that the fluorescence intensity observed was very similar between the two samples, indicating no significant enhancement in protein adherence as a result of the inclusion of gelatine. Several factors, such as hydrophilicity and surface energy, may account for the absence of significant difference in fluorescence intensity. Elango et al. (2023) reported that the protein adsorption capability of PVA hydrogels is dependent on surface energy, hydrophilicity, and electrostatic interactions, and modifications may not significantly impact protein adherence. However, it was reported that the incorporation of silver nanoparticles into PVA hydrogels enhanced protein adsorption due to increases surface roughness and electrostatic interactions [ 17 ]. It is important to acknowledge the limitations associated with CLSM in this context. The increased size of PVA-gelatine particles posed challenges during imaging, as some particles exceeded the optimal field of view for the microscope. This limitation may have hindered the capture of the complete particle images, potentially affecting the assessment of fluorescence distribution and coverage. Raman confocal microscopy Confocal Raman microscopy was employed to investigate the spatial distribution and co-localisation of the model biologic compound, ovalbumin, and the excipients (gelatine, L-lysine, and α-tocopherol) on PVA-gelatine particles. The PVA-gelatine particles were coated using the iDPC with a formulation consisting of 2% OVA, 1% α-tocopherol, and 1% L-lysine, under consistent processing parameters (20-minute run time, 25 L/min, 1800 rpm). The preliminary step involved obtaining individual Raman spectra for each component within the formulation to establish their unique spectral fingerprints. The reference spectra are presented in Fig. 3 and were used as the basis for subsequent spectral mapping and component identification with the particulate system. Following the completion of the reference spectra, an initial optical examination of the coated particles was conducted using a 10x objective lens (Fig. 4 A). However, at this magnification the laser’s penetration depth reached the particle core and only detected the Raman spectrum of PVA. As a result, a 100x objective lens was utilised (Fig. 4 B), and a ‘point and shoot’ mapping approach was implemented to enable the measurement of Raman spectrum at the particle surface. This method involved analysing an approximate 10 µm x 10 µm grid on the particle surface, with Raman spectra collected at 2 µm intervals, resulting in a mapping of the surface composition. Map data were processed using classic least squares (CLS) regression analysis (a supervised multivariate analysis approach), with each spectrum within the map expressed as a mathematical superposition of the reference spectra. Both the reference and map spectra were baseline corrected to remove the impact of fluorescence. This approach enabled a clear identification of spectral contributions from the components within the mapped region shown in Fig. 4 B. The resulting map (Fig. 5 ) demonstrates the presence of OVA, α-tocopherol, and L-lysine on the surface of the PVA-gelatine particles, confirming successful co-localisation. As shown in Fig. 5 , the spatial distribution of each component is distinct yet complementary, when superimposed, the individual maps collectively occupy the scanned area (Fig. 4 B). These results suggest that the iDPC process was effective in depositing multiple components uniformly onto the carrier particles. The iDPC process promotes particle deagglomeration, which enhances coating efficiency by overcoming cohesive forces such as van der Waals or electrostatic forces. The deagglomeration is promoted by the relative centrifugal force generated within the drum as the speed of the drum increases. As the drum speed increases, particles are propelled toward the drum wall, reducing particle agglomeration. In addition, the nitrogen gas blade likely aids the fluidisation of the particles attached to the drum wall, increasing their mobility and promoting particle interaction. As a result, the combined effects of deagglomeration and enhanced particle interaction enable a coating of the smaller particles onto the larger particles, allowing for efficient co-localisation of the smaller components onto the carrier polymer, as shown in Fig. 5 [ 18 , 19 ]. Inverse gas chromatography Inverse gas chromatography (IGC) was employed to characterise the surface area and surface energy profiles of PVA particles and PVA-gelatine particles. Understanding the surface energy profiles of these particles can help evaluate whether the inclusion of gelatine impacted their adhesivity, stability, and overall physicochemical interactions, thereby affecting the overall coating efficiency of the biologic and excipients [ 20 ]. IGC is an analytical technique widely used to characterise the physicochemical properties of solid materials, specifically powders and particulates [ 21 ]. Unlike traditional gas chromatography, where the stationary phase is a liquid or solid and the mobile phase is a gas, IGC inverts the role of stationary and mobile phases by using the solid sample as the stationary phase and introducing known gas-phase probe molecules as the mobile phase [ 22 , 23 ]. The interactions between these gas-phase probe molecules and the sample surface are analysed to determine the surface properties including surface energy, surface area, and acid-base characteristics [ 21 , 24 ]. IGC data are presented in terms of surface energy components such as, the total surface energy (γt), the dispersive surface energy component (γd), and the acid-base surface energy component (γab). The total surface energy (γt) represents the overall energy associated with the surface of the sample including all intermolecular interactions. The dispersive component (γd) represents non-polar interactions, such as van der Waals forces and the acid-base component (γab) represents polar interactions, including hydrogen bonding and electron-donor acceptor interactions [ 24 , 25 ]. The surface area analysis conducted by the IGC revealed that the PVA particles had a surface area of 1.7471 m 2 /g, whereas the PVA-gelatine particles had a significantly lower surface area of 0.7344 m 2 /g, seen in Table 2 . This 2.4-fold reduction in surface area may be attributed to the pores and rough surface morphology being altered by the inclusion of gelatine. Increased particle surface roughness typically enhances coating adhesion by providing additional contact points and interlocking sites, suggesting that the potential smooth surface associated with PVA-gelatine particles may reduce the likelihood of the other components (OVA, L-lysine, α-tocopherol) adhering to the PVA particles [ 26 ]. Table 2 Surface area of untreated PVA and PVA-gelatine calculated by IGC. Formulation Surface area (m 2 /g) PVA 1.7471 PVA coated with gelatine 0.7344 Subsequent surface energy analysis provided further insight into the characteristics of these particles. Untreated PVA particles demonstrated dispersive surface energy values (γd) that ranged from approximately 55.36 mJ/m 2 at a low surface coverage to -2.61 mJ/m 2 at high surface coverage. The acid-base surface energy distributions ranged (γab) from 13.49 mJ/m 2 to -0.95 mJ/m 2 , and the total surface energy (γt) ranged from around 68.85 mJ/m 2 to -3.50 mJ/m 2 , as presented in Table 3 . The minimum and maximum surface energy values (mJ/m 2 ) determined by IGC reflect the range of energetic heterogeneity present on the particle surface. The minimum energy indicates the least interactive sites and the maximum energy corresponds to the most interactive sites available for adsorption [ 27 ]. These values can further the understanding and prediction of interfacial phenomena such as adhesion and compatibility with other components as they relate to the thermodynamic interactions between probe molecules and the sample [ 27 , 28 ]. The negative values observed in Table 3 and Table 4 are likely mathematical artefacts of extrapolation rather than actual negative surface energies. These anomalies often arise due to applying linear extrapolation method, the Dorris-Gray approach in this case, to retention data for nonpolar probes. This issue is particularly common with materials that have highly heterogenous surfaces, as they may not align with the assumptions underlying the model [ 27 ]. In IGC, the area increment percentage is given at each surface energy and it represents the fraction of the total external surface area that exhibits that specific energy [ 29 ]. The γd area increments increased from 0.0011% to approximately 0.247%, while the γab area increments showed a similar trend of 0.0013% to 0.248% and the γt area increments ranged from 0.0012% to 0.247%. The small area increment percentages indicate that only a small fraction of the particle’s surface area corresponds to the specific energy level, indicating a highly heterogenous surface [ 29 , 30 ]. Table 3 Minimum and maximum values of surface energy components for PVA particles, dispersive energy (γd), acid-base surface energy (γab), and total surface energy (γt) as determined by IGC Surface energy (PVA) Minimum (mJ/m 2 ) Maximum (mJ/m 2 ) γd -2.61 55.36 γab -0.95 13.49 γt -3.50 68.85 The PVA-gelatine particles displayed significantly different surface energetics, as presented in Table 4 . The dispersive surface energy (γd) ranged from 52.94 mJ/m 2 at low surface coverage and 2.18 mJ/m 2 . The acid-base (γab) surface energy distributions ranged from 7.55 mJ/m 2 to -8.86 mJ/m 2 . The total surface energy (γt) ranged from 60.48 mJ/m 2 to -6.67 mJ/m 2 . The area increments for γd, γab, and γt had very similar area increments of 0.0004% to 0.40%. The area increment data for the PVA-gelatine particles indicate a heterogenous surface, similar to the PVA particles [ 30 ]. Table 4 Minimum and maximum values of surface energy components for PVA-gelatine particles, dispersive energy (γd), acid-base surface energy (γab), and total surface energy (γt) as determined by IGC Surface energy (PVA-gelatine) Minimum (mJ/m 2 ) Maximum (mJ/m 2 ) γd 2.18 52.94 γab -8.86 7.55 γt -6.67 60.48 The surface energy characteristics of PVA and PVA-gelatine particles may significantly influence their efficacy as the ‘host’ in the particulate system. IGC analysis revealed that PVA particles exhibited a higher total surface energy (68.85 mJ/m 2 ), indicating that the PVA particles have a greater propensity for intermolecular interactions [ 31 ]. In addition to total surface energy, PVA particles displayed higher dispersive and acid-base surface energy (55.36 mJ/m 2 and 13.49 mJ/m 2 , respectively), compared to PVA-gelatine particles (52.94 mJ/m 2 and 7.55 mJ/m 2 , respectively). This indicates that the PVA particles will have stronger capacity for non-polar and polar interactions [ 27 ]. The higher dispersive component exhibited in the PVA particles indicates stronger van der Waals forces, which may facilitate adhesion with hydrophobic excipients such as α-tocopherol [ 32 , 33 ]. Additionally, the higher acid-base component may increase polar interactions with the model biologic OVA and L-lysine [ 27 , 34 , 35 ]. These interactions are likely to improve initial drug and excipient adhesion to the PVA particles; however, they may also promote aggregation and reduced flowability, potentially compromising the manufacturing process [ 36 , 37 ]. Figure 6 shows the surface energy distribution of PVA, this plot illustrates the relationship between surface energy and area increment