Use case type

Therapeutics discovery

This category applies AI to discover or optimize drug candidates, including biologics and other therapeutic molecules. It helps researchers evaluate complex biological data and prioritize promising compounds earlier.

Data updated Aug 3, 2026
Use cases

3

Examples

3

Industries

2

Timeline

3 mo

Adoption over time

Documented cases per month

By case publish month · completed months only

3 cases documented across 34 months (Oct 23 – Jul 26), peaking at 1 in October 2023.

Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.

Company examples

Use cases of this type

3 shown from 3 use cases

Eli Lilly partnered with BigHat Biosciences to co-develop next-generation therapeutic antibodies using AI technology. BigHat's Milliner platform leverages machine learning and synthetic biology high-speed wet labs to optimize key antibody attributes for accelerated biologics development.

Eli LillyPharma

Latent Labs, led by ex-DeepMind scientist Dr. Simon Kohl, emerged as a generative AI service provider specializing in protein design for drug discovery. Using advanced AI, they aim to computationally design therapeutic molecules like antibodies and enzymes, revolutionizing treatments. Partnerships with Microsoft and renowned industry experts further strengthen their mission.

Latent LabsPharma

Pangaea Data partnered with Microsoft Azure to address inefficiencies in clinical trials and ensure data privacy. By leveraging Azure services, including Virtual Machines, Container Instances, Blob Storage, Health Data Services, and AI tools like Text Analytics for Health and OpenAI, they implemented a solution to characterize patients efficiently while preserving data privacy. This enabled clinicians and pharmaceutical companies to identify undiagnosed and misdiagnosed patients across 7,000 conditions. Key achievements included a collaboration between two pharmaceutical companies and the UK’s NHS, leading to improved trial efficiency, cost reductions, and significant financial savings. Through this partnership, Pangaea Data also expanded globally using the Azure Marketplace and Microsoft’s co-sell program.

Pangaea DataHealthcare

Common questions

Therapeutics discovery at a glance

How many therapeutics discovery use cases are documented?
The AI Use Case Hub documents 3 real therapeutics discovery deployments across 2 industries, with 3 detailed company examples you can browse.
Which industries adopt therapeutics discovery the most?
Therapeutics discovery is most common in Pharma (67%) and Healthcare (33%).
Which countries lead in therapeutics discovery?
United Kingdom leads documented therapeutics discovery deployments, followed by United States.
What technologies are used for therapeutics discovery?
Teams most often build therapeutics discovery with Azure ML, Azure AI and Azure OpenAI.
What AI capabilities power therapeutics discovery?
Across the documented deployments, the most common capability patterns are RAG (33%).
What results do companies report from therapeutics discovery?
Across the 3 deployments reporting outcomes, companies most often cite new product / capability (100%), ecosystem & partnerships (67%) and customer experience & trust (67%). Where impact is quantified, the strongest evidence is in other quantified impact: a median +500% across 1 reported metric.