Anthropic's Claude in Life Sciences: Accelerating Biotech and Healthcare R&D

Anthropic launched "Claude for Life Sciences" in October 2025, introducing new AI capabilities tailored to biotechnology and pharmaceutical research.

Overview: AI's Growing Role in Life Science Research

Anthropic – the company behind the Claude AI assistant – is making a concerted push into the life sciences as of late 2025. Increasing the rate of scientific progress is central to Anthropic's mission, and the Claude platform is being adapted to support researchers across drug discovery, genomics, and healthcare domains.

Until recently, scientists mostly used Claude for individual tasks (coding analyses, summarizing papers, etc.), but the goal now is for Claude to assist end-to-end – from early research hypotheses through clinical development and regulatory documentation. This strategic focus comes amid industry-wide moves to apply advanced AI to biotech: Google DeepMind, for example, released AlphaFold for protein structures and an "AI co-scientist" lab assistant system, and OpenAI has formed a science team and launched new models aimed at scientific reasoning.

Anthropic's approach with Claude emphasizes integrating AI into scientists' existing workflows rather than developing standalone scientific models.

Claude for Life Sciences: New Capabilities in 2025

To better serve biotech and pharma users, Anthropic unveiled Claude for Life Sciences with a suite of enhancements and tools in October 2025. At its core is an upgraded model (Claude Sonnet 4.5) which has significantly improved performance on scientific tasks.

For example, Claude scored 0.83 on the Protocol QA benchmark (lab protocol comprehension) – slightly above the human expert baseline of 0.79 and a notable jump from the previous Claude 4's 0.74. It also showed strong gains on BixBench, a set of bioinformatics challenges. These improvements suggest Claude can understand laboratory procedures and biomedical data more reliably than before, even matching or exceeding human-level accuracy in certain evaluations.

New Connectors and Tools

Alongside model tuning, Anthropic rolled out new "connectors" and tools that plug Claude into the software platforms scientists use daily. These connectors allow Claude to directly access data and functions in external applications. Key connectors added as part of the Life Sciences launch include:

Benchling – a lab informatics platform used for experiment tracking; the connector lets Claude answer questions about a team's experimental data and link back to electronic lab notebooks and records. This means researchers can query their R&D databases in natural language and get source-linked answers and summaries in minutes. The integration is enabled via Anthropic's Model Context Protocol (MCP), which maintains one-click traceability to underlying data and preserves existing data permissions for compliance.

BioRender – a tool with scientific illustration libraries; Claude can retrieve high-quality scientific figures and diagrams to include in reports or presentations.

PubMed – direct access to millions of biomedical research papers and clinical studies, allowing Claude to search and cite up-to-date literature. In practice, a scientist could ask Claude for a summary of recent papers on a gene or drug target, and Claude can pull relevant PubMed results with citations.

Wiley's Scholar – provides peer-reviewed journal content inside Claude's context, giving researchers a way to tap authoritative publications when formulating hypotheses.

Synapse.org – enables collaborative data sharing and analysis; Claude can interface with datasets in Synapse projects, facilitating team-based research in either public or private data spaces.

10x Genomics – connects to 10x Genomics' single-cell and spatial genomics tools, so scientists can perform complex genomics analyses through plain English prompts. Traditionally, using 10x's pipeline required writing code and managing high-performance computing, but now tasks like read alignment, clustering cells, and generating gene expression matrices can be done conversationally through Claude. This lowers the barrier for biologists who may not be computational experts, letting them focus on interpreting results rather than wrangling code.

These scientific connectors build on Claude's existing integrations (e.g. Google Workspace, Databricks, Snowflake) and highlight Anthropic's emphasis on workflow integration. Instead of treating Claude as a separate black-box, it's embedded in the tools and data flows researchers already use.

Agent Skills: Executable Scientific Workflows

Another enhancement is the introduction of Agent Skills – essentially packaged instruction sets, code, or protocols that Claude can execute to perform specific scientific workflows reliably. For instance, Anthropic released a skill for single-cell RNA sequencing quality control ("single-cell-rnaqc"), which follows best-practice pipelines (via the scVerse toolkit) to filter and QC single-cell gene expression data.

