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.

Considerations for Industry-Preparing for the FDA Model-Informed Drug Development (MIDD) Paired Meeting Program.

A recent industry perspective published in this journal describes the benefits received by drug companies from participation in the MIDD Pilot Program. Along with the primary objectives of supporting good decision-making in drug development, there were substantial savings in time and development costs. Furthermore, many sponsors reported qualitative benefits such as new learnings and clarity on MIDD strategies and methodology that could be applied to other development programs. Based on the success of the Pilot Program, the FDA recently announced the continuation of the MIDD Paired Meeting Program as part of the Prescription Drug User Fee Act (PDUFA VII). In this report, we describe the collective experiences of industry participants in the MIDD Program to date, including all aspects of the process from meeting request submission to follow-up actions. The purpose is to provide future participants with information to optimize the value of the MIDD Program.

Evaluation of the effect of erenumab on migraine-specific questionnaire in patients with chronic and episodic migraine.

Erenumab is a fully human anti-canonical calcitonin gene-related peptide receptor monoclonal antibody approved for migraine prevention. The Migraine-Specific Quality-of-Life Questionnaire (MSQ) is a 14-item patient-reported outcome instrument that measures the impact of migraine on health-related quality of life. Erenumab data from four phase II/III clinical trials were used to develop an item response theory (IRT) model within a nonlinear mixed effects framework, (i) evaluate the MSQ item information with respect to patient disability, (ii) characterize the longitudinal progression of the MSQ, and (iii) quantify the effect of erenumab on the MSQ in patients with migraine. The majority (80%) of information was found to be contained in 9 out of 14 items, extending the current knowledge on the reliability of the MSQ as a psychometric tool. Simulations across three MSQ domains show significant improvement from baseline, exceeding minimally important differences. Overall, the IRT model platform developed herein allows for systematic quantification of the effect of erenumab on the MSQ in patients with migraine.

Oncolytic viral kinetics mechanistic modeling of Talimogene Laherparepvec (T-VEC) a first-in-class oncolytic viral therapy in patients with advanced melanoma.

Talimogene Laherparepvec (T-VEC) is a first-in-class oncolytic virotherapy approved for the treatment of unresectable melanoma recurrent after initial surgery. Biodistribution data from a phase II study was used to develop a viral kinetic mechanistic model describing the interaction between cytokines such as granulocyte-macrophage colony-stimulating factor (GM-CSF), the immune system, and T-VEC treatment. Our analysis found that (1) the viral infection rate has a great influence on T-VEC treatment efficacy; (2) an increase in T-VEC dose of 102 plaque-forming units/ml 21 days and beyond after the initial dose of T-VEC resulted in an ~12% increase in response; and (3) at the systemic level, the ratio of resting innate immune cells to the death rate of innate immune impact T-VEC treatment efficacy. This analysis clarifies under which condition the immune system either assists in eliminating tumor cells or inhibits T-VEC treatment efficacy, which is critical to both efficiently design future oncolytic agents and understand cancer development.

Recent advances and clinical pharmacology aspects of Chimeric Antigen Receptor (CAR) T-cellular therapy development.

Advances in immuno-oncology have provided a variety of novel therapeutics that harness the innate immune system to identify and destroy neoplastic cells. It is noteworthy that acceptable safety profiles accompany the development of these targeted therapies, which result in efficacious cancer treatment with higher survival rates and lower toxicities. Adoptive cellular therapy (ACT) has shown promising results in inducing sustainable remissions in patients suffering from refractory diseases. Two main types of ACT include engineered Chimeric Antigen Receptor (CAR) T cells and T cell receptor (TCR) T cells. The application of these immuno-therapies in the last few years has been successful and has demonstrated a safe and rapid treatment regimen for solid and non-solid tumors. The current review presents an insight into the clinical pharmacology aspects of immuno-therapies, especially CAR-T cells. Here, we summarize the current knowledge of TCR and CAR-T cell immunotherapy with particular focus on the structure of CAR-T cells, the effects and toxicities associated with these therapies in clinical trials, risk mitigation strategies, dose selection approaches, and cellular kinetics. Finally, the quantitative approaches and modeling techniques used in the development of CAR-T cell therapies are described.

Population Pharmacokinetic Properties of Omecamtiv Mecarbil in Healthy Subjects and Patients With Heart Failure With Reduced Ejection Fraction.

