Model-based predictions of protective HIV pre-exposure prophylaxis adherence levels in cisgender women.

Most human immunodeficiency virus (HIV) infections occur in cisgender women in resource-limited settings. In women, self-protection with emtricitabine/tenofovir disoproxil fumarate pre-exposure prophylaxis (FTC/TDF-PrEP) constitutes a major pillar of HIV prevention. However, clinical trials in women had inconsistent outcomes, sparking uncertainty about adherence requirements and reluctance in evaluating on-demand regimens. We analyzed data from published FTC/TDF-PrEP trials to establish efficacy ranges in cisgender women. In a 'bottom-up' approach, we modeled hypotheses in the context of risk-group-specific, adherence-efficacy profiles and challenged those hypotheses with clinical data. We found that different clinical outcomes were related to the proportion of women taking the product, allowing coherent interpretation of the data. Our analysis showed that 90% protection was achieved when women took some product. We found that hypotheses of putative male/female differences were either not impactful or statistically inconsistent with clinical data. We propose that differing clinical outcomes could arise from pill-taking behavior rather than biological factors driving specific adherence requirements in cisgender women.

Synthesis of protective oral PrEP adherence levels in cisgender women using convergent clinical- and bottom-up modeling.

Globally, most HIV infections occur in heterosexual women in resource-limited settings. In these settings, female self-protection with generic emtricitabine/tenofovir disoproxil fumarate pre-exposure prophylaxis (FTC/TDF-PrEP) may constitute a major pillar of the HIV prevention portfolio. However, clinical trials in women had inconsistent outcomes, sparking uncertainty regarding risk-group specific adherence requirements and causing reluctance in testing and recommending on-demand regimen in women. We analyzed all FTC/TDF-PrEP trials to establish PrEP efficacy ranges in women. In a 'bottom-up' approach, we modeled hypotheses corroborating risk-group specific adherence-efficacy profiles. Finally, we used the clinical efficacy ranges to (in-)validate hypotheses. We found that different clinical outcomes could solely be explained by the proportion of enrolled participants not taking the product, allowing, for the first time, to unify clinical observations. This analysis showed that 90% protection was achieved, when women took some of the product. Using 'bottom-up' modelling, we found that hypotheses of putative male/female differences were either irrelevant, or statistically inconsistent with clinical data. Furthermore, our multiscale modelling indicated that 90% protection was achieved if oral FTC/TDF was taken at least twice weekly.

Population pharmacokinetics of tenofovir, emtricitabine and intracellular metabolites in transgender women.

AIMS: Transgender women (TGW) have been underrepresented in trials and use gender-affirming hormonal therapies (GAHT) that may alter renal function by significantly increasing creatinine clearance. Population pharmacokinetic (popPK) models and simulations would aid in understanding potential differences in emtricitabine/tenofovir disproxil fumarate (F/TDF) parent-metabolite concentrations in TGW on GAHT when compared to cisgender men (CGM) not exposed to GAHT. METHODS: Pharmacokinetic (PK) data from a Phase 1, open-label clinical trial with directly observed therapy of daily F/TDF consisting of 8 TGW and 8 CGM was utilized for model building. PopPK analysis was performed using nonlinear mixed effects modelling (NONMEM 7.5.0). Covariates of body weight, creatinine clearance, and gender were evaluated. Final models were subjected to Monte Carlo simulations to compare drug exposure following once daily and on-demand (IPERGAY 2 + 1 + 1) dosing of F/TDF. RESULTS: Tenofovir (TFV) and emtricitabine PK were best described by a 2-compartment model, first-order absorption/elimination with absorption lag time. Parent models were linked to their metabolites by first order formation and elimination. Creatinine clearance was a significant covariate influencing clearance in both models. Simulations demonstrated that at least 2, weekly 2 + 1 + 1 cycles of on-demand dosing in TGW on GAHT is necessary for TFV-diphosphate to reach similar exposure after the initial week of on-demand dosing in CGM not on GAHT. CONCLUSION: PopPK models of TFV, emtricitabine and intracellular metabolites in TGW were established. Dose simulations revealed that TGW should be treated for at least 2 weeks to have comparable exposures to CGM.

