Covariate modeling in pharmacometrics: General points for consideration.

Modeling the relationships between covariates and pharmacometric model parameters is a central feature of pharmacometric analyses. The information obtained from covariate modeling may be used for dose selection, dose individualization, or the planning of clinical studies in different population subgroups. The pharmacometric literature has amassed a diverse, complex, and evolving collection of methodologies and interpretive guidance related to covariate modeling. With the number and complexity of technologies increasing, a need for an overview of the state of the art has emerged. In this article the International Society of Pharmacometrics (ISoP) Standards and Best Practices Committee presents perspectives on best practices for planning, executing, reporting, and interpreting covariate analyses to guide pharmacometrics decision making in academic, industry, and regulatory settings.

Training the next generation of pharmacometric modelers: a multisector perspective.

The current demand for pharmacometricians outmatches the supply provided by academic institutions and considerable investments are made to develop the competencies of these scientists on-the-job. Even with the observed increase in academic programs related to pharmacometrics, this need is unlikely to change in the foreseeable future, as the demand and scope of pharmacometrics applications keep expanding. Further, the field of pharmacometrics is changing. The field largely started when Lewis Sheiner and Stuart Beal published their seminal papers on population pharmacokinetics in the late 1970's and early 1980's and has continued to grow in impact and use since its inception. Physiological-based pharmacokinetics and systems pharmacology have grown rapidly in scope and impact in the last decade and machine learning is just on the horizon. While all these methodologies are categorized as pharmacometrics, no one person can be an expert in everything. So how do you train future pharmacometricians? Leading experts in academia, industry, contract research organizations, clinical medicine, and regulatory gave their opinions on how to best train future pharmacometricians. Their opinions were collected and synthesized to create some general recommendations.

Semi-mechanistic population pharmacokinetic/pharmacodynamic modeling of a Plasmodium elongation factor 2 inhibitor cabamiquine for prevention and cure of malaria.

Cabamiquine is a novel antimalarial agent that demonstrates the potential for chemoprevention and treatment of malaria. In this article, the dose-exposure-response relationship of cabamiquine was characterized using a population pharmacokinetic (PK)/pharmacodynamic (PD) model, incorporating the effects of cabamiquine on parasite dynamics at the liver and blood stages of malaria infection. Modeling was performed sequentially. First, a three-compartmental population PK model was developed, comprising linear elimination, a transit absorption model in combination with first-order absorption, and a recirculation model. Second, this model was expanded into a PK/PD model using parasitemia data from an induced blood stage malaria (IBSM) human challenge model. To describe the parasite growth and killing in the blood, a turnover model was used. Finally, the liver stage parasite dynamics were characterized using data from a sporozoite challenge model (SpzCh), and system parameters were fixed based on biological plausibility. Cabamiquine concentration in the central compartment was used to drive parasite killing at the blood and liver stages. Blood stage minimum inhibitory concentrations (MICb) were estimated at 7.12 ng/mL [95% confidence interval (CI95%): 6.26-7.88 ng/mL] and 1.28 ng/mL (CI95%: 1.12-1.43 ng/mL) for IBSM and SpzCh populations, respectively, while liver stage MICl was lower (0.61 ng/mL; CI95%: 0.24-0.96 ng/mL). In conclusion, a population PK/PD model was developed by incorporating parasite dynamics and drug activity at the blood and liver stages based on clinical data and biological knowledge. This model can potentially facilitate antimalarial agent development by supporting the efficient selection of the optimal dosing regimen.

Causal chemoprophylactic activity of cabamiquine against Plasmodium falciparum in a controlled human malaria infection: a randomised, double-blind, placebo-controlled study in the Netherlands.

