Anthropic launched drug discovery programs for neglected diseases Big Pharma ignores. Novartis CEO Vas Narasimhan said AI could cut development from 12 to 7-8 years.
Key facts
- Anthropic launched drug discovery for neglected diseases.
- Novartis CEO: AI could cut development from 12 to 7-8 years.
- Success rate could double from 8% to 16%.
- UCSF researcher used Claude Science to find missed contamination.
- Claude analyzed 100 rare diseases in under an hour.
Anthropic is launching its own drug development programs for neglected diseases that the traditional pharmaceutical industry considers unprofitable. The company plans to research treatments for diseases that traditional pharma and biotech firms consider unprofitable, focusing on early, preclinical-stage drug development. Anthropic says the move aligns with its nonprofit mission and will help it build better AI models and tools for the broader industry through firsthand experience. The announcement (1:08:34) came during an event for the company's new science AI tool "Claude Science."
The event also featured early examples of how AI could speed up medical research. A researcher at UCSF used Claude Science to spot a viral contamination in minutes that his team had missed for an entire year, according to Anthropic. The company also says Claude analyzed 100 rare genetic diseases in under an hour and flagged 32 candidates for computational screening.
Small gains, massive impact
Novartis CEO Vas Narasimhan said that getting a finished drug candidate from development to approval currently takes about twelve years. He broke the delays into three categories: information latency, operational latency, and biological latency. New tools and models could sharply cut the first two categories, which account for roughly 40 percent of total development time. Biological latency, the time needed for animal testing, cell models, and human clinical trials, won't shrink much. That could bring development timelines down to seven or eight years.
Narasimhan also sees room to double success rates from 8 to 16 percent. Better safety predictions and optimized molecular properties could help, though the effect of improved patient selection remains unclear. The biggest challenge is still figuring out whether a drug target is biologically the right one for a given disease. According to Narasimhan, even these seemingly modest gains would be huge when scaled across major pharma. Together, the big companies spend $150 to $200 billion a year on R&D and have produced only 800 to 1,000 drugs in 120 years.
AI across healthcare
Other AI companies are also pushing into medicine. DeepMind CEO Demis Hassabis co-founded Isomorphic Labs with Alphabet to apply AI directly to drug discovery. Google DeepMind's protein structure prediction tool AlphaFold remains one of the most cited AI breakthroughs in biology. OpenAI has also entered the space with initiatives like ChatGPT Health, though neither has announced an in-house drug discovery program as Anthropic has.
The structural difference matters: Anthropic is not just selling tools to pharma—it's becoming a drug developer itself, at least at the preclinical stage. That creates a potential conflict of interest for any future tool sales to pharma partners, but it also gives Anthropic direct data on where its models fail in wet-lab reality. According to The Decoder
Key Takeaways
- Anthropic launched drug discovery for neglected diseases.
- Novartis CEO says AI could cut development from 12 to 7-8 years and double success rates.
What to watch
Watch for Anthropic's first preclinical candidate announcement or partnership with a contract research organization. Also monitor whether Novartis or other pharma companies publicly adopt Claude Science for their own pipelines, which would validate the platform beyond Anthropic's internal use.
Source: the-decoder.com
