Industry Guide: Pharma
How to Use Claude in Pharma: A Guide for Regulatory, Clinical, and Medical Teams
Faster documents, same evidence standard.
This guide is for medical writers, regulatory affairs, clinical operations, pharmacovigilance, and medical affairs teams at pharmaceutical companies who want to put Anthropic's Claude to work on the documents and data that move a medicine through development. It covers Anthropic's life sciences releases and what named pharma companies said in Anthropic's own announcements and solutions pages.
Knowing how to use Claude in pharma means focusing it on document-heavy work with a strict evidence trail: drafting clinical study report and regulatory sections from source tables, preparing clinical trial protocols and amendments, structuring pharmacovigilance case intake, answering medical information requests from approved content, and summarizing literature for medical affairs. Claude drafts and checks consistency. Qualified people own every medical, safety, and regulatory judgment, and all regulated output passes through your quality system.
Published
Key Takeaways
- The strongest pharma uses are medical and regulatory writing, protocol drafting, pharmacovigilance intake, medical information, and literature summaries.
- Anthropic's life sciences releases include connectors to Medidata, ClinicalTrials.gov, PubMed, and ChEMBL, and a sample skill for clinical trial protocol drafts.
- Anthropic's pages quote Sanofi, Genmab, AbbVie, Regeneron, and Bristol Myers Squibb on how they use Claude.
- Every AI-drafted regulated document must trace to controlled source data and pass normal review.
- Patient data, safety data, and unpublished results require approved deployments and privacy controls.
Copy and Paste
Prompts You Can Use Today
CSR results section from tables
You are a senior medical writer. Draft the efficacy results section of a clinical study report using only the statistical output tables pasted below. Report every number exactly as it appears, reference the table number after each statement, describe results neutrally without clinical interpretation beyond what the statistical analysis plan excerpt supports, and list any table that seems inconsistent with another. Tables and SAP excerpt: [paste].
Table references after each statement are what make QC of an AI draft fast.
Protocol amendment impact summary
Compare the current protocol and the proposed amendment below. List every change by section, classify each as substantial or non-substantial with a one-line reason, identify downstream documents that must also change, such as the informed consent form, CRF, and monitoring plan, and draft the summary of changes table. Flag any change that could affect participant safety for medical review. Documents: [paste].
Final classification of substantial changes is a regulatory decision, not the model's.
Pharmacovigilance case intake
Extract the four minimum criteria for a valid individual case safety report from the source text below: identifiable patient, identifiable reporter, suspect product, and adverse event. Then list the events as described, the dates exactly as given, seriousness information as stated, and any missing information to request in follow-up. Do not assess causality or seriousness yourself. Source: [paste].
Causality and seriousness assessment stay with qualified safety staff.
Medical information response
Draft a response to the healthcare professional inquiry below using only the approved standard response documents and label text pasted here. Answer the question directly, cite the section of the approved content for each statement, do not include any off-label claim beyond what the approved content already addresses, and flag if the question cannot be fully answered from the approved sources. Inquiry and approved content: [paste].
Restricting the draft to approved content is what keeps medical information compliant.
Literature summary for medical affairs
Summarize the attached publications on our product's therapeutic area for a medical science liaison briefing: study design, population, key efficacy and safety findings with numbers as reported, limitations noted by the authors, and how each relates to current practice. Cite each paper by first author and year. Do not cite anything I did not attach.
Attach the papers or retrieve them through an approved literature connector first.
From Anthropic
What Anthropic offers for Pharma
Claude for Life Sciences
Anthropic's life sciences offering, launched in October 2025, with connectors to Benchling, BioRender, PubMed, Wiley's Scholar Gateway, Synapse.org, and 10x Genomics, and implementation partners including Deloitte, Accenture, KPMG, and PwC.
· Source
Claude for Life Sciences (January 2026 expansion)
An expansion that added connectors to Medidata, ClinicalTrials.gov, ToolUniverse, bioRxiv and medRxiv, Open Targets, ChEMBL, Owkin, and Pathology Explorer, and Agent Skills including a sample for clinical trial protocol draft generation.
· Source
In Practice
How Pharma Teams Use Claude
According to Anthropic's published customer story
Sanofi
In Anthropic's October 2025 life sciences announcement, Sanofi's chief digital officer described Claude, paired with internal knowledge libraries, as integral to the company's AI transformation.
