CPT: Pharmacometrics & Systems Pharmacology (Nov 2024)

Development of a physiologically based pharmacokinetic model of fostemsavir and its pivotal application to support dosing in pregnancy

  • Farzaneh Salem,
  • Dung Nguyen,
  • Mark Bush,
  • Katy P. Moore,
  • Jennypher Mudunuru,
  • Konstantinos Stamatopoulos,
  • Nilay Thakkar,
  • Kunal S. Taskar

DOI
https://doi.org/10.1002/psp4.13156
Journal volume & issue
Vol. 13, no. 11
pp. 1881 – 1892

Abstract

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Abstract It is critical to understand the impact of significant physiological changes during pregnancy on the extent of maternal and fetal drug exposure. Fostemsavir (FTR) is a prodrug of temsavir (TMR) and is approved in combination with other antiretrovirals for multi‐drug‐resistant human immunodeficiency virus (HIV) infections. This physiologically based pharmacokinetic model (PBPK) study was used to estimate TMR PK in pregnant populations during each trimester of pregnancy to inform FTR dosing. A PBPK model was developed and validated for TMR using PK data collected following intravenous TMR and oral FTR dosing (immediate‐release and extended‐release tablets) in healthy volunteers. Predicted TMR concentration–time profiles accurately predicted the reported clinical data and variability in healthy (dense data) and pregnant (sparse data) populations. Predicted versus observed TMR geometric mean (CV%) clearance following intravenous administration was 18.01 (29) versus 17 (21) (L/h). Predicted versus observed TMR AUC0–inf (ng.h/mL) in healthy volunteers following FTR administration of the extended‐release tablet were 9542 (66) versus 7339 (33). The validated TMR PBPK model was then applied to predict TMR PK in a population of pregnant individuals during each trimester. Simulations showed TMR AUC in pregnant individuals receiving FTR 600 mg twice daily was decreased by 25% and 38% in the second and third trimesters, respectively. However, TMR exposure remained within the range observed in nonpregnant adults with no need for dose adjustment. The current PBPK model can also be applied for the prediction of local tissue concentrations and drug–drug interactions in pregnancy.