Mankind Pharma has announced a strategic collaboration with Denovo Sciences to launch an AI-led drug discovery programme, marking an important step in its focus on innovation-driven, technology-enabled research and development. The partnership brings together Mankind Pharma’s strong R&D capabilities, experimental validation infrastructure and clinical development expertise with Denovo Sciences’ proprietary platform for AI-driven molecular generation and prioritisation.
Together, the two organisations will work under a human-in-the-loop model, where AI generates and evaluates molecular candidates while scientific experts guide, validate and refine the results at every stage. This collaboration is centred on three key goals: reducing early drug discovery timelines, improving the quality of lead candidates and ensuring that only molecules with the strongest development potential move ahead. By using computational precision in the early stages of discovery, both partners aim to cut time and resources spent on candidates that may not succeed later in development.
Commenting on the collaboration, Sanjay Koul, President- R&D, Mankind Pharma, said, “By embracing AI-driven innovation, we aim to significantly enhance the speed and efficiency of our early-stage discovery efforts. Working with Denovo Sciences will help us identify and advance the most promising molecules more effectively, supporting our long-term goal of bringing better and more accessible therapies to patients.”
Sharing the technology partner’s perspective, Hovakim Zakaryan, CEO- Denovo Sciences, noted that the platform is designed to work closely with established drug discovery teams. “Our AI-led engine allows us to rapidly design, screen and prioritise molecular candidates, while scientific experts remain involved at every step to ensure robust decision-making. This human-in-the-loop approach ensures that we combine computational power with deep domain expertise to generate candidates that are both innovative and viable,” a Denovo Sciences spokesperson said.
The long-term goal highlighted by both organisations is to benefit patients. Faster discovery cycles and better candidate selection can help bring differentiated, effective and accessible therapies to patients sooner. The collaboration also reflects a broader shift in global pharma, where AI and machine learning are increasingly being integrated into traditional discovery workflows to unlock new possibilities across complex disease areas.
