{"paper_id":"1d9ccdd4-5c8c-4a4a-85e5-d1714b5eb32d","body_text":"1 \n \nNonclinical pharmacokinetics and relative efficacy of the first 25 novel 1 \ntuberculosis drug combinations from the PAN-TB consortium: Use of the 2 \nBALB/c relapsing mouse model and combination pharmacokinetics 3 \nwithin a modeling-based framework 4 \nSylvie Sordello,1 Alessia Tagliavini,2 Xavier Boulenc,3 Laure Brock,1 Simone Zannoni,2 5 \nChiara Roversi,2 Roberto Visentin,2 Darren Metcalf,4 Denise Federico,2 Simone Modolo,2 6 \nGiulia Calusi,2 Roberto Petterlini,2 Guillaume Golovkine,1 Cécile Pascal,3 Emilie Huc 7 \nClaustre,1 Zoï Vahlas,1 Marco Pergher,2 Khisimuzi Mdluli,4 Micha Levi,4 Todd A. Black,5 8 \nRobert H. Bates,6 David R Willé,7 Yongge Liu,8 Yohei Hayashi,9 Clara Aguilar-Pérez,10 9 \nDavid Hermann,11 Debra Flood,11 Anna M. Upton12 10 \n1-Translational Biology, Infection Diseases, Evotec France, Toulouse, France  11 \n2- Pharmacometrics, Aptuit (an Evotec Company), Verona, Italy   12 \n3- DMPK, Evotec Infectious Diseases Lyon, Lyon, France  13 \n4- Gates Medical Research Institute, Massachusetts, USA  14 \n5- TB Alliance, New York, USA 15 \n6- GSK Global Health Medicines R&D, Tres Cantos, Spain 16 \n7- GSK R&D, Stevenage, UK 17 \n8- Otsuka Pharmaceutical Development and Commercialization, Inc., Rockville, USA 18 \n9- Otsuka Pharmaceutical Co., Ltd., Tokyo, Japan. 19 \n10- Johnson & Johnson, Beerse, Belgium 20 \n11- Gates Foundation, Seattle, Washington, USA  21 \n12- Evotec USA inc., New Jersey, USA  22 \n 23 \n 24 \nCorresponding author 25 \nAAC Formatting Information Initial Submission Checklist  26 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n2 \n \nABSTRACT  27 \nThe Project to Accelerate New Treatments for Tuberculosis (PAN-TB) aims to accelerate 28 \ndevelopment of shorter, simpler and safer pan-TB combinations, effective for use in both 29 \nDrug Susceptible (DS)- and D rug Resistant (DR)- TB patients . Towards thi s aim, 30 \nbactericidal and sterilizing activity of  25 priority 4 -drug combinations was evaluated at 31 \ndoses targeting clinically relevant exposures, in the BALB/c relapsing mouse model of TB. 32 \nThe combinations comprised 8 PAN-TB drugs and candidates: bedaquiline (B), 33 \npretomanid (Pa), delamanid (Del), quabodepistat (Q), sutezolid (Sut), GSK2556286 (286), 34 \nGSK3211830 (830) and ganfeborole (GSK3036656, (656)). Combination PK studies in 35 \ninfected mice enabled dose selection and a population-PK approach guided dosing so that 36 \ncompounds should achieve mean AUC 0-24 within 2-fold of their clinical target exposures 37 \nduring the efficacy studies . All test combinations showed time-dependent bactericidal 38 \nactivity, with six regimens reducing lung bacterial burdens below the limit of detection 39 \nwith 8 weeks’ treatment, similar to the comparator BPaMZ (M is moxifloxacin and Z as 40 \npyrazinamide). Cure/Relapse data were modelled to derive population time to cure 90% 41 \nmice (T90)  values. Fifteen PAN-TB combinations  had T90s of  less than 5 months , 42 \nsterilizing mice faster than the standard of care for drug susceptible TB , RHZE/RH. The 43 \nbest-performing PAN-TB combinations, BPa830Sut, BPa286Sut and BQSut286, cured 44 \n90% of mice in less than 3 months. These 3 top-ranked 4-drug combinations are all centered 45 \non a diarylquinoline (B)/oxazolidinone (Sut) core, together with the nitroimidazole (Pa) or 46 \na DprE1 inhibitor (Q) plus a novel agent such as the LeuRS inhibitor (830) or the Rv1625c 47 \nagonist (286).   48 \n 49 \n  50 \nKey words: PAN-TB consortium, tuberculosis, efficacy, relapse   51 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n3 \n \nINTRODUCTION 52 \nTuberculosis (TB) remains a global health crisis with 1.25 million deaths reported in 2023 53 \n[1]. Available treatments are long, complex and poorly tolerated, resulting in suboptimal 54 \nadherence which impact s patient  outcomes. Due to  the presence of significant drug-55 \nresistance, access to rapid drug susceptibility testing  (DST) is critical  to appropriate 56 \ntreatment; the currently limited access  presents another barrier to TB control  [2]. 57 \nDevelopment of novel pan -TB combinatio ns, defined by World Health Organization  58 \n(WHO) as first-line regimens that could be used without prior knowledge of a TB patient’s 59 \ndrug-resistance profile [3], would obviate the need for DST, eliminating the time gap 60 \nbetween diagnosis and start of effective treatment. To maximize benefits, pan-TB regimens 61 \nshould be shorter, simpler, and safer than existing treatments. Introducing such regimens 62 \nin high TB burden  countries could result in substantial health improvements as well as 63 \nsavings t o patients and health systems [4]. Although progress  has been made towards 64 \ntreatments that fit WHO target regimen profiles for drug -susceptible TB (DS -TB) and 65 \nrifampicin resistant TB (RR -TB) [3], more limited progress has been made towards 66 \ndevelopment of pan-TB regimens.   67 \nThe Project to Accelerate New Treatments for Tuberculosis (PAN-TB) is a philanthropic, 68 \nnon-profit and private sector collaboration . The Collaboration aims  to accelerate 69 \nprioritization and development of promising pan-TB drug combinations  by leveraging 70 \nassets, resources, technologies and e xpertise of its members (Tuberculosis Prevention | 71 \nPAN-TB). At the outset of the Collaboration, eight candidates and marketed drugs  were 72 \nidentified among the members as PAN-TB priorities, due to their pan-TB potential (i.e. no 73 \nor limited existing clinical resistance). These comprised bedaquiline (B), an ATP synthase 74 \ninhibitor - [5], delamanid (Del) and pretomanid (Pa), two nitroimidazole mycolic acid 75 \nsynthesis inhibitors [6-7], quabodepistat (Q) an inhibitor of decaprenylphosphoryl -β-D-76 \nribose 2' -epimerase [DprE1]  [8], GSK2556286 (286) an Rv1625c agonist  and, c -AMP 77 \nmediated cholesterol catabolism inhibitor [10], sutezolid (Sut) an RNA translation inhibitor 78 \n[11], GSK3211830 (830) and ganfeborole (formerly GSK3036656, listed here as  656), 79 \nleucyl-tRNA synthetase (LeuRS) inhibitor s [9]. These two LeuRS inhibitors are close 80 \nanalogues with very similar PK and efficacy data. The consortium initially focused on 81 \ntesting 830 but later shifted toward 656 as it advanced further in the clinic.  82 \nThe Collaboration focuses on 4-drug pan-TB combinations, hypothesizing that treatment 83 \nwith 4 drugs  with novel and differing  modes of action, will maximize efficacy and 84 \nminimize emergence of resistance. Towards prioritizing the most promising 4 -drug 85 \ncombinations comprised of the initial 8 PAN-TB candidates, the Collaboration selected 25 86 \nunique regimens, avoiding inclusion of two nitroimidazoles in the same combination , for 87 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n4 \n \nnonclinical efficacy assessment. Some of the candidates had previou sly demonstrated 88 \nbactericidal efficacy and treatment -shortening activity when evaluated within TB drug 89 \ncombinations in the well-established BALB/c relapsing mouse model of TB (RMM)  [8, 90 \n12, 13, 14, 15, 16]. None had bee n evaluated within the context of these specific  25 91 \ncombinations.  92 \nThis work evaluated and compared the bactericidal and sterilizing efficacy of the 25 drug 93 \ncombinations in the BALB/c RMM of TB, at exposures relevant to clinical efficacy targets. 94 \nAn additional objective was to compare their estimated RMM time to cure parameters to 95 \nthose of clinical benchmark regimens . Benchmark TB combinations used in the reported 96 \nRMM studies included the standard of care for drug -susceptible TB, Rifampicin (R), 97 \nIsoniazid (H), Pyrazinamide (Z), Ethambutol given as RHZE/RH and BPaMZ. BPaMZ is 98 \na regimen that has been evaluated in clinical trials a nd demonstrated time to culture 99 \nconversion that was more rapid than RHZE/RH  [17]. However, the regimen did not meet 100 \nthe key secondary efficacy endpoint due to adverse events resulting in treatment 101 \nwithdrawal and additionally, includes pyrazinamide and moxifloxacin, to which there is 102 \nsignificant background resistance. Therefore, BPaMZ cannot be considered as a potential 103 \npan-TB regimen. We sought to identify pan-TB regimens with efficacy superior to BPaMZ 104 \nin this well-established mouse TB model.    105 \n  106 \n  107 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n5 \n \nRESULTS 108 \nCombination Pharmacokinetics Performed in Infected Mice Enabled Accurate 109 \nSelection of Human Equivalent Doses  110 \nThe 25 PAN-TB test combinations are listed in Table 1. Doses for evaluation in RMM 111 \nefficacy studies  were selected with the aim of achieving steady -state area under the 112 \nconcentration time curve from 0 -24 hours (AUC 0-24) for each drug, across all test 113 \ncombinations, within 2-fold of observed or targeted clinical plasma concentrations (Table 114 \n2). Preliminary dose selection was based on available mouse single drug plasma PK data 115 \nand rodent tolerability data . Doses were refined based on data generated through 5 -day 116 \nrepeat-dose combination PK studies, conducted for each test combination, administered at 117 \nthe preliminary doses to M.tb-infected mice. The average plasma AUC0-24 observed for 118 \neach drug, across the relevant 4 -drug combinations  in m ice, was compared to the 119 \ncorresponding observed or target clinical value. As a result of these comparisons, the final 120 \ndose for use in efficacy evaluations was decreased for Del, and increased for both 830 and 121 \n656, compared to the ir preliminary doses (Table 2 ). Q exposure was variable between 122 \ntested combinations. Although the median Q exposure in mice, at the preliminary dose, 123 \nwas higher than the clinical target, the final dose selected was slightly higher than the 124 \npreliminary, to ensure exposures across all test combinations were no more than 2 -fold 125 \nlower than the clinical target.   