Pharmacokinetics, Mass Balance, Safety, and Tolerability of Obeldesivir in Healthy Participants.

There is an unmet need for safe and efficacious oral therapies for COVID-19 with low potential for drug-drug interactions. Obeldesivir is an orally administered nucleoside prodrug that has shown antiviral potency in nonclinical studies against SARS-CoV-2 and its circulating variants. Obeldesivir is metabolized to the active nucleoside triphosphate (GS-443902), which acts as an inhibitor of the SARS-CoV-2 RNA-dependent RNA polymerase, thereby inhibiting viral RNA synthesis. Here, we report the safety, tolerability, and pharmacokinetics from a first-in-human, randomized, placebo-controlled, phase I study following oral administration of obeldesivir and a phase I, open-label absorption, distribution, metabolism, and excretion study following oral administration of [14C]-obeldesivir. Overall, obeldesivir was safe and well tolerated at single and multiple doses between 100 and 1,600 mg, with low potential for QT prolongation as assessed by QT-concentration analysis. The exposures to GS-441524 increased dose proportionally in the 100-900-mg dose range. GS-441524 accumulated by 35% after twice-daily and 12% after once-daily dosing for 5 days. Dose-proportional increases in the intracellular concentration of GS-443902 were also observed in peripheral blood mononuclar cells. Plasma exposure of GS-441524 was not significantly altered by food intake. Following oral administration of [14C]-obeldesivir (500 mg; 100 µCi), the mean cumulative [14C]-dose recovery was 90.7% with 58.5% in urine and 32.2% in feces. GS-441524 was the predominant plasma component (90% of 14C-area under the concentration-time curve) and was primarily eliminated via renal excretion. Collectively, data from these studies support selection of the obeldesivir 350 mg twice-daily dosing regimen for further evaluation in phase III studies for COVID-19.

Pharmacokinetics, safety, and tolerability of inhaled remdesivir in healthy participants.

Intravenous remdesivir (RDV) is US Food and Drug Administration-approved for hospitalized and nonhospitalized individuals with coronavirus disease 2019. RDV undergoes intracellular metabolic activation to form the active triphosphate, GS-443902, and other metabolites. Alternative administration routes, including localized pulmonary delivery, can lower systemic exposure and maximize exposure at the site of action. This study evaluated the pharmacokinetics (PK) and safety of inhaled RDV in healthy adults. This phase Ia, randomized, placebo-controlled study evaluated inhaled RDV in healthy participants randomized 4:1 to receive RDV or placebo as single doses (4 cohorts) or multiple once-daily doses (3 cohorts). Doses in cohorts 1-6 were administered as an aerosolized solution for inhalation through a sealed facemask; doses in cohort 7 were administered as an aerosolized solution for inhalation through a mouthpiece. Safety was assessed throughout the study. Seventy-two participants were enrolled (inhaled RDV, n = 58 and placebo, n = 14). Following single RDV doses, RDV, GS-704277, and GS-441524 plasma PK parameters indicated dose-proportional increases in area under the concentration-time curve (AUC) extrapolated to infinite time, AUC from time zero to last quantifiable concentration, and maximum observed concentration. Analyte plasma concentrations after multiple RDV doses were consistent with those for single-dose RDV. Analyte plasma exposures were lower when RDV was administered with a mouthpiece versus a sealed facemask. The most common adverse events included nausea, dizziness, and cough. Single- and multiple-dose inhaled RDV exhibited linear and dose-proportional plasma PK. Administration of RDV via inhalation was generally safe and well-tolerated.

Resistance Analyses in Highly Treatment-Experienced People With Human Immunodeficiency Virus (HIV) Treated With the Novel Capsid HIV Inhibitor Lenacapavir.

BACKGROUND: Lenacapavir (LEN) is a first-in-class inhibitor of human immunodeficiency virus type 1 (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 (ARV) classes and resistance to ≥2 ARV drugs per class. Baseline resistance analyses used commercial assays (HIV-1 protease, reverse transcriptase, integrase genotypic/phenotypic tests). Postbaseline 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. Postbaseline 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.

Characterizing and Quantifying Extrahepatic Metabolism of (-)-Δ9-Tetrahydrocannabinol (THC) and Its Psychoactive Metabolite, (±)-11-Hydroxy-Δ9-THC (11-OH-THC).

