AI excels at identifying patterns and generating insights across large datasets, but its output quality depends heavily on its training data. Meanwhile, projects involve making critical decisions – decisions that require a nuanced understanding of biology, subject-matter expertise and experience that AI lacks. That’s where humans come in.

Our fireside chat will explore a hybrid workflow that combines the best of both worlds: AI efficiency and human intelligence. Led by experts from Sygnature Discovery, we will discuss how this modern approach benefits drug discovery, shortening the path from target lists to confident decisions.

You will learn:

What “human-in-the-loop” and “lab-in-the-loop” means

The importance of expert intervention and wet-lab validation

The synergistic impact of well-trained AI and expert discretion

How they reduce project risk by flagging safety/IP/druggability issues and more

How cross-disciplinary input drives actionable results

Uncover insights into drug metabolism and pharmacokinetics (DMPK) with causation-driven interpretation and feasibility assays

Why explainability matters

How transparency and human expertise lead to defensible decisions