for the total surface energy, dispersive, and acid-base components. The broad total surface energy indicates a highly heterogenous and interactive surface. This heterogeneity indicates the presence of high energy sites that can form strong van der Waals and polar interactions [ 38 , 39 ]. The inclusion of gelatine likely induces morphological changes in the PVA particles, which leads to a smoother surface and reduced surface area likely due to pore filling (from 1.7471 m 2 /g to 0.7344 m 2 /g). These morphological changes may contribute to reduced dispersive and acid-base surface energy, resulting in a lower total surface energy. However, these reductions in surface energy can be advantageous for formulation stability, as they reduce interparticle cohesive forces, improve powder flow, and reduce the likelihood of moisture-induced clumping [ 40 , 41 ]. Figure 7 shows the surface energy distribution of PVA-gelatine particles. In contrast to the broader distributions observed in PVA particles, the total surface energy, dispersive, and acid-base distributions appear more linear. This linearity is likely due to the reduced surface heterogeneity of the PVA-gelatine particles, indicating a more energetically uniform surface with reduced variation in interaction potential across the particle adsorption sites [ 42 , 43 ]. In summary, the PVA particles provide stronger interaction potentials due to higher surface energy components, the PVA-gelatine particles likely provide improved flowability, reduced aggregation, and enhanced formulation stability. TR146 permeability studies To determine the impact of the inclusion of gelatine and the inclusion of L-lysine and α-tocopherol on the permeation of OVA through the buccal mucosa, the commonly used in vitro model, TR146 cell line, was utilised. TR146 is an immortalised epithelial cell line that forms stratified, non-keratinised layers that closely mimic the morphological and functional characteristics of buccal tissue [ 44 ]. Four formulations were prepared, and were identified F1-F4, as shown in Table 5 . Formulation F1, containing OVA alone, served as the control (F1) to establish baseline buccal permeation and evaluate the potential for enhancement. To determine the impact of the inclusion of gelatine, two PVA-based formulations (F2 and F3) were prepared with identical iDPC process parameters (1800 rpm, 20 minutes processing time, 25 L/min), with consistent concentrations of biologic and excipient. Formulation F2 was prepared using PVA alone, and F3 utilised PVA coated with gelatine. To investigate whether the iDPC method itself influenced the permeation efficacy, formulation F4 was prepared with the identical composition to F2, but the formulation was physically mixed using a spatula, thereby removing the iDPC step and allowing for a direct comparison. Table 5 Formulation key – the four formulations were tested for TR146 permeation studies Formulation Identifier Composition F1 Ovalbumin (Control) F2 iDPC - PVA, 2% OVA, 1% L-lysine, 1% α-tocopherol F3 iDPC – PVA coated with gelatine, 2% OVA, 1% L-lysine, 1% α-tocopherol F4 Physical mix – PVA, 2% OVA, 1% L-lysine, 1% α-tocopherol TR146 cells were grown on transwell inserts for 28–29 days prior to their use in permeability studies. The formation and integrity of the stratified layers was monitored and measured using transepithelial electrical resistance (TEER), which confirmed the formation of suitable stratified layers between days 28 and 29, these findings are consistent with those reported by Iyire et al. (2016), further validating the model’s suitability for permeability assessment [ 45 ]. All formulations were prepared to ensure a concentration of OVA 1 mg/mL remained consistent for accurate comparative analysis. Samples were collected at preset time points (5 minutes, 15 minutes, 30 minutes, 60 minutes, and 120 minutes) and quantified by HPLC analysis. TEER measurements post-permeation study indicated no significant disruptions to cellular integrity, confirming the reliability of the permeation results. The cumulative permeation profiles of OVA differed significantly between formulations (data not shown). Over 120 minutes, the control (F1) reached 86.59 ± 3.54% cumulative permeation, F2 reached 77.58 ± 3.42%, F3 reached 99.03 ± 2.42%, and F4 reached 56.43 ± 3.91%. Although OVA is a large, hydrophilic protein (~ 45 kDa), the cumulative permeation observed for the control over 120 minutes exceeded what might typically be expected for a macromolecule of this size [ 46 ]. However, buccal transport of high molecular weight compounds has been reported (e.g., dextrans in the 70–150 kDa range) [ 47 ] [ 48 ]. However, the control (F1) serves primarily as an internal benchmark for comparative assessment of formulation-dependent changes in permeation. At 120 minutes, formulation F3 produced a significantly greater cumulative permeation than the control (P = 0.0157), whereas F2 was not significantly different from the control (P = 0.1015). Direct comparison of F2 and F3 confirmed a significant increase associated with gelatine inclusion (P = 0.0002). To facilitate comparison of enhancement magnitude and mitigate ceiling effects associated with percentage scaling, permeation was expressed relative to the control at each time point (F1 = 100%; Fig. 8 ). Under this normalisation, the gelatine-containing iDPC formulation (F3) demonstrated sustained enhancement relative to control across all time points, peaking at approximately 151% of control at 30 min and remaining elevated at 120 min (approximately 114% of control). In contrast, the physically mixed formulation (F4) consistently showed reduced permeation relative to control, reaching approximately 65% of control at 120 min. The PVA iDPC formulation (F2) remained broadly comparable to the control, with modest enhancement at intermediate time points but reduced relative permeation at 120 min (approximately 90% of control). Collectively, these results indicate that the inclusion of gelatine within the iDPC particulate system produced the greatest enhancement in OVA permeation relative to baseline. The enhancement observed with F3 is consistent with gelatine-driven changes in particle surface properties and excipient co-localisation. Gelatine may form a film-like coating on the PVA surface, potentially increasing mucoadhesive interactions and residence time, thereby supporting increased transport across the TR146 layers [ 49 ]. In addition, IGC analysis revealed that the inclusion of gelatine altered the surface energetics, including a reduced total surface energy and a more uniform energy distribution (Tables 3 and 4 ). The reduced surface energy reduces interparticle cohesive forces, which may improve the flowability and dispersion of the particles [ 50 ]. Enhanced dispersion could contribute to a more homogeneous presentation of OVA at the TR146 interface, which is consistent with the higher permeation observed. However, confocal microscopy analysis (Fig. 2 ) indicated no notable increase in OVA deposition between formulations F2 and F3, suggesting that the increased permeation associated with F3 may be due to an improved interaction with the TR146 cell layers, rather than differences in particle surface deposition or coating efficiency. L-lysine may contribute to the permeation enhancement through ion-pairing mechanisms. At physiological pH, L-lysine carries a positive charge due to its amino groups, while OVA carries an overall negative charge [ 51 , 52 ]. This charge disparity facilitates electrostatic interaction, enabling the formation of ion-pairs, which may neutralise the net charge of the particulate complex, and therefore increase the lipophilicity and facilitate permeation across the cell layers [ 53 , 54 ]. Raman mapping demonstrated co-localisation of OVA and L-lysine on the particle surface (Fig. 5 ), which may promote ion-pairing by increasing proximity between the ion and counter-ion [ 55 ]. α-Tocopherol may further contribute by modulating lipid domains and increasing membrane fluidity; for example, α-tocopherol has been reported to improve the permeability of radiolabelled hydrocortisone in Franz diffusion cells [ 56 ]. A notable observation from the permeability studies was the reduced performance of the physically mixed formulations (F4) relative to the iDPC-prepared formulation. F4 produced significantly lower permeation than the control (P < 0.0001) and both iDPC formulations (P = 0.002), underscoring the importance of iDPC processing in depositing OVA and excipients onto the carrier particle surface. The iDPC utilises a high-speed rotating vessel in conjunction with a fluidising nitrogen gas blade to promote the deposition of fine particles onto larger particles, which is likely to better preserve the structural and functional integrity of the biologic during formulation manufacture [ 10 ]. Conclusion The formulation development involved optimisation of particle size distributions for the polymers, model biologic, and excipients to meet the iDPC processing criteria. IGC analysis revealed that the gelatine coating impacted the surface energetics of the PVA particles by reducing surface heterogeneity and total surface energy. However, confocal laser scanning microscopy indicated no significant increase in ovalbumin deposition onto untreated PVA and PVA-gelatine particles, suggesting that the addition of gelatine impacted particle morphology rather than OVA adsorption directly. Raman confocal microscopy analysis demonstrated evidence of effective co-localisation between OVA, L-lysine, and α-tocopherol on the PVA-gelatine particle surface. Permeability studies using the TR146 buccal cell line demonstrated significant differences among the four formulations tested. When expressed relative to control (F1 = 100%; Fig. 8 ), formulation F3 (PVA-gelatine particles) demonstrated sustained enhancement across all time points, remaining elevated at 120 minutes. This increase in permeation is consistent with gelatine-driven changes in particle surface properties and excipient co-localisation; improved particle dispersion and ion-pair formation between OVA and L-lysine likely contributed. Another key finding from the permeability studies was the significant reduction in permeation observed with the physically mixed formulation (F4) compared to formulations prepared via iDPC, indicating the importance of the coating method. The findings presented in this paper establish the role of iDPC and the use of gelatine as a promising method for enhancing buccal permeation of biologics using suitable polymers and excipients. Materials and methods Materials The TR146 cell line was obtained from Public Health England (Salisbury, UK). Ovalbumin (≥ 98% purity), microcrystalline polyvinyl alcohol (PVA) (Mw 89,000–98,000 Da, 99+% hydrolysed), L-lysine (≥ 98% purity), gelatine (Type A, 240 Bloom, porcine skin), α-tocopherol (≥ 96% purity) and trifluoracetic acid (TFA; HPLC grade) were purchased from Sigma-Aldrich (Merck, Gillingham, UK). Hank’s balanced salt solution (HBSS), foetal bovine serum (FBS), Ham’s F-12 nutrient mix and trypsin-EDTA were obtained from Gibco® (Thermo Fisher Scientific, Paisley, UK). Gentamicin and penicillin/streptomycin were obtained from BioSera (Sussex, UK). Acetonitrile (HPLC grade), absolute ethanol, Corning Costar® 12mm-diameter insert; 12-well 0.4 µm polycarbonate membrane tissue culture treated polystyrene plates, and Corning Costar® 24-well clear TC-treated well plates were purchased Fisher Scientific (Loughborough, UK). All water used was Ultrapure (Type 1) Direct-Q 