Determining the Exposure Threshold for Levonorgestrel Efficacy Using an Integrated Model Based Meta-Analysis Approach.

Combined oral contraceptive pills are the most commonly used hormonal contraceptives for the prevention of unintended pregnancies in United States. They consist of a progestin (e.g., levonorgestrel (LNG)) and an estrogen component, typically ethinyl estradiol (EE). In addition to adherence issues, drug-drug interactions (DDIs) and obesity (women with body mass index (BMI) ≥ 30 kg/m2 ) are prime suspects for decreased LNG efficacy. Therefore, we developed an integrated physiologically-based pharmacokinetic modeling and model-based meta-analysis approach to determine LNG's efficacy threshold concentrations and to evaluate the impact of DDIs and obesity on the efficacy of LNG-containing hormonal contraceptives (HCs). Based on this approach, co-administration of strong CYP3A4 inducers and LNG-containing HCs (LNG150: LNG 150 µg + EE 30 µg and LNG100: LNG 100 µg + EE 20 µg) resulted in a predicted clinically relevant decrease of LNG plasma exposure (women with BMI < 25 kg/m2 : 50-65%; obese women: 70-75%). Following administration of LNG150 or LNG100 in the presence of a CYP3A4 inducer, there was an increase in mean Pearl Index of 1.2-1.30 and 1.80-2.10, respectively, in women with BMI < 25 kg/m2 (incidence rate ratios (IRRs): 1.7-2.2), whereas it ranged from 1.6-1.80 and 2.40-2.85 in obese women (IRR: 2.2-3.0), respectively. Our results suggest that the use of backup or alternate methods of contraception is not necessarily required for oral LNG + EE formulations except within circumstances of both obesity and strong CYP3A4 inducer concomitance following administration of LNG100.

Quantitative Assessment of Levonorgestrel Binding Partner Interplay and Drug-Drug Interactions Using Physiologically Based Pharmacokinetic Modeling.

Levonorgestrel (LNG) is the active moiety in many hormonal contraceptive formulations. It is typically coformulated with ethinyl estradiol (EE) to decrease intermenstrual bleeding. Due to its widespread use and CYP3A4-mediated metabolism, there is concern regarding drug-drug interactions (DDIs), particularly a suboptimal LNG exposure when co-administered with CYP3A4 inducers, potentially leading to unintended pregnancies. The goal of this analysis was to determine the impact of DDIs on the systemic exposure of LNG. To this end, we developed and verified a physiologically-based pharmacokinetic (PBPK) model for LNG in PK-Sim (version 8.0) accounting for the impact of EE and body mass index (BMI) on LNG's binding to sex-hormone binding globulin. Model parameters were optimized following intravenous and oral administration of 0.09 mg LNG. The combined LNG-EE PBPK model was verified regarding CYP3A4-mediated interaction by comparing to published clinical DDI study data with carbamazepine, rifampicin, and efavirenz (CYP3A4 inducers). Once verified, the model was applied to predict systemic LNG exposure in normal BMI and obese women (BMI ≥ 30 kg/m2 ) with and without co-administration of itraconazole (competitive CYP3A4 inhibitor) and clarithromycin (mechanism-based CYP3A4 inhibitor). Total and free LNG exposures, when co-administered with EE, decreased 2-fold in the presence of rifampin, whereas they increased 1.5-fold in the presence of itraconazole. Although changes in total and unbound exposure were decreased in obese women compared with normal BMI women, the relative impact of DDIs on LNG exposure was similar between both groups.

Incorporating Pharmacometrics into Pharmacoeconomic Models: Applications from Drug Development.