BACKGROUND: Cabamiquine is a novel antimalarial that inhibits Plasmodium falciparum translation elongation factor 2. We investigated the causal chemoprophylactic activity and dose-exposure-response relationship of single oral doses of cabamiquine following the direct venous inoculation (DVI) of P falciparum sporozoites in malaria-naive, healthy volunteers. METHODS: This was a phase 1b, randomised, double-blind, placebo-controlled, adaptive, dose-finding, single-centre study performed in Leiden, Netherlands. Malaria-naive, healthy adults aged 18-45 years were divided into five cohorts and randomly assigned (3:1) to receive cabamiquine or placebo. Randomisation was done by an independent statistician using codes in a permuted block schedule with a block size of four. Participants, investigators, and study personnel were masked to treatment allocation. A single, oral dose regimen of cabamiquine (200, 100, 80, 60, or 30 mg) or matching placebo was administered either at 2 h (early liver-stage) or 96 h (late liver-stage) after DVI. The primary endpoints based on a per-protocol analysis set were the number of participants who developed parasitaemia within 28 days of DVI, time to parasitaemia, number of participants with documented parasite blood-stage growth, clinical symptoms of malaria, and exposure-efficacy modelling. The impact of cabamiquine on liver stages was evaluated indirectly by the appearance of parasitaemia in the blood. The Clopper-Pearson CI (nominal 95%) was used to express the protection rate. The secondary outcomes were safety and tolerability, assessed in those who had received DVI and were administered one dose of the study intervention. The trial was prospectively registered on ClinicalTrials.gov (NCT04250363). FINDINGS: Between Feb 17, 2020 and April 29, 2021, 39 healthy participants were enrolled (early liver-stage: 30 mg [n=3], 60 mg [n=6], 80 mg [n=6], 100 mg [n=3], 200 mg [n=3], pooled placebo [n=6]; late liver-stage: 60 mg [n=3], 100 mg [n=3], 200 mg [n=3], pooled placebo [n=3]). A dose-dependent causal chemoprophylactic effect was observed, with four (67%) of six participants in the 60 mg, five (83%) of six participants in the 80 mg, and all three participants in the 100 and 200 mg cabamiquine dose groups protected from parasitaemia up to study day 28, whereas all participants in the pooled placebo and 30 mg cabamiquine dose group developed parasitaemia. A single, oral dose of 100 mg cabamiquine or higher provided 100% protection against parasitaemia when administered during early or late liver-stage malaria. The median time to parasitaemia in those with early liver-stage malaria was prolonged to 15, 22, and 24 days for the 30, 60, and 80 mg dose of cabamiquine, respectively, compared with 10 days for the pooled placebo. All participants with positive parasitaemia showed documented blood-stage parasite growth, apart from one participant in the pooled placebo group and one participant in the 30 mg cabamiquine group. Most participants did not exhibit any malaria symptoms in both the early and late liver-stage groups, and those reported were mild in severity. A positive dose-exposure-efficacy relationship was established across exposure metrics. The median maximum concentration time was 1-6 h, with a secondary peak observed between 6 h and 12 h in all cabamiquine dose groups (early liver-stage). All cabamiquine doses were safe and well tolerated. Overall, 26 (96%) of 27 participants in the early liver-stage group and ten (83·3%) of 12 participants in the late liver-stage group reported at least one treatment-emergent adverse event (TEAE) with cabamiquine or placebo. Most TEAEs were of mild severity, transient, and resolved without sequelae. The most frequently reported cabamiquine-related TEAE was headache. No dose-related trends were observed in the incidence, severity, or causality of TEAEs. INTERPRETATION: The results from this study show that cabamiquine has a dose-dependent causal chemoprophylactic activity. Together with previously demonstrated activity against the blood stages combined with a half-life of more than 150 h, these results indicate that cabamiquine could be developed as a single-dose monthly regimen for malaria prevention. FUNDING: The healthcare business of Merck KGaA, Darmstadt, Germany.

Characterization of exposure-response relationships of ipatasertib in patients with metastatic castration-resistant prostate cancer in the IPATential150 study.

PURPOSE: The exposure-response relationships for efficacy and safety of ipatasertib, a selective AKT kinase inhibitor, were characterized using data collected from 1101 patients with metastatic castration-resistant prostate cancer in the IPATential150 study (NCT03072238). METHODS: External validation of a previously developed population pharmacokinetic model was performed using the observed pharmacokinetic data from the IPATential150 study. Exposure metrics of ipatasertib for subjects who received ipatasertib 400 mg once-daily orally in this study were generated as model-predicted area under the concentration-time curve at steady state (AUCSS). The exposure-response relationship with radiographic progression-free survival (rPFS) was evaluated using Cox regression and relationships with safety endpoints were assessed using logistic regression. RESULTS: A statistically significant correlation between ipatasertib AUCSS and improved survival was found in patients with PTEN-loss tumors (hazard ratio [HR]: 0.92 per 1000 ng h/mL AUCSS, 95% confidence interval [CI] 0.87-0.98, p = 0.011). In contrast, an improvement in rPFS was seen in subjects receiving ipatasertib treatment (HR: 0.84, 95% CI 0.71-0.99, p = 0.038) but this effect was not associated with ipatasertib AUCSS in the intention-to-treat population. Incidences of some adverse events (AEs) had statistically significant association with ipatasertib AUCSS (serious AEs, AEs leading to discontinuation, and Grade ≥ 2 hyperglycemia), while others were associated with only ipatasertib treatment (AEs leading to dose reduction, Grade ≥ 3 diarrhea, and Grade ≥ 2 rash). CONCLUSIONS: The exposure-efficacy results indicated that patients receiving ipatasertib may continue benefiting from this treatment at the administered dose, despite some variability in exposures, while the exposure-safety results suggested increased risks of AEs with ipatasertib treatment and/or increased ipatasertib exposures.

