The Bio Report: “Rewriting Drug Discovery with an AI-Multi-Omics Approach”

Q: “Sapient says it’s redefining how biology is measured and interpreted. What does that mean in practical terms, using your AI-multi-omics approach?”

A: By expanding what we can measure, we can understand disease processes much better. We can identify targets, figure out how to modify disease risk, and determine the earliest points to intervene – before the system breaks. We can ask: what’s the best therapeutic for a specific individual and their disease process? How do we deploy treatments to make them maximally effective?

All of these questions are answered by data. For the first time, we can generate that data at scale, across large systems, to start answering them. We can now take biological specimens – blood, urine, CSF, tears, saliva, tumors, tissues, even cells in a dish – and measure the proteome and metabolome at an unprecedented scale. Not just 1,000 or 2,000 proteins or metabolites, but 14,000 to 16,000 in complex matrices.

Now, just generating data without insight is pointless – you’ll just fill hard drives. The challenge is how we interpret that data. AI and advanced statistical tools are critical here, to help turn complex, multidimensional datasets into answers for questions like:

• What’s the best target?
• What are the on-target, off-tissue effects of my drug?
• What’s the best therapeutic?
• Which patients will respond?

AI is evolving beyond chemical optimization to address these questions across the entire drug development pipeline. That’s how AI-multi-omics integration accelerates the whole process.”