Application of AI for Advanced R&D

Generate Novel Drug Candidates

Analyze data sets, form hypotheses and generate novel insights
Identify novel drug candidates
Analyze data from patient samples in both healthy and diseased states to generate novel biomarkers and therapeutic targets
Predict binding affinity and other pharmacological properties of molecules
Allow filtering for drug-like properties of molecules
Reduce complexity in protein design

Clinical Trials

Optimize clinical trial study design
Transform diverse streams of biomedical and healthcare data into computer models representative of individual patients
Deliver personalized medicine at scale by revealing optimal health interventions for individual patients
Analyze medical records to find patients for clinical trials
Automate matching cancer patients to clinical trials through personal medical history and genetic analysis
Improve pathology analysis
Identify patients that would benefit from novel therapies

Design and Processing of Preclinical Experiments

Reduce time, money, and uncertainty in planning experiments
Decode open- and closed-access data on reagents and get actionable insights
Automate selection, manipulation, and analysis of cells
Expedite development of cell lines and automate manufacturing of cellular therapeutics
Automate sample analysis with a robotic cloud laboratory

Repurposing of Existing Drugs

Rapidly identify new indications for many known drugs
Match existing drugs with rare diseases
Conduct experimental biology at scale by testing 1000+ of compounds on 100+ of cellular disease models in parallel
Generate novel biomarkers and therapeutic targets

Aggregation and Synthesis of Information