Discovery of 12 (BMS-986172) as a Highly Potent MGAT2 Inhibitor that Achieved Targeted Efficacious Exposures at a Low Human Dose for the Treatment of Metabolic Disorders.

A series of dihydropyridinone (DHP) compounds was prepared and evaluated for MGAT2 activity. The efforts led to the identification of novel tetrazolones with potent MGAT2 inhibitory activity and favorable in vitro profiles. Further tests of select analogues in mouse models revealed significant reduction in food intake and body weight. Subsequent studies in MGAT2 knockout mice with the lead candidate 12 (BMS-986172) showed on-target- and mechanism-based pharmacology. Moreover, its favorable pharmacokinetic (PK) profile and the lack of species variability in the glucuronidation potential resulted in a greater confidence level in the projection of a low dose for achieving targeted efficacious exposures in humans. Consistent with these projections, PK data from a phase 1 trial confirmed that targeted efficacious exposures could be achieved at a low dose in humans, which supported compound 12 as our second and potentially superior development candidate for the treatment of various metabolic disorders.

Pharmacokinetic Drug-Drug Interaction Studies Between Trilaciclib and Midazolam, Metformin, Rifampin, Itraconazole, and Topotecan in Healthy Volunteers and Patients with Extensive-Stage Small-Cell Lung Cancer.

BACKGROUND AND OBJECTIVE: Trilaciclib is a cyclin-dependent kinase 4/6 inhibitor indicated to decrease the incidence of chemotherapy-induced myelosuppression in patients with extensive-stage small-cell lung cancer. Trilaciclib is a substrate and time-dependent inhibitor of cytochrome P450 3A4 and an inhibitor of multidrug and toxin extrusion 1, multidrug and toxin extrusion 2-K, organic cation transporter 1, and organic cation transporter 2. Here, we investigate the pharmacokinetic drug-drug interaction potential of trilaciclib. METHODS: Two phase I studies were conducted as prospective, open-label, fixed-sequence drug-drug interaction studies in healthy subjects (n = 57, n = 20) to investigate potential interactions between intravenously administered trilaciclib (200 or 240 mg/m2) and orally administered midazolam (5 mg), metformin (1000 mg), itraconazole (200 mg), and rifampin (600 mg). A population pharmacokinetic model was fit to phase Ib/IIa data in patients with extensive-stage small-cell lung cancer (n = 114) to assess the impact of trilaciclib dose and exposure (area under the plasma concentration-time curve) on topotecan clearance. RESULTS: Coadministration with trilaciclib had minimal effects on the exposure (area under the plasma concentration-time curve from time 0 to infinity) of midazolam (geometric least-square mean ratio [GMR] vs midazolam alone 1.065; 90% confidence interval [CI] 0.984-1.154) but statistically significantly increased plasma exposure (GMR 1.654; 90% CI 1.472-1.858) and decreased renal clearance (GMR 0.633; 90% CI 0.572-0.701) of metformin. Coadministration of trilaciclib with rifampin or itraconazole decreased trilaciclib area under the plasma concentration-time curve from time 0 to infinity by 17.3% (GMR 0.827; 90% CI 0.785-0.871) and 14.0% (GMR 0.860; 0.820-0.902), respectively, vs trilaciclib alone. Population pharmacokinetic modeling showed no significant effect of trilaciclib on topotecan clearance. CONCLUSIONS: Overall, the drug-drug interaction and safety profiles of trilaciclib in these studies support its continued use in patients with extensive-stage small-cell lung cancer. CLINICAL TRIAL REGISTRATION: Study 106: EudraCT number: 2019-002303-18; Study 114: not applicable; Study 03: Clinicaltrials.org: NCT02514447; August 2015.

Tenofovir Plasma Concentration from Preexposure Prophylaxis at the Time of Potential HIV Exposure: a Population Pharmacokinetic Modeling and Simulation Study Involving Serodiscordant Couples in East Africa.