126 \nRMM p lasma exposures were within 2 -fold of their clinical targets for most 127 \ncombination components  128 \nTo evaluate PK exposure achieved during RMM efficacy studies for each drug across the 129 \ntest combinations, population PK (popPK) analysis was performed using sparse-sampled 130 \ndrug concentration data obtained after 8 weeks’ dosing during the RMM studies, together 131 \nwith data generated through the combination PK studies. Individual RMM drug exposure 132 \ndistributions across all tested combinations are shown in Figures S1-S8 and Table S2. For 133 \nmost of the tested compounds, i.e.,  656, B, Del, Pa and Sut, their overall distributions of 134 \nRMM study drug exposures  (derived plasma AUC 0-24 values) achieved after 8 weeks’ 135 \ndosing were within 2-fold of their clinical targets (Figure 1 and Table S2). The Q RMM 136 \nexposures were variable across the tested combinations: none were more than 2-fold below 137 \nthe targeted exposure, and while the median observed Q plasma AUC0-24 was slightly more 138 \nthan 2-fold higher than the clinical target, exposures were within 2-fold of the clinical target 139 \nfor 8 out of 16  of the tested Q -containing combinations, namely when Q was  co-140 \nadministered with B and in the absence of Pa (Figure S7). The 286 RMM exposures were 141 \nslightly more than 2-fold lower than its clinical target on average (Figure 1 and Table S2). 142 \nNotably, AUC0-24 values for 286 were lowest when co -administered with B (Figure S1). 143 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n6 \n \nFinally, 830 RMM exposures were more than 2 -fold lower than the clinical target in all 144 \ntested combinations (Figure S3). When comparing exposures of companion drugs between 145 \nDel- and Pa - containing regimens, B exposure is , at least two -times higher in the Pa -146 \ncontaining regimens than those with D el, except for the regimens of BD el656286 and 147 \nBPa656286, in which B exposures are similar (Figure S4). Similarly, Q exposure is more 148 \nthan two-times higher in BPaQX regimens than those in the BD elQX regimens ( Figure 149 \nS7) 150 \nSix PAN-TB drug combinations demonstrated bactericidal activity in mice that was 151 \nat least as rapid as BPaMZ. 152 \nAll 25 4-drug combinations demonstrated time -dependent bactericidal activity over the 153 \ncourse of 8 weeks’ treatment  (Figures 2A and 2B). BPa286Sut and BQSut286 reduced 154 \nlung CFU to undetectable levels following 4 weeks of treatment, whereas BDel286Sut, 155 \nBDel830Sut, BPa830Sut, BPaQSut and BPaMZ required 8 weeks’ treatment. For the other 156 \n19 test combinations, as for the benchmark RHZE/RH, colonies were still detectable after 157 \n8-weeks' treatment (Figures 2A and 2B). However, 15 of these 19 reduced the mouse lung 158 \nbacterial burden (CFU/ lung) to a  greater extent than RHZE/RH by the 8 week treatment 159 \ntimepoint: BPa656286, BQ656286, BQ656Sut, BDelQSut, BDelQ286, BDelQ830, 160 \nBDel656286, PaQSut286, PaQ656Sut  reduced bacterial burden by an additional 2Log10, 161 \nand BDelQ830, BPaQ286, B656286Sut, PaQ656286, Del656 286Sut, BPaQ656 reduced 162 \nCFU/ lung by an additional 1Log10 compared to RHZE/RH (Tables 3A and 3B).   163 \nThree PAN-TB 4-drug combinations cured 90% of mice in less than 3 months , out-164 \nperforming RHZE/RH but not BPaMZ   165 \nTo establish the relationship between the tested regimens and length of treatment required 166 \nto achieve a durable cure in mice, we quantified the proportion of mice that were culture 167 \npositive twelve weeks after the end of treatment  (i.e. exhibiting relapse) (Tables 4A and 168 \n4B). No relapse events were recorded for any BPaMZ -treated mice after 6  weeks’ 169 \ntreatment. In contrast, at least 16 weeks’ treatment were required to achieve 100% cure (no 170 \nrelapse) for RHZE/RH . Of the PAN -TB test combinations, the best -performing were 171 \nBPa830Sut (100% mice cured after 8 weeks’ treatment ) and BPa286Sut, which cured all 172 \nmice after 10 weeks’ treatment. Six additional test combinations demonstrated 100% cure 173 \nafter 12 weeks of treatment (Table 4A). On the other hand, 8 of the 25 test combinations 174 \nfailed to effect cure after 12 weeks’ treatment:  all mice had detectable colonies (relapse) 175 \n12 weeks after treatment cessation (Table 4A and B). 176 \nA logistic Emax model was developed based on observed cure/relapse data reported herein 177 \nplus a historical dataset and used to estimate time-to-cure 50% of mice (T50), and time-to-178 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n7 \n \ncure 90% of mice (T90) for each combination  [23, 37]. Combinations for which 100% 179 \nrelapse was still observed after the maximum treatment duration were  excluded. The 180 \ndeveloped model, using a population approach, demonstrated generally good performance 181 \nin predicting relapse profiles of the 4 -drug combinations, especially for comparators  182 \nBPaMZ and RHZE/RH  for which data coming from different studies and labs were 183 \navailable (Figure S9). Individual probability of relapse-time curves for each combination 184 \nby study are shown in Figure 3. The corresponding estimated population T50 and derived 185 \nT90 values are listed in Table 5. T90 values for the 17 analyzed novel combinations ranged 186 \nfrom 2 to 6 months, whereas the T90 for the RHZE/RH comparator was approximately 5 187 \nmonths. Fifteen combinations performed better than RHZE/RH, with shorter T90s (Table 188 \n5 and Figure 3). Of these, BDel286Sut, BPa656286, BQ656286, BPaQSut, BDelQ286, 189 \nBPaQ286 displayed a T90 of less than 4 months. The best-performing novel combinations, 190 \nBPa830Sut, BPa286Sut, and BQSut286, had a derived population T90 less than 3 months 191 \nwith values of 2.11, 2.51 and 2.94 months respectively. None of the test combinations had 192 \npopulation time-to-cure parameter estimates T50 or T90 that were  as low as for  BPaMZ 193 \n(T90 of approximately one month ). When compared to population derived T90s for the 194 \ncombinations included in the historical dataset, s ome novel PAN-TB combinations  195 \nappeared to have out-performed clinical reference combinations in this BALB/c mouse 196 \nmodel (Figure 4) . For example, BPa 830Sut and BPa286Sut  displayed T90s similar to 197 \nBPaL (2.28 months) which is used for treatment of adults with Extensively Drug-resistant 198 \nTB (XDR-TB) or drug-intolerant or non-responsive Multi-Drug-Resistant TB (MDR-TB) 199 \nusing a 6-month regimen [6] (Table 5 and Figure 4).  200 \nComparison of T90s for combinations differing by one drug , indicate treatment-201 \nshortening contributions for several PAN -TB candidates,  that may be context 202 \ndependent  203 \nPairwise comparisons of T90 values were performed for 4-drug combinations differing in 204 \nonly one component.  In all cases, the presence of B reduced the T90 values and among 205 \nevaluable comparisons, the T90 differences were statistically significant (p < 0.05) (Table 206 \n6 and Table S3). For combinations differing only in the  nitroimidazole (Pa versus Del), 207 \nseveral that contained Pa had a shorter population derived T90 value, compared to those 208 \ncontaining Del: Significant differences in T90s were observed  for BPa830Sut vs 209 \nBDel830Sut (2.1 vs 5.1 months);  BPaQSut vs BDelQSut (3.5 vs 4.6 months); BPa656286 210 \nvs BDel656286 (3.4 vs 4.3 months); and BPa286Sut vs BDel286Sut (2.5 vs 3.2 months) . 211 \n(Table 6 and Table S3). However, exposures of B and Q are about 2-times higher in Pa 212 \ncontaining regimens than those of in the D el-containing regimens. Therefore, this 213 \ndifference between Pa and D el may be partly explained by the different drug -drug 214 \ninteractions in this mouse model.  For certain 4-drug combinations population T90 values 215 \ndid not differ when Q replaced a nitroimidazole : no significant differences or a low level 216 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n8 \n \nof confidence in the difference were observed between T90s for BQSut286 vs  BDel286Sut 217 \n(2.9 vs 3.2 months) or BQ 656286 vs  BPa656286 (3.4 vs 3.4 months) or  BQSut286 vs 218 \nBPa286Sut ( 2.9 vs 2.5 months ). On the other hand, r eplacing Del with Q significantly 219 \nreduced the T90 for  BDel656286 vs BQ656286 (4.3 vs 3.4 months) (Table 6 and Table 220 \nS3).  221 \nThe presence of 286 had a variable impact on  4-drug combination T90 depending on the 222 \ncompanion drugs. A reduction in T90 (faster cure) was observed when 286 replaced Q in 223 \nall tested regimens  (BDel286Sut vs BDelQSut (3.2 vs 4.6 months)  or BPa286Sut  vs 224 \nBPaQSut (2.5 vs 3.5 months )), and when 286 replaced 830, 656 or Sut in some tested 225 \nregimens: (BDel286Sut vs BDel830Sut (3.2 vs 5.1 months); BQ656286 vs BQ656Sut (3.4 226 \nvs 4.0 months) ; BDelQ286 vs BDelQSut (3.6 vs 4.6 months)  and BDel656286  vs 227 \nBDel830Sut (4.3 vs 5.1 months)). Finally, the presence of Sut significantly reduced 228 \n(improved) the T90 when it replaced 656 (BPaQSut vs BPaQ656 ( 3.5 vs 4.4 months) or 229 \nBQSut286 vs BQ656286 ( 2.9 vs 3.4 months) . As for B, Sut was present in all 3 best -230 \nperforming 4-drug combinations that displayed the shortest T90s: BPa830Sut, BPa286Sut 231 \nand BQSut286.  232 \nIn addition to these T90 pairwise comparisons , AUC0-24 ratios (AUCratio) were calculated 233 \nand compared for each of the 3 common drugs between pairs of combinations that differed 234 \nby only one drug. Overall, when only one drug differed, exposure ratios for the common 235 \ndrugs in paired combinations were variable  -, although some significant ratios were 236 \nobserved (p < 0.001) very few are more than 2-fold. (Table 6 and Table S3).  