According to Anthropic's published customer story
Genmab
Genmab's global head of data, digital and AI, quoted in Anthropic's October 2025 announcement, said the company sees strong potential in Claude streamlining how it brings drugs to market.
According to Anthropic's published customer story
AbbVie
On Anthropic's life sciences solutions page, AbbVie's vice president of AI strategy describes Claude powering the company's Intelligent Medical Insights work.
According to Anthropic's published customer story
Regeneron
Regeneron's chief AI officer, quoted on Anthropic's life sciences solutions page, describes Claude accelerating literature reviews that once took days.
According to Anthropic's published customer story
Bristol Myers Squibb
Bristol Myers Squibb's chief digital and technology officer, quoted on Anthropic's life sciences solutions page, describes AI as a major opportunity to advance the company's mission for patients.
Illustrative walkthrough
A patient narrative batch for a study report
- A medical writer loads the narrative template, the listings for each participant with a serious adverse event, and the style guide.
- Claude drafts each narrative using only the listings and marks any field it could not find.
- The writer checks dates and doses against the listings and resolves the marked gaps with the data management team.
- A second reviewer performs the standard QC on the full batch.
- The narratives move into the study report through normal document control.
Pharma and Claude: the Published Numbers
| Figure | Context | Source |
|---|---|---|
| roughly 60,000 employees | Daily users of Sanofi's Concierge app, as described on Anthropic's life sciences solutions page | Source |
Core Workflows
Claude Pharma Use Cases From Development to Launch
These are the areas where AI for pharma teams saves the most expert time while keeping the evidence trail intact.
Medical writing
AI medical writing support for clinical study reports, summaries, and narratives drafted from source tables, with every figure referenced back.
Regulatory affairs
AI for regulatory affairs in pharma covers submission sections, responses to agency questions, and change assessments, prepared for regulatory review.
Clinical trial documents
AI in clinical trials starts with protocols, amendments, informed consent forms, and site materials drafted from the synopsis and checked for consistency.
Pharmacovigilance
AI for pharmacovigilance intake extracts validity criteria, events, and dates from source reports, leaving causality to safety physicians.
Medical affairs
Medical information responses from approved content, literature summaries, and briefing materials for field medical teams.
Manufacturing and quality
Deviation and CAPA write-ups, SOP drafts, and batch record summaries, all routed through your quality system.
What Pharma Companies Report
How Pharma Companies Use AI Today
How is AI used in pharmaceutical companies? Anthropic's own pages give named examples. Sanofi's chief digital officer called Claude, paired with internal knowledge libraries, integral to the company's AI transformation, and Anthropic's life sciences page describes Sanofi's Concierge app being used daily across a large share of its workforce. Genmab said it sees potential in Claude streamlining how it brings drugs to market.
On Anthropic's life sciences solutions page, AbbVie describes Claude powering its Intelligent Medical Insights work, Regeneron's chief AI officer describes Claude accelerating literature reviews that once took days, and Bristol Myers Squibb's chief digital and technology officer describes AI as a major opportunity for the company's mission.
Across AI in the pharmaceutical industry, and generative AI in pharma in particular, these examples follow a clear pattern: knowledge access, literature, and writing first, with regulated outputs kept inside existing review and quality processes.
Anthropic's Releases
The Life Sciences Tools Relevant to Pharma
Anthropic's October 2025 life sciences launch connected Claude to Benchling, PubMed, Wiley's Scholar Gateway, Synapse.org, BioRender, and 10x Genomics. Its January 2026 expansion added connectors most relevant to pharma development, including Medidata for clinical trial data, ClinicalTrials.gov, ChEMBL, Open Targets, and bioRxiv and medRxiv, plus a sample Agent Skill for clinical trial protocol draft generation.
For AI in drug discovery, these connectors mainly shorten the path from question to evidence: pulling literature, compound data, and target evidence into one place for a scientist to assess. For development, they bring protocol and trial data into the drafting workflow.
Anthropic has also said its Fable models will continue to block professional biology and drug development queries, with a separate verification program for life sciences professionals. Confirm which models your organization's plan provides before designing workflows around them.
Writing in Practice
AI Medical Writing and Regulatory Drafting Done Well
The pattern that holds up in medical writing is narrow scope and hard references. Give Claude one section, the exact source tables or reports it may use, your template, and your style guide. Ask it to reference the table or report after every statement and to mark anything it cannot find instead of filling the gap. A draft built that way can be checked line by line, which is what QC needs.
