RISING TIDES
Observations from the IMC Research Process

Biotech’s Next Wave: From Digital Design to Physical Validation

AI is accelerating the design of promising drug candidates, driving demand for the physical infrastructure required to turn digital discoveries into viable drugs.

• From pixels to pipettes. AI is dramatically expanding the number of molecules researchers can design and evaluate computationally. But a predicted drug is still only a prediction. Candidates must be synthesized, screened against living cells and tested for efficacy, toxicity and manufacturability before they can advance.
• The lab is joining the loop. Drug discovery is becoming a continuous design-build-test-learn cycle: AI proposes candidates, laboratories generate experimental data, and those results are fed back into the models. As the cycle accelerates, demand rises for high-content imaging, synthetic biology, automated assays and outsourced preclinical testing—the physical infrastructure required to turn digital discoveries into viable drugs.
• The stocks are beginning to see it. Schrödinger sits at the front end, using computational tools to identify and optimize potential drugs. Revvity reported a tangible inflection in its high-content screening business during the second quarter, including double-digit order and organic growth and a shift from single-instrument purchases to multi-system orders. Twist Bioscience converts AI-generated sequences into physical proteins and antibodies, then produces the experimental data needed to refine the models. WuXi AppTec provides the downstream DMPK, toxicology and preclinical testing needed to move successful candidates toward clinical development.