3 UV. Methods Isothermal dry particle coating A benchtop isothermal dry particle coater (iDPC) was used to prepare powder blend formulations that consisted of ovalbumin, polyvinyl alcohol (PVA), L-lysine, gelatine, and α-tocopherol. The iDPC consists of a rotating drum connected to a stationary gas blade. The components were added to the dry particle coating drum, adhering to formulation parameters associated with the iDPC, such as, speed, processing time, and gas pressure [ 10 ]. At the end of the process, the powder was removed from the coating drum by tipping the drum and brushing the contents into an empty container. Planetary ball mill Milled formulations comprising of PVA, and gelatine (each individually) were prepared using a Fritsch Pulverisette 7 planetary ball mill (Idar-Oberstein, Germany). A ball to powder ratio (BPR) of 8:1 was used for all samples with varying milling speeds and times. Powders were accurately weighed according to the BPR. The samples were transferred into agate vials (45 cm 3 volume) along with 8 agate balls (10 mm diameter). The vials were then sealed with a plastic ring to prevent atmospheric contamination. High performance liquid chromatography (HPLC) assay The Agilent 1220 Infinity II LC system with UV/fluorescent detector was used, employing an Eclipse Plus column (C18 3.5 µm 4.6 x 150 mm). Two mobile phases were used: A, Acetonitrile: Water (5:95) + 0.1% (v/v) TFA; B, Acetonitrile: Water (95:5) + 0.1% (v/v) TFA. During the first 13 minutes the gradient was 85:15 (A:B) to 0:100 (A:B). At 13 minutes the gradient was returned to the initial gradient of 85:15 (A:B) for the final 2 minutes, to prepare for the next sample. The UV detection was set to 280nm, the flow rate 1 mL/min, and an injection volume of 100 µL. Using this protocol, ovalbumin eluted at approximately 8 minutes. Particle size analysis Laser diffraction was employed to measure particle size using a Sympatec HELOS/BR particle size analyser equipped with a RODOS dry dispersing system with VIBRI/I feeder (Clausthal-Zellerfield, Germany). For each run, nearly 500 mg of powder was weighed and placed on to the VIBRI/L feeder tray. A pressure of 3 bar was applied to disperse the powder using a RODOS disperser and sample measurements were undertaken using a 0-175 µm lens. All powders were measured in triplicate (n = 3), and the software calculate the 10% (D10), median (D50), 90% (D90) particle sizes and the volume mean diameter (VMD). Confocal Raman spectroscopy Micro Raman spectroscopy was performed using a HORIBA LabRAM HR Raman microscope. Spectra were collected using a 785 nm laser (at ~ 30 mW power), a 100x objective and a 200 µm confocal pinhole. To simultaneously scan a range of Raman shifts, a 300 lines mm − 1 rotatable diffraction grating along a path length of 800 mm was employed. Spectra were acquired using a Synapse CCD detector (1024 pixels) thermoelectrically cooled to − 60°C. Before spectra collection, the instrument was calibrated using the zero-order line and a standard Si(100) reference band at 520.7 cm − 1 . The spectral resolution is better than 1.7 cm − 1 in this configuration. Confocal laser scanning microscopy The fluorescence imaging was conducted based on a method described in the literature [ 57 , 58 ]. Briefly, Confocal microscopy (TCS SP8, Leica Microsystems, GmbH) was employed for imaging. A 405 nm diode laser and a white light laser at 70% power were used to excite the fluorophore AlexaFluor 430. The excitation and emission wavelengths for ovalbumin were 390 nm and 470 nm. HYD detectors were utilised for each channel, and imaging was performed with a 20X dry APO lens at a resolution of 2048 × 2048 pixels and an imaging speed of 200 Hz. To ensure consistent quantification, laser power, gain, and emission wavelength settings were kept uniform throughout. A 3D image of the particles was generated by merging two planes. For image analysis, LAS X 3.0 (Leica Microsystems GmbH) and Fiji software applications were used [ 59 ]. Inverse gas chromatography Surface energy measurements of PVA and PVA-gelatine particles were conducted using finite dilution inverse gas chromatography (FD-IGC) with an iGC SEA 2000 surface energy analyser (Surface Measurement Systems Ltd., London, UK). Approximately 800 mg of each sample was packed into pre-silanized glass columns (30 cm in length, 4 mm internal diameter), sealed at both ends with silanized glass wool (Sigma-Aldrich, UK). Uniform packing of the powder bed was achieved using a jolting volumeter (Surface Measurement Systems Ltd., London, UK), which applied mechanical tapping to minimise void spaces and ensure consistent sample density throughout the column. Prior to each measurement, columns were conditioned at 30°C for 1 hour under a flow of dry nitrogen to eliminate adsorbed moisture and equilibrate the sample. All IGC measurements were performed under a constant nitrogen carrier gas flow rate of 10 mL/min. Methane was employed as a non-interacting reference probe to determine dead volume and calculate net retention times of the injected probes. A flame ionisation detector (FID) was used to monitor the elution profiles and determine retention times. To determine the dispersive surface energy (γd), a homologous series of n-alkanes (octane, nonane, and decane) was injected at increasing concentrations to generate fractional surface coverages between 0% and 20%. The retention behaviour of the alkanes was analysed using the Dorris and Gray method, based on peak maximum positions. The resulting adsorption isotherms were used to construct the dispersive surface energy distribution across the sample surface. To evaluate the acid–base surface energy (γab), monopolar probe molecules were employed: dichloromethane (electron-acceptor, acidic) and ethyl acetate (electron-donor, basic). These were injected under the same flow conditions to quantify specific interactions between the probe and the PVA surface. Acidic (γ+) and basic (γ–) parameters were derived using the van Oss–Chaudhury–Good (vOCG) theory. The acid–base surface energy (γab) was calculated from these parameters, and the total surface energy (γt) was obtained as the sum of γd and γab. TR146 cell culture procedures TR146 cells were grown and maintained in 75 cm 2 T-flasks in Ham’s F-12 cell culture media with the addition of 50mL of foetal bovine serum (FBS), 2.5 mL of 1% penicillin-streptomycin, 10 mL of 2 mM glutamine, 1 mL of gentamicin (10 mg/mL), and 1 mL of amphotericin B (250 µg/mL). The cells were incubated at 37°C, 5% CO 2 and 95% air. The media was changed every 2–3 days and when 90% confluency was reached cells were passaged using 5 mL of Trypsin-EDTA solution and seeded onto 12-well transwell inserts at a density of 24,000 cells/cm 2 [ 45 ]. Transepithelial electric resistance (TEER) The ohmic resistance of cells grown on transwell inserts was measured every 2–3 days (30 minutes after changing the media) during the cell culture, and before and after each permeability experiment, using an EVOM3 (Epithelial Volt/Ohm Meter) with chopstick electrodes. The electrodes were placed upright, such that the longer electrode touched the basolateral chamber, while the shorter electrode touched the apical membrane chamber. TEER, which reveals the integrity of the cellular layers, was calculated from triplicate reading from replicate transwells (n = 9) [ 45 ]. In vitro permeation studies Permeability studies were conducted as described by Nielsen and Rassing at 37°C and 140 rpm in an orbital plate shaker [ 60 ]. Formulation solutions were prepared at 1 mg in 0.5 mL of HBSS. The pH of the solutions was measured before and after the permeation study. Cells on the transwell were rinsed twice with HBSS (37°C) by adding 0.5 mL to the apical chamber and 1.5 mL to the basolateral chamber. After 2 hours (duration of experiment), cells were rinsed with 0.5 mL HBSS and equilibrated for 30 minutes after which TEER values were measured [ 45 ]. All samples were analysed for ovalbumin content by HPLC. Statistical analysis The data were generated in triplicates, where n = 3, and analysed for statistical significance using one-way analysis of variance (ANOVA) and Dunnett's multiple comparisons post-test from GraphPad Prism® version 9.4.0. The level of significance was set to P < 0.05 (probability values of 95%). Declarations Competing interests The authors declare no competing financial interests Funding This work was supported by the Biotechnology and Biological Sciences Research Council (BBSRC) Midlands Integrative Biosciences Training Partnership (MIBTP) case award in partnership with Aston Particle Technologies (APT) (BB/T00746X/1). Author Contribution A.R conducted the research. A.R wrote the manuscript. A.I. provided cell culture training and supervised this study. M.A.A.T provided training and conducted confocal microscopy. A.R.M. conceived the project, wrote the grant application and supervised the project. DW and JK co-authored the grant application and supervise the project. All authors reviewed, revised and approved the manuscript. Data Availability All data generated or analysed during this study are included in this published article. References New, R. Oral Delivery of Biologics via the Intestine . Pharmaceutics , 13 (1). (2020). Trincado, V., Gala, R. P. & Morales, J. O. Buccal and Sublingual Vaccines: A Review on Oral Mucosal Immunization and Delivery Systems . Vaccines (Basel) , 9 (10). (2021). Anselmo, A. C., Gokarn, Y. & Mitragotri, S. Non-invasive delivery strategies for biologics. Nat. Rev. Drug Discovery . 18 (1), 19–40 (2019). Nair, V. V. et al. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8957044","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":604350216,"identity":"579fe7e3-07d2-418a-8a17-a424870e3b2b","order_by":0,"name":"Anthony Rajabi","email":"","orcid":"","institution":"Aston University","correspondingAuthor":false,"prefix":"","firstName":"Anthony","middleName":"","lastName":"Rajabi","suffix":""},{"id":604350217,"identity":"113ee352-d1c1-4573-a7aa-6c0bfd8e5996","order_by":1,"name":"Mohamad Anas Al Tahan","email":"","orcid":"","institution":"Aston University","correspondingAuthor":false,"prefix":"","firstName":"Mohamad","middleName":"Anas Al","lastName":"Tahan","suffix":""},{"id":604350218,"identity":"1bc0c7b4-4339-45ed-809f-8cbc6b2348cc","order_by":2,"name":"Affiong Iyire","email":"","orcid":"","institution":"Aston University","correspondingAuthor":false,"prefix":"","firstName":"Affiong","middleName":"","lastName":"Iyire","suffix":""},{"id":604350219,"identity":"feefb49a-f183-487d-a50f-0efeaceaf22a","order_by":3,"name":"David Wyatt","email":"","orcid":"","institution":"Aston Particle Technologies Ltd","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Wyatt","suffix":""},{"id":604350225,"identity":"3ed53569-635e-49f1-8cb8-985c993644de","order_by":4,"name":"Jasdip Koner","email":"","orcid":"","institution":"Aston Particle Technologies Ltd","correspondingAuthor":false,"prefix":"","firstName":"Jasdip","middleName":"","lastName":"Koner","suffix":""},{"id":604350226,"identity":"9c152767-3b4e-45cd-9d8a-7d753cb2f4bb","order_by":5,"name":"Afzal R Mohammed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYDADAzDJZoMkxEOcljQgJlHLYcJa+Bt4DJgrGLbJmbOfTt3woey8vPz85mMPGGrsGAzOHMCqReIAjwHjGYbbxpY9udtuzjh323DDMbZ0A4ZjyQwGZxuwWwPS0sBwO3HDgdxtt3nbbjNuYOMxk2BgO8BgcB67Dnm4lvNvt93+23bOfn4bSMs/3FoM4FpuAG1hbDuQ2HAMqAXIwOkww8NsBQcbDG4bG9x4u+1mz7nk5A3H0tIkEvuSeSRxeF/uePPGhw0Vt+UMzuduu/GjzM52fvPhYxIfvtnJ8Z1JwO4yZmAIQCMFCSQQjshRMApGwSgYBXgAADIAX9mXWDhnAAAAAElFTkSuQmCC","orcid":"","institution":"Aston University","correspondingAuthor":true,"prefix":"","firstName":"Afzal","middleName":"R","lastName":"Mohammed","suffix":""}],"badges":[],"createdAt":"2026-02-24 11:53:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8957044/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8957044/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104545698,"identity":"44fcce88-72fe-403f-879c-86e6d6869e3c","added_by":"auto","created_at":"2026-03-13 07:15:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":213923,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic design of biologic formulation\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8957044/v1/6eb0bc2e5fa4dd49c74131c6.png"},{"id":104780831,"identity":"41e8437f-cf0a-4275-88e7-6bdb294ff70c","added_by":"auto","created_at":"2026-03-17 07:54:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":425658,"visible":true,"origin":"","legend":"\u003cp\u003eA-D Confocal microscopy images taken following processing PVA particles and coating with FITC-OVA using the iDPC (20-minute processing time, 25 L/min, 1800 rpm). Images A and B are 1% FITC-OVA coated on sieved PVA (\u0026gt;120 µm). Images C and D are 1% FITC-OVA coated on PVA-gelatine particles processed with iDPC.