Modelling immune gene expression profiles as pharmacodynamic endpoints of antileishmanial treatment

This is a preprint and has not been peer reviewed. Data may be preliminary. Modelling immune gene expression profiles as pharmacodynamic endpoints of antileishmanial treatment Abstract Background: Cutaneous leishmaniasis (CL), a neglected infectious disease caused by the intracellular protozoan parasite Leishmania, affects over one million people annually. The type and magnitude of the inflammatory response elicited during infection leads to skin-specific immunopathology, resulting in the clinical manifestations of CL. Systemic antileishmanial drugs are the main control measure; however, these are highly toxic, long and difficult to access for affected populations. New drugs and optimized regimens are urgently needed. Despite the known participation of immune responses in the pathology of CL, preclinical drug evaluations target parasite elimination as the efficacy measure. This overlooks the potential of host immune responses to influence therapeutic success. Methods: In this study we evaluated the performance of non-linear pharmacokinetic/pharmacodynamic (PK/PD) models in recreating the exposure-response relationships between plasma Sb concentrations in CL patients treated with Glucantime (Sb V as meglumine antimoniate), and the gene expression dynamics of pro-inflammatory mediators in peripheral blood mononuclear cells. Results: A one compartment PK model, coupled to an indirect PD model with endogenous regulators fitted the data well, explaining 80-90% of the variance. Our results suggest a mechanism of drug-dependent immune gene regulation involving modulation of cell signalling and RNA stability in CL patients who cured after treatment. Conclusions: The model presented herein can be used for evaluating immune gene expression alongside parasite kill, as PD endpoints of antileishmanials, both for new drug developments as well as in optimization of available drug regimens. Supplementary Material File (pk-pd modeling_june17.docx) - Download - 296.87 KB Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Metrics & Citations Metrics Article Usage 181views 157downloads Citations Download citation Neal Alexander, Lina Giraldo-Parra, David E. Rebellón-Sánchez, et al. Modelling immune gene expression profiles as pharmacodynamic endpoints of antileishmanial treatment. Authorea. 18 June 2025. DOI: https://doi.org/10.22541/au.175024995.51140065/v1 DOI: https://doi.org/10.22541/au.175024995.51140065/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.