Model-informed approach for risk management of bleeding toxicities for bintrafusp alfa, a bifunctional fusion protein targeting TGF-ß and PD-L1.

PURPOSE: Bintrafusp alfa (BA) is a bifunctional fusion protein composed of the extracellular domain of the transforming growth factor-ß (TGF-ß) receptor II fused to a human immunoglobulin G1 antibody blocking programmed death ligand 1 (PD-L1). The recommended phase 2 dose (RP2D) was selected based on phase 1 efficacy, safety, and pharmacokinetic (PK)-pharmacodynamic data, assuming continuous inhibition of PD-L1 and TGF-ß is required. Here, we describe a model-informed dose modification approach for risk management of BA-associated bleeding adverse events (AEs). METHODS: The PK and AE data from studies NCT02517398, NCT02699515, NCT03840915, and NCT04246489 (n = 936) were used. Logistic regression analyses were conducted to evaluate potential relationships between bleeding AEs and BA time-averaged concentration (Cavg), derived using a population PK model. The percentage of patients with trough concentrations associated with PD-L1 or TGF-ß inhibition across various dosing regimens was derived. RESULTS: The probability of bleeding AEs increased with increasing Cavg; 50% dose reduction was chosen based on the integration of modeling and clinical considerations. The resulting AE management guidance to investigators regarding temporary or permanent treatment discontinuation was further refined with recommendations on restarting at RP2D or at 50% dose, depending on the grade and type of bleeding (tumoral versus nontumoral) and investigator assessment of risk of additional bleeding. CONCLUSION: A pragmatic model-informed approach for management of bleeding AEs was implemented in ongoing clinical trials of BA. This approach is expected to improve benefit-risk profile; however, its effectiveness will need to be evaluated based on safety data generated after implementation.

Pharmacometrics in tuberculosis: progress and opportunities.

Tuberculosis (TB) remains one of the leading causes of death by a communicable agent, infecting up to one-quarter of the world's population, predominantly in disadvantaged communities. Pharmacometrics employ quantitative mathematical models to describe the relationships between pharmacokinetics and pharmacodynamics, and to predict drug doses, exposures and responses. Pharmacometric approaches have provided a scientific basis for improved dosing of anti-TB drugs and concomitantly administered antiretrovirals at the population level. The development of modelling frameworks including physiologically based pharmacokinetics, quantitative systems pharmacology and machine learning provides an opportunity to extend the role of pharmacometrics to in-silico quantification of drug-drug interactions, prediction of doses for special populations, dose optimization and individualization, and understanding the complex exposure-response relationships of multi-drug regimens in terms of both efficacy and safety, informing regimen design for future study. This short, clinically focused review explores what has been done, and what opportunities exist for pharmacometrics to impact TB pharmacotherapy.

Translation of liver stage activity of M5717, a Plasmodium elongation factor 2 inhibitor: from bench to bedside.

BACKGROUND: Targeting the asymptomatic liver stage of Plasmodium infection through chemoprevention could become a key intervention to reduce malaria-associated incidence and mortality. METHODS: M5717, a Plasmodium elongation factor 2 inhibitor, was assessed in vitro and in vivo with readily accessible Plasmodium berghei parasites. In an animal refinement, reduction, replacement approach, the in vitro IC99 value was used to feed a Population Pharmacokinetics modelling and simulation approach to determine meaningful effective doses for a subsequent Plasmodium sporozoite-induced volunteer infection study. RESULTS: Doses of 100 and 200 mg would provide exposures exceeding IC99 in 96 and 100% of the simulated population, respectively. CONCLUSIONS: This approach has the potential to accelerate the search for new anti-malarials, to reduce the number of healthy volunteers needed in a clinical study and decrease and refine the animal use in the preclinical phase.

Pharmacokinetics and exposure-efficacy relationships of omalizumab in patients with nasal polyps.