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8957044/v1/9e897d0f8f1ff2907099280a.png"},{"id":104781337,"identity":"fdd6954b-0bf1-4b34-ab86-e2dc10e87714","added_by":"auto","created_at":"2026-03-17 07:55:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":286911,"visible":true,"origin":"","legend":"\u003cp\u003eRaman spectra of PVA, OVA, gelatine, L-lysine, and a-tocopherol used as a reference spectra - 785 nm (100% power), 300 lines mm\u003csup\u003e-1\u003c/sup\u003e, 50x, 30 s, 2 accumulations, absolute units, normalised, y-offset\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8957044/v1/a75d2cb912f7844740bff3a2.png"},{"id":104545702,"identity":"a0c90b8b-b9bc-4106-8502-7d81dd46026a","added_by":"auto","created_at":"2026-03-13 07:15:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":391034,"visible":true,"origin":"","legend":"\u003cp\u003eA-B Image A is the Raman confocal microscopy 10x optical image of a PVA-gelatine particle containing 2% OVA, 1% a-tocopherol, and 1% L-lysine. Image B is 100x optical image of the same particle.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8957044/v1/0df780aa5f06a8606890cf53.png"},{"id":104781273,"identity":"7ad7e497-3280-49bf-9196-846f05ee4fc1","added_by":"auto","created_at":"2026-03-17 07:55:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":273681,"visible":true,"origin":"","legend":"\u003cp\u003eRaman map 785 nm (100% power), 300 lines mm\u003csup\u003e-1\u003c/sup\u003e, 100x, 2 s, 2 accumulations, 10x10 µm in 2 µm steps, spectra and references baseline corrected\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8957044/v1/837faf00b2b5335e65826fb9.png"},{"id":104781298,"identity":"7c712836-8616-472e-9ba0-481bf69780cc","added_by":"auto","created_at":"2026-03-17 07:55:21","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":85425,"visible":true,"origin":"","legend":"\u003cp\u003eIGC surface energy distribution for PVA particles. Total surface energy (γt, red), dispersive (γd, green), and acid-base (γab, cyan) components are plotted as area increment (%) versus surface energy (mJ/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8957044/v1/23996b12f24fa84ace55d3a1.png"},{"id":104781379,"identity":"2a700ea5-02f5-4f21-a356-bada8b942324","added_by":"auto","created_at":"2026-03-17 07:55:34","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":75653,"visible":true,"origin":"","legend":"\u003cp\u003eIGC surface energy distribution for PVA-gelatine particles. Total surface energy (γt, red), dispersive (γd, green), and acid-base (γab, cyan) components are plotted as area increment (%) versus surface energy (mJ/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8957044/v1/3975247c2953f80f77f9af3a.png"},{"id":104781225,"identity":"f716c93a-e18f-4f11-b01c-a8e351cd7fb2","added_by":"auto","created_at":"2026-03-17 07:55:11","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":73383,"visible":true,"origin":"","legend":"\u003cp\u003eRelative permeation of ovalbumin across TR146 cell layers, normalised to the control (F1 = 100%) over 120 min (mean ± SD, n = 3). Data are expressed as percentage of the control at each time point (F1 set to 100%; dashed line). Samples were collected at 5, 15, 30, 60 and 120 min. Formulations: F1, ovalbumin control; F2, iDPC PVA + ovalbumin/L-lysine/α-tocopherol; F3, iDPC PVA–gelatine + ovalbumin/L-lysine/α-tocopherol; F4, physical mix PVA + ovalbumin/L-lysine/α-tocopherol.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8957044/v1/3f960eaf4995a433f8b6abfa.png"},{"id":106725869,"identity":"7dd43de9-921a-4d11-9b4d-bb119368c7c1","added_by":"auto","created_at":"2026-04-12 18:34:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2944134,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8957044/v1/9253dc8b-6f65-4b6b-95a3-990743af3c36.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Particle surface modification using isothermal dry coating to deliver biologics through the buccal route","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBiologics are crucial for the treatment and management of a wide range of diseases, including cancer, autoimmune disorders, and genetic conditions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, their delivery is often limited by the reliance on the parenteral route that require trained personnel, cold-chain logistics, and may lead to poor patient compliance [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Due to these limitations there is a need for alternative delivery strategies that are non-invasive, patient friendly, and accessible across varied healthcare settings [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Buccal delivery targets the inner cheek and oral mucosa, and presents several advantages including ease of administration [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The buccal route bypasses the first-pass effect of hepatic metabolism, avoids degradation by gastric enzymes, facilitates drug absorption through its moderately permeable epithelium, and offers a patient-friendly administration without needles [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these advantages, buccal delivery of biologics is underutilised due to challenges such as susceptibility to degradation during manufacturing and storage, necessitating cold-chain logistics to maintain stability. Upon administration, biologics may further degrade due to salivary enzymes, have limited residence time due to salivary flow, and exhibit poor permeation without appropriate excipients or delivery systems [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Addressing these challenges requires innovative formulation strategies to improve stability, retention, and absorption of biologics.\u003c/p\u003e \u003cp\u003eOvalbumin (OVA) is widely utilised as a model biologic in drug delivery research due to its well-characterised structure and cost-effectiveness [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. As a glycoprotein derived from chicken egg whites, OVA has been utilised in various studies to evaluate novel delivery systems. For example, Osswald and Kang-Mieler (2015) used OVA to investigate the release profiles of a protein within a microsphere delivery system [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In addition, Di Francesco et al. (2024) utilised OVA as a model biologic to investigate minimally invasive delivery through the nasal route [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In this study, OVA served as a convenient, well-characterised biologic to assess the efficacy of a novel buccal formulation.\u003c/p\u003e \u003cp\u003eThe primary objective of this study was to evaluate the feasibility of the buccal route for biologic administration, specifically focussing on optimising the co-localisation of the model biologic compound with excipients designed to enhance permeation and stability. To achieve this, a carrier polymer was selected and coated with gelatine to modify surface properties, followed by coating with OVA, L-lysine, and α-tocopherol, to produce the formulation depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A critical consideration was maintaining the stability and structural integrity of OVA during the formulation process. To achieve this, isothermal dry particle coating (iDPC), a technology that allows the controlled deposition of fine particles onto larger particles without the use of heat, solvents, or physical mixing was used. The iDPC mechanism utilises a high-speed rotating vessel combined with a fluidising nitrogen gas blade, creating a unique thin-layer fluidisation process that operates in a dry, ambient state [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This coating technique ensured the stability of the formulation, preserving the structural properties of OVA and enhancing the overall efficacy of the buccal delivery system.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Results and discussion","content":"\u003cp\u003eFormulation development\u003c/p\u003e \u003cp\u003eThe formulation strategy was to generate a particulate \u0026ldquo;host\u0026ndash;guest\u0026rdquo; system using isothermal dry particle coating (iDPC), enabling co-localisation of the model biologic (OVA) with excipients intended to support stability and buccal permeation while avoiding heat and solvents that can compromise protein integrity. Specifically, the approach was to use polyvinyl acetate (PVA) as a carrier (\u0026ldquo;host\u0026rdquo;) and apply a gelatine pre-coat to modify the carrier surface and promote adhesion/retention, before coating OVA with additional functional excipients, L-lysine and α-tocopherol.\u003c/p\u003e \u003cp\u003ePVA was selected as the carrier polymer due to its film-forming capability, mechanical robustness and biocompatibility, and because its predominantly neutral character supports mucoadhesion largely via hydrogen bonding and physical entanglement rather than strongly pH-dependent electrostatics [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Gelatine was selected as the primary surface-modifying coating component because of its well-characterised adhesive and film-forming properties, with the aim of enhancing carrier adhesiveness and promoting co-localisation of OVA and excipients at the mucosal interface to support transport across buccal cell layers [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In parallel, L-lysine was incorporated on the basis that it is positively charged at physiological pH and may promote electrostatic association/ion-pairing with negatively charged OVA, potentially increasing effective permeation while also contributing to protein stability [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. α-tocopherol was selected as an antioxidant stabiliser and as a candidate membrane-modulating excipient reported to influence barrier properties and macromolecular transport in mucosal models [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn accordance with iDPC requirements, the \u0026ldquo;guest\u0026rdquo; component should be at least two to three times smaller than the \u0026ldquo;host\u0026rdquo; component to enable efficient deposition [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. PVA was therefore carried forward as the host material; however, initial laser diffraction measurements indicated that the volume mean diameter (VMD) of PVA was 163.33 \u0026micro;m while gelatine was 97.44 \u0026micro;m. As a consequence, gelatine size reduction was required to satisfy the host\u0026ndash;guest criterion. The target was to reduce gelatine to a VMD\u0026thinsp;\u0026le;\u0026thinsp;32 \u0026micro;m (approximately three-fold smaller than PVA). Several particle-size reduction approaches were evaluated (homogenisation, ultrasonication, and cryogenic milling), but none achieved the required VMD threshold.