Predictors of sirolimus pharmacokinetic variability identified using a nonlinear mixed effects approach: a systematic review

Abstract

Several sirolimus (SRL) population pharmacokinetics (PopPK) were conducted to explain its pharmacokinetic variability, and the results varied across studies. Thus, we conducted a systematic review to summarize significant predictors influencing SRL pharmacokinetic variability. Moreover, discrepancies in model methodologies across studies were also reviewed and discussed. Four databases (PubMed, CINAHL Complete, Science Direct, and Scopus) were systematically searched. The PICO framework was used to identify eligible studies conducted in humans and employ a nonlinear-mixed effects strategy. Based on the inclusion and exclusion criteria, 20 studies were included. SRL pharmacokinetics were explained using 1-or 2-compartment models. Only one study assessed the model using an external approach, while the rest employed basic or advanced internal approaches. Significant covariates influencing SRL pharmacokinetics were bodyweight, age, CYP3A5 polymorphism, gender, BSA, height, cyclosporine dose or trough concentration, triglyceride, total cholesterol, hematocrit, albumin, aspartate aminotransferase, alanine aminotransferase, and total bilirubin. Of these, bodyweight, age, and CYP3A5 polymorphism were the three most identified significant predictors for SRL clearance. This review summarizes significant predictors to predict SRL clearance, which can subsequently be used to individualize SRL maintenance dose. However, the PopPK model selected for such prediction should be based on the resemblance of population characteristics Predictors of sirolimus pharmacokinetic variability identified using a nonlinear mixed effects approach e12

Beyond Rule of Five and PROTACs in Modern Drug Discovery: Polarity Reducers, Chameleonicity, and the Evolving Physicochemical Landscape

“…Our analysis was based on a comprehensive absorption data set that included a broad spectrum of human fraction absorbed (fa) values for approximately 1000 compounds, ,− rodent faFg values for over 10,000 compounds, and about 3000 compounds with measured EPSA, noting that there was some overlap among the three data sets (Figure A). In this context, we evaluated ∼1000 AbbVie tool PROTACs, ∼2000 bRo5s, and ∼7000 Ro5s, with 36 external compounds (inclusive of approved drugs, clinical candidates, and tool compounds).…”