Pharmacometrics is the science of quantifying the relationship between the pharmacokinetics and pharmacodynamics of drugs in combination with disease models and trial information to aid in drug development and dosing optimization for clinical practice. Considering the variability in the dose-concentration-effect relationship of drugs, an opportunity exists in linking pharmacokinetic and pharmacodynamic model-based estimates with pharmacoeconomic models. This link may provide early estimates of the cost effectiveness of drug therapies, thus informing late-stage drug development, pricing, and reimbursement decisions. Published case studies have demonstrated how integrated pharmacokinetic-pharmacodynamic-pharmacoeconomic models can complement traditional pharmacoeconomic analyses by identifying the impact of specific patient sub-groups, dose, dosing schedules, and adherence on the cost effectiveness of drugs, thus providing a mechanistic basis to predict the economic value of new drugs. Greater collaboration between the pharmacoeconomics and pharmacometrics community can enable methodological improvements in pharmacokinetic-pharmacodynamic-pharmacoeconomic models to support drug development.

Utility of Physiologically Based Pharmacokinetic Modeling in Point-of-Care Decisions: An Example Using Digoxin Dosing in Continuous Venovenous Hemodiafiltration.

We describe the case of a patient on continuous venovenous hemodiafiltration with atrial fibrillation with rapid ventricular response and hypotension requiring vasopressor use, which warranted digoxin therapy. In the absence of guidelines specifying appropriate digoxin dosing in patients undergoing continuous venovenous hemodiafiltration, anecdotal evidence-guided digoxin dosing was performed for this patient using plasma digoxin concentration-based therapeutic drug monitoring. We use this case to demonstrate the potential role of physiologically based pharmacokinetic modeling in assisting therapeutic decision making.

Diversity in the Era of Precision Medicine - From Bench to Bedside Implementation.

Recent evidence shows how patients' unique genetic makeup can affect disease outcomes and the increasing availability of targeted treatments promises a future in health care, whereby treatments will be tailored to individual needs. This article reports on the topics discussed at the 13th Annual Texas Conference on Health Disparities, organized by the Texas Center for Health Disparities at the University of North Texas Health Science Center; the meeting focused on the theme, "Diversity in the Era of Precision Medicine" and was held during June 2018 in Fort Worth, Texas. The primary focus of this conference, which brought together clinical and basic scientists, was on the inclusion of diversity in precision medicine to bridge the gap in health disparities. Here, we present the highlights of the conference that include the potential application of precision medicine at the population level, the effects of precision medicine and direct-to-consumer testing on health disparities, genetic basis of health disparities, pharmacogenomics, and strategies to enhance participation of under-represented populations in precision medicine. Furthermore, we conclude with recommendations for future implementation, including how to mitigate disparities in genomics services and enhance participation of diverse groups in clinical trials.

Assessment of Demographic and Socio-Behavioral Factors on Adherence to HIV Pre-Exposure Prophylaxis Using a Markov Modeling Approach.

Purpose: Adherence is important for the effectiveness of human immunodeficiency virus (HIV) preexposure prophylaxis (PrEP). The objective of the current work is to assess the impact of multiple demographic and socio-behavioral factors on the adherence to tenofovir-based PrEP among HIV serodiscordant couples in East Africa using Markov mixed-effects modeling approach. Methods: The Partners Demonstration Project was a prospective, open-label, implementation science-driven study of HIV PrEP among heterosexual HIV serodiscordant couples in Kenya and Uganda. The uninfected partner received oral PrEP according to the "bridge to antiretroviral therapy [ART]" strategy (i.e., until the infected partner had been on ART for ≥6 months). Adherence was monitored electronically; demographic and socio-behavioral data were collected during study visits. Analyzed data reflect 12 months of follow-up per participant. A two-state, first-order, discrete time Markov model was developed with longitudinal adherence data characterized by "dose taking (1)" and "dose missing (0)." Covariate effects were linearly added in the logit domain of transition probability parameters (P01 and P10) in the model. The full covariate model was initially developed, followed by backward elimination process to reduce the model. All significant covariates reported by a prior primary statistical analysis of the same data were included in the full covariate model. Results: The model included data from 920 participants, who were predominantly male (65%). Significant covariates associated with higher adherence were 25 years or older [odds ratio (OR) for P10, 0.61], female sex (OR for P10, 0.67), participant wanting the relationship with the partner to succeed (OR for P10, 0.79; OR for P01, 1.45), and sex with partner either with 100% or <100% condom use compared to those reported no sex (OR for P10, 0.84; OR for P01, 1.21). Significant covariates associated with lower adherence were partner on ART >6 months (OR for P01, 0.86; OR for P10, 1.34), subject in the study for >6 months (OR for P01, 0.8; OR for P10, 1.25), and problematic alcohol use (OR for P01, 0.63; OR for P10, 1.16). Conclusion: The developed Markov model provides a mechanistic understanding of relationship between demographic, socio-behavioral covariates, and PrEP adherence, by indicating the pattern of adherence influenced by each factor over time. Such data can be used for further intervention development to promote PrEP adherence.

