Innovative Approaches to Enhance Maternal and Pediatric Therapeutics: Integrating Real-World Evidence to Meet Medical Needs

Session Description

Early-stage drug development and pre-approval trials typically exclude pregnant/lactating mothers, and children until late in drug development, or at times, until years after approval. Given this limitation, the evidence on drug safety, efficacy, and optimal use in these special populations much-needed to inform drug labeling is lacking. As a result, this encumbers heavy reliance on the data obtained during trials and data from post-approval controlled observational studies for drug labeling and dose optimization.

In the era of model-informed drug development, much emphasis is laid on incorporating data obtained during the clinical trial, i.e. real-world data (RWD), to generate real-world evidence (RWE). This is increasingly utilized to monitor post-market safety, adverse events, and regulatory decision-making. RWD is data relating to patient health status and/or the delivery of health care routinely collected from different sources. Sources of RWD include electronic health records, claims and billing data, product- and disease-based registries, and data from mobile and wearable devices, etc. Incorporating the collection of RWD from thoughtful study designs serves as an efficient tool for assessment of drug-associated safety issues in pregnant/nursing mothers. Regulatory agencies are increasingly recommending complementing pregnancy registries with pregnancy cohorts nested within healthcare utilization databases for assessment of drug safety/optimal use. Furthermore, in-silico modeling strategies (PBPK modeling) utilizing RWD can be incorporated for dosing optimization in pregnant women, for which current dosing approaches are rather empirical. In addition, the pediatric population presents specific challenges to drug safety assessment, such as long-term follow-up, is needed to observe effects over multiple developmental stages that can be cumbersome with post-approval observational studies. Besides, children take medications less often than adults, and measurement of rare events requires large databases. To address these challenges, RWD can be utilized to inform our understanding of both prenatal as well long-term effects of drug exposure early in children’s development.

Learning Objectives

1. Gain insights on the recent development and utilization of real-world data/in-silico modeling and artificial intelligence tools to fill in existing knowledge gaps and enhance our understanding of maternal/pediatric research.

2. Gather an overview of challenges/opportunities in the utilization of real-world data for pregnant/lactating women/children, and address the underlying impediments in the translation of real-world data to real-world evidence in these populations.

Session Schedule

12:15 PM - 12:17 PM ET
Opening Remarks
Pooja Manchandani, PhD

12:17 PM - 12:25 PM ET
Challenges and Opportunities in Using Real World Data for Clinical Pharmacology Research
Sara Quinney, PharmD, PhD

12:25 PM - 12:31 PM ET
Real-World Data Sources: Sentinel Database
Danijela Stojanovic, PharmD, PhD

12:31 PM - 12:36 PM ET
Enhancing Maternal and Child Health Through Integrated Quantitative Science Approaches
Ping Zhao, PhD

12:36 PM - 12:43 PM ET
Integration of Real-World Evidence Through PBPK/PD Modeling
Xian Pan

12:43 PM - 1:15 PM ET
Roundtable Discussion with Live Q&A and Closing Remarks
All Speakers