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4. AI co-scientist
Research is at the heart of our work, whether that’s incremental updates that build on years of progress, or groundbreaking developments that change the industry and how our partners work. To help biomedical researchers create novel hypotheses and research plans, we recently launched an AI co-scientist, a new system built on Gemini 2.0. The AI co-scientist helps researchers parse large volumes of scientific literature and generate high-quality, novel hypotheses. For instance, let’s say researchers want to better understand the spread of a disease-causing microbe. They can specify this research goal using natural language, and the AI co-scientist will propose testable hypotheses, including a summary of relevant published literature and a possible experimental approach.
Though not meant to automate the scientific process, this collaborative tool is designed to help experts uncover new ideas and accelerate their work. We’re already working with partners, including Imperial College London, Houston Methodist and Stanford University, and are keen to see how researchers around the world use this tool. And while it’s in its early days, the enthusiasm is clear — we’ve received considerable interest for our upcoming trusted tester program.
5. TxGemma
The development of therapeutic drugs from concept to approved use is a long and expensive process, so we’re working with the wider research community to find new ways to make this development more efficient.
Today, we announced TxGemma, a collection of Gemma-based open models that we hope will help improve the efficiency of AI-powered drug discovery. TxGemma is able to understand regular text and the structures of different therapeutic entities, like small molecules, chemicals and proteins. This means researchers can ask TxGemma questions to help predict important properties of potential new therapies, like how safe or effective they might be.
Later this month, we’ll be making this available to the community to build on and improve through Health AI Developer Foundations.
6. Treatment options for pediatric oncology
With the help of Google, the Princess Máxima Center for pediatric oncology in the Netherlands is developing an AI tool called Capricorn. It uses Gemini models to help physicians accelerate the identification of personalized cancer treatments by combining vast public medical data and de-identified patient data.
Based on its analysis, Capricorn rapidly generates summaries of treatment options and relevant medical publication, which allows physicians to have more in-depth discussions on how to achieve the best possible health outcomes for their pediatric patients. With AI, physicians have more time to dedicate to what’s most important: patient care.
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