The Partners Demonstration Project was a prospective, open-label, implementation science-driven study of preexposure prophylaxis (PrEP) among heterosexual HIV serodiscordant couples in Kenya and Uganda. Adherence data were collected using the Medication Event Monitoring System (MEMS), and time of sexual activity was collected using the mobile phone short message service (SMS). Two plasma samples were collected at a single study visit. We integrated adherence, pharmacokinetics, and SMS data using a population pharmacokinetic (PopPK) model to simulate tenofovir plasma concentrations from PrEP at the time of sexual activity. In the first stage of this analysis, we used data from the current study to update a prior PopPK model of tenofovir (TFV) developed with data from the Partners PrEP Study (a phase III clinical trial). The second stage involved simulating plasma concentrations at the time of sexual activity using empirical Bayes estimates (EBEs) derived from the final model. In addition, EBEs from a previously published parent metabolite model of TFV (MTN-001, an open-label 3-way crossover study in healthy women) was used to simulate tenofovir diphosphate (TFV-DP) concentrations. We estimated percent PrEP "coverage" as the number of reported sexual events during which simulated concentrations were above an a priori threshold concentrations associated with a high degree of protection from HIV infection: plasma TFV of >40 ng/ml and peripheral blood mononuclear cell (PBMC) TFV-DP concentration of >36 fmol/million cells. The levels of coverage were 72% for TFV and 81% for TFV-DP. These levels are consistent with a high degree of protection against HIV acquisition in this study of a pragmatic delivery model for antiretroviral-based HIV prevention.

Hospitalized Patients With and Without Hemodialysis Have Markedly Different Vancomycin Pharmacokinetics: A Population Pharmacokinetic Model-Based Analysis.

BACKGROUND: Despite being in clinical use for about 6 decades, vancomycin dosing remains perplexing and complex. METHODS: A population pharmacokinetic modeling and simulation approach was used to evaluate the efficiency of the current nomogram-based dosing of vancomycin. Serum vancomycin concentrations were obtained as a part of routine therapeutic drug monitoring from two 500-bed academic medical centers. A population pharmacokinetic model was first built using these therapeutic drug monitoring data. Population pharmacokinetic modeling was conducted using NONMEM (7.2 and 7.3). The forward addition-backward elimination approach was used to test the covariate effects. Appropriate numerical and visual criteria were used as model diagnostics for checking model appropriateness and model qualification. The current nomogram efficiency was evaluated by determining the percentage of subjects in the therapeutic range (10-20 mg/L). RESULTS: A 2-compartment model with between-subject variability on clearance (CL), central volume of distribution (Vc), and peripheral volume of distribution best fit the data. Blood urea nitrogen, age, creatinine clearance, and hemodialysis status were significant covariates on clearance. Hemodialysis status was a significant covariate on Vc and peripheral volume of distribution. In the final model, creatinine clearance was retained as a covariate on CL whereas hemodialysis status was retained as covariate on both CL and Vc. Using Monte Carlo simulations, the current nomogram was optimized by the addition of a loading dose and reducing the maintenance doses. The current nomogram is suboptimal. Optimization of the nomogram resulted in >40% subjects consistently being in the therapeutic range at troughs collected after the first 6 doses. CONCLUSIONS: CL and Vc differ markedly between patients undergoing hemodialysis and those not undergoing hemodialysis. Dosing nomogram based on these covariate relationships may potentially help in accurate dosing of vancomycin.

Population Pharmacokinetics of Tenofovir in HIV-1-Uninfected Members of Serodiscordant Couples and Effect of Dose Reporting Methods.

Antiretroviral preexposure prophylaxis (PrEP) with once-daily dosing of tenofovir and tenofovir-emtricitabine was shown to be effective for preventing HIV-1 infection in individuals who had HIV-1-seropositive partners (the Partners PrEP Study). We developed a population pharmacokinetic model for tenofovir and investigated the impacts of different dose reporting methods. Dosing information was collected as patient-reported dosing information (PRDI) from 404 subjects (corresponding to 1,280 drug concentration records) from the main trial and electronic monitoring-based adherence data collected from 211 subjects (corresponding to 327 drug concentration records) in an ancillary adherence study. Model development was conducted with NONMEM (7.2), using PRDI with a steady-state assumption or using PRDI replaced with electronic monitoring records where available. A two-compartment model with first-order absorption was the best model in both modeling approaches, with the need for an absorption lag time when electronic monitoring-based dosing records were included in the analysis. Age, body weight, and creatinine clearance were significant covariates on clearance, but only creatinine clearance was retained in the final models per stepwise selection. Sex was not a significant covariate on clearance. Tenofovir population pharmacokinetic parameter estimates and the precisions of the parameters from the two final models were comparable with the point estimates of the parameters, differing from 0% to 35%, and bootstrap confidence intervals widely overlapped. These findings indicate that PRDI was sufficient for population pharmacokinetic model development in this study, with a high level of adherence per multiple measures.