class=”wistia_preload_transcript_text” aria-hidden=”true” tabindex=”-1″ style=”text-align: justify; font-size: 5px !important;”>Children are not small adults, yet over half of medicines lack pediatric labeling, leaving pediatric and especially neonatal care in a dosing Wild West. Regulators expect pediatric strategy as a core pillar of global submissions and is mandatory in some regions, shifting development from wait and see to proactive by design planning. Dosing isn’t simple scaling clearance reflects growth, ontology driven enzyme maturation and organ development, captured through POPK and PBPK to design smarter trials. Artificial intelligence and machine learning accelerate exploration, thousands of models in hours while experts ensure biological plausibility, transparency, and validation. Precision dosing starts with a population dose and adapts through Bayesian individualization, turning models into real time patient decisions. In infants with rare diseases, model derived dosing has guided clinical care and prospective trials, enabling safer, faster, and more confident in pediatric development. Engage regulators early, from phase one onward. With the right models, pediatric development can be ethical, efficient, and confident.
Originally aired: Tuesday, January 13, 2026
Duration: 60 minutes
Pediatric drug development is no longer optional, it is a critical component of global regulatory strategy and long-term product success. Regulatory agencies such as the FDA and EMA require early pediatric planning through Pediatric Study Plans (PSPs) and Pediatric Investigation Plans (PIPs), and these commitments directly influence development timelines, approvals, and market access.
This on-demand webinar brings together perspectives from industry, regulatory science, and academia to demonstrate how an integrated, model-informed approach can de-risk pediatric programs and support efficient development.
Speakers discuss:
- The clinical need and real-world challenges in pediatric populations
- Regulatory expectations and common pitfalls in clinical pharmacology gap analysis
- The role of Model-Informed Drug Development (MIDD)—including population pharmacokinetics/pharmacodynamics (PopPK/PD), physiologically based pharmacokinetic (PBPK) modeling, quantitative systems pharmacology (QSP), model-based meta-analysis (MBMA), and machine learning—in optimizing pediatric dose selection and streamlining development across modalities, from small molecules to biologics
- The session concludes with a panel discussion highlighting practical lessons learned and emerging trends shaping the future of pediatric drug development.
Key Learning Objectives
- After watching this on-demand webinar, participants will be able to:
- Explain why pediatric drug development is essential to both patient care and regulatory submission strategy
- Identify key regulatory requirements (PIP, PSP, ICH E11/E11A) and approaches to conducting a clinical pharmacology gap analysis
- Describe how pharmacometric tools (PopPK/PD, PBPK, QSP, MBMA) and machine learning can support pediatric dose prediction and study design
- Apply lessons from case studies across modalities—including small molecules, biologics, and advanced therapies—to their own development programs
Speakers
- Amy Cheung, PhD, VP, EU/APAC Regional Lead of Quantitative Science, Global Lead of Certara’s Pediatric and Maternal Innovation Engine
- Justin Hay, PhD, Sr. Director, Clinical Pharmacology Consulting, Co-Lead of Certara’s Rare and Neglected Innovation Engine
- Tomoyuki Mizuno, PhD, Cincinnati Children’s Hospital Medical Center
