What to Expect in 2026?
Model-informed drug development has crossed a critical threshold. With the ICH M15 guideline now finalized and industry pressure mounting to accelerate timelines while reducing development risk, quantitative approaches are moving from a supportive discipline used mainly for dose optimization into a driver of decisions across discovery, translational science, clinical development and regulatory strategy.
As adoption accelerates, new challenges surface. Teams are tasked with embedding MIDD when data is limited, combining simulation with AI, demonstrating model credibility to regulators and internal stakeholders alike, and turning quantitative insight into development impact that actually lands.
The 2nd Model-Informed Drug Development Summit brings together modelling and simulation experts, senior pharmacometricians, clinical pharmacologists, QSP scientists, translational leaders and regulatory experts to work through exactly these questions. Because the room is capped at 60 to 80 senior practitioners rather than the thousand-plus crowd of the big association meetings, conversations go deeper and connections outlast the event itself.
Designed with the full MIDD ecosystem in mind, it has been built around strategy and implementation, not a "what is MIDD" primer. Expect case studies on how MIDD has fast-tracked data, saved money and supported real regulatory submissions, delivered by practitioners who have actually done it.
Unmissable Event Highlights
Decode ICH M15 With Direct Regulatory Insight
Hear from the experts who helped shape the newly finalized ICH M15 guidance, and those now implementing it, to understand how the evidence standard is being applied in practice and where it remains unresolved for AI-assisted submissions and advanced modalities.
Bridge Pharmacometrics and Biostatistics
Examine how the pharmacometrics-biostatistics interface is evolving, with practical discussion on where the two disciplines align and where friction still slows decision-making, giving you a clearer view of how to structure that collaboration in your own team.
Bring AI Into MIDD Without Losing Regulator Trust
Work through the tension between scientific inference and operational efficiency in AI-assisted modelling, including the unresolved challenge of validating novel AI methods where no direct comparison to established approaches exists, to inform how you approach validation in your own programs.
Win Buy-In Internally, Not Just Externally
Treat internal stakeholder alignment as a parallel challenge to regulatory acceptance, not a secondary one, with practical approaches to embedding MIDD from day one rather than after entering the clinic, so you can identify where internal alignment is most likely to stall and plan around it earlier.
See Case Studies Across Every Modality
From small molecules to ADCs, cell and gene therapy and beyond, hear how MIDD is being applied across a modality-agnostic agenda, reflecting the reality that most pharmacometrics teams don't work in just one therapeutic area.
Explore the 2026 Full Event Guide
- Expert Speakers from Your Peers at Big Pharma, Emerging Biotechs & Regulatory Agencie
- Hands-On Workshops Covering AI Integration and Package Submission Readiness
- Case Studies Spanning Oncology, Autoimmune, Cell and Gene Therapy and Beyond
- Direct Regulatory Insight From the U.S FDA and Health Canada Perspectives
Attending Companies Include
Explore the Agenda
Preview strategy-led case studies on AI-enabled MIDD, pharmacometrics-biostatistics collaboration and ICH M15 in practice, alongside interactive discussions and hands-on workshops across three content-rich days.
Partner With Us
Position your organization as the go-to solution provider by showcasing your technologies, services and expertise to senior MIDD decision-makers actively evaluating modelling and simulation partners.
Join Biopharma Experts
Connect with pharmacometricians, clinical pharmacologists, QSP scientists and regulatory leaders through case studies, roundtables and structured networking designed for an intimate room, not a crowd.