In spring 2025, Anthropic launched its AI for Science program, an initiative aimed at accelerating scientific research through API access. Since then, the program has supported researchers on high-impact projects spanning drug repurposing to quantum simulation. Anthropic found that projects tend to be more productive when multiple grantees work on related questions and share insights, so the company is now introducing thematic calls within the broader program.
The latest call focuses specifically on rare genetic diseases. Accepted applicants will receive up to $50,000 in Claude API credits over six months, with the aim of building a community of researchers exploring how AI can transform rare disease understanding. The program features two tracks: one for scientists conducting basic research, and another for early-stage biotechs working to accelerate clinical development for rare diseases.
Rare disease research is a field where fundamental scientific knowledge remains limited. In aggregate, rare diseases are among the most prevalent conditions globally-an estimated 400 million people live with one of more than 7,000 rare diseases.^1 However, these conditions are distributed across small populations, making it difficult for clinicians to build patient registries, identify promising therapeutic targets, and design clinical trials. Rare diseases are also typically studied in isolation based on their unique features (such as specific genetic variations or symptom combinations), which makes it nearly impossible to identify mechanisms shared across diseases. Additionally, rare diseases face the same challenge as all drug development: the lengthy timeline required to move promising candidates into patient trials.
Anthropic believes AI can address these and related challenges. AI enables accurate modeling of rare genetic diseases and pattern detection across them. It also helps researchers synthesize findings from large bodies of literature, extract information from limited datasets, and establish shared terminology-all of which helps researchers make better use of existing information even as efforts continue to generate more data and tackle access and geographic barriers.
Track One: Expanding Basic Science Partnerships
The first track of Anthropic's rare disease research grants program aims to foster collaboration between clinical researchers, patient organizations, and data scientists to accelerate progress in basic science and the discovery of mechanisms underlying rare diseases.
An early partner in this effort is the Monarch Initiative, an international consortium focused on improving diagnosis and mechanism discovery for rare disease patients. Monarch develops standards and resources including the Mondo Disease Ontology, a computational framework and coding system that reconciles disease definitions from OMIM, Orphanet, ICD, and dozens of other sources, as well as the Monarch Knowledge Graph, which integrates genotype-phenotype data across species to support diagnostics and mechanism discovery.
Recently, Monarch contributors have been assembling data and knowledge into a new agent-friendly mechanistic disease classification library called DisMech, where Claude can process case reports, variant databases, registry schemas, raw public data, and more, identifying mechanistic similarities between diseases at unprecedented pace and scale. Monarch is inviting AI for Science grantees to use and contribute to its resources, such as Mondo and DisMech, to uncover new mechanistic hypotheses that support treatment development.
Monarch's work on improving the interoperability of rare disease data is an area where Claude can already have significant impact. However, more work is needed to gather better and more data, improve diagnostic infrastructure, promote patient-led approaches across the rare disease ecosystem, and make information accessible to agentic science. Anthropic plans to continue partnering with Monarch and others to tackle aspects of this problem where AI is less obviously applicable, and will share findings along the way.
Track Two: Expanding Biotech Partnerships
The second track supports biotechnologists and early-stage biotechs working to accelerate drug development for rare diseases. Currently, it takes one to two years to move from a confirmed genetic diagnosis to an available treatment, with much of that time spent waiting for certified manufacturing slots, running safety studies sequentially rather than in parallel, and manually assembling thousands of pages of chemistry and regulatory documentation required for in-patient testing.
Anthropic believes it is possible to radically compress phases of this process with Claude-particularly by streamlining documentation (such as drafting and reviewing regulatory dossiers), speeding up therapeutic strategy selection (such as analyzing whether a target is druggable across modalities like small molecules, antibodies, and genetic medicines), and identifying shared mechanisms across individual genetic therapies that could allow approval under a single "basket trial" rather than requiring a separate IND for each patient.
