Another Step Toward Qualification of Pediatric Physiologically Based Pharmacokinetic Models to Facilitate Inclusivity and Diversity in Pediatric Clinical Studies

Abstract

Study HighlightsWHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? Accurate prediction of pharmacokinetics (PKs) in pediatric subjects of diverse ages, ethnicities, and morbidities is critical. Qualification of pediatric physiologically-based pharmacokinetic (P-PBPK) models is an essential step towards enabling precision dosing of these vulnerable groups. WHAT QUESTION DID THIS STUDY ADDRESS? As a step toward qualification, the prediction accuracy of the pediatric module within the Simcyp simulator was assessed using robust PBPK models published previously for drugs in clinical use or development. WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE? PK parameters for 22 small-molecule compounds metabolized via CYP, UGT, FMO3, renal, non-renal, and complex routes were adequately predicted in pediatric cohorts, thus providing further confidence in the application of the pediatric module for dose predictions. HOW MIGHT THIS CHANGE CLINICAL PHARMA COLOGY OR TRANSLATIONAL SCIENCE? The analysis presented herein provides context for modelers, regulatory bodies, and other stake holders to support the full integration of P-PBPK modeling into critical Pediatric Investigation Plan and Pediatric Study Plans documents and for making informed decisions in real-world scenarios.

Development and Verification of a Japanese Pediatric Physiologically Based Pharmacokinetic Model with Emphasis on Drugs Eliminated by Cytochrome P450 or Renal Excretion

“…51 Many of the pediatric studies present data over a very large age range, for example, from 1 month to 18 years, rather than in discrete age bands, which make the data less useful, especially in relation to verification of the underlying ontogeny associated with the elimination pathways. In agreement with a recent study, 16 there were few data presented in neonates; this is a population where further clinical data, including patient information as well as research and verification of the PBPK modeling approach, is needed.…”

“…A recent study on the verification of pediatric PBPK models that presented P:O data from 22 small molecule compounds has highlighted the need to build and qualify such models based on their context of use. 16 Of the 22 examples, only 3 considered ethnic differences, even though some of the drugs were highly likely to be used in such groups, and this highlights the importance of expanding pediatric PBPK models beyond the North European population. Building a Japanese pediatric population and other ethnic pediatric populations within these models is clearly important in terms of bridging PK studies among the populations and expanding the examples in adults to pediatric populations.…”

“…The EMA and FDA have indicated that a more formal assessment of models within a specific platform based on context of use is required. 16 For example, if the objective of the PBPK model is to determine the optimal dose of a CYP3A4metabolized drug in a Japanese pediatric population, then the context of use is to predict the PK of the drug of interest in this population. Supporting evidence is required in terms of systems and drugs data for the model, both in adults and children, and how well it can capture the clinical data.…”

“…Regulators both in the USA and in Japan report an increase in submissions involving pediatric PBPK models 14,15 . A recent publication 16 has highlighted cases specifically involving neonates, infants, and children where ethnicity and disease were not fully accounted for using this approach, with many cases only reported using a pediatric population based on a North European population, and with few examples where any other specific ethnicity is included 17 . The draft ICH E11 guideline on pediatric extrapolation mentions PBPK modeling and states that “the specific characteristics of the target population should be incorporated into the model.” 18 Therefore, there is a clear need to develop PBPK models that account for inter‐ethnic physiological differences for bridging pediatric ethnic groups.…”

Diversity, Equity, and Inclusion: Translating Clinical Pharmacology for All

“…Equally important to appreciate for successful personalization of therapeutics and dosing across diverse populations is the multiplicity of intrinsic and extrinsic determinants of benefit/risk of drugs and our often incomplete understanding of the role of these factors, particularly in under-represented racial groups, as reviewed for direct oral anticoagulants by Thompson et al 13 With the exponential increase in our ability to harness multi-modal data and digital technologies, translation of our understanding of population sources of variability to precision dosing solutions for all patients is an opportunity for intelligent clinical decision support systems, as reviewed by Hughes et al 14 We are witnessing substantial progress in the science and technology required to develop EDITORIAL intelligent, continuously learning precision dosing systems driven by population pharmacology models built from clinical trial and real-world data in diverse populations. [14][15][16] Translating scientific and medical advances to equity in health care will, however, need to consider and address the critically important extrinsic factor of Social Determinants of Health through innovative health system, public health, and policylevel interventions, as eloquently discussed by Golden 17 -reflecting her compelling State of the Art lecture at the ASCPT 2022 Annual Meeting.…”