237 \n DISCUSSION  238 \nThis translational research  utilized the well-established BALB/c TB RMM within a 239 \nmodelling-based framework to evaluate and compare bactericidal and sterilizing efficacy 240 \nof 25 novel 4 -drug combinations of 8 PAN-TB candidate drugs, administered at dose s 241 \ntargeting clinically-relevant exposures. The absolute and relative time -dependent 242 \nbactericidal activities of the RHZE/RH and BPaMZ regimens , as observed  here, were 243 \nconsistent with previous data published by Evotec and others [18, 19, 20]. Time-dependent 244 \nsterilizing activity, evaluated by modelling BALB/c RMM data, has been estimated using 245 \nvarying methodologies by several groups. Despite these differing approaches, the derived 246 \npopulation T90s for RHZE/RH and BPaMZ in the present study are consistent with 247 \npublished values [21, 22, 23]. We identified 15 novel PAN-TB 4-drug combinations - i.e. 248 \nwith relevance to the WHO pan -TB Target Regimen Profile - with shorter time to cure 249 \n(population derived T90)  in this model  than the current standard of care for DS-TB, 250 \nRHZE/RH.  251 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n9 \n \nThe best -performing combinations , BPa830Sut, BPa286Sut, and BQSut286 , achieved 252 \nT90s of less than 3 months in this BALB/c TB model and for BPa830Sut and BPa286Sut, 253 \nT90 values were similar to BPaL. This means that if developable and safe, these 2 regimens 254 \ncould represent alternatives to BPaL with a pan-TB potential.    255 \nNone of the PAN -TB combinations cured mice as rapidly as the benchmark regimen 256 \nBPaMZ, which demonstrated potential to cure patients in less time than RHZE/RH in 257 \nclinical trials. However, it is promising that several novel 4 -drug combinations with pan-258 \nTB potential cured BALB/c mice faster than RHZE/RH and at least as rapidly as BPaL. 259 \nFurther, both BPa286Sut and BQSut286 demonstrated rapid bactericidal activity, similar 260 \nto that of BPaMZ. Rapidly bactericidal regimens may be beneficial by quickly reducing 261 \nsymptoms and infectiousness of TB patients, positively influencing patient and population 262 \nlevel outcomes. The observation that BPa286Sut and BQSut286 did not match the cure rate 263 \nof BPaMZ even after demonstrating similar bactericidal activity is interesting and deserves 264 \nfurther attention. First, it underscores what has always been known in TB therapy that rapid 265 \nelimination of replicating organisms does not necessarily lead to rapid sterilization and 266 \nlasting cure, even for regimens that contain highly efficacious and long half-life agents like 267 \nB. Second, it points to a certain sterilizing activity for M and Z, the two agents in BPaMZ, 268 \nand demands a concerted effort in the field to find agents with similar sterilizing potential. 269 \nAll 10 PAN-TB combinations that demonstrated T90s of less than 4 months contained B - 270 \nincluding the 5 with the most rapid  bactericidal activity . In contrast , most B-free 271 \ncombinations didn’t clear lung bacteria after 8 weeks’  treatment or cure mice  after 12 272 \nweeks of treatment. Both these findings  highlight the potentially significant contribution 273 \nof B and possibly other diarylquinolines to pan-TB treatments. This is in line with previous 274 \nwork demonstrating  the importance of  this ATP-synthase inhibitor class in the  TB 275 \ntreatment backbone [13, 19, 24 ]. The introduction of B has significantly improv ed 276 \ntreatment outcomes and survival among patients with MDR/XDR-TB.  However, since its 277 \nimplementation in 2012, reports of B resistance have emerged [26]. The identification of 278 \npotent B-free regimens is therefore of interest . The novel B -free 4 -drug combination  279 \nDelQSut286 demonstrated a slightly shorter T90 than  RHZE/RH (by 0.4 months) in this 280 \nstudy, offering a qualified hope for B-free regimen for the future. 281 \nThese results also confirmed the contribution of protein synthesis inhibitors to the 282 \nperformance of novel regimens, with the oxazolidinone Sut present in all 3 combinations 283 \nwith T90s of less than 3 months. Indeed, interest in Sut as a potential novel TB drug led to 284 \nits evaluation as part of regimens in the Phase2b SUDOCU trial [ 39] and the PAN -TB 285 \nGates MRI-TBD06-21-trial (Int J Tuberc Lung Dis 2025: 29 (11 Suppl 1): S1 – S963). 286 \nFurther, the novel drug candidate 286, which inhibits cholesterol metabolism [3] - a new 287 \nmode of action for potential TB drugs - is included in 2 of the top 3. The sterilizing activity 288 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n10 \n \nobserved here for BPa286Sut is similar to published data for BPa286L, where full 289 \nsterilization of mice was achieved within 3 months [12]. L, like Sut, is an oxazolidinone 290 \ndrug and has demonstrated treatment-shortening activity in mice [16, 17] . Notably, in the 291 \nstudy of Nuermberger et al [12], undetectable levels of mouse lung CFU were reached after 292 \n2 months of treatment with BPa286L as opposed to 4 weeks for BPa286Sut in our study. 293 \nThis difference in bactericidal kinetics may be related to a more potent bactericidal activity 294 \nof Sut, compared to L, as shown in the study of Tasneen et al [24]. In addition to Sut, the 295 \noxaborole leucyl tRNA synthetase inhibitor 830 was present in one of the top 3 regimens, 296 \ndemonstrating the potential utility of this novel mechanism of action which also inhibits 297 \nprotein synthesis, for the treatment of TB. 298 \nThis is the first time preclinical studies have compared head-to-head bactericidal and 299 \nsterilizing activity for drug combinations including  the two nitroimidazole drugs Pa and 300 \nDel, at doses confirmed to be relevant to their respective clinical exposures. In these 301 \nstudies, Pa was dose d at 40 mg/kg and Del at 2  mg/kg, lower doses than used in some 302 \npreviously published BALB/c RMM studies  [13, 14, 27]. Overall, and especially when 303 \nconsidering T90s, the Pa-containing combinations tested here performed better than those 304 \ncontaining Del. However, exposures of B and Q are about 2-times higher in Pa containing 305 \nregimens than those of in the D el-containing regimens. Since B is a known potent 306 \nsterilizing drug, this difference between Pa - and Del-containing regimens may be partly 307 \nexplained by the different drug -drug interactions in this mouse model.  Whether similar 308 \ndrug-drug interactions occur in humans will need to be carefully evaluated.  In previous 309 \nwork conducted to compare  their bactericidal activity as monotherapies  in two mouse 310 \nmodels, Del at 2.5 mg/kg demonstrated similar efficacy to Pa at 20 mg/kg and 30 mg/kg  311 \n[22]. Our results are consistent with this outcome, taking into account the higher dose and 312 \npresumably exposure of Pa used in our studies . Interestingly, the difference observed in 313 \nsterilizing activity between Pa-containing and Del-containing matched combinations was 314 \nsometimes but not always observed when comparing their relative bactericidal activity. For 315 \nexample, whereas BPa286Sut and BDel286Sut reduced lung CFU to undetectable levels at 316 \nthe end of 4 and 8 weeks ’ treatment respectively, with corresponding T90s of 2.5 vs 3.2 317 \nmonths, this correlation between bactericidal and sterilizing activities was not observed for 318 \nBPa830Sut and BDel830Sut. Both regimens reduced bacterial levels to undetectable levels 319 \nwith 8 weeks’ treatment, whereas there is a 3-month difference in T90 between the two 320 \ncombinations (T90s of  2.1 and 5.1 months respectively) . Further work is needed to 321 \nunderstand the drivers of sterilizing versus bactericidal activity for these combinations and 322 \nto identify the PK and/or PD factors driving the differentiation in behavior between these 323 \ntwo sets of nitroimidazole-containing combinations. Some possible contributors are greater 324 \npost-antibiotic effect ( PAE) for Pa than for Del [28], differentiated PD interactions with 325 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n11 \n \ncompanion drugs for Pa versus Del, and  differing impacts on exposures of highly 326 \nefficacious companion drugs for the two nitroimidazoles.  327 \n 328 \nOur pop-PK analysis indicated that differences in T90s were associated with significantly 329 \nlower AUC0-24 values for B or Q, or both, in Del-containing combinations compared to the 330 \nPa-containing equivalents while exposure was in the 2x range of clinical target for almost 331 \nall the comparisons . B exposure in BDelQ830 is the lowest compared to  all other B-332 \ncontaining combinations and significantly lower (more than 2-fold) compared to BPaQ656.  333 \n(Table 6, Figure S4, Table S3).  In other hand, this analysis indicated that differences in 334 \ndifferences in time to cure were associated with a significant lower AUC0-24 values for Q 335 \nin all B-free combinations compared to the B- containing combinations (Table 6, Table 336 \nS3). More generally, numerical results, included in Table S3, suggest variable relationships 337 \nbetween drug exposure variations and T90 changes. Although some statistically significant 338 \nAUCratio were observed,  most of them are not clinically relevant as they are within the 2-339 \nfold range of clinical target , it is difficult to identify associations between drug exposure 340 \nand sterilization activity, as significant T90 reductions occur together with either increased 341 \nor reduced AUCratio (i.e., >2 or <.0.5, respectively) across paired combinations where one 342 \ndrug differs.   Overall, this exploratory analysis highlights that observed exposure-T90 343 \nassociations must be treated with caution , in the absence of established PK -PD 344 \nrelationships for each compound within the context of these specific 4-drug combinations. 345 \nFurther caution should be exercised when considering translation:  any PK drug -drug 346 \ninteraction occurring which may be responsible for observed changes in AUC ratios when 347 \none drug is substituted for another, may not translat e from mouse to human considering 348 \nmetabolic and/or transporter mechanisms that influence drug (parent and/or metabolite) 349 \ndisposition may differ.  