Building on the milestones of QSP Summit 2025, this dedicated Day 2 track showcases how Quantitative Systems Pharmacology (QSP) is an increasingly adopted methodology in model-informed drug development. The QSP Summit at Certainty will unite industry innovators, academics, and thought leaders to explore how computational modeling is bridging biology and pharmacology to predict clinical outcomes, inform first-in-human dose decisions, and accelerate drug development timelines.
New for 2026, we will spotlight Certara’s revolutionary AI-enabled QSP platform that is enhancing predictive power, automating model building, and expanding the reach of mechanistic modeling.
Highlights include:
- Case studies demonstrating scalability across rare and neurodegenerative diseases.
- Strategies for reducing reliance on animal models via nonanimal safety evaluation tools, and innovative applications like virtual patient populations and Virtual Twin® methodology.
- Forward-looking discussions on how regulatory acceptance, AI integration, and rigorous mechanistic modeling are transforming QSP from a niche methodology into a foundational pillar across R&D.
April 15, 2026
Agenda
8:00 – 9:00
Breakfast & Badge Pick Up
9:00 – 10:30
Morning session 1
10:30 – 11:00
Morning break
11:00 – 12:30
Morning session 2
12:30 – 2:00
Lunch and learns
2:00 – 3:30
Afternoon session
3:30 -3:45
Close of day
As a QSP Summit at Certainty attendee you may also be interested in this session
Modeling and Simulation from Preclinical to Approval
Join us on Day 1 of Certainty to learn how empirical PK/PD methods like NCA and popPK are complementing in silico approaches like PBPK and QSP to answer the most daunting challenges in development, from optimal first-in-human dosing to presenting clin pharm evidence effectively in your NDA or BLA.
Reserve your spot
Reserve your spot for the Certainty US 2026 customer event for exclusive access to the Certara community of experts, industry leaders, and peers as we collectively explore the latest innovations and opportunities to bring greater certainty to drug discovery and development.
