The pharmaceutical industry is poised for a paradigm shift: moving away from animal models prior to human trials. This conference unites leaders from pharma, academia, and the exhibitor ecosystem to address the critical question: What is needed to engineer the post-animal drug discovery pipeline? Achieving this future requires fundamental changes – testing compounds earlier in more relevant cells, at significantly larger scales, to generate the comprehensive foundational data necessary to reduce animal dependency.

Our 4 structured sessions will tackle the core transitions we need to make to achieve this future state. Relevant biology at scale will explore innovations in complex in vitro models and showcase where we are already having success. Redesign of assay and data pipelines will address the overhaul needed for handling vast, multi-dimensional cell-based read-outs, ensuring we get the most from our data. AI and ML in cell-based screening will focus on deep learning for image-based phenotyping, integration of multi-OMICs and how AI is transforming complex cellular data. Finally, AI and prediction: how do we best prepare? will delve into data integrity & FAIR workflows, managing data pipelines & metadata for AI-prediction readiness, and the skillsets required to operationalise these advanced approaches.

This event is essential for professionals across the cell-based discovery continuum who are actively preparing for an AI-driven future. Through collaborative dialogue, we aim to help this community rework early discovery from animal-gated milestones to human-first decision making. This new blueprint needs us to deliberate on how our hit-to-lead processes should change, where cells should replace animals, and how AI can enhance the predictive accuracy of our efforts to deliver transformative therapies.