350 \n 351 \nSimilar to B-free combinations, nitroimidazole-free combinations are of interest for their  352 \nutility against nitroimidazole -resistant TB which may emerge in the future  [30]. We 353 \nevaluated the sterilizing activity  of the DprE1 inhibitor Q, within multiple 4 -drug 354 \ncombinations, for the first time . When either Pa or Del was replaced by Q,  these 355 \nnitroimidazole-free combinations performed as well as the corresponding Pa - containing 356 \ncombinations (i.e. BQSut286; T90 < 3 months) suggesting a similar sterilizing contribution 357 \nof this DprE1 inhibitor compared to nitroimidazoles, in these particular combinations. The 358 \nrecently reported evaluation of Q together with B and Del in a Phase II clinical trial 359 \nsupports the positive performance of Q within nitroimidazole-containing drug 360 \ncombinations [29]. Our mouse study suggest s Q might be useful in  nitroimidazole-free 361 \nregimens 362 \n 363 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n12 \n \nThe datasets and modeling approaches used in this work allowed us to compare efficacy of 364 \ncombinations across studies and to historical data, to compare exposures achi eved in PD 365 \nstudies to clinical targets and to explore comparative contributions of drugs using PK and 366 \nPD data. However, further investigation of PK/PD for each agent within the combinations 367 \nof interest, and direct comparisons of PK and PD for 4 -drug combinations versus their 3-368 \ndrug components, are needed to better understand the contributions of each agent and, in 369 \nsome cases, their active metabolites, to overall combination efficacy, exposure-response 370 \nrelationships and potential PK or PD drug-drug interactions. 371 \n  372 \nThese studies constitute the first step in PAN -TB's nonclinical strategy to prioritize and 373 \ncharacterize novel drug combinations to support decision-making and progression through 374 \ndevelopment. The use of this  well-established mouse model together with careful dose 375 \nselection and exposure evaluation, allowed us to assess  and compare  bactericidal and 376 \nsterilizing activity of large numbers of drug combinations at relevant exposures in mice as 377 \na first step towards prioritization and characterization. The population model ling 378 \napproaches used for both T90 derivation and PK allowed us to rank combinations with 379 \nhistorically tested combinations, across studies and understand the relationship between 380 \nduration of treatment and cure for each tested combinations  while reducing the overall 381 \nnumber of mice required . Although the T90 rankings from these BALB/c data  appeared 382 \ngenerally consistent with clinical results, the model has limitations, including pathology 383 \nthat does not include all lesion types seen in TB patients (e.g those exhibiting caseous 384 \nnecrosis and cavitation).  385 \n 386 \nFor this reason, the extent to which findings from BALB/c RMM studies translate to the 387 \nclinic is hard to predict  without further clinical data for comparison to mouse -tested 388 \ncombinations or BALB/c mouse RMM data for regimens recently evaluated in the clinic  389 \n(e.g Rifapentine (P)HMZ) [31]. Notably, the recently completed Gates MRI -TBD06-201 390 \nPAN-TB trial, which evaluated the PAN -TB investigational regimens DBQS and PBQS, 391 \nconcluded that although both regimens demonstrated strong bactericidal activity by the end 392 \nof treatment when administered for 4 months neither, showed sufficient evidence for being 393 \nable to treat TB in 3 months or less  based on 2- and 3-month sputum culture conversion 394 \nrates and TB recurrences after treatment completion . When assessed by 12 -month post-395 \nrandomization unfavorable outcome rates, the 4-month PBQS regimen performed similarly 396 \nto 6-month HRZE (Int J Tuberc Lung Dis 2025: 29 (11 Suppl 1): S1 – S963).  397 \n 398 \nThese findings are consistent with the data reported here, where BPaQS ut and BDelQSut 399 \nT90s are 3.48 and 4.6 months, respectively compared with RHZE/RH which cured 90% of 400 \nmice in 5.09 months. 401 \n 402 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n13 \n \n 403 \nFor combinations of interest identified through these studies, as well as those prioritized 404 \nbased on subsequent BALB/c RMM studies, PAN -TB intends to generate significant 405 \nadditional nonclinical data for use as translational model ling inputs for prediction of 406 \nclinical performance and to support decision-making. Some examples include nonclinical 407 \nlesion PK studies, activity studies in caseum (using an ex vivo assay), and evaluation of 408 \nT90s in mouse models featuring caseous necrotic lesions (the Kramnik RMM). Evaluation 409 \nof p erformance of combinations against mouse models where the  infecting strain is 410 \nresistant to a key drug class will also be important. Finally, combination efficacy studies 411 \nwill be conducted in mouse models to better understand the individual contributions of 412 \neach agent, to confirm the ir pharmacological value and to inform future regimen design. 413 \nPromising data has been recently reported for both newer diarylquinolines (e.g. 414 \nsorfequiline (TBAJ-876) [25]) and oxazolidinones (e.g. TBD09 –[32]) as well as for 415 \nTBD11, a compound from a different chemical series with a similar mechanism of action 416 \nas 286, suggest potential to improve on the high -performing first generation PAN -TB 417 \nregimens by introducing these next generation compounds. Accordingly, the PAN -TB 418 \ncollaboration has introduced sorfequiline, TBD09 and TBD11 to its candidate pool and in 419 \naddition to seeking a better understanding of the top performing regimens reported here, is 420 \nconducting further BALB/c RMM studies using th e above  workflow, to evaluate and 421 \ncompare their bactericidal and sterilizing activities at exposures likely to be targeted in the 422 \nclinic in potential next generation regimens. The most important outcome of this first study 423 \nfrom the PAN -TB consortium has been the successful assembly of novel drugs from 424 \ndifferent partner organizations and designing and testing drug combinations in a consistent 425 \nformat that will highlight the most promising regimens ready for direct clinical evaluation, 426 \nthus reducing the time to delivery of these needed interventions to patients. 427 \n 428 \nMATERIAL AND METHODS 429 \nAnimals and ethics 430 \nAll mouse experiments were carried out at the Evotec France SAS animal facility. This 431 \nfacility is accredited by the French Ministry of Agriculture and by the Association for 432 \nAssessment and Accreditation of Laboratory Animal Care International (AAALAC). All 433 \nstudies were performed under the European Communities Council Directive 434 \n(2010/063/EU) for the care and use of laboratory animals and approved by local Ethical 435 \nCommittee CEPAL: CE 029 and authorized by the French Ministry of Education, 436 \nAdvanced Studies , and Research. Six-week-old female BALB/cJRj mice from Janvier 437 \nLaboratories were group housed in bioconfined cages (Isocage, Tecniplast®) under a 12h 438 \nlight:12h dark with free access to filtered water and a standard rodent diet (AO4C, Safe, 439 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n14 \n \nFrance). An ambient temperature of 22 ± 2°C, a relative humidity of 55 ± 10 % , and a 440 \nnegative pressure of -20Pa were maintained throughout the study.  All mice were allowed 441 \nto acclimatize to their new environment for at least 5 days prior to the start of the study. 442 \nDrug Formulations and Dosing Strategies 443 \nDrugs were acquired  or provided by PAN -TB consortium members , and formulations 444 \nprepared for dosing as follows at the selected doses (Table 2). B (J&J IM) was formulated 445 \nin 20% 2 -hydroxypropy-β-cyclodextrin; Pa (TB Alliance) was formulated in 10% 446 \nHydroxy-propyl-beta-cyclodextrin and 2% soy lecithin for dosing at 100mg/kg for the 447 \nBPaMZ control group, and at 40 mg/kg for the PAN -TB 4-drug combinations. M (LTK 448 \nLaboratories) and Z (Sigma) were co-formulated in water for dosing at 100mg/kg and 150 449 \nmg/kg, respectively. R (Sigma) was prepared in water for dosing at 10 mg/kg; H (Sigma), 450 \nZ (Sigma) and E (Sigma) were co-formulated in water for dosing at 10, 150 and 100mg/kg, 451 \nrespectively. Del (Otsuka) and Q (Otsuka) were formulated in 5% Arabic gum. 286 (GSK), 452 \n656 (GSK) and 830 (GSK) were formulated in 1% methylcellulose solution. Sut (TB 453 \nAlliance) was formulated in 0.5% methylcellulose and 5% PEG200 . For each PAN-TB 454 \ncombination, each drug was dosed individually with an interval of 2 hours between each 455 \ndrug. The order of dosing for each drug in each combination was based on the half-life of 456 \neach drug where drugs with longest half -lives were administered first and drugs with 457 \nshorter half-lives were given later in the day. The drug dosing order for each combination 458 \nis indicated in the name of the combination i.e. the drug listed first was dosed first, and so 459 \non. For the BPaMZ comparator, B was administered first, followed by Pa and finally MZ, 460 \ndosed as a co-formulation. For the RHZE/RH comparator, R was dosed individually  for 461 \nthe first 8 weeks, followed by co-formulated HZE. For the following 8 weeks, R and H 462 \nwere dosed individually. The same 2h interval was applied between 2 administrations for 463 \nthe comparators as for the test combinations.  