Some women take medication during pregnancy to address a variety of clinical conditions. Because of ethical and logistical concerns, it is impossible to determine fetal drug exposure, and therefore fetal risk, during pregnancy. Hence, alternative approaches need to be developed to predict maternal-fetal drug exposure throughout pregnancy. To do so, we previously developed and verified a maternalfetal physiologically based pharmacokinetic model, which can predict fetal exposure to drugs that passively cross the placenta. However, many drugs are actively transported by the placenta (e.g., human immunodeficiency virus protease inhibitors). To extend our maternal-fetal physiologically based pharmacokinetic model to these actively transported drugs, we determined the gestational age-dependent changes in the protein abundance of placental transporters. Total cellular membrane fractions from first trimester (T1; n = 15), second trimester (T2; n = 19), and term (n = 15) human placentae obtained from uncomplicated pregnancies were isolated by ultracentrifugation. Transporter protein abundance was determined by targeted quantitative proteomics using liquid chromatography tandem mass specrometry. We observed that breast cancer resistance protein and P-glycoprotein abundance significantly decreased from T1 to term by 55% and 69%, respectively (per gram of tissue). Organic anion-transporting polypeptide (OATP) 2B1 abundance significantly decreased from T1 to T2 by 32%. In contrast, organic cation transporter (OCT) 3 and organic anion transporter 4 abundance significantly increased with gestational age (2-fold from T1 to term, 1.6-fold from T2 to term). Serotonin transporter and norepinephrine transporter did not change with gestational age. The abundance of bile salt export pump, multidrug resistance-associated protein 1-5, Na +-taurocholate cotransporting polypeptide, OATP1B1, OATP1B3, OCTN1-2, concentrative nucleoside transporter 1-3, equilibrative nucleoside transporter 2, and multidrug and toxin extrusion 1 could not be quantified. These data can be incorporated into our maternal-fetal physiologically based pharmacokinetic model to predict fetal exposure to drugs that are actively transported across the placenta. SIGNIFICANCE STATEMENT We quantified the protein abundance of key placental uptake and efflux transporters [organic cation transporter (OCT) 3, P-glycoprotein (P-gp), breast cancer resistance protein (BCRP)] across gestational ages (first trimester, second trimester, and term) using quantitative targeted proteomics. We observed that the protein abundance of P-gp and BCRP decreased, whereas that of OCT3 increased with gestational age. Incorporating the protein abundance determined in this study into maternal-fetal physiologically based pharmacokinetic model can help us better predict fetal drug exposure to substrates of these transporters.

5 th percentile: 5 th percentile confidence value; 95 th percentile: 95 th percentile confidence value; AAFE: absolute average fold error; AUC f : area under the curve of total fetal plasma concentration-time profile; AUC m : area under the curve of total maternal plasma concentration-time profile; BCRP: breast cancer resistance protein; BID: Bis in die, twice daily; CI 90% : 90% confidence interval spanning between 5th and 95th percentiles; CL int,PD,placenta : intrinsic placental passive diffusion clearance; CL int,Pgp,placenta : In vivo P-gp mediated efflux clearance from the placenta; C max : maximum plasma drug concentration; C-T profile: drug plasma concentration-time profile; CYP: cytochrome P450; DEX: dexamethasone; DRV: darunavir; ER: This article has not been copyedited and formatted. The final version may differ from this version.

Background Lenacapavir is a first-in-class inhibitor of HIV-1 capsid function in clinical development for the treatment of heavily treatment-experienced (HTE) people with HIV (PWH) harboring multidrug resistance (MDR) in combination with an optimized background regimen (OBR). Here we describe resistance analyses conducted in the pivotal phase 2/3 CAPELLA study. Methods CAPELLA enrolled viremic HTE PWH with resistance to ≥ 3 of 4 of the main antiretroviral classes and resistance to ≥ 2 ARV drugs per class. Baseline resistance analyses used commercial assays (HIV-1 protease, RT, integrase genotypic/phenotypic tests). Post-baseline resistance was evaluated in participants experiencing virologic failure. Results At baseline, 46% of participants had resistance to the 4 main ARV drug classes, with one third of participants having exhausted all drugs from ≥ 3 of the 4 main ARV classes. Treatment with LEN + OBR for 26 weeks led to viral suppression in 81% of participants. Post-baseline resistance mutations to lenacapavir occurred in 8 participants (6 with M66I, 1 with K70H, 1 with Q67H + K70R) who were receiving unintended functional LEN monotherapy at the time of resistance selection. Conclusions LEN added to OBR led to high efficacy in this HTE patient population with MDR but could select for resistance when used unintentionally as functional monotherapy.

Marijuana use by pregnant women is increasing. To predict developmental risk to the fetus/neonate from such use, in utero fetal exposure to (2)-Δ 9 -tetrahydrocannabinol (THC), the main psychoactive cannabinoid in marijuana and its active psychoactive metabolite, 11-hydroxy-Δ 9 -tetrahydrocannabinol (11-OH-THC), needs to be determined. Since such measurement is not possible, physiologically based pharmacokinetic (PBPK) modeling and simulation can provide an alternative method to estimate fetal exposure to cannabinoids. To do so, pharmacokinetic parameters for the disposition of THC and 11-OH-THC need to be elucidated. Here, we report a first step to estimate these parameters, namely, those related to maternal metabolism of THC/11-OH-THC in human liver microsomes (HLMs) at plasma concentrations observed after smoking marijuana. Using recombinant cytochrome P450 (P450) and UDP-glucuronosyltransferase (UGT) enzymes, CYP1A1, 1A2, 2C9, 2C19, 2D6, 3A4, 3A5, 3A7, and UGT1A9 and UGT2B7 were found to be involved in the disposition of THC/11-OH-THC. Using pooled HLMs, the fraction metabolized (f m ) by relevant enzymes was measured using selective enzyme inhibitors, and then adjusted for enzyme cross-inhibition. As previously reported, CYP2C9 was the major enzyme responsible for depletion of THC and formation of 11-OH-THC with f m values of 0.82 6 0.08 and 0.99 6 0.10, respectively (mean 6 S.D.), while CYP2D6 and CYP2C19 were minor contributors. 11-OH-THC was depleted by UGT and P450 enzymes with f m values of 0.60 6 0.05 and 0.40 6 0.05, respectively (mean 6 S.D.), with UGT2B7, UGT1A9, CYP2C9, and CYP3A4 as contributors. These mechanistic data represent the first set of drug-dependent parameters necessary to predict maternalfetal cannabinoid exposure during pregnancy using PBPK modeling.

Accurately predicting unbound brain interstitial fluid (ISF) concentrations of CNS drugs is challenging, especially when drugs are substrates of efflux transporters (e.g., P-glycoprotein). This is one reason why development of CNS drugs has a high attrition rate. WHAT QUESTION DID THIS STUDY ADDRESS?  We determined whether the proteomics-informed relative expression factor (REF) approach can successfully predict the unbound human brain ISF distribution of drugs at steady state or pseudoequilibrium.