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.

Population Pharmacokinetics of Pemetrexed in Adult Non-Small Cell Lung Cancer in Indian Patients.

The objective of the study was to develop a population pharmacokinetic model of pemetrexed and identify factors contributing to variability in exposure in Indian patients. Plasma samples were obtained from a cohort of 85 patients following 500 mg/m2 intravenous infusion and population pharmacokinetic analysis was performed using NONMEM (version 7.3.0). The stochastic approximation expectation maximization method was used to estimate parameters. The full covariate model approach was used by specifying clinically meaningful covariates a priori. Credible intervals obtained using Markov chain Monte Carlo Bayesian analysis were used to reduce the full covariate model by eliminating the covariates whose CI included the null. Model qualification was performed using visual predictive check and bootstrap. The final population parameter estimates and relative standard error for clearance (CL) was 3.3 L/h (10.8), central volume of distribution (V1) was 5.2 L (7.8), peripheral volume of distribution (V2) was 5.9 L (14.5) and intercompartmental clearance (Q) was 6.8 L/h (14.3). A large between-subject variability (50%-108% coefficient of variation) was observed in pharmacokinetic parameters. The percent coefficient of variation for the area under the plasma concentration-time curve from time zero to infinity was 72% and for maximum concentration was 68.25%. Diagnostic plots showed no major bias in the model. The final model included V1, V2, and Q scaled to body surface area raised to a fixed exponent of 1. Creatinine clearance and sex on clearance and albumin on V1 were statistically significant covariates based on Bayesian credible interval. However, traditional bootstrap resulted in a 95% confidence interval of the sex effect parameter including null. Given the size and nonsignificant sex effect in traditional bootstrap, it is considered clinically not significant.

Population pharmacokinetics of primaquine and the effect of hepatic and renal dysfunction: An exploratory approach.

OBJECTIVES: We attempted to develop a population pharmacokinetic model for primaquine (PQ) and evaluate the effect of renal and hepatic dysfunction on PQ pharmacokinetics. MATERIALS AND METHODS: The data were collected from a prospective, nonrandomized clinical study in healthy volunteers and patients with mild-moderate hepatic dysfunction and renal dysfunction. Model development was conducted using NONMEM® software, and parameter estimation was conducted using first-order conditional estimation with interaction method. RESULTS: Final data included a total of 53 study participants (13 healthy individuals, 12 with mild hepatic dysfunction, 6 with moderate hepatic dysfunction, and 22 with renal dysfunction) with 458 concentrations records. Absorption rate constant (Ka) was constrained to be higher than elimination rate constant to avoid flip-flop situation. Mild hepatic dysfunction was a significant covariate on volume of distribution, and it is approximately three folds higher compared to other subjects. Fixed effects parameter estimates of the final model - absorption rate constant (Ka), volume of distribution (V), and clearance (CL) - were 0.95/h, 498 L, and 39 L/h, respectively. Between-subject variability estimates (% CV) on Ka, V, and CL were 77, 66, and 65, respectively. Residual error was modeled as combination error model with the parameter estimates for proportion error 12% CV and additive error (standard deviation) 1.5 ng/ml. CONCLUSION: Population pharmacokinetic modeling showed that the volume of distribution of PQ in subjects with moderate hepatic dysfunction increases approximately three folds resulting in a significantly lower plasma concentration.

A Systematic Evaluation of Effect of Adherence Patterns on the Sample Size and Power of a Clinical Study.