464 \nRelapsing Mouse Model  465 \nThe 25 PAN -TB combinations were evaluated across two RMM studies. The first 12 466 \ncombinations were tested in Study 1 (named Wave 2022 in the C-PATH APEX database: 467 \nhttps://c-path.org/tools-platforms/tb-apex) and the second 13  combinations in Study 2 468 \n(named Wave 2023 in the C-PATH APEX database: https://c-path.org/tools-platforms/tb-469 \napex). BPaMZ and RHZE/RH comparators were included as controls in each Study. Both 470 \nstudies included 4  to 6 mice per group, per time point, allocated following a similar 471 \napproach to that reported  previously [23] and described in Table S1. M.tb H37Rv stock 472 \nsolution was prepared at exponential growth phase in 7H9 medium / 10% OADC (oleic 473 \nacid-albumin dextrose-catalase) / 15% glycerol. At Day -14, female BALB/c mice were 474 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n15 \n \nanaesthetized with 2.5% isoflurane in 97.5% oxygen and were intranasally infected with 475 \n50µL M.tb H37Rv at an inoculum level of 4.5 Log 10 CFU/mouse.. Treatment started 14 476 \ndays post infection, designated Day 0. All drug combinations except RHZE/RH were dosed 477 \nonce daily by oral gavage for 5 days a week (omitting the weekend) for 2, 4, 6, 8, 10, or 12 478 \nweeks. RHZE/RH was dosed for 2, 4, 6, 8, 10, 12, 14 or 16 weeks where RHZE was given 479 \nfor the first 8 weeks followed by RH only for the following 8 weeks. For analysis of mouse 480 \nlung bacterial burden at the end of each designated treatment period, mice were sacrificed 481 \n24h post last dosing. For relapse assessment, mice were sacrificed 12 weeks after the end 482 \nof each designated treatment period. Following sacrifice, lungs were collected , weighed 483 \nand lung samples homogenized and plated undiluted, or serially diluted on 7H11-OADC + 484 \n0.4% activated charcoal. Plates were incubated at 37°C for 6 weeks for CFU quantification. 485 \nUndetectable level was considered when no colonies were observed in all plates for the 486 \nsample.  487 \n 488 \nPharmacokinetics 489 \nCombination PK studies were conducted , before the RMM studies, in  female BALB/c 490 \nmice, intranasally infected with M.tb H37Rv in the same manner as for the RMM studies 491 \n(see RMM section of Materials and Methods) . Beginning 14 days post-infection (Day 0) 492 \n24 mice per group were treated with each test combination via oral gavage  either once or 493 \nonce daily for 5 days. The 5-day dosing period was selected based on the short terminal 494 \nhalf-lives of the drugs ( Table S3), suggesting at least 80% of the s teady-state is reached 495 \nafter 5 days treatment duration (5 days > 5 times of  T1/2). The only exception is the 496 \nbedaquiline M2 (desmethyl) metabolite (B -M2), which  exhibits a longer half -life. It is 497 \nassumed that the late sparse PK samples in  the RMM study (Week 8) provide enough 498 \ninformation to correctly estimate the PK parameters for this entity. Doses were selected 499 \nbased on historical data from PAN-TB members. The order and spacing of administrations 500 \nwere performed as for the RMM studies (see Dose Formulations and Dosing Strategies) . 501 \nBlood samples were collected from the tail vein on days 1 (after single dosing) and 5 (after 502 \nonce daily repeat administration) at 0.5, 2.5, 5.5, 7.5, 10, 12, 14, 24, 36, 29, and 31 hours 503 \npost administration of the first drug. Additionally, for each combination, plasma and blood 504 \nintra-cardiac concentrations were assessed on Day 1 and Day 5 at 2.5, 7.5, 14, and 31 hours 505 \npost-first compound dosing. During RMM studies, on the 5 th day of the 8 th week of 506 \ntreatment, blood was collected from the tail vein at 0.5, 2.5, 5.5, 7.5, 9 and 24 hours post -507 \nfirst compound dosing. In all cases, after blood processing, each compound, including B -508 \nM2, and the active (sulfoxide) metabolite of sutezolid (PNU -101603) were quantified by 509 \nliquid chromatography tandem mass spectrometry (LC -MS/MS). Bioanalytical methods, 510 \nsamples handling, as well as MS conditions are described in supplemental data. All PK 511 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n16 \n \nassessments were conducted in blood. Blood and plasma concentrations determined 512 \nthrough the Combination PK studies were used to calculate mouse geometric mean Blood-513 \nto-Plasma (BP) ratios ( Table 2 ) for each drug . These values were used  to facilitate 514 \ntranslation of blood to plasma exposure  values for head -to-head comparison s between 515 \nobserved mouse and clinical target exposures (see Population PK Modelling).  516 \n Population PK Modelling 517 \nFor each compound tested across the 25 PAN-TB combinations, a population 518 \npharmacokinetic (popPK) model was developed to describe the mouse PK profile. After 519 \nidentifying each specific model, post-hoc estimates were used to calculate total exposures, 520 \ni.e. AUC0-24, accounting for the variability observed across animals in terms of summary 521 \nstatistics (median, 5 th, 25th, 75th and 95th percentiles). Blood concentration data collected 522 \nduring the RMMs were pooled with those collected in the Combination PK studies to 523 \nensure a sufficient number of observations required for robust model development  and 524 \nparameters estimation. More details about model selection criteria are provided in the 525 \nsupplemental material (see PopPK model verification and quality criteria). For B and Sut 526 \ntheir main active metabolites , B-M2 and PNU-101603 respectively, were included in the 527 \nmodel description to derive the overall exposure. As the parent drug and corresponding 528 \nmetabolite contribute to efficacy in mouse and human at different relative levels  [33, 34, 529 \n35, 36], the active moiety approach was adopted to compare the relevance of preclinical 530 \nexposure values to clinical exposures, considering the plasma AUC 0-24/MIC90 ratios 531 \n(AUC24MIC) in both human and mouse: 532 \n𝐴𝑈𝐶24𝑀𝐼𝐶 = (𝐴𝑈𝐶24\n𝑀𝐼𝐶 )\n𝑝𝑎𝑟𝑒𝑛𝑡\n+ (𝐴𝑈𝐶24\n𝑀𝐼𝐶 )\n𝑚𝑒𝑡𝑎𝑏𝑜𝑙𝑖𝑡𝑒\n 533 \nTo enable comparisons of mouse exposures against clinical plasma targets, simulated blood 534 \nconcentrations were converted to plasma values using the compound -specific geometric 535 \nmean Blood-to-Plasma (BP) ratio (Table 2). The area under the curve, during the 24 hours 536 \npost drug administration (AUC0-24, ngh/mL) was determined, assuming a dense simulation 537 \ntime grid (i.e., 0.1 h sampling frequency) which enabled robust determination of the total 538 \nexposure in plasma. PopPK modelling was performed with Monolix Suite® (Build 2024R1, 539 \nLixoft) running on a Windows 11, 64 -bit operating system. All models were identified 540 \nusing a Stochastic Approximation Expectation-Maximization ( SAEM) algorithm. All 541 \nanalyses for the extrapolation of exposure metrics were performed using R Statistical 542 \nSoftware (v4.4.2; R Core Team 2024).  543 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n17 \n \nLogistic Emax Model 544 \nA logistic Emax model was applied, as previously described [23] using data obtained from 545 \nStudy 1 and Study 2  plus a historical dataset. The historical dataset  consisted of data 546 \nutilized in previous modelling efforts  [37] as well as other literature data [19, 38, 39] and 547 \nunpublished historical data generated at Evotec . The Evotec internal studies  assessed 548 \nefficacy of RHZ/RH, BPaL and PaMZ dosed 5/7 or 7/7 days per week in a BALB/c RMM 549 \nand data from these studies  is available via the  C-PATH APEX platform  (https://c-550 \npath.org/tools-platforms/tb-apex).  551 \nData were pooled from the same treatment group collected from different studies (i.e. 552 \nwithin the historical and present datasets). For each combination, i and study k, γ and T50 553 \nparameters were estimated and subsequently used to calculate the related T90, according 554 \nto the following formula: 555 \n𝑇90𝑖 = 10\n𝑙𝑜𝑔10(𝑇50𝑖)+( 1\n𝛾′𝑖\n𝑙𝑜𝑔10( 90\n100−90))\n  (Population) 556 \n𝑇90𝑖𝑘 = 10\n𝑙𝑜𝑔10(𝑇50𝑖𝑘)+( 1\n𝛾′𝑖\n𝑙𝑜𝑔10( 90\n100−90))\n (Individual) 557 \nPopulation parameters T50 and T90 enabled characterization of the average time to 50% 558 \nor 90% cure respectively, for a particular combination across studies, independent of study-559 \nrelated factors (e.g., starting inoculum), while individual parameters (e.g. T50ik and T90ik) 560 \nprovide the average time to 50% or 90% cure for each specific study. To limit the number 561 \nof parameters to be estimated and overcome identifiability issues , c ombinations in the 562 \nhistorical dataset that share the same drugs but were administered at different dose levels 563 \nor with differing dose schedules were parametrized with different T50 parameters, 564 \nassuming the same γ value (i.e. steepness of the relapse -time curve). To estimate model 565 \nprecision and support comparison s of the combinations, confidence intervals (CI) were 566 \ncomputed for T90s. Since T90 was derived from T50 and γ estimates, the delta method 567 \n[41] was employed to compute an approximation of its standard error (SE), assuming that 568 \ncorrelation between T50 and γ is negligible (assessed by the non -parametric Spearman 569 \ncorrelation test being T50 and γ not normally distributed, with p -value lower than 0.05 570 \nconsidered statistically significant) . Once T90  SE had been obtained, 2.5 th and 97.5 th 571 \npercentiles (i.e. CI lower limit  and C Iupper limit , respectively) were computed for each 572 \ncombination by assuming normally distributed data, as follows: 573 \n𝑇90 𝐶𝐼𝑙𝑜𝑤𝑒𝑟 𝑙𝑖𝑚𝑖𝑡  = 𝑇90 − 𝑆𝐸 ∗ 1.96 574 \n𝑇90 𝐶𝐼𝑢𝑝𝑝𝑒𝑟 𝑙𝑖𝑚𝑖𝑡  = 𝑇90 + 𝑆𝐸 ∗ 1.96 575 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n18 \n \nThe logistic Emax model was developed using NONMEM® 7.5.1 and data handling was 576 \nperformed using SAS® version 9.4 and R Statistical Software (v4.4.2; R Core Team 2024). 577 \nStatistical Analysis  578 \nStatistical analysis was conducted to evaluate differences between a set of pairwise drug 579 \ncombinations that differed by only one component. The analysis considered both overall 580 \nT90 results and exposure  levels (AUC0-24) of the drugs common to the combinations.  581 \nSpecifically, T90 results were compared using a Z -test, assuming that T90 values are 582 \nnormally distributed, and their standard errors are known. AUC comparisons were 583 \nperformed using a t -test with unequal variances on log -transformed data. No formal 584 \ncorrection for multiple comparisons was applied, as the analyses were exploratory . P-585 \nvalues below 0.05 were considered statistically significant.  