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Google Unveils New Open AI Models Named “TxGemma” to Accelerate Drug Discovery

Google Unveils New Open AI Models Named “TxGemma” to Accelerate Drug Discovery

Date: March 19, 2025

Google introduces TxGemma, open AI models aimed at revolutionizing drug discovery by accelerating research, despite AI’s mixed success in the field.

Google is taking another big leap in artificial intelligence—this time, in the world of drug discovery. The tech giant has announced plans to release a set of open AI models designed to help researchers develop new medicines faster and more efficiently.

Dubbed TxGemma, these models aim to simplify one of the most complex and expensive challenges in medicine: developing new drugs. They are built to understand everything from molecular structures to how different compounds interact—giving scientists a powerful tool to speed up the research process.

Karen DeSalvo, Google’s Chief Health Officer, highlighted the impact of these new AI tools: 

“The development of therapeutic drugs from concept to approval is a long and expensive process. We’re working with the research community to find new ways to make this process more efficient.”

The models will be available later this month as part of Google’s Health AI Developer Foundations program, allowing researchers worldwide to integrate them into their studies.

The Growing Role of AI in Pharma

AI has already started transforming drug discovery, with pharmaceutical companies using machine learning to predict how new drugs might behave before they’re even synthesized. Google isn’t new to this space—its subsidiary Isomorphic Labs has been partnering with major pharmaceutical companies like Eli Lilly and Novartis to use AI in drug development.

With the launch of TxGemma, Google is taking things a step further by making AI-driven drug discovery more accessible to scientists outside big pharma.

Challenges and Unmet Expectations

Countless companies, including Google spin-out Isomorphic Labs, have promised that AI could one day revolutionize drug discovery by dramatically accelerating the earliest R&D steps. While there have been some successes, AI has not provided an immediate magical solution in the lab. AI-designed drugs still need to go through rigorous testing, and not all companies using AI in drug discovery have succeeded. 

Several firms employing AI for drug discovery, including Exscientia and BenevolentAI, have suffered high-profile clinical trial failures in recent years. Meanwhile, the accuracy of leading AI systems for drug discovery, like Google DeepMind’s AlphaFold 3, tends to vary widely. Clinical trials remain a major hurdle, and setbacks are common.

Still, the industry is betting big on AI. With Google throwing its weight behind open-source models like TxGemma, the potential for breakthroughs in medicine is growing. If AI can cut down the time and cost of bringing new drugs to market, it could revolutionize how we treat diseases in the years to come.

For now, all eyes are on Google as researchers get their hands on these new tools and put them to the test.

Arpit Dubey

By Arpit Dubey LinkedIn Icon

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