The anti-immunoglobulin E (IgE) antibody, omalizumab (Xolair), is approved in the United States for the treatment of allergic asthma and chronic spontaneous urticaria, and has recently been studied for the treatment of nasal polyposis following completion of the two replicate phase 3 studies (POLYP 1 and POLYP 2). The dosing of omalizumab used in the phase 3 studies is based on a combination of patients' pre-treatment IgE level and body weight, similar to the approach used in allergic asthma. The objectives of the current analyses were to evaluate whether the pharmacokinetics (PK) of omalizumab and its pharmacodynamic (PD) effect on free and total IgE level in chronic rhinosinusitis with nasal polyps (CRSwNP) are consistent with those in allergic asthma via population PK/PD modeling and simulation, and to graphically explore exposure-response relationships and free IgE-response relationships in CRSwNP. Omalizumab PK and PD effect of total and free IgE in CRSwNP are generally consistent with those in asthma. Observed post-treatment free IgE suppressions were generally within the target range of the baseline IgE- and body weight-based omalizumab dosing table, with 74.2% and 93.0% of patients achieving a serum free IgE level below 25 ng/mL and 50 ng/mL, respectively at Week 24. Exposure-response analyses indicated that there was no clear correlation between omalizumab or free IgE concentration and key efficacy endpoints within the POLYP studies. Overall, these results indicate that the body weight and IgE-based dosing regimen of omalizumab was appropriate for use in CRSwNP patients.

Population Pharmacokinetics of Ipatasertib and Its Metabolite in Cancer Patients.

Ipatasertib is a selective AKT kinase inhibitor currently in development for the treatment of several solid tumors, including breast and prostate cancers. This study was undertaken to characterize pharmacokinetic profiles of ipatasertib and its metabolite M1 (G-037720) and to understand the sources of variability. Population pharmacokinetic models of ipatasertib and M1 were developed separately using data from 342 individuals with cancer from 5 phase 1 and 2 studies. The final population pharmacokinetic models for ipatasertib and M1 were 3-compartmental, with first-order elimination and sequential zero- and first-order absorption. Ipatasertib bioavailability and M1 formation increased after multiple dosing, resulting in an increase in exposure beyond that expected from accumulation alone. Covariate effects of ipatasertib include decreased oral clearance with increasing age and with coadministration of abiraterone, as well as decreased bioavailability with increasing weight. For ages 37 and 80 years, steady-state area under the curve (AUCss ) was predicted to be 81% and 109%, respectively, of the typical population value (64 years). For body weight of 49 and 111 kg, AUCss was predicted to be 132% and 78%, respectively, of the typical population value (75 kg). The small magnitude of change in ipatasertib exposure is not likely to be clinically relevant. For M1, the peripheral distribution volume and intercompartmental clearance increased with increasing weight. Coadministration of abiraterone was estimated to increase M1 exposure by 61% at steady state. Mild and moderate renal impairment, mild hepatic impairment, and race were not identified as significant covariates in the final models for ipatasertib and M1.

Selection of the Recommended Phase 2 Dose for Bintrafusp Alfa, a Bifunctional Fusion Protein Targeting TGF-ß and PD-L1.

Bintrafusp alfa, a first-in-class bifunctional fusion protein composed of the extracellular domain of the TGF-ßRII receptor (TGF-ß "trap") fused to a human IgG1-blocking PD-L1, showed a manageable safety profile and clinical activity in phase I studies in patients with heavily pretreated advanced solid tumors. The recommended phase 2 dose (RP2D) was selected based on integration of modeling, simulations, and all available data. A 1,200-mg every 2 weeks (q2w) dose was predicted to maintain serum trough concentration (Ctrough ) that inhibits all targets of bintrafusp alfa in circulation in > 95% of patients, and a 2,400-mg every 3 weeks (q3w) dose was predicted to have similar Ctrough . A trend toward an association between exposure and efficacy variables and a relatively stronger inverse association between clearance and efficacy variables were observed. Exposure was either weakly or not correlated with probability of adverse events. The selected intravenous RP2D of bintrafusp alfa is 1,200 mg q2w or 2,400 mg q3w.

Changing Body Weight-Based Dosing to a Flat Dose for Avelumab in Metastatic Merkel Cell and Advanced Urothelial Carcinoma.

Avelumab, an anti-programmed death-ligand 1 monoclonal antibody approved for the treatment of metastatic Merkel cell carcinoma and platinum-treated urothelial carcinoma, was initially approved with a 10 mg/kg weight-based dose. We report pharmacokinetic (PK)/pharmacodynamic analyses for avelumab comparing weight-based dosing and a flat 800 mg dose, developed using data from 1,827 patients enrolled in 3 clinical trials (NCT01772004, NCT01943461, and NCT02155647). PK metrics were simulated for weight-based and flat-dosing regimens and summarized by quartiles of weight. Derived exposure metrics were used in simulations of exposure-safety (various tumors) and exposure-efficacy (objective responses; Merkel cell or urothelial carcinoma). Flat dosing was predicted to provide similar exposure to weight-based dosing, with slightly lower variability. Exposure-safety and exposure-efficacy simulations suggested similar benefit:risk profiles for the two dosing regimens. These pharmacometric analyses provided the basis for the US Food and Drug Administration approval of a flat dose of avelumab 800 mg every 2 weeks in approved indications.

