Model-Based Dose Selection of Fostemsavir for Pediatric Populations With Multidrug-Resistant HIV-1 and Relative Bioavailability Assessment in Healthy Adults.

Fostemsavir, a prodrug of the first-in-class HIV-1 attachment inhibitor temsavir, is approved for the treatment of multidrug-resistant HIV-1 in adults; its use in pediatric populations is currently being studied. Population pharmacokinetic modeling across pediatric weight bands was used to guide pediatric fostemsavir dose selection. Dosing simulations demonstrated that twice-daily fostemsavir 600-mg (adult dose) and 400-mg doses met safety and efficacy criteria for 35 kg or greater and 20 or greater to less than 35 kg pediatric weight bands, respectively. Temsavir relative bioavailability of 2 low-dose fostemsavir extended-release formulations (3 × 200 mg; formulations A and B) and reference formulation (600 mg extended release) was assessed in a 2-part, open-label, randomized, crossover study in healthy adults. Part 1 (N = 32) compared single-dose temsavir relative bioavailability, and Part 2 (N = 16) evaluated the impact of fed versus fasted conditions using the selected low-dose formulation. Temsavir geometric mean ratios for the area under the plasma concentration-time curve from time zero to infinity and maximum concentration for formulation B were bioequivalent to the reference formulation. Temsavir maximum concentration for formulation B was similar in fed and fasted states, but area under the plasma concentration-time curve from time zero to infinity geometric mean ratio was increased under fed conditions, consistent with previous results in adults. These analyses demonstrated efficient pediatric dose selection using a model-based approach.

Assessment of effect size and power for survival analysis through a binary surrogate endpoint in clinical trials.

A strategy for early-stage breast cancer trials in recent years consists of a neoadjuvant trial with pathological complete response (pCR) at time of surgery as the efficacy endpoint, followed by the collection of long-term data to show efficacy in survival. To calculate an appropriate sample size to detect a survival difference based upon pCR data, it is necessary to relate the effect size in pCR with the effect size in survival. Here, we propose an exponential mixture model for survival time with parameters for the neoadjuvant pCR rates and an estimated benefit of achieving pCR to determine the treatment effect size. Through simulation studies, we demonstrated how to estimate the empirical power for detecting the survival efficacy under a parameter setting. We also showed a more efficient way to estimate the power for detecting the survival efficacy through estimated average hazard ratios and the Schoenfeld formula. Our method can be used to power future confirmatory adjuvant trials based on the preliminary data obtained from the neoadjuvant component.