ABSTRACT: Omecamtiv mecarbil is a small molecule that has been shown to improve cardiac function in patients with heart failure (HF) with reduced ejection fraction and is currently being developed as an oral modified release tablet for subjects with chronic HF. The objectives of this study were to analyze the pharmacokinetic (PK) properties of omecamtiv mecarbil and to investigate the effects of potential covariates on pertinent PK parameters using population PK modeling of data from 3 clinical trials in healthy subjects (n = 85) and 3 clinical trials in patients with HF (n = 4261). The population PK analysis was performed using a nonlinear mixed effects modeling approach. Omecamtiv mecarbil has a clearance of 11.7 L/h (0.701% relative standard error) and a central volume distribution of 275 L (2.12% relative standard error). The estimated half-life of omecamtiv mecarbil was 33 hours. Body weight and estimated glomerular filtration rate were significant covariates, but their effect on exposure was modest and lacked clinical relevance. Additional covariates, including sex, race, bilirubin, albumin, concomitant medications, New York Heart Association Functional Classification, N-terminal-pro hormone B-type natriuretic peptide, troponin I, creatine kinase MB, serum hemoglobin, tablet formulation, aspartate aminotransferase, and serum urea, were tested and found to have no impact on omecamtiv mecarbil exposures. The results of this integrated evaluation of the impact of covariates on the systemic exposure of omecamtiv mecarbil suggest that dose adjustment is not required for the studied subpopulations of patients with HF.

A Disease Progression Model to Quantify the Nonmotor Symptoms of Parkinson's Disease in Participants With Leucine-Rich Repeat Kinase 2 Mutation.

Leucine-rich repeat kinase 2 (LRRK2) inhibitors are currently in clinical development as interventions to slow progression of Parkinson's disease (PD). Understanding the rate of progression in PD as measured by both motor and nonmotor features is particularly important in assessing the potential therapeutic effect of LRRK2 inhibitors in clinical development. Using standardized data from the Critical Path for Parkinson's Unified Clinical Database, we quantified the rate of progression of the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part I (nonmotor aspects of experiences of daily living) in 158 participants with PD who were carriers and 598 participants with PD who were noncarriers of at least one of three different LRRK2 gene mutations (G2019S, R1441C/G, or R1628P). Age and disease duration were found to predict baseline disease severity, while presence of at least one of these three LRRK2 mutations was a predictor of the rate of MDS-UPDRS Part I progression. The estimated progression rate in MDS-UPDRS Part I was 0.648 (95% confidence interval: 0.544, 0.739) points per year in noncarriers of a LRRK2 mutation and 0.259 (95% confidence interval: 0.217, 0.295) points per year in carriers of a LRRK2 mutation. This analysis demonstrates that the rate of progression based on MDS-UPDRS Part I is ~ 60% lower in carriers as compared with noncarriers of LRRK2 gene mutations.

Performance of longitudinal item response theory models in shortened or partial assessments.

This work evaluates the performance of longitudinal item response (IR) theory models in shortened assessments using an existing model for part II and III of the MDS-UPDRS score. Based on the item information content, the assessment was reduced by removal of items in multiple increments and the models' ability to recover the item characteristics of the remaining items at each level was evaluated. This evaluation was done for both simulated and real data. The metric of comparison in both cases was the item information function. For real data, the impact of shortening on the estimated disease progression and drug effect was also studied. In the simulated data setting, the item characteristics did not differ between the full and the shortened assessments down to the lowest level of information remaining; indicating a considerable independence between items. In contrast when reducing the assessment in a real data setting, a substantial change in item information was observed for some of the items. Disease progression and drug effect estimates also decreased in the reduced assessments. These changes indicate a shift in the measured construct of the shortened assessment and warrant caution when comparing results from a partial assessment with results from the full assessment.

Challenges in Alzheimer's Disease Drug Discovery and Development: The Role of Modeling, Simulation, and Open Data.

Alzheimer's disease (AD) is the leading cause of dementia worldwide. With 35 million people over 60 years of age with dementia, there is an urgent need to develop new treatments for AD. To streamline this process, it is imperative to apply insights and learnings from past failures to future drug development programs. In the present work, we focus on how modeling and simulation tools can leverage open data to address drug development challenges in AD.

Population pharmacokinetics of orally administrated bromopride: Focus on the absorption process.

Bromopride is a prokinetic and antiemetic drug used to treat nausea and vomiting. Although its prescription is common in Brazil, there is a lack of studies about bromopride pharmacokinetics. Therefore, the aims of this study were to investigate the population pharmacokinetics of bromopride and to evaluate the influence of covariates on its absorption. This study is a retrospective analysis of data collected from bioequivalence studies. The data was modeled using MONOLIX 2018R2. Assuming one-compartment and linear elimination, the absorption phase was evaluated with different structural models. The model of sequential first- and zero-order with combined error and exponential inter-individual variability in all parameters best described the atypical absorption profile of bromopride. Population estimates were first-order absorption rate (ka) of 0.08 h - 1, fraction of dose absorbed by first-order (Fr) of 32.60%, duration of the zero-order absorption (Tk0) of 0.88 h with latency time (Tlag) of 0.47 h, volume of distribution of 230 l and clearance of 46.80 l h - 1. Bodyweight affects Tk0, dosage form was found to correlate with Tk0 and Tlag, while gender affects Tlag. However, simulations evaluating the clinical importance of these covariates on steady-state indicated minimal changes on bromopride exposure. The mixed absorption model was reasonable to describe the absorption process of bromopride because it had the flexibility to fit multiple-peaks profile and shows good agreement with physicochemical properties of drug.