Performance of the SAEM and FOCEI Algorithms in the Open-Source, Nonlinear Mixed Effect Modeling Tool nlmixr.

The free and open-source package nlmixr implements pharmacometric nonlinear mixed effects model parameter estimation in R. It provides a uniform language to define pharmacometric models using ordinary differential equations. Performances of the stochastic approximation expectation-maximization (SAEM) and first order-conditional estimation with interaction (FOCEI) algorithms in nlmixr were compared with those found in the industry standards, Monolix and NONMEM, using the following two scenarios: a simple model fit to 500 sparsely sampled data sets and a range of more complex compartmental models with linear and nonlinear clearance fit to data sets with rich sampling. Estimation results obtained from nlmixr for FOCEI and SAEM matched the corresponding output from NONMEM/FOCEI and Monolix/SAEM closely both in terms of parameter estimates and associated standard errors. These results indicate that nlmixr may provide a viable alternative to existing tools for pharmacometric parameter estimation.

Population Pharmacokinetic Analysis of Bintrafusp Alfa in Different Cancer Types.

INTRODUCTION: Bintrafusp alfa, an innovative first-in-class bifunctional fusion protein composed of the extracellular domain of the TGF-ßRII receptor (a TGF-ß "trap") fused to a human IgG1 monoclonal antibody blocking programmed death ligand 1, has shown promising antitumor activity and manageable safety. METHODS: To support the dosing strategy for bintrafusp alfa, we developed a population pharmacokinetics model using a full covariate modeling approach, based on pharmacokinetic and covariate data from 644 patients with various solid tumors who received bintrafusp alfa intravenously in two clinical studies. RESULTS: A two-compartmental linear model best described bintrafusp alfa concentrations, and no time-varying clearance was identified. Using this model, the estimated clearance was 0.0158 l/h (relative standard error, 4.1%), and the central and peripheral volume of distribution were 3.21 l (relative standard error, 3.2%) and 0.483 l (relative standard error, 9.8%), respectively. The estimated mean elimination half-life of bintrafusp alfa was 6.93 days (95% CI 4.69-9.65 days). Several intrinsic factors (bodyweight, albumin, sex, and tumor type) were found to influence bintrafusp alfa pharmacokinetics, but none of these covariate effects was considered clinically meaningful and no dosage adjustments are recommended. Notably, simulations from the model suggested less variability in exposure metrics with flat dosing versus weight-based dosing. CONCLUSIONS: Pharmacokinetic analysis of bintrafusp alfa supports the use of a flat dose regimen in further clinical trials (recommended phase 2 dose: 1200 mg every 2 weeks). TRIAL REGISTRATION: ClinicalTrials.gov identifiers: NCT02517398 and NCT02699515. FUNDING: Merck Healthcare KGaA as part of an alliance between Merck Healthcare KGaA and GlaxoSmithKline.

Nonlinear Mixed-Effects Model Development and Simulation Using nlmixr and Related R Open-Source Packages.

nlmixr is a free and open-source R package for fitting nonlinear pharmacokinetic (PK), pharmacodynamic (PD), joint PK-PD, and quantitative systems pharmacology mixed-effects models. Currently, nlmixr is capable of fitting both traditional compartmental PK models as well as more complex models implemented using ordinary differential equations. We believe that, over time, it will become a capable, credible alternative to commercial software tools, such as NONMEM, Monolix, and Phoenix NLME.

Time-Varying Clearance and Impact of Disease State on the Pharmacokinetics of Avelumab in Merkel Cell Carcinoma and Urothelial Carcinoma.

Avelumab, a human anti-programmed death ligand 1 immunoglobulin G1 antibody, has shown efficacy and manageable safety in multiple tumors. A two-compartment population pharmacokinetic model for avelumab incorporating intrinsic and extrinsic covariates and time-varying clearance (CL) was identified based on data from 1,827 patients across three clinical studies. Of 14 tumor types, a decrease in CL over time was more notable in metastatic Merkel cell carcinoma and squamous cell carcinoma of the head and neck, which had maximum decreases of 32.1% and 24.7%, respectively. The magnitude of reduction in CL was higher in responders than in nonresponders. Significant covariate effects of baseline weight, baseline albumin, and sex were identified on both CL and central distribution volume. Significant covariate effects of black/African American race, C-reactive protein, and immunogenicity were found on CL. None of the covariate or time-dependent effects were clinically important or warranted dose adjustment.