\u003c/p\u003e \u003cp\u003eA practical size-classification method was then developed in which gelatine was placed on a 32 \u0026micro;m sieve and agitated using a vortex mixer rather than a conventional sieve shaker. This vortex-assisted approach reduced powder bridging and cohesive clumping, increasing the fraction of particles passing the sieve (\u0026le;\u0026thinsp;32 \u0026micro;m), as summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In contrast to the standard sieve shaker (\u0026asymp;\u0026thinsp;5% yield below 32 \u0026micro;m), the vortex-mixer method produced\u0026thinsp;\u0026asymp;\u0026thinsp;40% yield and exceeded the original size target, giving a gelatine VMD of 12.74 \u0026micro;m. This size-reduced gelatine was therefore suitable for subsequent iDPC coating onto PVA under the host\u0026ndash;guest size constraint.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticle size analysis of unprocessed and vortex-mixer method gelatine powder determined by laser diffractometry. Each sample, approximately 100 mg, was dispersed at 3 bar of pressure and measurements were performed in triplicate (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProperties (\u0026micro;m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnprocessed gelatine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVortex-mixer method gelatine\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e42.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e96.06\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e153.21\u0026thinsp;\u0026plusmn;\u0026thinsp;3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.94\u0026thinsp;\u0026plusmn;\u0026thinsp;2.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e97.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eConfocal laser scanning microscopy\u003c/p\u003e \u003cp\u003eConfocal laser scanning microscopy (CLSM) was employed to evaluate whether the inclusion of gelatine influenced the adherence of fluorescently labelled ovalbumin (FITC-OVA) to PVA particles. Both PVA and PVA-gelatine particles were coated with 1% FITC-OVA under identical iDPC processing conditions (20-minute run time, 25 L/min nitrogen gas flow, 1800 rpm). CLSM images are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Figures\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB show FITC-OVA coated PVA particles, and Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD are FITC-OVA coated PVA-gelatine particles. Visual analysis indicated that the fluorescence intensity observed was very similar between the two samples, indicating no significant enhancement in protein adherence as a result of the inclusion of gelatine.\u003c/p\u003e \u003cp\u003eSeveral factors, such as hydrophilicity and surface energy, may account for the absence of significant difference in fluorescence intensity. Elango et al. (2023) reported that the protein adsorption capability of PVA hydrogels is dependent on surface energy, hydrophilicity, and electrostatic interactions, and modifications may not significantly impact protein adherence. However, it was reported that the incorporation of silver nanoparticles into PVA hydrogels enhanced protein adsorption due to increases surface roughness and electrostatic interactions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is important to acknowledge the limitations associated with CLSM in this context. The increased size of PVA-gelatine particles posed challenges during imaging, as some particles exceeded the optimal field of view for the microscope. This limitation may have hindered the capture of the complete particle images, potentially affecting the assessment of fluorescence distribution and coverage.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRaman confocal microscopy\u003c/p\u003e \u003cp\u003eConfocal Raman microscopy was employed to investigate the spatial distribution and co-localisation of the model biologic compound, ovalbumin, and the excipients (gelatine, L-lysine, and α-tocopherol) on PVA-gelatine particles. The PVA-gelatine particles were coated using the iDPC with a formulation consisting of 2% OVA, 1% α-tocopherol, and 1% L-lysine, under consistent processing parameters (20-minute run time, 25 L/min, 1800 rpm).\u003c/p\u003e \u003cp\u003eThe preliminary step involved obtaining individual Raman spectra for each component within the formulation to establish their unique spectral fingerprints. The reference spectra are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and were used as the basis for subsequent spectral mapping and component identification with the particulate system.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFollowing the completion of the reference spectra, an initial optical examination of the coated particles was conducted using a 10x objective lens (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). However, at this magnification the laser\u0026rsquo;s penetration depth reached the particle core and only detected the Raman spectrum of PVA. As a result, a 100x objective lens was utilised (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), and a \u0026lsquo;point and shoot\u0026rsquo; mapping approach was implemented to enable the measurement of Raman spectrum at the particle surface. This method involved analysing an approximate 10 \u0026micro;m x 10 \u0026micro;m grid on the particle surface, with Raman spectra collected at 2 \u0026micro;m intervals, resulting in a mapping of the surface composition.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMap data were processed using classic least squares (CLS) regression analysis (a supervised multivariate analysis approach), with each spectrum within the map expressed as a mathematical superposition of the reference spectra. Both the reference and map spectra were baseline corrected to remove the impact of fluorescence. This approach enabled a clear identification of spectral contributions from the components within the mapped region shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB.\u003c/p\u003e \u003cp\u003eThe resulting map (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) demonstrates the presence of OVA, α-tocopherol, and L-lysine on the surface of the PVA-gelatine particles, confirming successful co-localisation. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the spatial distribution of each component is distinct yet complementary, when superimposed, the individual maps collectively occupy the scanned area (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). These results suggest that the iDPC process was effective in depositing multiple components uniformly onto the carrier particles.\u003c/p\u003e \u003cp\u003eThe iDPC process promotes particle deagglomeration, which enhances coating efficiency by overcoming cohesive forces such as van der Waals or electrostatic forces. The deagglomeration is promoted by the relative centrifugal force generated within the drum as the speed of the drum increases. As the drum speed increases, particles are propelled toward the drum wall, reducing particle agglomeration. In addition, the nitrogen gas blade likely aids the fluidisation of the particles attached to the drum wall, increasing their mobility and promoting particle interaction. As a result, the combined effects of deagglomeration and enhanced particle interaction enable a coating of the smaller particles onto the larger particles, allowing for efficient co-localisation of the smaller components onto the carrier polymer, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eInverse gas chromatography\u003c/p\u003e \u003cp\u003eInverse gas chromatography (IGC) was employed to characterise the surface area and surface energy profiles of PVA particles and PVA-gelatine particles. Understanding the surface energy profiles of these particles can help evaluate whether the inclusion of gelatine impacted their adhesivity, stability, and overall physicochemical interactions, thereby affecting the overall coating efficiency of the biologic and excipients [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. IGC is an analytical technique widely used to characterise the physicochemical properties of solid materials, specifically powders and particulates [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Unlike traditional gas chromatography, where the stationary phase is a liquid or solid and the mobile phase is a gas, IGC inverts the role of stationary and mobile phases by using the solid sample as the stationary phase and introducing known gas-phase probe molecules as the mobile phase [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The interactions between these gas-phase probe molecules and the sample surface are analysed to determine the surface properties including surface energy, surface area, and acid-base characteristics [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIGC data are presented in terms of surface energy components such as, the total surface energy (γt), the dispersive surface energy component (γd), and the acid-base surface energy component (γab). The total surface energy (γt) represents the overall energy associated with the surface of the sample including all intermolecular interactions. The dispersive component (γd) represents non-polar interactions, such as van der Waals forces and the acid-base component (γab) represents polar interactions, including hydrogen bonding and electron-donor acceptor interactions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe surface area analysis conducted by the IGC revealed that the PVA particles had a surface area of 1.7471 m\u003csup\u003e2\u003c/sup\u003e/g, whereas the PVA-gelatine particles had a significantly lower surface area of 0.7344 m\u003csup\u003e2\u003c/sup\u003e/g, seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. This 2.4-fold reduction in surface area may be attributed to the pores and rough surface morphology being altered by the inclusion of gelatine. Increased particle surface roughness typically enhances coating adhesion by providing additional contact points and interlocking sites, suggesting that the potential smooth surface associated with PVA-gelatine particles may reduce the likelihood of the other components (OVA, L-lysine, α-tocopherol) adhering to the PVA particles [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSurface area of untreated PVA and PVA-gelatine calculated by IGC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSurface area (m\u003csup\u003e2\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.7471\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVA coated with gelatine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.7344\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSubsequent surface energy analysis provided further insight into the characteristics of these particles. Untreated PVA particles demonstrated dispersive surface energy values (γd) that ranged from approximately 55.36 mJ/m\u003csup\u003e2\u003c/sup\u003e at a low surface coverage to -2.61 mJ/m\u003csup\u003e2\u003c/sup\u003e at high surface coverage. The acid-base