Consistency checking is an underrated use. Long submissions repeat the same facts across modules, and small differences in a dose, a date, or a population count cause questions from agencies. Claude can compare two documents and list every place they disagree, which gives reviewers a focused list instead of a full reread.
Keep the division of labor explicit. Claude drafts and cross-checks. Medical writers own clarity and accuracy, medical reviewers own interpretation, and regulatory affairs owns what is submitted and how it is framed. Writing that division into your procedures makes AI assistance easier to defend in an audit.
Choosing Tools
Claude vs ChatGPT for Pharma
The Claude vs ChatGPT for pharma comparison should use your own approved documents: a CSR section already finalized, a medical information response already approved, and a protocol amendment already assessed. Compare accuracy, citation behavior, and how each handles gaps.
In pharma the decision is usually made on validation and governance: which deployment your IT and quality teams approve, how outputs are documented under GxP where applicable, data residency for patient and trial data, and connectors to your clinical and scientific systems.
Is Claude HIPAA compliant for pharma data? HIPAA applies to covered entities and their business associates. Anthropic announced HIPAA-ready offerings for providers and payers in January 2026. Whether your data falls under HIPAA, GDPR, or other rules, and which deployment is approved, is a question for your privacy and legal teams.
Getting Started
A Safe First Month for a Pharma Team
Start with finalized documents
Test prompts on documents that are already approved, and compare the AI draft with the final version.
Load templates and style guides
Put your document templates, style guide, and glossary into a project so drafts match house standards.
Choose one document type
Pick one high-volume document, such as patient narratives or medical information responses, and measure review time.
Define the GxP boundary
Agree with quality which work is exploratory and how AI-assisted regulated work is reviewed and documented.
Limits
Where Qualified People Must Decide
Claude can misstate a number, invent a reference, or drift into interpretation the data does not support. In regulated documents every statement must trace to controlled source data, and every AI-assisted draft goes through the same QC and approval steps as any other.
Causality assessment in pharmacovigilance, benefit-risk judgments, off-label questions, and regulatory strategy require qualified professionals. Claude prepares information for those decisions and does not make them.
Patient-level data, safety reports, and unpublished results are highly sensitive. Use only approved deployments, de-identify where possible, and keep regulated records in validated systems.
Build Reliable AI Habits for Regulated Work
Getting trustworthy drafts from AI is a practiced skill: grounding, referencing, and review. The free Nightschool AI curriculum is hands-on from the first lesson.
Frequently Asked Questions
How is AI used in pharmaceutical companies?
Mainly for knowledge access, literature review, and document drafting: clinical and regulatory writing, protocols, medical information, and safety intake. Anthropic's pages quote Sanofi, Genmab, AbbVie, Regeneron, and Bristol Myers Squibb on their use of Claude. Regulated outputs stay inside existing review and quality processes.
How does AI speed up drug discovery?
Mostly by shortening the path from question to evidence: pulling literature, compound data from sources such as ChEMBL, and target evidence from sources such as Open Targets into one place, and helping scientists write analysis code. The scientific judgment and experiments still determine the pace of a program.
Can AI write clinical trial protocols?
AI can draft protocol sections from a synopsis and prior data, and Anthropic has published a sample skill for protocol drafts. Endpoints, eligibility, dosing, and safety monitoring need medical, statistical, and regulatory sign-off before anything is final.
Is Claude HIPAA compliant for pharma data?
Anthropic announced HIPAA-ready offerings for healthcare providers and payers in January 2026. HIPAA applies to covered entities and business associates, and much pharma data falls under other rules such as GDPR. Your privacy and legal teams should confirm which deployment is approved for which data.
How much time can AI save in medical writing?
It varies with the document type and the quality of source data, so measure it on your own documents. Time savings come from drafting against templates and source tables. QC and review time does not disappear, and it should not.
What are the biggest AI use cases in pharma?
The most common are literature review and knowledge search, medical and regulatory writing, clinical trial document drafting, pharmacovigilance intake, medical information responses, and code for data analysis. Each works best with approved source content and human review.
Can AI help with pharmacovigilance intake?
Yes, for extracting the minimum criteria for a valid case, events, dates, and missing information from source reports. Causality and seriousness assessments remain with qualified safety staff, and case processing follows your validated safety system.
Does AI change GxP obligations?
No. Where work is GxP-relevant, your validation, documentation, data integrity, and review obligations apply regardless of whether AI drafted it. Agree with quality how AI-assisted work is controlled.