586 \nAcknowledgements  587 \nThis work was supported by the  Gates Foundation [ INV-008993]. The conclusions and 588 \nopinions expressed in this work are those of the author(s) alone and shall not be attributed 589 \nto the Foundation. Under the grant conditions of the Foundation, a Creative Commons 590 \nAttribution 4.0 License has already been assigned to the Author Accepted Manuscript 591 \nversion that might arise from this submission. Please note works submitted  as a preprint 592 \nhave not undergone a peer review process.  593 \nWe would like to thank the Evotec BSL3 In Vivo Pharmacology, Bioanalytical and 594 \nPharmacometrics teams for their valuable support and collaboration. We are especially 595 \ngrateful to Augusto Celon  and Andrea Boscolo Panzin for their insightful input and 596 \ncontributions to the analytical aspects of this work, as well as Jeanne Jaen, Fanny Deglave 597 \nand Eric Erdocain for expert bioanalytical work. 598 \nConflict of interest statement 599 \nC.A.-P. is a full-time employee and potential stockholder of Johnson &Johnson (previously 600 \nJanssen Pharmaceutica).  601 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n19 \n \n 602 \nREFERENCES 603 \n[1] World Health Organization, Global tuberculosis report 2024 604 \n[2] Cox H, Dickson-Hall L, Ndjeka N, Van't Hoog A, Grant A, Cobelens F, Stevens W, 605 \nNicol M . 2017. Delays and loss to follow -up before treatment of drug -resistant 606 \ntuberculosis following implementation of Xpert MTB/RIF in South Africa: a 607 \nretrospective cohort study. PLoS Med. 14(2):e1002238. doi: 608 \n10.1371/journal.pmed.1002238.  609 \n[3] Lienhardt C, Dooley KE, Nahid P, Wells C, Ryckman TS, Kendall EA, Davies G, 610 \nBrigden G, Churchyard G, Cirillo DM, Di Meco E, Gopinath R, Mitnick C, Scott 611 \nC, Amanullah F, Bansbach C, Boeree M, Campbell M, Conradie F, Crook A, Daley 612 \nCL, Dheda K, Diacon A, Gebhard A, Hanna D, Heinrich N, Hesseling A, Holtzman 613 \nD, Jachym M, Kim P, Lange C, McKenna L, Meintjes G, Ndjeka N, Nhung NV, 614 \nNyang'wa BT, Paton NI, Rao R, Rich M, Savic R, Schoeman I, Makokotlela BS, 615 \nSpigelman M, Sun E, Svensson E, Tisile P, Varaine F, Vernon A, Diul MY, 616 \nKasaeva T, Zignol M, Gegia M, Mirzayev F, Schumacher SG. 2024. Target 617 \nregimen profiles for tuberculosis treatment. Bull World Health Organ. 102(8):600-618 \n607. doi: 10.2471/BLT.24.291881. Epub 2024 May 28. 619 \n[4] WHO Target regimen profiles for tuberculosis treatment. Nov 2, 620 \n2023. https://www.who.int/publications-detail-redirect/9789240081512 [DOI] 621 \n[PMC free article] [PubMed] 622 \n[5] Hards K, Robson JR, Berney M, Shaw L, Bald D, Koul A, Andries K, Cook GM. 2015. 623 \nBactericidal mode of action of bedaquiline. J Antimicrob Chemother. 70(7):2028 -624 \n37. doi: 10.1093/jac/dkv054. Epub 2015 Mar 8. PMID: 25754998 625 \n[6] Conradie F, Bagdasaryan TR, Borisov S, Howell P, Mikiashvili L, Ngubane N, 626 \nSamoilova A, Skornykova S, Tudor E, Variava E, Yablonskiy P, Everitt D, Wills 627 \nGH, Sun E, Olugbosi M, Egizi E, Li M, Holsta A, Timm J, Bateson A, Crook AM, 628 \nFabiane SM, Hunt R, McHugh TD, Tweed CD, Foraida S, Mendel CM, Spigelman 629 \nM; ZeNix Trial Team . 2022 . Bedaquiline-Pretomanid-Linezolid Regimens for 630 \nDrug-Resistant Tuberculosis. N Engl J Med  387(9): 810 -823. 631 \n10.1056/NEJMoa2119430 632 \n[7] Khoshnood S, Taki E, Sadeghifard N, Kaviar VH, Haddadi MH, Farshadzadeh Z, 633 \nKouhsari E, Goudarzi M, Heidary M. 2021. Mechanism of Action, Resistance, 634 \nSynergism, and Clinical Implications of Delamanid Against Multidrug -Resistant 635 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n20 \n \nMycobacterium tuberculosis . Front Microbiol 12: 717045. 636 \n10.3389/fmicb.2021.717045 637 \n[8] Hariguchi N, Chen X, Hayashi Y, Kawano Y, Fujiwara M, Matsuba M, Shimizu H, 638 \nOhba Y, Nakamura I, Kitamoto R, Shinohara T, Uematsu Y, Ishikawa S, Itotani M, 639 \nHaraguchi Y, Takemura I, Matsumoto M. 2020. OPC-167832, a Novel Carbostyril 640 \nDerivative with Potent Antituberculosis Activity as a DprE1 Inhibitor. Antimicrob 641 \nAgents Chemother 64(6). 10.1128/aac.02020-19 642 \n[9] Tenero D, Derimanov G, Carlton A, Tonkyn J, Davies M, Cozens S, Gresham S, 643 \nGaudion A, Puri A, Muliaditan M, Rullas -Trincado J, Mendoza -Losana A, 644 \nSkingsley A, Barros-Aguirre D. 2019. First-Time-in-Human Study and Prediction 645 \nof Early Bactericidal Activity for GSK3036656, a Potent Leucyl-tRNA Synthetase 646 \nInhibitor for Tuberculosis Treatment. Antimicrob Agents Chemother 63(8). 647 \n10.1128/aac.00240-19 648 \n[10] Brown KL, Wilburn KM, Montague CR, Grigg JC, Sanz O, Pérez -Herrán E, Barros 649 \nD, Ballell L, VanderVen BC, Eltis LD . 2023. Cyclic AMP-Mediated Inhibition of 650 \nCholesterol Catabolism in Mycobacterium tuberculosis by the Novel Drug 651 \nCandidate GSK2556286. Antimicrob Agents Chemother 67(1): e0129422. 652 \n10.1128/aac.01294-22 653 \n[11] Bruinenberg P, Nedelman J, Yang TJ, Pappas F, Everitt D . 2022. Single Ascending-654 \nDose Study To Evaluate the Safety, Tolerability, and Pharmacokinetics of 655 \nSutezolid in Healthy Adult Subjects. Antimicrob Agents Chemother 66(4): 656 \ne0210821. 10.1128/aac.02108-21 657 \n[12]  Nuermberger EL, Martínez -Martínez MS, Sanz O, Urones B, Esquivias J, Soni H, 658 \nTasneen R, Tyagi S, Li SY, Converse PJ, Boshoff HI, Robertson GT, Besra GS, 659 \nAbrahams KA, Upton AM, Mdluli K, Boyle GW, Turner S, Fotouhi N, Cammack 660 \nNC, Siles JM, Alonso M, Escribano J, Lelievre J, Rullas-Trincado J, Pérez-Herrán 661 \nE, Bates RH, Maher -Edwards G, Barros D, Ballell L, Jiménez E.  2022. 662 \nGSK2556286 Is a Novel Antitubercular Drug Candidate Effective In Vivo with the 663 \nPotential To Shorten Tuberculosis Treatment. Antimicrob Agents Chemother. 2022 664 \nJun 21;66(6):e0013222. doi: 10.1128/aac.00132-22. Epub 2022 May 24. 665 \n[13] Tasneen R, Garcia A, Converse PJ, Zimmerman MD, Dartois V, Kurbatova E, Vernon 666 \nAA, Carr W, Stout JE, Dooley KE, Nuermberger EL. 2022. Novel Regimens of 667 \nBedaquiline-Pyrazinamide Combined with Moxifloxacin, Rifabutin, Delamanid 668 \nand/or OPC -167832 in Murine Tuberculosis Models. Antimicrob Agents 669 \nChemother. 66(4):e0239821. doi: 10.1128/aac.02398-21.  670 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n21 \n \n[14]  Walter K, Te Brake LHM, Lemm AK, Hoelscher M, Svensson EM, Hölscher C, 671 \nHeinrich N. 2024. Investigating the treatment shortening potential of a combination 672 \nof bedaquiline, delamanid and moxifloxacin with and without sutezolid, in a murine 673 \ntuberculosis model with confirmed drug exposures. J Antimicrob Chemother. 674 \n1;79(10):2607-2610. doi: 10.1093/jac/dkae266. 675 \n[15]  Williams K, Minkowski A, Amoabeng O, Peloquin CA, Taylor D, Andries K, Wallis 676 \nRS, Mdluli KE, Nuermberger EL. 2012. Sterilizing activities of novel combinations 677 \nlacking first- and second-line drugs in a murine model of tuberculosis. Antimicrob 678 \nAgents Chemother. 56(6):3114-20. doi: 10.1128/AAC.00384-12.  679 \n[16] Lanoix JP, Betoudji F, Nuermberger E. 2014. Novel regimens identified in mice for 680 \ntreatment of latent tuberculosis infection in contacts of patients with multidrug -681 \nresistant tuberculosis. Antimicrob Agents Chemother. 2014;58(4):2316 -21. doi: 682 \n10.1128/AAC.02658-13. 683 \n[17] Cevik M, Thompson LC, Upton C, Rolla VC, Malahleha M, Mmbaga B, Ngubane N, 684 \nAbu Bakar Z, Rassool M, Variava E, Dawson R, Staples S, Lalloo U, Louw C, 685 \nConradie F, Eristavi M, Samoilova A, Skornyakov SN, Ntinginya NE, Haraka F, 686 \nPraygod G, Mayanja -Kizza H, Caoili J, Balanag V, Dalcolmo MP, McHugh T, 687 \nHunt R, Solanki P, Bateson A, Crook AM, Fabiane S, Timm J, Sun E, Spigelman 688 \nM, Sloan DJ, Gillespie SH; SimpliciTB Consortium . 2024. Bedaquiline -689 \npretomanid-moxifloxacin-pyrazinamide for drug -sensitive and drug -resistant 690 \npulmonary tuberculosis treatment: a phase 2c, open -label, multicentre, partially 691 \nrandomised controlled trial. The Lancet Infectious Diseases 24(9): 1003 -1014. 692 \n10.1016/S1473-3099(24)00223-8 693 \n[18] Li SY, Irwin SM, Converse PJ, Mdluli KE, Lenaerts AJ, Nuermberger EL. 2015. 694 \nEvaluation of moxifloxacin-containing regimens in pathologically distinct murine 695 \ntuberculosis models. Antimicrob Agents Chemother. 59(7):4026 -30. doi: 696 \n10.1128/AAC.00105-15. 697 \n[19] Li SY, Tasneen R, Tyagi S, Soni H, Converse PJ, Mdluli K, Nuermberger EL . 2017. 698 \nBactericidal and Sterilizing Activity of a Novel Regimen with Bedaquiline, 699 \nPretomanid, Moxifloxacin, and Pyrazinamide in a Murine Model of Tuberculosis. 700 \nAntimicrob Agents Chemother 61(9). 10.1128/aac.00913-17 701 \n[20] Zhang M, Li SY, Rosenthal IM, Almeida DV, Ahmad Z, Converse PJ, Peloquin CA, 702 \nNuermberger EL,  Grosset JH. 2011.  Treatment of tuberculosis with rifamycin -703 \ncontaining regimens in immune -deficient mice. Am J Respir Crit Care Med. 704 \n183(9):1254-61.  705 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n22 \n \n[21] Mourik BC, Svensson RJ, de Knegt GJ, Bax HI, Verbon A, Simonsson USH, de 706 \nSteenwinkel JEM. 2018. Improving treatment outcome assessment in a mouse 707 \ntuberculosis model. Nature/Scientific report 8:5714.  708 \n[22] Mudde SE, Ayoun Alsoud R, van der Meijden A, Upton AM, Lotlikar MU, Simonsson 709 \nUSH, Bax HI, de Steenwinkel JEM. 2022. Predictive Modeling to Study the 710 \nTreatment-Shortening Potential of Novel Tuberculosis Drug Regimens, Toward 711 \nBundling of Preclinical Data. J Infect Dis 225(11):1876-1885. 712 \n[23] Sordello S, Brock L, Tagliavini A, Federico D, Boulenc X, Pergher M, Huc Claustre 713 \nE, Metcalf D, Walter N, Robertson  G, Clary J, Berg A, Mdluli  K, Hermann D, 714 \nFlood D, Upton A. 2026. A modeling-based framework to evaluate forgiveness of 715 \ntuberculosis treatment in a BALB/c relapsing mouse model . Antimicrob Agents 716 \nChemother Antimicrob Agents Chemother. 15:e0110925. doi: 10.1128/aac.01109-717 \n25. Online ahead of print.PMID: 41537590 718 \n[24] Tasneen R, Betoudji F, Tyagi S, Li SY, Williams K, Converse PJ, Dartois V, Yang T, 719 \nMendel CM, Mdluli KE, Nuermberger EL. 2015 . Contribution of Oxazolidinones 720 \nto the Efficacy of Novel Regimens Containing Bedaquiline and Pretomanid in a 721 \nMouse Model of Tuberculosis. Antimicrob Agents Chemother. 