(-)-Δ9-Tetrahydrocannabinol (THC) is the psychoactive constituent of cannabis, a drug recreationally consumed orally or by inhalation. Physiologically based pharmacokinetic (PBPK) modeling can be used to predict systemic and tissue exposure to THC and its psychoactive metabolite, (±)-11-hydroxy-Δ9-THC (11-OH-THC). To populate a THC/11-OH-THC PBPK model, we previously characterized the depletion clearance of THC (by CYP2C9) and 11-OH-THC (by UDP-glucuronosyltransferase (UGT), CYP3A, and CYP2C9) in adult human liver microsomes. Here we focused on quantifying extrahepatic depletion clearance of THC/11-OH-THC, important after oral (intestine) and inhalational (lung) consumption of THC as well as prenatal THC use (placenta and fetal liver). THC (500 nM) was metabolized in adult human intestinal microsomes (n = 3-5) by CYP2C9 [Vmax: 1.1 ± 0.38 nmol/min/mg; Michaelis-Menten constant (Km): 70 nM; intrinsic clearance (CLint): 15 ± 5.4 ml/min/mg; fraction metabolized (fm): 0.89 ± 0.31 at concentration ≪ 70 nM] and CYP3A (CLint: 2.0 ± 0.86 ml/min/mg; fm: 0.11 ± 0.050). 11-OH-THC (50 nM) was metabolized by CYP3A (CLint: 0.26 ± 0.058 ml/min/mg; fm: 0.51 ± 0.11) and UGT2B7 (CLint: 0.13 ± 0.027 ml/min/mg; fm: 0.25 ± 0.053). THC at 500 nM (CLint: 4.7 ± 0.22 ml/min/mg) and 11-OH-THC at 50 nM (CLint: 2.4 ± 0.13 ml/min/mg) were predominately (fm: 0.99 and 0.80, respectively) metabolized by CYP3A in human fetal liver microsomes (n = 3). However, we did not observe significant depletion of THC/11-OH-THC in adult lung, first trimester, second trimester, or term placentae microsomes. Using PBPK modeling and simulation, these data could be used in the future to predict systemic and tissue THC/11-OH-THC exposure in healthy and special populations. SIGNIFICANCE STATEMENT: This is the first characterization and quantification of (-)-Δ9-tetrahydrocannabinol (THC) and (±)-11-hydroxy-Δ9-THC (11-OH-THC) depletion clearance by cytochrome P450 and UDP-glucuronosyltransferase enzymes in extrahepatic human tissues: intestine, fetal liver, lung, and placenta. These data can be used to predict, through physiologically based pharmacokinetic modeling and simulation, systemic and tissue THC/11-OH-THC exposure after inhalational and oral THC use in both healthy and special populations (e.g., pregnant women).

Successful Prediction of Human Fetal Exposure to P-Glycoprotein Substrate Drugs Using the Proteomics-Informed Relative Expression Factor Approach and PBPK Modeling and Simulation.

Many women take drugs during their pregnancy to treat a variety of clinical conditions. To optimize drug efficacy and reduce fetal toxicity, it is important to determine or predict fetal drug exposure throughout pregnancy. Previously, we developed and verified a maternal-fetal physiologically based pharmacokinetic (m-f PBPK) model to predict fetal Kp,uu (unbound fetal plasma AUC/unbound maternal plasma AUC) of drugs that passively cross the placenta. Here, we used in vitro transport studies in Transwell, in combination with our m-f PBPK model, to predict fetal Kp,uu of drugs that are effluxed by placental P-glycoprotein (P-gp)-namely, dexamethasone, betamethasone, darunavir, and lopinavir. Using Transwell, we determined the efflux ratio of these drugs in hMDR1-MDCKcP-gpKO cells, in which human P-gp was overexpressed and the endogenous P-gp was knocked out. Then, using the proteomics-informed efflux ratio-relative expressive factor approach, we predicted the fetal Kp,uu of these drugs at term. Finally, to verify our predictions, we compared them with the observed in vivo fetal Kp,uu at term. The latter was estimated using our m-f PBPK model and published fetal [umbilical vein (UV)]/maternal plasma drug concentrations obtained at term (UV/maternal plasma). Fetal Kp,uu predictions for dexamethasone (0.63), betamethasone (0.59), darunavir (0.17), and lopinavir (0.08) were successful, as they fell within the 90% confidence interval of the corresponding in vivo fetal Kp,uu (0.30-0.66, 0.29-0.71, 0.11-0.22, 0.04-0.19, respectively). This is the first demonstration of successful prediction of fetal Kp,uu of P-gp drug substrates from in vitro studies. SIGNIFICANCE STATEMENT: For the first time, using in vitro studies in cells, this study successfully predicted human fetal Kp,uu of P-gp substrate drugs. This success confirms that the m-f PBPK model, combined with the ER-REF approach, can successfully predict fetal drug exposure to P-gp substrates. This success provides increased confidence in the use of the ER-REF approach, combined with the m-f PBPK model, to predict fetal Kp,uu of drugs (transported by P-gp or other transporters), both at term and at earlier gestational ages.

Estimating fetal exposure to the P-gp substrates, corticosteroids, by PBPK modeling to inform prevention of neonatal respiratory distress syndrome.

We have previously developed a maternal-fetal physiologically-based pharmacokinetic (m-f PBPK) model to dynamically predict (and verify) fetal-maternal exposure to drugs that passively diffuse across the placenta. Here, we extended the application of this model to dynamically predict fetal exposure to drugs which are effluxed by placental P-glycoprotein, namely the antenatal corticosteroids (ACS; dexamethasone [DEX], and betamethasone [BET]). To do so, we estimated both the placental P-gp mediated efflux clearance (CL) and the passive diffusion CL of the ACS. The efficacy and toxicity of the currently used maternal ACS dosing regimens to prevent neonatal respiratory distress syndrome could be improved by altering their dosing regimens. Therefore, to illustrate the utility of our m-f PBPK model, we used it to design alternative dosing regimens of DEX and BET that could potentially improve their efficacy and reduce their toxicity. The redesigned dosing regimens are convenient to administer, maintain maternal-fetal exposure (area under the concentration-time curve [AUC]) or maximum plasma concentration (Cmax ) or both (DEX and BET) or minimize maternal exposure while maintaining fetal drug plasma concentrations above the minimum therapeutic threshold of 1 ng/ml for 48 h (BET only; based on efficacy data in sheep). To our knowledge, this is the first study to dynamically predict fetal plasma concentrations of placental P-gp effluxed drugs. Our approach and our m-f PBPK model could be used in the future to predict maternal-fetal exposure to any drug and to design alternative dosing regimens of the drug.

