Jose Miguel Calderin Miranda1, Jerry Nedelman2, David H Salinger3, Thanakorn Vongjarudech4, Paolo Denti1, Elin M Svensson4,5
1Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, 2Global Alliance for TB Drug Development, 3Certara, Inc., 4Department of Pharmacy, Uppsala University, 5Department of Pharmacy, Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center
Objectives: TBAJ-876 is a novel second-generation oral diarylquinoline under development for the treatment of tuberculosis (TB). TBAJ-876 and its metabolite M3 exhibit enhanced anti-TB activity, and a potentially improved safety profile compared to bedaquiline and its metabolite M2 (1, 2). In vitro data indicate that this lipophilic compound and its metabolite are CYP3A4 substrates, suggesting susceptibility to first-pass metabolism and drug-drug interactions (DDI) (3). However, limited pharmacokinetic (PK) data exist in humans, and no models have been reported that simultaneously characterize the PK of TBAJ-876 and M3. To address this gap, we developed a joint parent-metabolite model using data from two studies in healthy volunteers. Methods: This PK analysis included data from a Phase I study (CL-001) of TBAJ-876 in healthy volunteers, consisting of three cohorts. In the single-ascending dose (SAD) cohort, participants received a single oral suspension dose of 10, 25, 50, 100, 200, 400, or 800 mg in the fasted state, with an additional group receiving 100 mg under fed conditions. The multiple-ascending dose (MAD) cohort received 25, 75, or 200 mg of TBAJ-876 as an oral suspension once daily for 14 days under fed conditions. In the relative bioavailability (RBA) cohort, participants received 100 mg in tablet form under either fed or fasted conditions. Additionally, data from another study (CL-002) were included, where fed healthy volunteers received TBAJ-876 as an oral suspension (200 mg/day for 8 days, then 165 mg/day for 4 days). In the CL-001 study, blood samples were collected intensively over 24 h on day 1 and sparsely up to 1500 h (SAD cohort) and 312 h (RBA cohort) post-dose. In the MAD cohort, intensive sampling was performed on day 1 and day 14, with sparse sampling on the days in between and post-day 14 up to 3000 h. In CL-002, intensive sampling was conducted over 24 h post-dose on day 12. Plasma concentrations of TBAJ-876 and M3 were quantified using LC-MS/MS. Data were analysed in NONMEM v7.5.1, starting with the RBA cohort and then including the remaining cohorts. The modelling followed a sequential approach, first characterizing the parent compound and then incorporating the metabolite data, assuming complete conversion of TBAJ-876 to M3. One-, two-, and three-compartment disposition models with first-order elimination were evaluated for both analytes. First-order absorption, with or without lag time or transit compartments, was tested for TBAJ-876. An intestinal metabolism fraction was included to account for the drug absorbed as M3 due to metabolism in the gut wall. A combined proportional and additive error model described the residual unexplained variability for each analyte, with correlation applied using the L2 data item. Allometric scaling of disposition parameters was tested using body weight (WT) or fat-free mass (FFM) (4). The effects of food, formulation, study visit, and other covariates on the PK of TBAJ-876 and M3 were assessed. Results: A total of 138 individuals underwent PK sampling across the two studies, providing 4638 samples. The overall population had a median (min–max) age of 35 (19–55) years, WT of 76 (49–153) kg, and FFM of 52 (33–81) kg. TBAJ-876 PK was described by a three-compartment disposition model with first-order absorption delayed by transit compartments and first-order elimination. M3 PK was also three-compartmental with first-order elimination, using TBAJ-876 clearance as input. The typical clearance values, best allometrically scaled using FFM, were 5.10 L/h for TBAJ-876 and 38.1 L/h for M3. The fraction of drug absorbed as M3 was estimated at 0.388, decreasing to 0.130 in fed individuals. The absorption rate constant (0.140 h?¹) increased by 22.2% with food. The mean transit time (0.882 h) increased to 1.75 h in participants taking the tablet formulation with food. The model showed a 43.3% reduction in bioavailability at doses of 400 mg and 800 mg. In the CL-002 study, bioavailability was 51.8% higher. Conclusions: We developed a joint model that semi-mechanistically characterizes the PK of TBAJ-876 and M3. Our findings suggest that food reduces intestinal metabolism, likely by enhancing drug solubility at the absorption site, which accelerates absorption and limits gut metabolism. The observed reduction in bioavailability at higher doses may result from saturation of absorption mechanisms. This model can be used for future PK/PD analyses and DDI evaluations.
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Reference: PAGE 33 (2025) Abstr 11359 [www.page-meeting.org/?abstract=11359]
Poster: Drug/Disease Modelling - Infection