Side by side

Four programs, one approach.

Each program follows the same arc: a scientific challenge, an AI technology, how it is applied today, a real-world example and the impact. Click any cell to open that stage in full.

Scroll sideways to see all four programs.

TDSBTarget, Disease & Systems BiologyDiscover hidden biology.

QSPQuantitative Systems PharmacologyDigital patient twins.

IDDIntegrated Drug DiscoveryPredictive drug design.

LMRLarge Molecule ResearchMolecules by design.

01Challenge

Disease knowledge is fragmented across data sources.

Predicting human outcomes before clinical trials remains one of drug development’s greatest challenges.

Drug discovery requires thousands of decisions.

Identifying the right biologic candidates while balancing potency, developability, manufacturability and stability.

02AI Technology

AI-powered engines that identify therapeutic targets.

Virtual patient populations that simulate disease and treatment response.

AI helps prioritize which compounds to synthesize next.

BioAIM evaluates developability and performance before experimental testing.

03Applied Today

Target Engines across multiple therapeutic areas.

Supporting candidate selection across 29 programs.

Improving every design cycle.

Predictive models throughout the biologics discovery workflow.

04Real-World Example

Microscopic colitis opportunity identified by SANDIE.

Novel asthma treatment accelerated by more than one year.

Significantly fewer compounds in data-rich programs.

Microbial CMC teams use BioAIM prediction models today.

05Impact

More confident target, indication and portfolio decisions.

Faster decisions. Better predictions. Fewer animal studies.

Turning data into better decisions.

Better biologic therapies to patients, faster.