PharmaMar Partners with Globant to Deploy AI-Powered Drug Discovery Platform Achieving 15x Faster Cancer Research Insights
核心洞察
PharmaMar (搜索) and Globant (搜索) have launched a multi-agent AI system that delivers over 90% accuracy in complex data retrieval and reduces time to insights by up to 15-fold for cancer drug discovery.
The platform utilizes over 20 specialized digital agents working across preclinical, clinical, regulatory, commercial and strategy areas to analyze large volumes of scientific and regulatory data.
The system can review over 4,500 research documents to prioritize the 10 most viable treatment-indication combinations from over 8,000 possibilities, completing work that would have taken months for human researchers.
PharmaMar (搜索), a world leader in the discovery, development and commercialization of marine-derived anti-cancer drugs, has announced a strategic collaboration with Globant (搜索) to accelerate cancer drug discovery through artificial intelligence. The partnership has resulted in the creation of a multi-agent AI system that delivers more than 90% accuracy in complex data retrieval and reduces time to insights up to 15-fold, enabling scientists to select high-potential drug candidates for clinical development in a fraction of the time previously required.
Revolutionary Multi-Agent AI Framework
Through Globant (搜索) Enterprise AI, the two organizations have developed a sophisticated platform capable of analyzing large volumes of scientific, regulatory, and clinical data sources to assist with decision-making across PharmaMar (搜索)'s R&D ecosystem. The system features over 20 specialized digital agents working across preclinical, clinical, regulatory, commercial and strategy areas, uniting human creativity and machine precision in the fight against cancer.
Each agent collaborates within GEAI's secure architecture to process documents, simulate scenarios, and rank the most promising pharmaceutical assets. The intelligent system integrates information from internal databases, scientific publications, and global regulatory sources such as the FDA and EMA, allowing PharmaMar (搜索)'s teams to identify promising treatment combinations and make more informed, faster decisions.
Unprecedented Processing Capabilities
The platform demonstrates remarkable efficiency in handling complex research tasks. The system enables reviews of over 4,500 research documents to prioritize the 10 most viable treatment-indication combinations out of over 8,000 possibilities - work that would have taken months for human researchers to complete. This capability represents a significant advancement in pharmaceutical research methodology, where time-to-insight can be critical for patient outcomes.
"Drug discovery has always been a race against time, and in oncology, that time can mean everything," said Dr. Javier Jimenez, Chief Medical Officer at PharmaMar (搜索). "By integrating Globant (搜索)'s AI technologies, we can process data from thousands of documents in seconds, simulate scenarios, and focus our research efforts where they have the highest potential to make a difference for patients."
Enhanced Decision-Making and Future Capabilities
Beyond speed and efficiency, the collaboration strengthens PharmaMar (搜索)'s ability to reuse institutional knowledge and fosters a new culture of digital innovation across its teams. The platform enables continuous, self-improving workflows that adapt and optimize over time, creating a sustainable competitive advantage in drug discovery.
In the next phase of the project, PharmaMar (搜索) plans to extend these capabilities to enable hypothesis generation, real-time compliance checks, and automated content creation for scientific reporting. These enhancements will further streamline the research process and reduce administrative burden on scientific teams.
Industry Impact and Vision
"PharmaMar (搜索)'s vision proves what's possible when human intelligence and AI systems work side by side," said Ariel Capone, CEO of Globant (搜索)'s Healthcare and Life Sciences AI Studio. "By leveraging agentic AI, we're building a new model for drug discovery; one that brings precision and scalability to a field that directly impacts millions of lives."
The collaboration represents a significant step forward in the application of artificial intelligence to pharmaceutical research, potentially setting new standards for efficiency and accuracy in cancer drug discovery. The system's ability to process vast amounts of data while maintaining high accuracy rates could accelerate the development of new treatments for cancer patients worldwide.