Day One

• Reflecting on how MIDD has evolved from a specialist modelling discipline into a strategic framework that influences decisions across discovery, clinical development, regulatory interactions, and lifecycle management
• Assessing the impact of recent regulatory developments, including the finalisation of ICH M15, and discussing what successful implementation looks like across industry, regulatory agencies, and development teams
• Exploring how emerging technologies are expanding the scope of questions that MIDD can address while introducing new expectations around model credibility and validation

• Exploring a strategic, case-based perspective on how MIDD connects evidence, learning, and decisions across development; from translational evidence and first-inhuman strategy through adaptive dose and regimen optimization to proof-of-concept planning
• Explaining how using complex oncology biologics to illustrate how quantitative insights can shape the development path

• Combining clinical, mechanistic, biomarker, and historical datasets to support modelinformed decision-making in rare disease programmes
• Designing development strategies when untreated baseline data is unavailable
• Building modelling frameworks that connect study design, analysis, and reporting to improve confidence in dose selection decisions

This informal session provides the perfect opportunity to meet and connect with your industry

colleagues, from clinical pharmacologists, modelling & simulation specialists, to pharmacometrics

experts. Take advantage of these introductions and build upon these newly-formed connections for

the rest of the conference, and beyond

• How pharma and biotech integrate diverse external datasets including public -omics resources, published literature, standard of care data, and real-world evidence to improve confidence in early-stage predictions with limited clinical datasets
• Practical approaches for incorporating heterogenous data into mechanistic models, methodological challenges associated with data quality and population differences, and strategies for communicating uncertainty and model assumptions to project teams and regulators

• Developing Pop-PK and Exposure-Response models to identify patient characteristics that could impact PK of Bicycle Drug Conjugates® (BDC)
• Integrating PK, efficacy, and safety data to characterise risk-benefit profile and identify optimal dosing strategies
• Establishing a modelling platform to support BDC® decision making in drug development

• Designing AI-enabled systems that can interpret analysis outputs, extract figures, and generate standardised reports directly from modelling workflows
• Managing hallucination risk and ensuring scientific accuracy when AI contributes to regulatory or decision-support documentation
• Lessons learned from integrating AI into existing R-based and modelling environments
• Future opportunities for creating end-to-end automated workflows across analysis, reporting, and communication

• Exploring the role of AI in QSP model development, parameter estimation, and model refinement
• Comparing AI-generated outputs against established modelling approaches to assess reliability and reproducibility
• Practical strategies for validating AI-assisted models and mitigating hallucination risk in complex modelling environments
• Understanding what evidence regulators and internal stakeholders may require before AI-informed models can support critical development decisions

• Exploring how organisations are applying the M15 framework to support strategic decision-making and regulatory interactions
• Examining the role of MIDD in cell & gene therapies, novel modalities, and other emerging therapeutic platforms
• Leveraging MIDD alongside New Approach Methodologies (NAMs) to generate evidence and reduce development uncertainty
• Sharing practical lessons learned for embedding MIDD frameworks across multidisciplinary teams and global development programmes

• Addressing uncertainty and establishing confidence in extrapolation frameworks
• Lessons learned from regulatory interactions involving paediatric extrapolation strategies
• Opportunities to accelerate access to therapies for rare disease populations