BioLogic Summit – 2026

Theme: Harnessing ML/AI for the Design & Optimization of Biotherapeutics

Target Audience

• Experimental scientists integrating machine‑learning and AI into biologics research
• Data scientists and computational biologists working on protein engineering and drug discovery
• Professionals from pharma, biotech, life‑science, clinical, healthcare, and IT sectors

Speakers & Keynotes

• Stephanie Truhlar, PhD – Eli Lilly & Company
• Andrew Nixon, PhD – Boehringer Ingelheim Pharmaceuticals
• Charlotte Deane, PhD – University of Oxford
• Peyton Greenside, PhD – BigHat Biosciences
• Peter Tessier, PhD – University of Michigan

Topics & Sessions

• Data Strategies and the Future of AI Models
• Optimizing training data pipelines
• Active learning integration
• Overcoming data scarcity
• Emerging model architectures

• Practical deployment in R&D

• ML/AI for Biologics Developability, Optimization, and de novo Design

• Lab‑in‑the‑Loop approaches
• Generative & multi‑modal AI models
• Structure‑based & physics‑informed design
• Developability & optimization predictions
• AI‑driven predictive preclinical models

Goals

• Unlock the potential of ML/AI to accelerate biotherapeutic discovery and development
• Empower hybrid scientists who combine wet‑lab experimentation with computational tools
• Provide actionable insights for near‑term implementation of AI technologies in pharma and biotech

Format

• Two parallel conference tracks covering data strategy and biologics design
• Luminary plenary keynotes from leading academic and industry experts
• Moderated small‑group discussions for focused problem‑solving
• Three one‑day training seminars (Monday) for skill development at all levels
• Interactive elements including networking forums and collaborative sessions