Researchers can thus ask Claude to clean up and analyze a raw single-cell dataset, and Claude will internally use this skill to produce reproducible results (e.g. filtering low-quality cells, normalizing data) just as a bioinformatician would. Scientists can also develop their own custom skills to teach Claude new lab procedures or analyses, making the platform extensible as methods evolve.

Example of Claude using an "Agent Skill" to perform quality control on single-cell RNA sequencing data. Researchers can invoke such skills to have Claude execute bioinformatics workflows step-by-step, outputting analyses and visualizations without manual coding.

To help life science teams get started quickly, Anthropic has also created a library of curated prompts tuned for common tasks (literature review, experimental design, etc.) and is providing dedicated support staff with scientific backgrounds to assist in deployment. This indicates a push toward enterprise adoption – recognizing that large pharma and biotech companies often need onboarding, compliance checks, and custom integration when bringing AI into research.

Applications in Biotech, Pharma, and Healthcare

With these new features, Claude is being positioned as a versatile assistant across many life science use cases. Some key applications include:

Literature Review and Hypothesis Generation

Claude can ingest and summarize vast amounts of biomedical literature, then suggest testable hypotheses or research ideas based on the findings. For example, a scientist could ask Claude to review recent papers on a disease pathway and propose novel angles for drug targeting. Claude can provide summaries with citations and even brainstorm potential experiments, essentially acting as a knowledgeable research aide.

Anthropic reports that Claude's advanced reasoning allows scientists to "sit down with [it] to brainstorm ideas and generate hypotheses," much like software engineers use AI coding assistants for ideation.

Laboratory Protocols and Experiment Design

Using the Benchling connector, Claude can draft experimental protocols, standard operating procedures (SOPs), and even informed consent documents for clinical studies. Researchers can describe an experiment in natural language, and Claude will produce a structured protocol or method, pulling in relevant details (reagents, concentrations, procedural steps) and linking to past experiments in Benchling as references.

This accelerates the preparation of lab documents and ensures consistency with prior in-house experiments. Notably, pharmaceutical companies have already leveraged Claude in this area – Novo Nordisk reportedly cut the time for assembling a clinical study document from over 10 weeks to just 10 minutes using Claude, a dramatic efficiency gain.

Similarly, Sanofi has integrated Claude into its internal knowledge systems, with most of its employees using Claude daily for a variety of tasks. Such anecdotes underscore how AI can streamline traditionally time-consuming documentation processes in pharma.

Bioinformatics and Genomic Analysis

Claude (especially with the Claude Code capability) can assist in analyzing complex biological datasets – from genomic sequences to clinical trial data. Researchers can ask Claude to run a data analysis pipeline or perform statistical tests, and it will generate code, execute it, and explain the results in plain language.

For instance, with the 10x Genomics connector and the single-cell analysis skill, a biologist could prompt Claude to "find cell clusters with similar expression profiles in my dataset" and get results without writing R or Python code. 10x Genomics' CEO noted that tasks like read alignment and cell clustering can now be done "through plain English conversation" with Claude, lowering the technical barrier for life scientists and speeding up analysis cycles.

Companies like Schrödinger (which develops computational drug discovery software) have even used Claude Code to accelerate their research coding by up to 10× in some projects – Claude can quickly prototype bioinformatics code, enabling scientists to iterate faster.

Clinical and Regulatory Compliance

Claude is also applied in drafting and reviewing regulatory documents, such as clinical trial reports, FDA submission sections, or pharmacovigilance summaries. Its ability to generate structured text with references is valuable for ensuring compliance and thoroughness.

Anthropic has tailored Claude to reduce AI "hallucinations" (fabrications) in these high-stakes contexts and to provide audit trails for any content it produces, which is crucial for regulatory review. Additionally, Claude's safety guardrails are configured to block inadvisable requests (for example, it will refuse instructions to design a dangerous pathogen or illicit substance), aligning with the need for biosafety in life science applications.

Early adopters in healthcare analytics have noted the importance of these features: the CEO of Komodo Health, a health data company, emphasized that their partnership with Anthropic is delivering "transparent, auditable solutions" where AI outputs can be trusted in regulated environments.

General Productivity in Pharma

Beyond research per se, large pharma companies are finding myriad uses for Claude across their operations. Sanofi's Chief Digital Officer described Claude as "integral" to the daily work of employees, boosting efficiency across the value chain from R&D to commercial teams.