Novel Trifluoromethyl Pyrimidinone Compounds With Activity Against Mycobacterium tuberculosis.

The identification and development of new anti-tubercular agents are a priority research area. We identified the trifluoromethyl pyrimidinone series of compounds in a whole-cell screen against Mycobacterium tuberculosis. Fifteen primary hits had minimum inhibitory concentrations (MICs) with good potency IC90 is the concentration at which M. tuberculosis growth is inhibited by 90% (IC90 < 5 µM). We conducted a structure-activity relationship investigation for this series. We designed and synthesized an additional 44 molecules and tested all analogs for activity against M. tuberculosis and cytotoxicity against the HepG2 cell line. Substitution at the 5-position of the pyrimidinone with a wide range of groups, including branched and straight chain alkyl and benzyl groups, resulted in active molecules. Trifluoromethyl was the preferred group at the 6-position, but phenyl and benzyl groups were tolerated. The 2-pyridyl group was required for activity; substitution on the 5-position of the pyridyl ring was tolerated but not on the 6-position. Active molecules from the series demonstrated low selectivity, with cytotoxicity against eukaryotic cells being an issue. However, there were active and non-cytotoxic molecules; the most promising molecule had an MIC (IC90) of 4.9 µM with no cytotoxicity (IC50 > 100 µM). The series was inactive against Gram-negative bacteria but showed good activity against Gram-positive bacteria and yeast. A representative molecule from this series showed rapid concentration-dependent bactericidal activity against replicating M. tuberculosis bacilli with ~4 log kill in <7 days. Overall the biological properties were promising, if cytotoxicity could be reduced. There is scope for further medicinal chemistry optimization to improve the properties without major change in structural features.

Successful Prediction of Human Steady-State Unbound Brain-to-Plasma Concentration Ratio of P-gp Substrates Using the Proteomics-Informed Relative Expression Factor Approach.

In order to optimize central nervous system (CNS) drug development, accurate prediction of the drug's human steady-state unbound brain interstitial fluid-to-plasma concentration ratio (Kp,uu,brain ) is critical, especially for drugs that are effluxed by the multiple drug resistance transporters (e.g., P-glycoprotein, P-gp). Due to lack of good in vitro human blood-brain barrier models, we and others have advocated the use of a proteomics-informed relative expressive factor (REF) approach to predict Kp,uu,brain . Therefore, we tested the success of this approach in humans, with a focus on P-gp substrates, using brain positron emission tomography imaging data for verification. To do so, the efflux ratio (ER) of verapamil, N-desmethyl loperamide, and metoclopramide was determined in human P-gp-transfected MDCKII cells using the Transwell assay. Then, using the ER estimate, Kp,uu,brain of the drug was predicted using REF (ER approach). Alternatively, in vitro passive and P-gp-mediated intrinsic clearances (CLs) of these drugs, estimated using a five-compartmental model, were extrapolated to in vivo using REF (active CL) and brain microvascular endothelial cells protein content (passive CL). The ER approach successfully predicted Kp,uu,brain of all three drugs within twofold of observed data and within 95% confidence interval of the observed data for verapamil and N-desmethyl loperamide. Using the in vitro-to-in vivo extrapolated clearance approach, Kp,uu,brain was reasonably well predicted but not the brain unbound interstitial fluid drug concentration-time profile. Therefore, we propose that the ER approach be used to predict Kp,uu,brain of CNS candidate drugs to enhance their success in development.

Gestational Age-Dependent Abundance of Human Placental Transporters as Determined by Quantitative Targeted Proteomics.

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 maternal-fetal 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.

Hepatic Enzymes Relevant to the Disposition of (-)-∆9-Tetrahydrocannabinol (THC) and Its Psychoactive Metabolite, 11-OH-THC.

Marijuana use by pregnant women is increasing. To predict developmental risk to the fetus/neonate from such use, in utero fetal exposure to (-)-∆9-tetrahydrocannabinol (THC), the main psychoactive cannabinoid in marijuana and its active psychoactive metabolite, 11-hydroxy-∆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 ± 0.08 and 0.99 ± 0.10, respectively (mean ± 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 ± 0.05 and 0.40 ± 0.05, respectively (mean ± S.D.), with UGT2B7, UGT1A9, CYP2C9, and CYP3A4 as contributors. These mechanistic data represent the first set of drug-dependent parameters necessary to predict maternal-fetal cannabinoid exposure during pregnancy using PBPK modeling.