surface energy distributions ranged (γab) from 13.49 mJ/m\u003csup\u003e2\u003c/sup\u003e to -0.95 mJ/m\u003csup\u003e2\u003c/sup\u003e, and the total surface energy (γt) ranged from around 68.85 mJ/m\u003csup\u003e2\u003c/sup\u003e to -3.50 mJ/m\u003csup\u003e2\u003c/sup\u003e, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The minimum and maximum surface energy values (mJ/m\u003csup\u003e2\u003c/sup\u003e) determined by IGC reflect the range of energetic heterogeneity present on the particle surface. The minimum energy indicates the least interactive sites and the maximum energy corresponds to the most interactive sites available for adsorption [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These values can further the understanding and prediction of interfacial phenomena such as adhesion and compatibility with other components as they relate to the thermodynamic interactions between probe molecules and the sample [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The negative values observed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e are likely mathematical artefacts of extrapolation rather than actual negative surface energies. These anomalies often arise due to applying linear extrapolation method, the Dorris-Gray approach in this case, to retention data for nonpolar probes. This issue is particularly common with materials that have highly heterogenous surfaces, as they may not align with the assumptions underlying the model [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn IGC, the area increment percentage is given at each surface energy and it represents the fraction of the total external surface area that exhibits that specific energy [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The γd area increments increased from 0.0011% to approximately 0.247%, while the γab area increments showed a similar trend of 0.0013% to 0.248% and the γt area increments ranged from 0.0012% to 0.247%. The small area increment percentages indicate that only a small fraction of the particle\u0026rsquo;s surface area corresponds to the specific energy level, indicating a highly heterogenous surface [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMinimum and maximum values of surface energy components for PVA particles, dispersive energy (γd), acid-base surface energy (γab), and total surface energy (γt) as determined by IGC\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurface energy\u003c/p\u003e \u003cp\u003e(PVA)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimum (mJ/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum (mJ/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eγd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eγab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eγt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe PVA-gelatine particles displayed significantly different surface energetics, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The dispersive surface energy (γd) ranged from 52.94 mJ/m\u003csup\u003e2\u003c/sup\u003e at low surface coverage and 2.18 mJ/m\u003csup\u003e2\u003c/sup\u003e. The acid-base (γab) surface energy distributions ranged from 7.55 mJ/m\u003csup\u003e2\u003c/sup\u003e to -8.86 mJ/m\u003csup\u003e2\u003c/sup\u003e. The total surface energy (γt) ranged from 60.48 mJ/m\u003csup\u003e2\u003c/sup\u003e to -6.67 mJ/m\u003csup\u003e2\u003c/sup\u003e. The area increments for γd, γab, and γt had very similar area increments of 0.0004% to 0.40%. The area increment data for the PVA-gelatine particles indicate a heterogenous surface, similar to the PVA particles [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMinimum and maximum values of surface energy components for PVA-gelatine particles, dispersive energy (γd), acid-base surface energy (γab), and total surface energy (γt) as determined by IGC\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurface energy\u003c/p\u003e \u003cp\u003e(PVA-gelatine)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimum (mJ/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum (mJ/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eγd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eγab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-8.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eγt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-6.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe surface energy characteristics of PVA and PVA-gelatine particles may significantly influence their efficacy as the \u0026lsquo;host\u0026rsquo; in the particulate system. IGC analysis revealed that PVA particles exhibited a higher total surface energy (68.85 mJ/m\u003csup\u003e2\u003c/sup\u003e), indicating that the PVA particles have a greater propensity for intermolecular interactions [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In addition to total surface energy, PVA particles displayed higher dispersive and acid-base surface energy (55.36 mJ/m\u003csup\u003e2\u003c/sup\u003e and 13.49 mJ/m\u003csup\u003e2\u003c/sup\u003e, respectively), compared to PVA-gelatine particles (52.94 mJ/m\u003csup\u003e2\u003c/sup\u003e and 7.55 mJ/m\u003csup\u003e2\u003c/sup\u003e, respectively). This indicates that the PVA particles will have stronger capacity for non-polar and polar interactions [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe higher dispersive component exhibited in the PVA particles indicates stronger van der Waals forces, which may facilitate adhesion with hydrophobic excipients such as α-tocopherol [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Additionally, the higher acid-base component may increase polar interactions with the model biologic OVA and L-lysine [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. These interactions are likely to improve initial drug and excipient adhesion to the PVA particles; however, they may also promote aggregation and reduced flowability, potentially compromising the manufacturing process [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the surface energy distribution of PVA, this plot illustrates the relationship between surface energy and area increment for the total surface energy, dispersive, and acid-base components. The broad total surface energy indicates a highly heterogenous and interactive surface. This heterogeneity indicates the presence of high energy sites that can form strong van der Waals and polar interactions [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe inclusion of gelatine likely induces morphological changes in the PVA particles, which leads to a smoother surface and reduced surface area likely due to pore filling (from 1.7471 m\u003csup\u003e2\u003c/sup\u003e/g to 0.7344 m\u003csup\u003e2\u003c/sup\u003e/g). These morphological changes may contribute to reduced dispersive and acid-base surface energy, resulting in a lower total surface energy. However, these reductions in surface energy can be advantageous for formulation stability, as they reduce interparticle cohesive forces, improve powder flow, and reduce the likelihood of moisture-induced clumping [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows the surface energy distribution of PVA-gelatine particles. In contrast to the broader distributions observed in PVA particles, the total surface energy, dispersive, and acid-base distributions appear more linear. This linearity is likely due to the reduced surface heterogeneity of the PVA-gelatine particles, indicating a more energetically uniform surface with reduced variation in interaction potential across the particle adsorption sites [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In summary, the PVA particles provide stronger interaction potentials due to higher surface energy components, the PVA-gelatine particles likely provide improved flowability, reduced aggregation, and enhanced formulation stability.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTR146 permeability studies\u003c/p\u003e \u003cp\u003eTo determine the impact of the inclusion of gelatine and the inclusion of L-lysine and α-tocopherol on the permeation of OVA through the buccal mucosa, the commonly used \u003cem\u003ein vitro\u003c/em\u003e model, TR146 cell line, was utilised. TR146 is an immortalised epithelial cell line that forms stratified, non-keratinised layers that closely mimic the morphological and functional characteristics of buccal tissue [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFour formulations were prepared, and were identified F1-F4, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Formulation F1, containing OVA alone, served as the control (F1) to establish baseline buccal permeation and evaluate the potential for enhancement. To determine the impact of the inclusion of gelatine, two PVA-based formulations (F2 and F3) were prepared with identical iDPC process parameters (1800 rpm, 20 minutes processing time, 25 L/min), with consistent concentrations of biologic and excipient. Formulation F2 was prepared using PVA alone, and F3 utilised PVA coated with gelatine. To investigate whether the iDPC method itself influenced the permeation efficacy, formulation F4 was prepared with the identical composition to F2, but the formulation was physically mixed using a spatula, thereby removing the iDPC step and allowing for a direct comparison.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFormulation key \u0026ndash; the four formulations were tested for TR146 permeation studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormulation Identifier\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComposition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvalbumin (Control)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eiDPC - PVA, 2% OVA, 1% L-lysine, 1% α-tocopherol\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eiDPC \u0026ndash; PVA coated with gelatine, 2% OVA, 1% L-lysine, 1% α-tocopherol\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical mix \u0026ndash; PVA, 2% OVA, 1% L-lysine, 1% α-tocopherol\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTR146 cells were grown on transwell inserts for 28\u0026ndash;29 days prior to their use in permeability studies. The formation and integrity of the stratified layers was monitored and measured using transepithelial electrical resistance (TEER), which confirmed the formation of suitable stratified layers between days 28 and 29, these findings are consistent with those reported by Iyire et al. (2016), further validating the model\u0026rsquo;s suitability for permeability assessment [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAll formulations were prepared to ensure a concentration of OVA 1 mg/mL remained consistent for accurate comparative analysis. Samples were collected at preset time points (5 minutes, 15 minutes, 30 minutes, 60 minutes, and 120 minutes) and quantified by HPLC analysis. TEER measurements post-permeation study indicated no significant disruptions to cellular integrity, confirming the reliability of the permeation results.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe cumulative permeation profiles of OVA differed significantly between formulations (data not shown). Over 120 minutes, the control (F1) reached 86.59\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54% cumulative permeation, F2 reached 77.58\u0026thinsp;\u0026plusmn;\u0026thinsp;3.42%, F3 reached 99.