Another pharma executive noted that with Claude, they are "not just automating tasks, [they're] transforming how medicines get from discovery to patients", suggesting that AI is being woven into project management and knowledge sharing in drug development. In practice, this might include using Claude as an internal chatbot that can instantly retrieve clinical data or market research when asked, draft emails and reports, or help plan experiments – all of which frees human experts to focus on higher-level decision making.

Recent Developments and Partnerships

Anthropic's life sciences push has been accompanied by a series of partnerships with industry and academia, many announced in October 2025. To facilitate adoption, Anthropic is working with consulting firms (like Deloitte, Accenture, KPMG, PwC, and specialized AI integrators) that can help biotech companies implement Claude safely and effectively.

The company also launched an "AI for Science" program offering free Claude API credits to academics and nonprofits working on high-impact scientific projects – an initiative similar to OpenAI's and others' efforts to support research use of AI. This has attracted collaborations with leading research institutes; for example, the Broad Institute is exploring how Claude-based agents on the Terra platform can enable new scales of genomic analysis, and Stanford University researchers are leveraging Claude to turn static research papers into interactive AI "agents" that can answer questions about the work (the Paper2Agent project).

Industry Integrations

Several biomedical technology companies have partnered with Anthropic to integrate Claude's capabilities directly into their products. We saw the Benchling partnership earlier, embedding Claude as an intelligent layer in a widely used R&D data platform.

Likewise, 10x Genomics' collaboration with Anthropic (announced Oct 20, 2025) exemplifies this trend – by connecting 10x's Cloud Analysis pipelines with Claude via the Model Context Protocol, researchers can interrogate single-cell datasets conversationally. Instead of manually coding each analysis step, a scientist could ask, "Claude, find genes that differentiate these two cell clusters and generate a plot," and Claude will utilize the 10x tools behind the scenes to fulfill the request, then return the result in an easy-to-understand format.

This kind of integration demonstrates how AI assistants can bridge the gap between bench scientists and complex bioinformatics software.

Availability and Accessibility

Anthropic has also made Claude for Life Sciences accessible through cloud marketplaces – it's available via Claude.com and the AWS Marketplace now, with Google Cloud support on the way. While specific pricing for the life science offering hasn't been disclosed, the presence of free credit programs suggests Anthropic is prioritizing wider adoption and feedback over immediate monetization.

The company is likely aiming to establish Claude as a standard platform in pharma and biotech, which could yield significant enterprise revenue as those industries embrace AI. (Analysts have noted that life sciences could become a lucrative vertical for AI providers; Anthropic's own projections see substantial revenue growth tied to such industry-focused solutions.)

Claude vs. OpenAI: How Does It Compare?

Claude's expansion into life sciences inevitably invites comparison to OpenAI, which is the other major player in advanced language models. Both Anthropic and OpenAI are racing to empower scientific research with AI, but their strategies show some differences.

OpenAI's Approach: General Power and Medical Expertise

OpenAI's approach has been to develop extremely powerful general models (GPT-4, and recently GPT-5) and then highlight their performance in scientific domains. In August 2025, OpenAI launched GPT-5, touting it as "a legitimate Ph.D.-level expert" especially in healthcare.

OpenAI reported that GPT-5 is their most reliable model on medical and clinical tasks, outperforming previous models on a suite of real-world health questions. In fact, health and medicine are seen as top use cases for ChatGPT and GPT-5 – the model scored highest on OpenAI's new HealthBench benchmark (designed with input from 250 physicians) and was described by CEO Sam Altman as "the best model ever for health".

OpenAI also noted that GPT-5 can be used in life sciences research; for example, biotech company Amgen was an early tester and used GPT-5 for drug design, finding it excelled at "deep reasoning with complex data" like scientific literature and experimental results. These claims suggest that OpenAI's latest model has attained a strong grasp of biomedical knowledge and reasoning, making it a direct rival to Claude in tasks like literature analysis, data interpretation, and hypothesis generation.

Anthropic's Strategy: Domain-Specific Augmentation

Where Anthropic's strategy differs is in domain-specific augmentation: rather than solely relying on a monolithic model's prowess, Anthropic is equipping Claude with tools, skills, and safety features tailored to life sciences. For instance, Claude's connectors into lab databases and its ability to produce traceable, audit-ready outputs address practical needs in pharma R&D (like compliance and data governance).

