Biotech & Pharma

Biotech and pharma move at the speed of documents. AI can process them without the headcount.

CTD submissions reviewed manually against guidance documents. Clinical study reports with hundreds of pages of supporting data that need structured extraction. A scientific team that cannot keep pace with publication volume in their field. IP counsel monitoring patent filings one-by-one.

We build AI systems for biotech and pharma companies that handle the document processing and monitoring layer of regulatory and research operations, built with 21 CFR Part 11 compliance, GxP validation requirements, and HIPAA architecture in scope from the start.

How we work

Tell us about your regulatory or research document workflow.

What we build.

Five specific AI workflows for biotech and pharma operations.

Regulatory submission document review (FDA/EMA)

AI reads CTD sections, module summaries, and supporting study reports: cross-referencing against regulatory guidance to identify gaps, inconsistencies, and missing required elements before submission. Reduces review cycles with the agency.

Clinical trial document processing

Extract structured data from clinical study reports, protocol amendments, adverse event narratives, and site monitoring reports. Feeds into your clinical data management system and reduces data entry burden on CRAs and data managers.

Scientific literature summarization

AI monitors PubMed and preprint servers for publications relevant to your pipeline, summarizing new data by mechanism of action, endpoint, and competitive significance. Your scientific team reads summaries, not abstracts, and digs into the papers that matter.

IP and patent monitoring

Monitor patent filings and publications for claims that overlap with your compound pipeline, manufacturing processes, or platform technology. Generates weekly IP landscape summaries for your patent counsel and business development team.

Compliance Q&A for internal teams

A RAG system trained on your SOPs, regulatory agency guidance documents, and internal compliance policies answers staff questions with source citations. Reduces the load on regulatory affairs staff for questions that are already answered in your document library.

Who we build for.

Biotech companies in IND-enabling or Phase I/II stages with document-intensive regulatory workflows
Pharma companies managing large regulatory submission portfolios
CROs building AI-enabled clinical data processing capabilities
Medical device manufacturers navigating FDA 510(k) or PMA submissions
Life sciences technology companies adding AI to regulatory information management systems

Who this isn't for.

Companies looking for AI to generate regulatory submissions autonomously
AI assists regulatory writers and scientists. It does not replace them. Regulatory submissions require human authorship, expert scientific review, and accountability under 21 CFR. AI accelerates the writing and review process; it does not remove the human from it.
Early preclinical companies without a document library to build from
Regulatory submission review and compliance Q&A require a document library of SOPs, protocols, and prior submissions to be useful. Preclinical-stage companies without that library benefit more from literature monitoring and IP watching than from RAG-based Q&A.
Research projects without a defined regulatory pathway
We build AI for development-stage workflows with regulatory endpoints. Pure discovery research projects without a defined regulatory pathway are better served by bioinformatics tools than by regulatory document processing AI.

Frequently asked questions.

How do you address 21 CFR Part 11 compliance for electronic records?: 21 CFR Part 11 requires that electronic records used in FDA-regulated activities meet specific requirements for audit trails, access controls, and system validation. We design AI systems with compliant audit logging, role-based access controls, and documented change management. We provide a system validation package (IQ/OQ/PQ documentation templates) that your validation team can execute before production use.
What audit trail requirements apply to AI-assisted regulatory review?: Every AI-generated output that enters a regulated workflow should have an audit trail: who requested it, when, what input was provided, what the AI returned, and who reviewed and accepted or modified the output. We build this audit trail into every system that produces output used in regulatory submissions or quality records. The audit trail is exportable in formats your regulatory team can archive.
How do you handle GxP validation requirements?: GxP-applicable AI systems require validation before production use in regulated workflows. We provide a validation package including User Requirements Specification, Functional Specification, and test scripts appropriate for the system's GxP classification. Your validation team executes the testing and owns the validation record. We support re-validation when the system changes.
How do you handle HIPAA for patient data in clinical trial records?: Clinical trial records containing patient-identifiable information are subject to HIPAA. We sign a BAA before any patient data touches our systems. For AI systems processing clinical narratives, we apply de-identification or pseudonymization before data reaches the model where possible, and use zero-data-retention API agreements where patient data must appear in model context.

Ready to accelerate your regulatory or research document workflow?

Tell us which document processing or review workflow creates the most bottleneck in your pipeline. We will reply within one business day with a rough scope and price range.

Biotech and pharma move at the speed of documents. AI can process them without the headcount.

What we build.

Five specific AI workflows for biotech and pharma operations.

Regulatory submission document review (FDA/EMA)

Clinical trial document processing

Scientific literature summarization

IP and patent monitoring

Compliance Q&A for internal teams

Who we build for.

Biotech companies in IND-enabling or Phase I/II stages with document-intensive regulatory workflows

Pharma companies managing large regulatory submission portfolios

CROs building AI-enabled clinical data processing capabilities

Medical device manufacturers navigating FDA 510(k) or PMA submissions

Life sciences technology companies adding AI to regulatory information management systems

Who this isn't for.

Companies looking for AI to generate regulatory submissions autonomously

AI assists regulatory writers and scientists. It does not replace them. Regulatory submissions require human authorship, expert scientific review, and accountability under 21 CFR. AI accelerates the writing and review process; it does not remove the human from it.

Early preclinical companies without a document library to build from

Regulatory submission review and compliance Q&A require a document library of SOPs, protocols, and prior submissions to be useful. Preclinical-stage companies without that library benefit more from literature monitoring and IP watching than from RAG-based Q&A.

Research projects without a defined regulatory pathway

We build AI for development-stage workflows with regulatory endpoints. Pure discovery research projects without a defined regulatory pathway are better served by bioinformatics tools than by regulatory document processing AI.

Frequently asked questions.

How do you address 21 CFR Part 11 compliance for electronic records?

21 CFR Part 11 requires that electronic records used in FDA-regulated activities meet specific requirements for audit trails, access controls, and system validation. We design AI systems with compliant audit logging, role-based access controls, and documented change management. We provide a system validation package (IQ/OQ/PQ documentation templates) that your validation team can execute before production use.

What audit trail requirements apply to AI-assisted regulatory review?

Every AI-generated output that enters a regulated workflow should have an audit trail: who requested it, when, what input was provided, what the AI returned, and who reviewed and accepted or modified the output. We build this audit trail into every system that produces output used in regulatory submissions or quality records. The audit trail is exportable in formats your regulatory team can archive.

How do you handle GxP validation requirements?

GxP-applicable AI systems require validation before production use in regulated workflows. We provide a validation package including User Requirements Specification, Functional Specification, and test scripts appropriate for the system's GxP classification. Your validation team executes the testing and owns the validation record. We support re-validation when the system changes.

How do you handle HIPAA for patient data in clinical trial records?

Clinical trial records containing patient-identifiable information are subject to HIPAA. We sign a BAA before any patient data touches our systems. For AI systems processing clinical narratives, we apply de-identification or pseudonymization before data reaches the model where possible, and use zero-data-retention API agreements where patient data must appear in model context.

Ready to accelerate your regulatory or research document workflow?

Tell us which document processing or review workflow creates the most bottleneck in your pipeline. We will reply within one business day with a rough scope and price range.