Model-Informed Drug Development in Pediatric Dose Selection

An integrated population pharmacokinetic model of febuxostat in pediatric patients with hyperuricemia including gout and adult population of healthy subjects and patients with renal dysfunction

The study objective was to validate febuxostat dosage and administration in pediatric patients with hyperuricemia including gout, using an integrated population pharmacokinetic (PopPK) analysis in the Japanese population. Integrated PopPK analysis of febuxostat used a nonlinear mixed-effects modeling (NONMEM) program on plasma febuxostat concentration data for 2611 samples from Japanese pediatric patients with hyperuricemia including gout (n = 29) and from adult subjects who are healthy or have renal dysfunction (n = 113). We described febuxostat pharmacokinetics using an integrated PopPK model applicable both to pediatric patients and to the adult population. The covariates of body weight and eGFR were identified for CL/F and the covariate of fasted/fed status for bioavailability. The range of steady-state exposures (Cmax,ss and AUCτ,ss) for 5, 10, 20, and 30 mg of febuxostat in fed pediatric patients weighing 20 to 40 kg was within that for 10, 20, 40, and 60 mg of febuxostat in fed pediatric patients and adults weighing 40 to 120 kg. Post hoc estimates of CL/F, adjusted by body weight, differed little between pediatric patients and the adult population in the renal function categories of normal, mild dysfunction, and moderate dysfunction. We successfully validated the febuxostat dose that provided the same level of exposure in pediatric patients as in the adult population: half the adult dose for pediatric patients weighing <40 kg and the full adult dose for pediatric patients weighing ≥40 kg. As in adults, the results support the use of febuxostat without dose adjustment in pediatric patients who have mild to moderate renal dysfunction.

Application of Model-Informed Drug Development in Dose Selection and Optimization for siRNA Therapies

The application of model-informed drug development (MIDD) has revolutionized drug development and regulatory decision making, transforming the process into one that is more efficient, effective, and patient centered. A critical application of MIDD is to facilitate dose selection and optimization, which play a pivotal role in improving efficacy, safety, and tolerability profiles of a candidate drug. With the surge of interest in small interfering RNA (siRNA) drugs as a promising class of therapeutics, their applications in various disease areas have been extensively studied preclinically. However, dosing selection and optimization experience for siRNA in humans is limited. Unique challenges exist for the dose evaluation of siRNA due to the temporal discordance between pharmacokinetic and pharmacodynamic profiles, as well as limited available clinical experience and considerable interindividual variability. This review highlights the pivotal role of MIDD in facilitating dose selection and optimization for siRNA therapeutics. Based on past experiences with approved siRNA products, MIDD has demonstrated its ability to aid in dose selection for clinical trials and enabling optimal dosing for the general patient population. In addition, MIDD presents an opportunity for dose individualization based on patient characteristics, enhancing the precision and effectiveness of siRNA therapeutics. In conclusion, the integration of MIDD offers substantial advantages in navigating the complex challenges of dose selection and optimization in siRNA drug development, which in turn accelerates the development process, supports regulatory decision making, and ultimately improves the clinical outcomes of siRNA-based therapies, fostering advancements in precision medicine across a diverse range of diseases.

Population pharmacokinetics, enzyme occupancy, and pharmacodynamic modeling of soticlestat in patients with developmental and epileptic encephalopathies

Soticlestat (TAK-935) is a first-in-class, selective inhibitor of cholesterol 24-hydroxylase (CH24H) under phase III development for the treatment of the developmental and epileptic encephalopathies (DEEs), Dravet syndrome (DS), and Lennox-Gastaut syndrome (LGS). A previous model characterized the pharmacokinetics (PKs), CH24H enzyme occupancy (EO), and pharmacodynamics (PDs) of soticlestat in healthy volunteers. The present study extended this original model for patients with DEEs and investigated sources of variability. Model-based simulations were carried out to optimize dosing strategies for use in clinical trials. Data from eight phase I and II trials of healthy volunteers or patients with DEEs receiving oral soticlestat 15-1350 mg were included, encompassing 218 individuals for population PK (PopPK) analyses and 306 individuals for PK/PD analyses. Dosing strategies were identified through model-based simulations. The final mixed-effect PopPK/EO/PD model consisted of a two-compartment PK model and an effect-site compartment in the PK/EO model; soticlestat concentrations at the effect site were linked to 24S-hydroxycholesterol plasma concentrations using a semimechanistic inhibitory indirect response model. Covariates were included to account for sources of variability. Pediatric dosing strategies were developed for four body weight bands (10 to <15, 15 to <30, 30 to <45, and 45-100 kg) to account for covariate effects by body weight. The final PopPK and PK/EO/PD models accurately described PK, EO, and PD profiles of soticlestat in healthy volunteers and patients with DEEs. Covariate analyses and model-based simulations facilitated optimization of phase III trial dosing strategies for patients with DS or LGS.