60(1):270 -7. doi: 722 \n10.1128/AAC.01691-15.[25] Li SY, Converse PJ, Betoudji F, Lee J, Mdluli K, 723 \nUpton A, Fotouhi N, Nuermberger EL. 2023. Next -Generation Diarylquinolines 724 \nImprove Sterilizing Activity of Regimens with Pretomanid and the Novel 725 \nOxazolidinone TBI -223 in a Mouse Tuberculosis Model. Antimicrob Agents 726 \nChemother. 67(4):e0003523. doi: 10.1128/aac.00035-23.  727 \n[26] Nimmo C, Millard J, van Dorp L, Brien K, Moodley S, Wolf A, Grant AD, Padayatchi 728 \nN, Pym AS, Balloux F, O'Donnell M. 2020. Population -level emergence of 729 \nbedaquiline and clofazimine resistance -associated variants among patients with 730 \ndrug-resistant tuberculosis in southern Africa: a phenotypic and phylogenetic 731 \nanalysis. Lancet Microbe. 2020 Aug;1(4):e165 -e174. doi: 10.1016/S2666 -732 \n5247(20)30031-8. PMID: 32803174 733 \n[27] Pieterman ED, Keutzer L, van der Meijden A, van den Berg S, Wang H, Zimmerman 734 \nMD, Simonsson USH, Bax HI, de Steenwinkel JEM. 2021. Superior Efficacy of a 735 \nBedaquiline, Delamanid, and Linezolid Combination Regimen in a Mouse 736 \nTuberculosis Model. J Infect Dis. 224(6):1039-1047. doi: 10.1093/infdis 737 \n[28] Matthew J Reichlen , Emmanuel Musisi , Samuel T Tabor , Holly Nielsen, Ashley M 738 \nGerwing , Firat Kaya, Matthew Zimmerman, Martin I Voskuil, Gregory T 739 \nRobertson, Nicholas D Walter. 2025. Same class, different activity: Delamanid and 740 \npretomanid have comparable bactericidal activity but pretomanid potently inhibits 741 \nMycobacterium tuberculosis ribosomal rRNA synthesis. bioRxiv [Preprint]. 2025 742 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n23 \n \nDec 30:2025.12.30.697025. doi: 10.64898/2025.12.30.697025.PMID: 41509415 743 \nPMCID: PMC12776329 DOI: 10.64898/2025.12.30.697025 744 \n[29] Dawson R, Diacon AH, Takuva S, Liu Y, Zheng B, Karwe V, Hafkin J. Quabodepistat 745 \nin combination with delamanid and bedaquiline in participants with drug -746 \nsusceptible pulmonary tuberculosis: protocol for a multicenter, phase 2b/c, open -747 \nlabel, randomized, dose -finding trial to evaluate safety and efficacy. Trials. 2024 748 \nJan 19;25(1):70. doi: 10.1186/s13063-024-07912-5. PMID: 38243296 749 \n[30] Lee BM, Harold LK, Almeida DV, Afriat -Jurnou L, Aung HL, Forde BM, Hards K, 750 \nPidot SJ, Ahmed FH, Mohamed AE, Taylor MC, West NP, Stinear TP, Greening 751 \nC, Beatson SA, Nuermberger EL, Cook GM, Jackson CJ. 2020 Predicting 752 \nnitroimidazole antibiotic resistance mutations in Mycobacterium tuberculosis with 753 \nprotein engineering. PLoS Pathog. 2020 Feb 7;16(2):e1008287. doi: 754 \n10.1371/journal.ppat.1008287. eCollection 2020 Feb. PMID: 32032366  755 \n[31] Dorman SE, Nahid P, Kurbatova EV, Phillips PPJ, Bryant K, Dooley KE, Engle M, 756 \nGoldberg SV, Phan HTT, Hakim J, Johnson JL, Lourens M, Martinson NA, 757 \nMuzanyi G, Narunsky K, Nerette S, Nguyen NV, Pham TH, Pierre S, Purfield AE, 758 \nSamaneka W, Savic RM, Sanne I, Scott NA, Shenje J, Sizemore E, Vernon A, Waja 759 \nZ, Weiner M, Swindells S, Chaisson RE, Tuberculosis Trials Consortium. 2021. 760 \nFour-month rifapentine regimens with or without moxifloxacin for tuberculosis. N 761 \nEngl J Med 384:1705–1718. 10.1056/NEJMoa2033400. 762 \n[32] Crowley BM, Boshoff HI, Boving A, Tan VY, Zhu J, Hoyt F, Miller RR, Ehrhart J, 763 \nBoyce CW, Young K, Nantermet PG, Su J, Yang L, Painter RE, Corcoran EB, Hoar 764 \nJL, Oh S, Holtzman DL, Levi M, Anderson A, Otieno MA, Zimmerman M, Kaya 765 \nF, Massoudi LM, Ramey ME, Bauman AA, Lenaerts AJ, Roberston GT, Dartois 766 \nV, Wells CD, Barry CE 3rd, Olsen DB. 2026. Discovery and development of a new 767 \noxazolidinone with reduced toxicity for the treatment of tuberculosis. Nat Med. 768 \n2026 Jan 13. doi: 10.1038/s41591 -025-04164-x. Online ahead of print.  PMID: 769 \n41530381. 770 \n[33] Li, W., Vazvaei-Smith, F., Dear, G., Boer, J., Cuyckens, F., Fraier, D., Liang, Y., Lu, 771 \nD., Mangus, H., Moliner, P., Pedersen, M. L., Romeo, A. A., Spracklin, D. K., 772 \nWagner, D. S., Winter, S., & Xu, X. S. (2024). Metabolite Bioanalysis in Drug 773 \nDevelopment: Recommendations from the IQ Consortium Metabolite Bioanalysis 774 \nWorking Group. Clinical pharmacology and therapeutics, 115(5), 939 –953. 775 \nhttps://doi.org/10.1002/cpt.3144  776 \n 777 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n24 \n \n[34] MacLeod, A. K., Coquelin, K. S., Huertas, L., Simeons, F. R. C., Riley, J., Casado, 778 \nP., Guijarro, L., Casanueva, R., Frame, L., Pinto, E. G., Ferguson, L., Duncan, C., 779 \nMutter, N., Shishikura, Y., Henderson, C. J., Cebrian, D., Wolf, C. R., & Read, K. 780 \nD. (2024). Acceleration of infectious disease drug discovery and development 781 \nusing a humanized model of drug metabolism. Proceedings of the National 782 \nAcademy of Sciences of the United States of America, 121(7), e2315069121. 783 \nhttps://doi.org/10.1073/pnas.2315069121  784 \n 785 \n[35] Rouan, M. C., Lounis, N., Gevers, T., Dillen, L., Gilissen, R., Raoof, A., & Andries, 786 \nK. (2012). Pharmacokinetics and pharmacodynamics of TMC207 and its N -787 \ndesmethyl metabolite in a murine model of tuberculosis. Antimicrobial agents and 788 \nchemotherapy, 56(3), 1444–1451. https://doi.org/10.1128/AAC.00720-11  789 \n 790 \n[36] Wallis, R. S., Dawson, R., Friedrich, S. O., Venter, A., Paige, D., Zhu, T., Silvia, A., 791 \nGobey, J., Ellery, C., Zhang, Y., Eisenach, K., Miller, P., & Diacon, A. H. (2014). 792 \nMycobactericidal activity of sutezolid (PNU-100480) in sputum (EBA) and blood 793 \n(WBA) of patients with pulmonary tuberculosis. PloS one, 9(4), e94462. 794 \nhttps://doi.org/10.1371/journal.pone.0094462   795 \n[37] Berg A, Clary J, Hanna D, Nuermberger E, Lenaerts A, Ammerman N, Ramey M, 796 \nHartley D, Hermann D. 2022. Model -Based Meta-Analysis of Relapsing Mouse 797 \nModel Studies from the Critical Path to Tuberculosis Drug Regimens Initiative 798 \nDatabase. Antimicrob Agents Chemother. 2022 Mar 15;66(3):e0179321. doi: 799 \n10.1128/AAC.01793-21. Epub 2022 Jan 31. 800 \n[38] Xu J, Li SY, Almeida DV, Tasneen R, Barnes -Boyle K, Converse PJ, Upton AM, 801 \nMdluli K, Fotouhi N, Nuermberger EL. 2019. Contribution of Pretomanid to Novel 802 \nRegimens Containing Bedaquiline with either Linezolid or Moxifloxacin and 803 \nPyrazinamide in Murine Models of Tuberculosis. Antimicrob Agents Chemother . 804 \n2019 Apr 25;63(5):e00021 -19. doi: 10.1128/AAC.00021 -19. Print 2019 805 \nMay.PMID: 30833432 806 \n[39] Walter ND, Born SEM, Robertson GT, Reichlen M, Dide-Agossou C, Ektnitphong 807 \nVA, Rossmassler K, Ramey ME, Bauman AA, Ozols V, Bearrows SC, Schoolnik 808 \nG, Dolganov G, Garcia B, Musisi E, Worodria W, Huang L, Davis JL, Nguyen NV, 809 \nNguyen HV, Nguyen ATV, Phan H, Wilusz C, Podell BK, Sanoussi ND, de Jong 810 \nBC, Merle CS, Affolabi D, McIlleron H, Garcia -Cremades M, Maidji E, Eshun -811 \nWilson F, Aguilar-Rodriguez B, Karthikeyan D, Mdluli K, Bansbach C, Lenaerts 812 \nAJ, Savic RM, Nahid P, Vásquez JJ, Voskuil MI. 2021. Mycobacterium 813 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n25 \n \ntuberculosis precursor rRNA indicates treatment -shortening activity of drugs and 814 \nregimens. Nature Communications 12(1):2899. 815 \n 816 \n[40] Heinrich N, Manyama C, Koele SE, Mpagama S, Mhimbira F, Sebe M, Wallis RS, 817 \nNtinginya N, Liyoyo A, Huglin B, Minja LT, Wagnerberger L, Stoycheva K, 818 \nZumba T, Noreña I, Peter DD, Makkan H, Sloan DJ, Brake LT, Schildkraut J, 819 \nAarnoutse RE, McHugh TD, Wildner L, Boeree M, Aldana BH, Phillips PPJ, 820 \nHoelscher M, Svensson EM; PanACEA consortium. 2025 . Sutezolid in 821 \ncombination with bedaquiline, delamanid, and moxifloxacin for pulmonary 822 \ntuberculosis (PanACEA -SUDOCU-01): a prospective, open -label, randomised, 823 \nphase 2b dose -finding trial. Lancet Infect Dis. 2025 Nov;25(11):1208 -1218. doi: 824 \n10.1016/S1473-3099(25)00213-0. Epub 2025 Jul 8. 825 \n 826 \n[41] Casella G, Wu R, Wu SS, Weidman ST; National Research Council (US) Board on 827 \nMathematical Sciences and Their Applications . 2002. Making Sense of 828 \nComplexity: Summary of the Workshop on Dynamical Modeling of Complex 829 \nBiomedical Systems.Washington (DC): National Academies Press (US); 2002.  830 \nPMID: 25057601   831 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n26 \n \n 832 \nFIGURE LEGENDS 833 \nFigure 1 Distribution of plasma AUC0-24 (AUC0-24/MIC for B and Sut) from popPK 834 \nanalysis versus clinical target. 835 \n 836 \nFigure 2 Lung bacterial burden at end of treatment in Study 1 (A) and Study 2 (B).  837 \nWhole lung CFU of BALB/c mice, intranasally infected with M.tb H37Rv, after different 838 \ndurations of oral treatment with 4-drug combinations, dosed 5/7. Treatments were initiated 839 \n2-weeks post infection.  840 \nFigure 3 Probability of relapse with treatment duration for BALB/c mice treated with 841 \ncombinations tested in Study 1 and Study 2 RMM studies (ordered by individual T90 842 \nin the legend). 843 \nSterilization curves indicating the probability of relapse over treatment time, constructed 844 \nby fitting observed relapse data (Table 4) to an Emax model developed using a large 845 \nhistorical RMM dataset. Observed relapse data are indicated for each test regimen using 846 \nopen symbols and crosses. The time to 50% cure/relapse is estimated from these curves, 847 \nand the time to 90% cure (i.e. 10% relapse) is derived utilizing time to 50% cure estimates 848 \ntogether with steepness of the curve (gamma) as explained in Methods. 849 \nFigure 4 Ranking of population T90 values with 95% confidence intervals for all 850 \ncombinations (historical dataset + Study 1 and Study 2 RMM combinations). 