BIOT Spotlight: Artificial Intelligence and Machine Learning

Artificial Intelligence and Machine Learning: Discovery, Development, and Manufacturing

Artificial Intelligence (AI) and Machine Learning (ML) now power every phase of modern biopharmaceutical innovation—from illuminating disease biology and designing novel modalities to streamlining process development and ensuring reliable, GMP-compliant manufacturing. For 2026 we are hosting a single, integrated session that captures this full continuum and showcases how data-driven methods accelerate the journey from first hypothesis to commercial product.

We invite scientists, engineers, and industry leaders to submit abstracts that highlight original research, case studies, or novel methodologies in any of the following areas:

• Early Discovery & Design: AI/ML for target or pathway elucidation; prediction of drug–target interactions, ADME, or toxicity; generative or reinforcement-learning approaches to protein and modality design; active-learning loops and high-throughput screening; strategies for dataset curation, integration, or federated learning.
• Process Development & Scale-Up: Autonomous or hybrid modeling for upstream/downstream optimization; in-silico manufacturability assessment; predictive scale-up and tech transfer; integration of AI with high-throughput experimentation platforms.
• Manufacturing & Operations: Real-time monitoring, control, and continued process verification; digital twins, predictive maintenance, and facility scheduling; AI-enhanced quality control and assurance; data integrity, cybersecurity, and regulatory considerations surrounding AI/ML deployment.

Across all topics, we encourage submissions that address challenges such as data quality, model interpretability, and regulatory engagement, and that demonstrate clear benefits in speed, efficiency, cost, or product quality.