The objective of our study was to evaluate the effect of adherence patterns on the sample size and power of a clinical trial. Simulations from a population pharmacokinetic/pharmacodynamic (PK/PD) model linked to an adherence model were used. Four types of drug characteristics, such as long (~35 hours) and short (~12 hours) half-life in combination with earlier or delayed time to reach steady-state PD end points were studied. Adherence patterns were simulated using Markov chains. Our results clearly demonstrate the significant impact of varying levels and patterns of nonadherence on the sample size and power of a study. For drugs with short half-lives the evidence to support efficacy could be diluted by various patterns of nonadherence that would make its efficacy indistinguishable from the response to placebo. Prospectively utilizing clinical trial simulations with thorough incorporation of various adherence patterns would provide valuable information when designing a trial.

Establishing a Multidisciplinary Framework to Study Drug-Drug Interactions of Hormonal Contraceptives: An Invitation to Collaborate.

Hormonal contraceptive agents (HCAs) are widely used throughout the world, and women taking HCAs are likely to take other medications. However, little is known about the clinical effect of most drug-drug interactions (DDIs) associated with HCAs. A team of interdisciplinary outcomes and pharmacometric researchers from academia and industry jointly engage in a research project to (i) quantitatively elucidate DDI impacts on unintended pregnancies and breakthrough bleeding, and (ii) establish a DDI-prediction framework to inform optimal use of HCAs.

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.

Markov Mixed Effects Modeling Using Electronic Adherence Monitoring Records Identifies Influential Covariates to HIV Preexposure Prophylaxis.

Adherence is a major factor in the effectiveness of preexposure prophylaxis (PrEP) for HIV prevention. Modeling patterns of adherence helps to identify influential covariates of different types of adherence as well as to enable clinical trial simulation so that appropriate interventions can be developed. We developed a Markov mixed-effects model to understand the covariates influencing adherence patterns to daily oral PrEP. Electronic adherence records (date and time of medication bottle cap opening) from the Partners PrEP ancillary adherence study with a total of 1147 subjects were used. This study included once-daily dosing regimens of placebo, oral tenofovir disoproxil fumarate (TDF), and TDF in combination with emtricitabine (FTC), administered to HIV-uninfected members of serodiscordant couples. One-coin and first- to third-order Markov models were fit to the data using NONMEM® 7.2. Model selection criteria included objective function value (OFV), Akaike information criterion (AIC), visual predictive checks, and posterior predictive checks. Covariates were included based on forward addition (α = 0.05) and backward elimination (α = 0.001). Markov models better described the data than 1-coin models. A third-order Markov model gave the lowest OFV and AIC, but the simpler first-order model was used for covariate model building because no additional benefit on prediction of target measures was observed for higher-order models. Female sex and older age had a positive impact on adherence, whereas Sundays, sexual abstinence, and sex with a partner other than the study partner had a negative impact on adherence. Our findings suggest adherence interventions should consider the role of these factors.

Investigation of the Dermal Absorption and Irritation Potential of Sertaconazole Nitrate Anhydrous Gel.

Effective topical therapy of cutaneous fungal diseases requires the delivery of the active agent to the target site in adequate concentrations to produce a pharmacological effect and inhibit the growth of the pathogen. In addition, it is important to determine the concentration of the drug in the skin in order to evaluate the subsequent efficacy and potential toxicity for topical formulations. For this purpose, an anhydrous gel containing sertaconazole nitrate as a model drug was formulated and the amount of the drug in the skin was determined by in vitro tape stripping. The apparent diffusivity and partition coefficients were then calculated by a mathematical model describing the dermal absorption as passive diffusion through a pseudo-homogenous membrane. The skin irritation potential of the formulation was also assessed by using the in vitro Epiderm™ model. An estimation of the dermal absorption parameters allowed us to evaluate drug transport across the stratum corneum following topical application. The estimated concentration for the formulation was found to be higher than the MIC100 at the target site which suggested its potential efficacy for treating fungal infections. The skin irritation test showed the formulation to be non-irritating in nature. Thus, in vitro techniques can be used for laying the groundwork in developing efficient and non-toxic topical products.

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.