851 \n 852 \n  853 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n27 \n \n 854 \nTABLES 855 \n 856 \nDelamanid-containing \ncombinations \nPretomanid-containing \ncombinations \nNitroimidazole-free \ncombinations \n1. B Del Q 830 11. B Pa Q 656 21. B Q 656 286 \n2. B Del Q 286 12. B Pa Q 286 22. B Q 656 Sut \n3. B Del Q Sut 13. B Pa Q Sut 23. B Q Sut 286 \n4. B Del 656 286 14. B Pa 656 286 24. Q 656 286 Sut \n5. B Del 830 Sut  15. B Pa 830 Sut 25. B 656 286 Sut \n6. B Del 286 Sut 16. B Pa 286 Sut  \n7. Del Q 656 286 17. Pa Q 656 286  \n8. Del Q 656 Sut 18. Pa Q 656 Sut  \n9. Del Q Sut 286 19. Pa Q Sut 286  \n10. Del 656 286 Sut 20. Pa 656 286 Sut  \nTotal: 10 Total: 10 Total: 5 \n \nTable 1 PAN-TB 4-drug Combinations  \nCombinations in blue font were tested in Study 1. Combinations in black font were tested in \nStudy 2. 830 was replaced by 656 in Study 2. \n857 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n28 \n \n 858 \nCompounds  \n(Blood to plasma ratio) \nTarget \nhuman \nplasma \nAUC0-24 \n(µg*h/mL) \nReferences for \ntarget human \nplasma AUC0-24 \nInitial \nDose \n(mg/kg) \nMouse/ \nhuman \nplasma  \nAUC0-24  \nratio \nDose selected \nfor RMM \nstudies (mg/kg) \nBedaquiline (0.60) 23 \nNDA 204384 \n25 \n1.02 \n25 \nBedaquiline active \nmetabolite BDQ-M2 \n(0.83) \n6 - - \nPretomanid (1.71) 52 NDA 212862 40 1.35 40 \nDelamanid (0.48) 5.9 Provided by \nOtsuka  6 3.4 2 \nSutezolid (1.57) 7.1 \n(Wallis et al., \n2014) \n100 \n1.1 \n100 \nSutezolid active \nmetabolite  \nPNU-101603 (1.01) \n36.8 - - \nQuabodepistat (0.64) 2.5 Dawson R et al \n2025 9 3.58 14 \nGSK2556286 [286] (1.04) 22.5 \n(predicted) \nprovided by \nGSK 35 1.12 35 \nGSK3211830 [830] (2.09) 6.5 \n(predicted) \nprovided by \nGSK 2 0.2 5 \nGSK3036656 [656] (2.04) \n6.5 (based \non clinical \nexposure) \n(Tenero et al \n2019) 4 0.5 8 \nTable 2 Doses Used in Mouse Studies to reach Clinical Target Plasma Exposures  859 \n  860 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n29 \n \nA Study 1 861 \nMean + SD Log10 CFU/ lung (positive culture mice/total number of mice) \nGroups Day -13 (1 dpi) Day 0 end of 2W \nTreatment \nend of 4W \nTreatment \nend of 8W \nTreatment \nUntreated 5.0 ± 0.1 (5/5) 7.2 ± 0.2 (5/5) NA NA NA \nB Pa 286 Sut NA NA 4.5 ± 0.2 (5/5) 0.0 ± 0.0 (0/5) 0.0 ± 0.0 (0/6) \nB Q Sut 286 NA NA 4.6 ± 0.3 (5/5) 0.0 ± 0.0 (0/5) 0.0 ± 0.0 (0/6) \nB Pa M Z NA NA 4.3 ± 0.2 (5/5) 0.5 ± 0.5 (2/4) 0.0 ± 0.0 (0/5) \nB Pa 830 Sut NA NA 3.7 ± 0.7 (5/5) 1.3 ± 0.9 (3/4) 0.0 ± 0.0 (0/6) \nB Pa Q Sut NA NA 4.4 ± 0.2 (5/5) 1.4 ± 0.9 (4/5) 0.0 ± 0.0 (0/6) \nB Del 286 Sut NA NA 4.9 ± 0.9 (5/5) 2.1 ± 1.4 (3/4) 0.0 ± 0.0 (0/6) \nB Del 830 Sut NA NA 4.9 ± 0.4 (5/5) 3.2 ± 0.3 (5/5) 0.0 ± 0.0 (0/6) \nPa Q Sut 286 NA NA 4.6 ± 0.6 (5/5) 1.4 ± 1.6 (2/4) 0.4 ± 0.8 (1/3) \nB Del Q 286 NA NA 5.6 ± 0.1 (5/5) 3.6 ± 0.5 (4/4) 0.4 ± 0.6 (1/3) \nB Del Q Sut NA NA 4.9 ± 0.6 (5/5) 4.3 ± 0.8 (5/5) 0.4 ± 0.5 (3/6) \nB Del Q 830 NA NA 5.8 ± 0.3 (5/5) 4.0 ± 0.6 (5/5) 1.0 ± 1.1 (3/6) \nB Pa Q 286 NA NA 5.5 ± 0.2 (5/5) 3.4 ± 0.3 (5/5) 1.4 ± 0.4 (6/6) \nDel Q Sut 286 NA NA 5.2 ± 0.5 (5/5) 3.7 ± 0.6 (4/4) 2.4 ± 0.8 (6/6) \nR H Z E / R H NA NA 6.0 ± 0.4 (5/5) 4.2 ± 0.3 (5/5) 2.2 ± 0.2 (5/5) \n 862 \n  863 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n30 \n \nB Study 2 864 \nMean + SD Log10 CFU/ lung (positive culture mice/total number of mice) \nGroups Day -13 (1 dpi) Day 0 end of 2W \nTreatment \nend of 4W \nTreatment \nend of 8W \nTreatment \nUntreated 4.6 ± 0.3 (5/5) 7.4 ± 0.1 (5/5) NA NA NA \nB Pa M Z NA NA 4.8 ± 0.3 (3/3) 0.4 ± 0.3 (2/3) 0.0 ± 0.0 (0/3) \nB Pa 656 286 NA NA 3.8 ± 0.4 (5/5) 0.4 ± 0.8 (1/4) 0.1 ± 0.2 (1/6) \nB Q 656 Sut NA NA 4.1 ± 0.1 (3/3) 2.4 ± 0.3 (3/3) 0.4 ± 0.8 (1/4) \nPa Q 656 Sut NA NA 4.6 ± 0.3 (4/4) 2.2 ± 0.7 (4/4) 0.6 ± 0.9 (2/5) \nB Q 656 286 NA NA 4.3 ± 0.1 (3/3) 2.7 ± 0.5 (4/4) 0.4 ± 0.7 (2/4) \nB Del 656 286 NA NA 5.6 ± 0.1 (2/2) 2.2 ± 0.3 (3/3) 0.6 ± 0.7 (3/5) \nB 656 286 Sut NA NA 3.9 ± 0.5 (3/3) 2.6 ± 0.0 (2/2) 0.8 ± 1.1 (1/2) \nPa Q 656 286 NA NA 5.7 ± 0.1 (4/4) 1.8 ± 0.4 (4/4) 1.3 ± 1.2 (3/5) \nDel 656 286 Sut NA NA 4.3 ± 1.2 (5/5) 3.5 ± 0.2 (5/5) 0.6 ± 0.6 (4/6) \nPa 656 286 Sut NA NA ND 2.5 ± 0.2 (4/4) 1.6 ± 0.0 (1/1) \nB Pa Q 656 NA NA 4.8 ± 0.1 (5/5) 3.9 ± 0.2 (5/5) 1.5 ± 1.0 (3/3) \nQ 656 286 Sut NA NA 2.5 ± 0.7 (4/4) 2.5 ± 0.9 (5/5) 2.2 ± 0.6 (6/6) \nDel Q 656 Sut NA NA 4.0 ± 1.4 (5/5) 3.5 ± 0.3 (4/4) 2.0 ± 0.6 (5/5) \nR H Z E NA NA 5.4 ± 0.2 (5/5) 3.9 + 0.1 (5/5) 2.4 + 0.3 (6/6) \nDel Q 656 286 NA NA 6.1 ±0.4 (5/5) 5.5 ±0.2 (5/5) 4.4 ±0.1 (6/6) \nTable 3: Lung bacterial burden prior and at the end of treatment in Study 1 (A) and Study 865 \n2 (B) after different durations of oral treatment with 4-drug combinations.  866 \n 867 \n  868 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n31 \n \n 869 \n 870 \nA _ Study 1  871 \nCOMBINATION \n2W TX \n+ \n12WR \n4W TX \n+ \n12WR \n6W TX \n+ \n12WR \n8W TX \n+ \n12WR \n10W \nTX + \n12WR \n12W \nTX + \n12WR \n16W \nTX + \n12WR \nB Pa M Z 100% \n(5/5) \n16% \n(1/6) \n0% \n(0/6) \n0% \n(0/5) - 0% \n(0/4) - \nB Pa 830 Sut - 100% \n(4/4) \n100% \n(4/4) \n0% \n(0/6) \n0% \n(0/5) \n0% \n(0/6) - \nB Pa 286 Sut - 100% \n(3/3) \n75% \n(3/4) \n33% \n(2/6) \n0% \n(0/6) \n0% \n(0/6) - \nB Q Sut 286 - 100% \n(4/4) \n75% \n(3/4) \n33% \n(2/6) \n20% \n(1/5) \n0% \n(0/6) - \nB Pa Q Sut - 100% \n(4/4) \n75% \n(3/4) \n66% \n(4/6) \n16% \n(1/6) \n0% \n(0/6) - \nB Del 286 Sut - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n33% \n(2/6) \n0% \n(0/6) - \nB Del Q 286 - 100% \n(4/4) \n100% \n(4/4) \n66% \n(4/6) \n50% \n(3/6) \n0% \n(0/6) - \nB Pa Q 286 - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n16% \n(1/6) \n20% \n(1/5) - \nB Del 830 Sut - 100% \n(4/4) \n100% \n(4/4) \n100% \n(4/4) \n83% \n(5/6) \n60% \n(3/5) - \nB Del Q Sut - 100% \n(3/3) \n100% \n(4/4) \n100% \n(2/2) \n100% \n(6/6) \n83% \n(5/6) - \nDel Q Sut 286 - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n100% \n(6/6) \n83% \n(5/6) - \n2R H Z E /2R H - - - 100% \n(6/6) \n100% \n(6/6) \n83% \n(5/6) \n0% \n(0/6) \nPa Q Sut 286 - 100% \n(4/4) \n100% \n(4/4) \n83% \n(5/6) \n83% \n(5/6) \n100% \n(6/6) - \nB Del Q 830 - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n100% \n(5/5) \n100% \n(5/5) - \n 872 \n  873 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n32 \n \n 874 \n 875 \nB _ Study 2  876 \nCOMBINATION \n2W TX \n+ \n12WR \n4W TX \n+ \n12WR \n6W TX \n+ \n12WR \n8W TX \n+ \n12WR \n10W \nTX + \n12WR \n12W \nTX + \n12WR \n16W \nTX + \n12WR \nB Pa M Z 100% \n(4/4) \n40% \n(2/5) \n0% \n(0/5) \n0% \n(0/5) - - - \nB Pa 656 286 - 100% \n(4/4) \n100% \n(4/4) \n83% \n(5/6) \n33% \n(2/6) \n0% \n(0/6) - \nB Q 656 286 - 100% \n(3/3) \n100% \n(3/3) \n83% \n(5/6) \n33% \n(2/6) \n0% \n(0/6) - \nB 656 286 Sut - 100% \n(3/3) \n66% \n(2/3) \n80% \n(4/5) \n17% \n(1/6) \n50% \n(3/6) - \nPa Q 656 Sut - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n80% \n(4/5) \n67% \n(2/3) - \nB Del 656 286 - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n80% \n(4/5) \n33% \n(2/6) - \nB Q 656 Sut - 100% \n(4/4) \n100% \n(4/4) \n100% \n(5/5) \n100% \n(5/5) \n33% \n(2/6) - \n2R H Z E/2R H - - - 100% \n(5/5) \n83% \n(5/6) \n50% \n(3/6) \n17% \n(1/6) \nB Pa Q 656 - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n100% \n(6/6) \n66% \n(4/6) - \nPa Q 656 286 - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n100% \n(6/6) \n100% \n(6/6) - \nPa 656 286 Sut - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n100% \n(5/5) \n100% \n(6/6) - \nQ 656 286 Sut - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n100% \n(6/6) \n100% \n(5/5) - \nDel 656 286 Sut - 100% \n(3/3) \n100% \n(4/4) \n100% \n(6/6) \n100% \n(6/6) \n100% \n(5/5) - \nDel Q 656 SUT - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n100% \n(6/6) \n100% \n(6/6) - \nDel Q 656 286 - 100% \n(4/4) \n100% \n(4/4) \n100% \n(6/6) \n100% \n(6/6) \n100% \n(6/6) - \nTable 4 Percentage of relapsing mice, following different treatment durations with the 877 \ntested drug combinations in study 1 (A) and in Study 2 (B). 878 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n33 \n \n 879 \nSTUDY Combinations \nEstimated \nPopulation \nT50 (Months) \nDerived \nPopulation \nT90 (Months) \nBoth B Pa M Z 0.86 1.06 \nStudy 1 B Pa 830 Sut 1.95 2.11 \nStudy 1 B Pa 286 Sut 2.04 2.51 \nStudy 1 B Q Sut 286 2.11 2.94 \nStudy 1 B Del 286 Sut 2.97 3.22 \nStudy 2 B Pa 656 286 2.85 3.38 \nStudy 2 B Q 656 286 2.85 3.39 \nStudy 1 B Pa Q Sut 2.32 3.48 \nStudy 1 B Del Q 286 2.77 3.56 \nStudy 1 B Pa Q 286 2.92 4.00 \nStudy 2 B Q 656 Sut 3.74 4.04 \nStudy 2 B Del 656 286 3.60 4.28 \nStudy 2 B Pa Q 656 3.99 4.40 \nStudy 1 Del Q Sut 286 4.13 4.60 \nStudy 1 B Del Q Sut 4.13 4.60 \nStudy 1 B Del 830 Sut 3.93 5.08 \nBoth R H Z E / R H 4.15 5.09 \nStudy 2 Pa Q 656 Sut 4.08 5.35 \nStudy 2 B 656 286 Sut 2.92 6.07 \nStudy 1 Pa Q Sut 286,  \nB Del Q 830 NC NC \nStudy 2 \nQ 656 286 Sut,  \nDel Q 656 Sut,  \nPa Q 656 286,  \nDel 656 286 Sut,  \nDel Q 656 286,  \nPa 656 286 Sut \nNC NC \nTable 5 Estimated population T50 and derived population T90 values for combinations 880 \ntested in Study1 and Study 2 RMM studies. 881 \nNC, Not computable for combinations which showed 100% relapse at the last treatment 882 \ntime point.  883 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n34 \n \n 884 \n                          885 \nTable 6 Statistical comparison of T90 and AUCratio between combinations differing by one 886 \ndrug.  887 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n35 \n \nGreen (Delta T90 < 0) and red (Delta T90 > 0) indicate statistically significant differences (p < 888 \n0.05) in T90 between Combination 1 and Combination 2. Green (AUC ratio >2; AUC 0-24 889 \nDrugCombination1 > 2×AUC0-24 DrugCombination2) and red (AUC ratio <0.5; AUC 0-24 DrugCombination1 < 890 \n0.5×AUC0-24 DrugCombination2) indicate statistically significant differences in AUCratio. 891 \nGrey cells indicate not available delta T90 due to not computable T90 values (assumed > 3 months). 892 \nNS means “Not significant” (p > 0.05). NC means “Not Computable” T90 value. 893 \n830 and 656 are considered as equivalent compounds. 894 \n 895 \n 896 \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint \n\n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 7, 2026. ; https://doi.org/10.64898/2026.05.05.722941doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}