Anthropic has introduced a new phase of its AI for Science initiative with a dedicated grant programme to improve research into rare genetic diseases. The company will offer selected researchers and early-stage biotechnology firms up to $50,000 (roughly Rs 43 lakh) in Claude API credits to explore how AI can improve disease discovery, diagnosis and drug development.
Anthropic has divided the programme into two categories. The first focuses on researchers studying the biology and underlying mechanisms of rare diseases, while the second is designed for biotech companies to accelerate clinical development and bring treatments to patients faster.
The company said that it wants a collaborative research community where participants can exchange ideas and work on similar scientific challenges. As per the brand, this will help in uncovering patterns across thousands of rare diseases that are often studied in isolation.
To support the research ecosystem, Anthropic is also collaborating with Monarch Initiative, an international consortium that develops tools and datasets for rare disease diagnosis and research. Scientists selected under the programme will be encouraged to use resources such as the Monarch Knowledge Graph and DisMech, a new AI-friendly disease classification framework designed to identify shared biological mechanisms across disorders.
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The second track targets the biotech companies developing therapies for rare diseases. Anthropic believes Claude can reduce the time spent on several stages of drug development by helping researchers analyse scientific literature, identify potential therapeutic targets and prepare regulatory documentation.
The company said AI could also support clinical trial planning, dose selection, biomarker identification and the drafting of investigational new drug (IND) applications.
Anthropic said selected applicants will receive access to Claude Opus and other approved AI models for biology-related research. The company expects participants to contribute projects ranging from disease mechanism discovery and variant analysis to improving regulatory workflows and clinical research.