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42%, and F4 reached 56.43\u0026thinsp;\u0026plusmn;\u0026thinsp;3.91%. Although OVA is a large, hydrophilic protein (~\u0026thinsp;45 kDa), the cumulative permeation observed for the control over 120 minutes exceeded what might typically be expected for a macromolecule of this size [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. However, buccal transport of high molecular weight compounds has been reported (e.g., dextrans in the 70\u0026ndash;150 kDa range) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the control (F1) serves primarily as an internal benchmark for comparative assessment of formulation-dependent changes in permeation.\u003c/p\u003e \u003cp\u003eAt 120 minutes, formulation F3 produced a significantly greater cumulative permeation than the control (P\u0026thinsp;=\u0026thinsp;0.0157), whereas F2 was not significantly different from the control (P\u0026thinsp;=\u0026thinsp;0.1015). Direct comparison of F2 and F3 confirmed a significant increase associated with gelatine inclusion (P\u0026thinsp;=\u0026thinsp;0.0002). To facilitate comparison of enhancement magnitude and mitigate ceiling effects associated with percentage scaling, permeation was expressed relative to the control at each time point (F1\u0026thinsp;=\u0026thinsp;100%; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Under this normalisation, the gelatine-containing iDPC formulation (F3) demonstrated sustained enhancement relative to control across all time points, peaking at approximately 151% of control at 30 min and remaining elevated at 120 min (approximately 114% of control). In contrast, the physically mixed formulation (F4) consistently showed reduced permeation relative to control, reaching approximately 65% of control at 120 min. The PVA iDPC formulation (F2) remained broadly comparable to the control, with modest enhancement at intermediate time points but reduced relative permeation at 120 min (approximately 90% of control). Collectively, these results indicate that the inclusion of gelatine within the iDPC particulate system produced the greatest enhancement in OVA permeation relative to baseline.\u003c/p\u003e \u003cp\u003eThe enhancement observed with F3 is consistent with gelatine-driven changes in particle surface properties and excipient co-localisation. Gelatine may form a film-like coating on the PVA surface, potentially increasing mucoadhesive interactions and residence time, thereby supporting increased transport across the TR146 layers [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In addition, IGC analysis revealed that the inclusion of gelatine altered the surface energetics, including a reduced total surface energy and a more uniform energy distribution (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The reduced surface energy reduces interparticle cohesive forces, which may improve the flowability and dispersion of the particles [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Enhanced dispersion could contribute to a more homogeneous presentation of OVA at the TR146 interface, which is consistent with the higher permeation observed. However, confocal microscopy analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) indicated no notable increase in OVA deposition between formulations F2 and F3, suggesting that the increased permeation associated with F3 may be due to an improved interaction with the TR146 cell layers, rather than differences in particle surface deposition or coating efficiency.\u003c/p\u003e \u003cp\u003eL-lysine may contribute to the permeation enhancement through ion-pairing mechanisms. At physiological pH, L-lysine carries a positive charge due to its amino groups, while OVA carries an overall negative charge [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. This charge disparity facilitates electrostatic interaction, enabling the formation of ion-pairs, which may neutralise the net charge of the particulate complex, and therefore increase the lipophilicity and facilitate permeation across the cell layers [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Raman mapping demonstrated co-localisation of OVA and L-lysine on the particle surface (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), which may promote ion-pairing by increasing proximity between the ion and counter-ion [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. α-Tocopherol may further contribute by modulating lipid domains and increasing membrane fluidity; for example, α-tocopherol has been reported to improve the permeability of radiolabelled hydrocortisone in Franz diffusion cells [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA notable observation from the permeability studies was the reduced performance of the physically mixed formulations (F4) relative to the iDPC-prepared formulation. F4 produced significantly lower permeation than the control (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and both iDPC formulations (P\u0026thinsp;=\u0026thinsp;0.002), underscoring the importance of iDPC processing in depositing OVA and excipients onto the carrier particle surface. The iDPC utilises a high-speed rotating vessel in conjunction with a fluidising nitrogen gas blade to promote the deposition of fine particles onto larger particles, which is likely to better preserve the structural and functional integrity of the biologic during formulation manufacture [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe formulation development involved optimisation of particle size distributions for the polymers, model biologic, and excipients to meet the iDPC processing criteria. IGC analysis revealed that the gelatine coating impacted the surface energetics of the PVA particles by reducing surface heterogeneity and total surface energy. However, confocal laser scanning microscopy indicated no significant increase in ovalbumin deposition onto untreated PVA and PVA-gelatine particles, suggesting that the addition of gelatine impacted particle morphology rather than OVA adsorption directly. Raman confocal microscopy analysis demonstrated evidence of effective co-localisation between OVA, L-lysine, and α-tocopherol on the PVA-gelatine particle surface. Permeability studies using the TR146 buccal cell line demonstrated significant differences among the four formulations tested. When expressed relative to control (F1\u0026thinsp;=\u0026thinsp;100%; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), formulation F3 (PVA-gelatine particles) demonstrated sustained enhancement across all time points, remaining elevated at 120 minutes. This increase in permeation is consistent with gelatine-driven changes in particle surface properties and excipient co-localisation; improved particle dispersion and ion-pair formation between OVA and L-lysine likely contributed. Another key finding from the permeability studies was the significant reduction in permeation observed with the physically mixed formulation (F4) compared to formulations prepared via iDPC, indicating the importance of the coating method. The findings presented in this paper establish the role of iDPC and the use of gelatine as a promising method for enhancing buccal permeation of biologics using suitable polymers and excipients.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eMaterials\u003c/p\u003e \u003cp\u003eThe TR146 cell line was obtained from Public Health England (Salisbury, UK). Ovalbumin (\u0026ge;\u0026thinsp;98% purity), microcrystalline polyvinyl alcohol (PVA) (Mw 89,000\u0026ndash;98,000 Da, 99+% hydrolysed), L-lysine (\u0026ge;\u0026thinsp;98% purity), gelatine (Type A, 240 Bloom, porcine skin), α-tocopherol (\u0026ge;\u0026thinsp;96% purity) and trifluoracetic acid (TFA; HPLC grade) were purchased from Sigma-Aldrich (Merck, Gillingham, UK). Hank\u0026rsquo;s balanced salt solution (HBSS), foetal bovine serum (FBS), Ham\u0026rsquo;s F-12 nutrient mix and trypsin-EDTA were obtained from Gibco\u0026reg; (Thermo Fisher Scientific, Paisley, UK). Gentamicin and penicillin/streptomycin were obtained from BioSera (Sussex, UK). Acetonitrile (HPLC grade), absolute ethanol, Corning Costar\u0026reg; 12mm-diameter insert; 12-well 0.4 \u0026micro;m polycarbonate membrane tissue culture treated polystyrene plates, and Corning Costar\u0026reg; 24-well clear TC-treated well plates were purchased Fisher Scientific (Loughborough, UK). All water used was Ultrapure (Type 1) Direct-Q 3 UV.\u003c/p\u003e \u003cp\u003eMethods\u003c/p\u003e\n\u003ch3\u003eIsothermal dry particle coating\u003c/h3\u003e\n\u003cp\u003eA benchtop isothermal dry particle coater (iDPC) was used to prepare powder blend formulations that consisted of ovalbumin, polyvinyl alcohol (PVA), L-lysine, gelatine, and α-tocopherol. The iDPC consists of a rotating drum connected to a stationary gas blade. The components were added to the dry particle coating drum, adhering to formulation parameters associated with the iDPC, such as, speed, processing time, and gas pressure [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. At the end of the process, the powder was removed from the coating drum by tipping the drum and brushing the contents into an empty container.\u003c/p\u003e\n\u003ch3\u003ePlanetary ball mill\u003c/h3\u003e\n\u003cp\u003eMilled formulations comprising of PVA, and gelatine (each individually) were prepared using a Fritsch Pulverisette 7 planetary ball mill (Idar-Oberstein, Germany). A ball to powder ratio (BPR) of 8:1 was used for all samples with varying milling speeds and times. Powders were accurately weighed according to the BPR. The samples were transferred into agate vials (45 cm\u003csup\u003e3\u003c/sup\u003e volume) along with 8 agate balls (10 mm diameter). The vials were then sealed with a plastic ring to prevent atmospheric contamination.\u003c/p\u003e\n\u003ch3\u003eHigh performance liquid chromatography (HPLC) assay\u003c/h3\u003e\n\u003cp\u003eThe Agilent 1220 Infinity II LC system with UV/fluorescent detector was used, employing an Eclipse Plus column (C18 3.5 \u0026micro;m 4.6 x 150 mm). Two mobile phases were used: A, Acetonitrile: Water (5:95)\u0026thinsp;+\u0026thinsp;0.1% (v/v) TFA; B, Acetonitrile: Water (95:5)\u0026thinsp;+\u0026thinsp;0.1% (v/v) TFA. During the first 13 minutes the gradient was 85:15 (A:B) to 0:100 (A:B). At 13 minutes the gradient was returned to the initial gradient of 85:15 (A:B) for the final 2 minutes, to prepare for the next sample. The UV detection was set to 280nm, the flow rate 1 mL/min, and an injection volume of 100 \u0026micro;L. Using this protocol, ovalbumin eluted at approximately 8 minutes.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eParticle size analysis\u003c/h2\u003e \u003cp\u003eLaser diffraction was employed to measure particle size using a Sympatec HELOS/BR particle size analyser equipped with a RODOS dry dispersing system with VIBRI/I feeder (Clausthal-Zellerfield, Germany). For each run, nearly 500 mg of powder was weighed and placed on to the VIBRI/L feeder tray. A pressure of 3 bar was applied to disperse the powder using a RODOS disperser and sample measurements were undertaken using a 0-175 \u0026micro;m lens. All powders were measured in triplicate (n\u0026thinsp;=\u0026thinsp;3), and the software calculate the 10% (D10), median (D50), 90% (D90) particle sizes and the volume mean diameter (VMD).