Eric Kauderer-Abrams, Anthropic's head of life sciences, explained that they focus on "amplifying individual scientists' capabilities" by giving biologists an AI assistant that works within their workflow, as opposed to trying to have the AI independently discover drugs itself. This is somewhat in contrast to initiatives like DeepMind's Isomorphic Labs, which aims to have AI drive drug discovery directly.

Anthropic's view is that a tool like Claude should partner with scientists (e.g. helping write code, summarize data, check protocols) rather than operate as an autonomous drug-hunter. In practice, this means Claude is optimized to reduce errors (hallucinations) and provide explanations, so that human experts can trust and build on its outputs.

OpenAI's Scientific AI Initiatives

OpenAI, meanwhile, has been investing in scientific AI from another angle as well – creating specialized models and teams for science. They collaborated with a biotech startup on a custom model called GPT-4B Micro (a scaled-down GPT-4 specialized for protein engineering) which successfully designed improved protein variants for stem cell reprogramming (achieving a 50× increase in expression of certain biomarkers in lab tests).

OpenAI also established an "OpenAI for Science" division in early 2025, hiring top scientists (like a renowned black-hole physicist) after demonstrating that early versions of GPT-5 could solve complex theoretical problems in minutes. These moves indicate OpenAI's models are becoming sophisticated enough to contribute to scientific discoveries directly – for example, GPT-5 was reported to rediscover a new astrophysics symmetry and assist mathematicians.

While those examples are outside biomedicine, they underscore OpenAI's ambition to position GPT-5 as a general "AI researcher." OpenAI's models have also shown prowess in biomedical competitions and benchmarks, and the company even launched HealthBench to evaluate AI on healthcare tasks.

The Bottom Line on Competition

In summary, Anthropic's Claude and OpenAI's GPT series are converging on similar goals in life sciences, but via complementary paths. Claude for Life Sciences offers a more bespoke toolkit for industry practitioners – with integrations into lab platforms, ready-made skills for genomics, and an emphasis on safe, explainable outputs for regulated use.

On the other hand, OpenAI provides raw model strength and broad knowledge, exemplified by GPT-5's high performance on medical reasoning and its use by companies like Amgen and Moderna for drug R&D.

It's worth noting that as of October 2025, no AI system (Claude or GPT-5 included) has independently discovered an approved drug without human scientists – many AI-suggested compounds still fail in trials. However, the productivity gains and acceleration of research are tangible. Novo Nordisk's "10 weeks to 10 minutes" story and Sanofi's company-wide AI adoption highlight how quickly these models can handle research paperwork and queries, while OpenAI's claims of GPT-5 being a PhD-level expert suggest scientists can lean on AI for insight across any biomedical field.

Outlook

As of late 2025, Claude's role in life sciences is rapidly expanding, supported by Anthropic's active development and collaboration with the biotech ecosystem. Researchers and physicians are beginning to use Claude as a trusted AI colleague – one that can read the entire corpus of biomedical knowledge, execute data analyses, and draft complex documents in a fraction of the time.

The latest announcements (connectors to Benchling, PubMed, etc., and specialized skills like single-cell analysis) show that Anthropic is serious about tailoring its AI to the needs of pharma and biotech professionals. This comes at a time of intense competition: every major AI lab (OpenAI, Google's DeepMind, Meta, and others) is investing in scientific AI, from drug discovery to healthcare applications.

For the biotech and healthcare audience, the takeaway is that large language models like Claude are becoming practical tools in research and development, not just chatbots for generic Q&A. They are now assisting in real scientific workflows – writing code, managing lab knowledge bases, analyzing genetic data, and ensuring compliance.

Anthropic's Claude, with its new life science-focused features, is positioned as a neutral, reliable AI assistant that can help scientists compress research timelines and augment human expertise. As the technology continues to mature (and as models are further fine-tuned to biomedical content), we can expect even deeper integration of AI in labs and clinics.

Both Claude and its competitors will likely drive forward the next wave of breakthroughs by handling the drudgery and complexity of data, thereby allowing human researchers to focus on creativity and critical thinking – ultimately speeding up the journey from scientific hypothesis to life-saving therapies.