Although many aspects of drug development are difficult to accelerate due to manufacturing constraints or safety testing requirements, Anthropic believes significant improvements are possible. By providing API credits and Claude Science access to biotechnologists and startups in this space, the company hopes to encourage the experimentation needed to identify such solutions.
Anthropic also hopes grantees will build on and replicate the work of existing partners in rare disease therapeutics. For example, Every Cure, an existing AI for Science grantee, uses Claude to identify drug repurposing opportunities across millions of candidates; the Centre for Population Genomics, a collaboration between the Garvan Institute and the Murdoch Children's Research Institute, is building a Claude-based system that drafts variant classifications for expert review-one of the biggest bottlenecks in diagnosing rare genetic conditions; and the Violet Research Institute, a small nonprofit researching ultra-rare genetic diseases (defined as extremely rare genetic disorders affecting fewer than 1 in 50,000 births), uses Claude to navigate FDA guidelines, run bioinformatics pipelines, analyze experimental data, draft regulatory filings, and more.
How to Apply
To apply to either track of Anthropic's AI for Science rare disease research program, interested researchers should fill out the application. Applications are being accepted through August 2, 2026 at 11:59 PM PST. Accepted applicants can use credits to access Claude Opus or other generally available models approved for use in biology. Projects that may run up against Anthropic's bio classifiers may be eligible for exemptions.
Examples of track one projects include:
- Proposing and ranking mechanistic links between distinct rare diseases that share a gene or pathway, suggesting candidate disease relationships with evidence an expert can validate in Monarch's DisMech.
- Curating and summarizing patient organization data to conduct or improve existing natural history studies.
- Building evaluations that measure how well models handle rare disease tasks-such as revealing candidate mechanisms for variants of unknown significance, phenotype-to-disease matching, and mechanism prediction-including an honest accounting of where they fail.
Outputs from track one will be made publicly available at Monarchinitiative.org. The program will be augmented by additional community-building efforts, such as future rare disease hackathons. Those interested can stay updated with the Monarch Initiative at monarchinitiative.org/community/get-involved.
Examples of track two projects include:
- Justifying starting doses from sparse data by synthesizing PK/PD modeling, allometric scaling, and precedent from related modalities to build first-in-human dose rationales for bespoke therapies where traditional dose-ranging studies are impossible.
- Mining natural history data and case reports to identify measurable biomarkers and functional endpoints sensitive enough to show a response within the timeframe an N-of-1 or ultra-rare program can afford.
- Drafting, cross-checking, and precedent-mining regulatory documentation (IND sections, investigator brochures, CMC modules), compressing months of dossier assembly into days of expert review.
This rare disease grant program is directly connected to Anthropic's mission and work in beneficial deployments, aiming to extend AI benefits to areas that might not emerge naturally through market forces. However, Anthropic acknowledges that rare disease is too large a problem for any single organization or approach. The company also wants to be transparent about AI's limitations in this area. While Claude may help shorten therapeutic development timelines and curate biological data more efficiently than human teams alone, it cannot help where data is too sparse or poorly organized for agents to work with. It may also struggle with aspects of the "diagnostic odyssey" related to insurance authorization or access to diagnostic facilities and infrastructure. Anthropic hopes this program will be complemented by efforts from other organizations and research institutions to generate more high-quality, longitudinal data, as well as initiatives encouraging robust public-private partnerships.
^1 Other sources estimate the number of rare diseases as high as 10,000. There is also no agreed-upon definition of what constitutes a rare disease, despite the frequently cited claim that as many as 1 in 10 people in the US have one. Various terminologies (Orphanet, OMIM, GARD, ICD, the NCI Thesaurus, and dozens more) each define "disease" differently; some exclude chromosomal disorders (such as Pallister-Killian syndrome); some ignore diseases with environmental causes (such as congenital Zika syndrome); and some require a single anatomical system for classification, overlooking many multi-system rare diseases (such as Fanconi anemia, with its combination of bone marrow failure, congenital malformations, and cancer risk).