Barrail-Tran, A. | Search bioRxiv

bioRxiv2026

A novel workflow integrating whole-body PET microdosing data and therapeutic-dose pharmacokinetics across species to inform first-in-human dose selection

Introduction: First-in-human studies require dose extrapolation from pharmacokinetic animal studies combined with safety assessments. Subtherapeutic doses of radiolabelled drugs can be administered in preclinical and early clinical development to gain a dynamic pharmacokinetic understanding, potentially informing pharmacologically-based pharmacokinetics (PBPK) models through whole-body PET data. Aims: to develop a PET-informed modelling framework for preclinical-to-human extrapolation, with dolutegravir as a case-study. Methods: We developed a structured workflow integrating micro- and conventional-dose data for interspecies and dose extrapolation. We built a whole-body PBPK model in PK-Sim/MoBi (v12.1) using non-human primate (NHP) data in 5 key organs incorporating dolutegravir physico-chemical properties, protein binding, metabolism and efflux. Sensitivity analyses and parameter estimation were performed sequentially first with PET microdosing organ data over 3h, then with fluid and tissue concentrations following a 2.5 mg/kg IV injection. Finally, 100 Caucasian healthy adults (50% male, 20-80 years) receiving 50 mg qd po after high-fat meals were simulated using the two sets of estimated parameters and physiology-related parameter distributions provided by PK-Sim. Results: Dolutegravir blood data were well described in NHPs over 3 hours, with parameters adjusted to handle the macrodose-related changes. While microdose-based parameter estimates systematically underpredicted exposure, combining NHP micro- and conventional dose data predicted steady-state geometric mean AUC0-24 and Cmax closely matching human reported profiles, although slightly underpredicting Ctrough. Conclusions: PET-PBPK modelling combining micro- and conventional doses in NHPs successfully predicted dolutegravir concentrations in healthy volunteers, additionally informing tissue distribution. This proof of concept study supports early PET data acquisition to build robust priors for first-in-human studies.

pharmacology and toxicology↗

bioRxiv2026

Modeling how memory CD8 T cells can elicit post-treatment control of HIV infection

While most people living with HIV suffer progressive disease following cessation of antiretroviral therapy, a small fraction elicits lasting post-treatment control. Understanding the mechanisms underlying this control is key to devising effective HIV remission strategies. Although recent studies implicate memory CD8 T cells, how these cells establish lasting viremic control remains unknown. Here, we combine mathematical modeling and analysis of data from SIV-infected non-human primates to elucidate the underlying mechanisms. We recognized that sustained antigenic stimulation leads to heritable epigenetic remodeling of the CD8 T cell pool, impairing memory cell survivability. Antiretroviral therapy rapidly suppresses viremia, thereby arresting antigenic stimulation and preserving memory potential. The greater this preservation is, the better would be the memory recall response following viral rebound post-treatment. Our mathematical model based on this hypothesis predicts that post-treatment control is an alternative steady state to progressive infection, realized by strong memory-driven recall responses. Our model fits longitudinal virological data spanning the pre-, during-, and post-antiretroviral treatment phases of infection, and recapitulates the outcomes of progressive disease and long-term remission realized, the latter predominantly with early treatment initiation. It shows, consistently with data, that memory CD8 T cells could drive post-treatment control independently of the size of the latent reservoir, explaining how such control may be realized more widely than estimated with prevalent hypotheses. Our model further explains the existence of a window of treatment initiation times that maximizes the chances of post-treatment control. Finally, model predictions inform interventions targeting memory CD8 T cells for HIV remission.

immunology↗