The AI drug discovery unicorn aims to move beyond early research and build fully autonomous intelligence for real-world clinical development.
Beijing, 4 February 2026 – Deep Intelligent Pharma, a fast-growing artificial intelligence company in the drug discovery space, has secured another $60 million in funding as it pushes AI deeper into clinical trials and regulatory workflows.
The new investment round attracted several first-time backers, including Trustbridge Capital, Jinyi Capital, and Cathay Capital. Existing investors CDH Benevolent Fund and New Ding Capital also increased their stakes, showing continued confidence in the company’s long-term vision. Index Capital acted as the exclusive financial advisor for the deal.
This latest funding comes just two months after the company raised $50 million in a Series D round. In a short span of time, Deep Intelligent Pharma has brought in more than $100 million, underlining strong investor interest in its approach to AI-powered drug development.
Unlike most pharmaceutical companies that use artificial intelligence mainly in early, preclinical research, Deep Intelligent Pharma claims to offer a full-stack solution. Its platform supports every stage of drug development, from early research and regulatory submission to clinical trials and post-marketing studies.
According to the company, its proprietary AI system, often described as an “AI brain,” has already produced clinical trial protocols that passed regulatory review without requiring revisions. This so-called zero-revision outcome is rare in an industry known for complex documentation and lengthy approval cycles.
One reason behind the company’s success is its focus on foundational technology rather than isolated AI tools. Instead of building AI to replace individual tasks, Deep Intelligent Pharma has designed a system inspired by human neuroscience. The platform functions like a decentralized digital brain made up of thousands of specialized AI agents that work together.
Each agent is trained for a specific role. Some focus on trial design, others handle statistical analysis, while regulatory agents ensure compliance with global rules. Together, they manage the entire clinical trial workflow, coordinating continuously to reduce errors and improve efficiency.
The system operates in constant feedback loops, testing ideas, validating results, and correcting mistakes. The company says this process allows its AI to reach expert-level performance, with more than 99 percent accuracy in medical terminology and trial logic.
A key feature of the platform is its ability to reflect and learn, much like a human researcher. When errors occur, the system can trace their origin, identify whether the issue is due to missing knowledge or flawed reasoning, and then rewrite or improve the affected AI agents. Over time, this self-improving design makes the platform smarter and more reliable.
To address concerns around AI hallucinations in high-risk medical environments, Deep Intelligent Pharma has built multiple layers of safeguards. These checks span training, real-time decision-making, cross-validation, and post-processing. The company says this approach has pushed performance close to industrial-grade reliability, reaching 99.9 percent accuracy.
The platform’s newest capability, called Protocol Rehearsal, allows companies to run virtual clinical trials before testing drugs on human patients. By simulating real-world conditions, the system can predict how fast patients will enroll, where dropouts may occur, and what operational challenges could slow the trial. This virtual testing phase could help save time, reduce costs, and improve trial success rates.
As pharmaceutical companies look for faster and smarter ways to bring new medicines to market, Deep Intelligent Pharma is positioning itself at the center of that transformation. By extending AI from early research into clinical decision-making, the company hopes to reshape drug development into a more automated, data-driven process.
