AI in Action
LMRLarge Molecule Research · Driven by data & AI

Molecules by design.

70% fewer molecules requiring experimental characterization.

BioAIM helps scientists identify the right biologic candidates earlier by combining predictive AI, computational biology, and experimental data to support smarter discovery decisions.

From evaluating developability and manufacturability to focusing laboratory efforts on the most promising molecules, BioAIM empowers researchers to design better biologics with greater confidence.

01Challenge02AI Technology03Applied Today04Real-World Example05Impact
04 · Real-World Example

Microbial CMC teams use BioAIM prediction models today.

Today, Microbial CMC teams use BioAIM prediction models to identify biologic candidates with the right properties earlier, helping scientists focus experimental work on the most promising molecules and accelerate development.

Data-driven quality improvements
Prediction models identify colloidal stability risks earlier
Prediction models distinguish high- and low-expressing molecules
Combined with high-throughput workflows to accelerate verification and CMC development
Accelerates development while increasing the probability of success
Story · 04 Real-World Example
01Data-driven quality improvements
←→ to move between stages · Stage 4 of 5 · LMR
Smarter decisions.Better biologics.Better medicines.

Helping scientists identify the right biologic candidates earlier and with greater confidence.

LMR original poster
Original poster · click anywhere or press Esc to close
Next program: TDSB →