Development of a Disease Progression Model for Leucine-Rich Repeat Kinase 2 in Parkinson's Disease to Inform Clinical Trial Designs.

A quantitative assessment of Parkinson's disease (PD) progression is critical for optimizing clinical trials design. Disease progression model was developed using pooled data from the Progression Marker Initiative study and the Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation in Parkinson's Disease study. Age, gender, concomitant medication, and study arms were predictors of baseline. A mutation in the leucine-rich repeat kinase 2 (LRRK2) encoding gene was associated with the disease progression rate. The progression rate in subjects with PD who carried LRRK2 mutation was slightly slower (~0.170 points/month) than that in PD subjects without the mutation (~0.222 points/month). For a nonenriched placebo-controlled clinical trial, approximately 70 subjects/arm would be required to detect a drug effect of 50% reduction in the progression rate with 80% probability, whereas 85, 93, and 100 subjects/arm would be required for an enriched clinical trial with 30%, 50%, and 70% subjects with LRRK2 mutations, respectively.

Operating characteristics of stepwise covariate selection in pharmacometric modeling.

Stepwise covariate modeling (SCM) is a widely used tool in pharmacometric analyses to identify covariates that explain between-subject variability (BSV) in exposure and exposure-response relationships. However, this approach has several potential weaknesses, including over-estimated covariate effect and incorrect selection of covariates due to collinearity. In this work, we investigated the operating characteristics (i.e., accuracy, precision, and power) of SCM in a controlled setting by simulating sixteen scenarios with up to four covariate relationships. The SCM analysis showed a decrease in the power to detect the true covariates as model complexity increased. Furthermore, false highly correlated covariates were frequently selected in place of or in addition to the true covariates. Relative root mean square errors (RMRSE) ranged from 1 to 51% for the fixed effects parameters, increased with the number of covariates included in the model, and were slightly higher than the RMRSE obtained with a simple re-estimation exercise with the true model (i.e., stochastic simulation and estimation). RMRSE for BSV increased with the number of covariates included in the model, with a covariance parameter RMRSE of almost 135% in the most complex scenario. Loose boundary conditions on the continuous covariate power relation appeared to have an impact on the covariate model selection in SCM. A stricter boundary condition helped achieve high power (> 90%), even in the most complex scenario. Finally, reducing the sample size in terms of number of subjects or number of samples proved to have an impact on the power to detect the correct model.

Molecular Neuroimaging of the Dopamine Transporter as a Patient Enrichment Biomarker for Clinical Trials for Early Parkinson's Disease.

The Critical Path for Parkinson's (CPP) Imaging Biomarker and Modeling and Simulation working groups aimed to achieve qualification opinion by the European Medicines Agency (EMA) Committee for Medical Products for Human Use (CHMP) for the use of baseline dopamine transporter neuroimaging for patient selection in early Parkinson's disease clinical trials. This paper describes the regulatory science strategy to achieve this goal. CPP is an international consortium of three Parkinson's charities and nine pharmaceutical partners, coordinated by the Critical Path Institute.

Time dependent pharmacokinetics of pembrolizumab in patients with solid tumor and its correlation with best overall response.

Pembrolizumab is a monoclonal antibody that targets the programmed death-1 receptor to induce immune-mediated clearance (CL) of tumor cells. Originally approved by the US Food and Drug Administration in 2014 for treating patients with unresectable or metastatic melanoma, pembrolizumab is now also used to treat patients with non-small-cell lung cancer, classical Hodgkin lymphoma, head and neck cancer, and urothelial cancer. This paper describes the recently identified feature of pembrolizumab pharmacokinetics, the time-dependent or time-varying CL. Overall results indicate that CL decreases over the treatment period of a typical patient in a pattern well described by a sigmoidal function of time with three parameters: the maximum proportion change in CL from baseline (approximately Imax or exactly eImax - 1), the time to reach Imax/2 (TI50), and a Hill coefficient. Best overall response per response evaluation criteria in solid tumor category was found to be associated with the magnitude of Imax.

Evaluation of dosing strategy for pembrolizumab for oncology indications.

