BenevolentAI

AI-powered drug discovery platform integrating biological knowledge graphs with generative chemistry.

BenevolentAI has built a proprietary biological knowledge graph containing over 1 billion interconnected biomedical data points. Their platform uses machine learning to identify disease mechanisms, predict novel targets, and design drug candidates, with a pipeline spanning neurodegeneration, inflammatory disease, and oncology. In March 2025 BenevolentAI delisted from Euronext Amsterdam through a merger into Osaka Holdings S.à r.l., which then converted its legal form and rebranded as BenevolentAI; the company now operates as a privately held entity.

Headquarters: London, United Kingdom
Founded: 2013
Compliance: ISO 27001, SOC 2 Type II
Deployment options: cloud, private-cloud
Website: https://www.benevolent.com
LinkedIn: https://www.linkedin.com/company/benevolentai

AI Use Cases

Target Identification & Validation

Vendor Scorecard

100% — Complete coverage. Coverage score — how completely Atlas documents BenevolentAI across 7 buyer-evaluation areas. Reflects available Atlas data, not solution quality.

Compliance & Validation — Documented

ISO 27001, SOC 2 Type II

Deployment & Hosting — Documented

cloud, private cloud

Pricing Transparency — Documented

Annual platform license

Implementation & Onboarding — Documented

6–12 months

Organization & Role Fit — Documented

Mid-Size Biotech, Large Pharma, Top 20 Pharma, Drug Discovery, R&D Leadership

Solution Scope — Documented

Biomarker Discovery, Drug Repurposing, Natural Language Processing, Target Identification

Company Viability — Documented

Private, $292M raised, 300+ employees, Founded 2013

Always ask the vendor

Not captured in Atlas data — confirm directly. Excluded from the score above.

Data Rights & IP

Who owns model outputs? Is our proprietary data used to train models others can access, and where does our data reside?

Model Credibility & Explainability

Can you share validation studies or benchmarks, explain how the model reaches its conclusions, and describe how bias and drift are monitored?

Clinical Trial Activity

3 registered trials where BenevolentAI is the lead sponsor. Source: ClinicalTrials.gov, verified 2026-07-29.

Phases: Phase 1 (1), Phase 2 (1), Phase 1/Phase 2 (1)

Top conditions studied: Atopic Dermatitis, Excessive Daytime Sleepiness, Healthy Volunteer Study, Parkinson Disease

Study Investigating the Safety, Tolerability, PK and Food Effect of BEN8744. (NCT06118385, completed)
A First-in-Human PoC Study With BEN2293 in Patients With Mild to Moderate Atopic Dermatitis (NCT04737304, completed)
BEN-2001 in Parkinson Disease Patients With Excessive Daytime Sleepiness (NCT03194217, completed)

Evidence & Outcomes

AI knowledge-graph identified baricitinib as a COVID-19 treatment candidate

BenevolentAI used its biomedical knowledge graph to identify the existing rheumatoid-arthritis drug baricitinib as a candidate COVID-19 therapeutic. The hypothesis was subsequently tested in clinical trials and baricitinib later received FDA Emergency Use Authorization for hospitalized COVID-19 patients.

peer reviewed (PubMed Central) · 2021-08-13

AstraZeneca collaboration delivers novel targets in CKD and IPF

Under its long-running collaboration with AstraZeneca, BenevolentAI's platform contributed AI-generated novel drug targets that AstraZeneca selected to advance in chronic kidney disease and idiopathic pulmonary fibrosis.

press release (BenevolentAI (Business Wire)) · 2024-06-24 — Partner: AstraZeneca

Questions to Ask This Vendor

How is the knowledge graph updated with new literature?
What validation studies exist for your target confidence scores?
How do you measure and report false positive rates in target predictions?