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eConfocal Raman spectroscopy\u003c/h3\u003e\n\u003cp\u003eMicro Raman spectroscopy was performed using a HORIBA LabRAM HR Raman microscope. Spectra were collected using a 785 nm laser (at ~\u0026thinsp;30 mW power), a 100x objective and a 200 \u0026micro;m confocal pinhole. To simultaneously scan a range of Raman shifts, a 300 lines mm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e rotatable diffraction grating along a path length of 800 mm was employed. Spectra were acquired using a Synapse CCD detector (1024 pixels) thermoelectrically cooled to \u0026minus;\u0026thinsp;60\u0026deg;C. Before spectra collection, the instrument was calibrated using the zero-order line and a standard Si(100) reference band at 520.7 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The spectral resolution is better than 1.7 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in this configuration.\u003c/p\u003e\n\u003ch3\u003eConfocal laser scanning microscopy\u003c/h3\u003e\n\u003cp\u003eThe fluorescence imaging was conducted based on a method described in the literature [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Briefly, Confocal microscopy (TCS SP8, Leica Microsystems, GmbH) was employed for imaging. A 405 nm diode laser and a white light laser at 70% power were used to excite the fluorophore AlexaFluor 430. The excitation and emission wavelengths for ovalbumin were 390 nm and 470 nm. HYD detectors were utilised for each channel, and imaging was performed with a 20X dry APO lens at a resolution of 2048 \u0026times; 2048 pixels and an imaging speed of 200 Hz. To ensure consistent quantification, laser power, gain, and emission wavelength settings were kept uniform throughout. A 3D image of the particles was generated by merging two planes. For image analysis, LAS X 3.0 (Leica Microsystems GmbH) and Fiji software applications were used [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eInverse gas chromatography\u003c/h2\u003e \u003cp\u003eSurface energy measurements of PVA and PVA-gelatine particles were conducted using finite dilution inverse gas chromatography (FD-IGC) with an iGC SEA 2000 surface energy analyser (Surface Measurement Systems Ltd., London, UK). Approximately 800 mg of each sample was packed into pre-silanized glass columns (30 cm in length, 4 mm internal diameter), sealed at both ends with silanized glass wool (Sigma-Aldrich, UK). Uniform packing of the powder bed was achieved using a jolting volumeter (Surface Measurement Systems Ltd., London, UK), which applied mechanical tapping to minimise void spaces and ensure consistent sample density throughout the column. Prior to each measurement, columns were conditioned at 30\u0026deg;C for 1 hour under a flow of dry nitrogen to eliminate adsorbed moisture and equilibrate the sample. All IGC measurements were performed under a constant nitrogen carrier gas flow rate of 10 mL/min. Methane was employed as a non-interacting reference probe to determine dead volume and calculate net retention times of the injected probes. A flame ionisation detector (FID) was used to monitor the elution profiles and determine retention times. To determine the dispersive surface energy (γd), a homologous series of n-alkanes (octane, nonane, and decane) was injected at increasing concentrations to generate fractional surface coverages between 0% and 20%. The retention behaviour of the alkanes was analysed using the Dorris and Gray method, based on peak maximum positions. The resulting adsorption isotherms were used to construct the dispersive surface energy distribution across the sample surface. To evaluate the acid\u0026ndash;base surface energy (γab), monopolar probe molecules were employed: dichloromethane (electron-acceptor, acidic) and ethyl acetate (electron-donor, basic). These were injected under the same flow conditions to quantify specific interactions between the probe and the PVA surface. Acidic (γ+) and basic (γ\u0026ndash;) parameters were derived using the van Oss\u0026ndash;Chaudhury\u0026ndash;Good (vOCG) theory. The acid\u0026ndash;base surface energy (γab) was calculated from these parameters, and the total surface energy (γt) was obtained as the sum of γd and γab.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTR146 cell culture procedures\u003c/h2\u003e \u003cp\u003eTR146 cells were grown and maintained in 75 cm\u003csup\u003e2\u003c/sup\u003e T-flasks in Ham\u0026rsquo;s F-12 cell culture media with the addition of 50mL of foetal bovine serum (FBS), 2.5 mL of 1% penicillin-streptomycin, 10 mL of 2 mM glutamine, 1 mL of gentamicin (10 mg/mL), and 1 mL of amphotericin B (250 \u0026micro;g/mL). The cells were incubated at 37\u0026deg;C, 5% CO\u003csub\u003e2\u003c/sub\u003e and 95% air. The media was changed every 2\u0026ndash;3 days and when 90% confluency was reached cells were passaged using 5 mL of Trypsin-EDTA solution and seeded onto 12-well transwell inserts at a density of 24,000 cells/cm\u003csup\u003e2\u003c/sup\u003e [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eTransepithelial electric resistance (TEER)\u003c/h2\u003e \u003cp\u003eThe ohmic resistance of cells grown on transwell inserts was measured every 2\u0026ndash;3 days (30 minutes after changing the media) during the cell culture, and before and after each permeability experiment, using an EVOM3 (Epithelial Volt/Ohm Meter) with chopstick electrodes. The electrodes were placed upright, such that the longer electrode touched the basolateral chamber, while the shorter electrode touched the apical membrane chamber. TEER, which reveals the integrity of the cellular layers, was calculated from triplicate reading from replicate transwells (n\u0026thinsp;=\u0026thinsp;9) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eIn vitro permeation studies\u003c/h2\u003e \u003cp\u003ePermeability studies were conducted as described by Nielsen and Rassing at 37\u0026deg;C and 140 rpm in an orbital plate shaker [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Formulation solutions were prepared at 1 mg in 0.5 mL of HBSS. The pH of the solutions was measured before and after the permeation study. Cells on the transwell were rinsed twice with HBSS (37\u0026deg;C) by adding 0.5 mL to the apical chamber and 1.5 mL to the basolateral chamber. After 2 hours (duration of experiment), cells were rinsed with 0.5 mL HBSS and equilibrated for 30 minutes after which TEER values were measured [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. All samples were analysed for ovalbumin content by HPLC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data were generated in triplicates, where n\u0026thinsp;=\u0026thinsp;3, and analysed for statistical significance using one-way analysis of variance (ANOVA) and Dunnett's multiple comparisons post-test from GraphPad Prism\u0026reg; version 9.4.0. The level of significance was set to P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (probability values of 95%).\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch3\u003eCompeting interests\u003c/h3\u003e\n\u003cp\u003eThe authors declare no competing financial interests\u0026nbsp;\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Biotechnology and Biological Sciences Research Council (BBSRC) Midlands Integrative Biosciences Training Partnership (MIBTP) case award in partnership with Aston Particle Technologies (APT) (BB/T00746X/1).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.R conducted the research. A.R wrote the manuscript. A.I. provided cell culture training and supervised this study. M.A.A.T provided training and conducted confocal microscopy. A.R.M. conceived the project, wrote the grant application and supervised the project. DW and JK co-authored the grant application and supervise the project. All authors reviewed, revised and approved the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNew, R. \u003cem\u003eOral Delivery of Biologics via the Intestine\u003c/em\u003e. \u003cem\u003ePharmaceutics\u003c/em\u003e, \u003cb\u003e13\u003c/b\u003e(1). (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrincado, V., Gala, R. P. \u0026amp; Morales, J. O. \u003cem\u003eBuccal and Sublingual Vaccines: A Review on Oral Mucosal Immunization and Delivery Systems\u003c/em\u003e. \u003cem\u003eVaccines (Basel)\u003c/em\u003e, \u003cb\u003e9\u003c/b\u003e(10). (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnselmo, A. C., Gokarn, Y. \u0026amp; Mitragotri, S. 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Pharm.\u003c/em\u003e \u003cb\u003e185\u003c/b\u003e (2), 215\u0026ndash;225 (1999).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"buccal delivery, biologic, ovalbumin, gelatine, coating, TR146, permeation, large molecule","lastPublishedDoi":"10.21203/rs.3.rs-8957044/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8957044/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBuccal delivery offers a non-invasive route for biologics but is limited by poor permeation and susceptibility to processing-induced structural disruption. This challenge is compounded for the delivery of biologics particularly where co-localisation of excipients is required. This study evaluated the application of a solvent-free isothermal dry particle coating (iDPC) technology for buccal permeation of ovalbumin (OVA) by co-localisation of OVA with functional excipients on a polymer carrier. Polyvinyl alcohol (PVA) was used as the host carrier and pre-coated with gelatine to modify surface properties and improve retention, before coating with OVA alongside L-lysine and α-tocopherol. iDPC coated particles were characterised by confocal microscopy, confocal Raman mapping, and inverse gas chromatography (IGC). Raman mapping confirmed surface co-localisation of OVA, L-lysine and α-tocopherol on PVA\u0026ndash;gelatine, and IGC indicated that gelatine reduced PVA surface area (1.7471 to 0.7344 m\u0026sup2;/g) and altered surface energetics towards a more uniform profile. Buccal permeation was assessed across TR146 cell layers over 120 minutes (OVA 1 mg/mL). To facilitate comparison and mitigate ceiling effects, permeation was expressed relative to the OVA control (F1\u0026thinsp;=\u0026thinsp;100%). Under this normalisation, the gelatine-containing iDPC formulation (F3) demonstrated sustained enhancement across all time points, peaking at approximately 151% of control at 30 minutes and remaining elevated at 120 minutes (approximately 114% of control). In contrast, the physically mixed formulation (F4) consistently reduced permeation relative to control, reaching approximately 65% of control at 120 minutes, while the PVA iDPC formulation (F2) remained broadly comparable to control but decreased to approximately 90% of control at 120 minutes. TEER remained stable post-study, supporting model integrity. Overall, these findings confirm iDPC combined with gelatine surface modification is an effective strategy to enhance buccal delivery of protein therapeutics through altered particle surface properties and excipient co-localisation.\u003c/p\u003e","manuscriptTitle":"Particle surface modification using isothermal dry coating to deliver biologics through the buccal route","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-13 07:15:15","doi":"10.21203/rs.3.rs-8957044/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"159d52f5-50fc-44ee-ab2e-518a11eeae80","owner":[],"postedDate":"March 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":64309670,"name":"Biological sciences/Biotechnology"},{"id":64309671,"name":"Physical sciences/Chemistry"},{"id":64309672,"name":"Physical sciences/Materials science"}],"tags":[],"updatedAt":"2026-04-10T05:10:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-13 07:15:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8957044","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8957044","identity":"rs-8957044","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}