Pharmacokinetic and pharmacodynamic principles: unique considerations for optimal design of neonatal clinical trials

Core clinical pharmacology principles must be considered when designing and executing neonatal clinical trials. In this review, the authors discuss important aspects of drug dose selection, pharmacokinetics, pharmacogenetics and pharmacodynamics that stakeholders may consider when undertaking a neonatal or infant clinical trial.

Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations

There has been a significant increase in the use of physiologically based pharmacokinetic (PBPK) models during the past 20 years, especially for pediatrics. The aim of this study was to give a detailed overview of the growth and areas of application of pediatric PBPK (P‐PBPK) models. A total of 181 publications and publicly available regulatory reviews were identified and categorized according to year, author affiliation, platform, and primary application of the P‐PBPK model (in clinical settings, drug development or to advance pediatric model development in general). Secondary application areas, including dose selection, biologics, and drug interactions, were also assessed. The growth rate for P‐PBPK modeling increased 33‐fold between 2005 and 2020; this was mainly attributed to growth in clinical and drug development applications. For primary applications, 50% of articles were classified under clinical, 18% under drug development, and 33% under model development. The most common secondary applications were dose selection (75% drug development), pharmacokinetic prediction and covariate identification (47% clinical), and model parameter identification (68% model development), respectively. Although population PK modeling remains the mainstay of approaches supporting pediatric drug development, the data presented here demonstrate the widespread application of P‐PBPK models in both drug development and clinical settings. Although applications for pharmacokinetic and drug–drug interaction predictions in pediatrics is advocated, this approach remains underused in areas such as assessment of pediatric formulations, toxicology, and trial design. The increasing number of publications supporting the development and refinement of the pediatric model parameters can only serve to enhance optimal use of P‐PBPK models.

Challenges and opportunities for improving access to approved neonatal drugs and devices

Neonatal drug and device development has lagged behind other patient populations. Oftentimes, providers are using drugs and devices without adequate study of safety and efficacy. Neonates deserve dedicated drug and device development programs, which will require novel approaches and unique collaborations between multiple key stakeholders. Legislative efforts, infrastructure, clinical trial methodology, and international collaborations have all contributed to improvements in neonatal drug and device development, but more work is still needed. Leadership from neonatologists, clinical care providers, and parents is essential to implement needed changes.

Model-Informed Drug Development Approaches to Assist New Drug Development in the COVID-19 Pandemic

Leveraging limited clinical and nonclinical data through modeling approaches facilitates new drug development and regulatory decision making amid the coronavirus disease 2019 (COVID‐19) pandemic. Model‐informed drug development (MIDD) is an essential tool to integrate those data and generate evidence to (i) provide support for effectiveness in repurposed or new compounds to combat COVID‐19 and dose selection when clinical data are lacking; (ii) assess efficacy under practical situations such as dose reduction to overcome supply issues or emergence of resistant variant strains; (iii) demonstrate applicability of MIDD for full extrapolation to adolescents and sometimes to young pediatric patients; and (iv) evaluate the appropriateness for prolonging a dosing interval to reduce the frequency of hospital visits during the pandemic. Ongoing research activities of MIDD reflect our continuous effort and commitment in bridging knowledge gaps that leads to the availability of effective treatments through innovation. Case examples are presented to illustrate how MIDD has been used in various stages of drug development and has the potential to inform regulatory decision making.