BACKGROUND: Traditionally, most monoclonal antibodies (mAbs) have been dosed based on body weight because of perceived contribution of body size in pharmacokinetic variability. The same approach was used in the initial pembrolizumab studies; however, following availability of PK data, the need for weight-based dosing for pembrolizumab was reassessed. METHODS: A previously established population PK (popPK) model as well as exposure-response results from patients with advanced melanoma or non-small cell lung cancer (NSCLC) were used to evaluate the potential application of a fixed dosing regimen with the aim of maintaining pembrolizumab exposures within the range demonstrated to provide near maximal efficacy and acceptable safety. Individual PK exposures for the selected fixed dosing regimen from recently completed trials with head and neck cancer, NSCLC, microsatellite instability high (MSI-H) in colorectal cancer (CRC) and urothelial cancer were used to confirm acceptability. To determine whether fixed dosing would maintain exposures within the range of clinical experience, the individual AUC distributions with fixed dosing were compared with the range of exposures from the pembrolizumab doses that were evaluated in early studies (2 mg/kg Q3W, 10 mg/kg Q3W/Q2W). RESULTS: Body-weight dependence of clearance was characterized by a power relationship with an exponent of 0.578, a value consistent with fixed- and weight-based dosing providing similar control of PK variability. A fixed dose of 200 mg Q3W was investigated in trials based on predicted exposures maintained within the established exposure range in all patients. Mean (% CV, n) AUCss, 6-weeks was 1.87 (37%, 830), 1.38 (38%, 760) and 7.63 (35%, 1405) mg*day/mL in patients receiving 200 mg, 2 mg/kg and 10 mg/kg Q3W pembrolizumab. High-weight patients had the lowest exposures with 200 mg Q3W; however, exposures in this group (>90 kg) were within the range of prior clinical experience at 2 mg/kg Q3W associated with near maximal efficacy. CONCLUSIONS: Doses of 200 mg and 2 mg/kg provide similar exposure distributions with no advantage to either dosing approach with respect to controlling PK variability. These findings suggest that weight-based and fixed-dose regimens are appropriate for pembrolizumab.

Methods and strategies for assessing uncontrolled drug-drug interactions in population pharmacokinetic analyses: results from the International Society of Pharmacometrics (ISOP) Working Group.

The purpose of this work was to present a consolidated set of guidelines for the analysis of uncontrolled concomitant medications (ConMed) as a covariate and potential perpetrator in population pharmacokinetic (PopPK) analyses. This white paper is the result of an industry-academia-regulatory collaboration. It is the recommendation of the working group that greater focus be given to the analysis of uncontrolled ConMeds as part of a PopPK analysis of Phase 2/3 data to ensure that the resulting outcome in the PopPK analysis can be viewed as reliable. Other recommendations include: (1) collection of start and stop date and clock time, as well as dose and frequency, in Case Report Forms regarding ConMed administration schedule; (2) prespecification of goals and the methods of analysis, (3) consideration of alternate models, other than the binary covariate model, that might more fully characterize the interaction between perpetrator and victim drug, (4) analysts should consider whether the sample size, not the percent of subjects taking a ConMed, is sufficient to detect a ConMed effect if one is present and to consider the correlation with other covariates when the analysis is conducted, (5) grouping of ConMeds should be based on mechanism (e.g., PGP-inhibitor) and not drug class (e.g., beta-blocker), and (6) when reporting the results in a publication, all details related to the ConMed analysis should be presented allowing the reader to understand the methods and be able to appropriately interpret the results.

Prediction of concentration-time profile and its inter-individual variability following the dermal drug absorption.

Estimation of systemic exposure after absorption of any xenobiotic from the skin is very important in development of dermal pharmaceutical products as well as assessing un-intended exposures due to cosmetic products or environmental and occupational compounds. Historically, animal models have been used to evaluate dermal drug absorption before conducting human trials. However, occasional disparity between the animal and human data plus rising public interest and regulatory requirements to reduce animal usage in research combined with high cost and time-consuming attributes of animal experiments have prompted many academic and industrial researchers to develop economically viable and scientifically robust in silico and in vitro methods to assess dermal drug absorption. There are a number of in silico models available in literature from quantitative structure-activity relationship to semi-mechanistic to physiologically based mechanistic models. Nonetheless, to the best of our knowledge, so far, there has been no attempt to combine mechanistic skin absorption model with database of physiological variability to simulate the inter- and intra-individual variability observed in human trials. Thus, we report here mechanistic dermal absorption model with formulation, stratum corneum, viable epidermis-dermis and blood compartments along with datab"ase of human dermal physiological variability including gender, ethnic and site of application variations. The developed model is incorporated into the Simcyp simulator which is a 'bottom-up' platform and database for mechanistic modelling and simulation of the drug disposition process using full body physiologically based pharmacokinetics model. The built model is validated using the clinical pharmacokinetic data from five different topical formulations of diclofenac. The effect of penetration enhancers, site of application, gender and ethnic variations were incorporated to simulate the clinical trials. The applied mechanistic dermal absorption model when combined with skin physiological database was able to recover well the observed clinical pharmacokinetics and population variability in all the five validation studies.