Loading…
Hire a RAG Developer · Philadelphia, PA
This is for regulatory affairs managers at GSK, AstraZeneca (Wilmington, 25 miles away), Incyte, or Merck's Blue Bell site. A drug regulatory dossier runs 50,000-200,000 pages: clinical study reports, preclinical data, labeling history, CMC documentation. During FDA review, your team must locate specific data points across that corpus to respond to information requests within 2-week deadlines.
The current process at most Philadelphia-area regulatory teams is manual search through the eCTD submission. The right data point is in the dossier. Finding it in hours rather than days determines whether you meet the FDA deadline.
A RAG system built for regulatory document libraries returns answers with precise citations: CTD section, document name, version, page number, scoped as a fixed-price engagement.
Tell us about your regulatory document library.
Philadelphia and the surrounding Philadelphia metro area houses one of the densest concentrations of pharmaceutical regulatory operations in North America. GSK's US headquarters is in the Navy Yard. AstraZeneca is 25 miles south in Wilmington. Incyte is in Wilmington. Merck's Blue Bell site is 20 miles northwest. Penn Medicine and Jefferson Health anchor the academic medical and clinical research community.
These organizations share a common document challenge. Large regulatory submissions accumulate over years of development programs. By the time a new drug application reaches the FDA review phase, the dossier contains thousands of documents created by different teams, at different sites, over a 10-15 year development timeline.
This is not the right solution if your regulatory team is small (under 5 people) and works on a single active submission at a time. Manual search is manageable at that scale. The ROI becomes clear when a team is managing multiple active submissions simultaneously or when FDA information requests require pulling data across multiple dossiers.
Independence Blue Cross and other large Philadelphia health insurers face a structurally similar problem with coverage policy libraries. The page-count scale is smaller, but the citation precision requirements are the same.
FDA information requests during NDA or BLA review require locating specific data points within the full dossier: a particular patient subgroup analysis, a specific batch record, a particular stability data point. The deadline is not negotiable. A slow response signals to the review division that the submission has documentation problems.
The Common Technical Document structure organizes documents into modules, but each module can contain hundreds of individual documents. Knowing that a data point is 'in Module 2.7.4' does not make finding it fast when Module 2.7.4 contains 300 pages of clinical summary tables.
FDA reviewers frequently ask questions that require verifying consistency across multiple sections of a dossier: does the patient population description in the clinical overview match the inclusion criteria in each individual study report? That check currently requires a regulatory affairs manager to read multiple documents in parallel.
During labeling negotiations, the team must quickly retrieve prior labeling proposals, FDA comments, and the regulatory rationale for specific label language. This history is spread across multiple years of correspondence and earlier label versions. Manual retrieval in a negotiation meeting is slow.
Regulatory dossiers are not standard document libraries. Several architecture decisions must be made correctly before building.
Documents must be chunked at CTD section boundaries, not character counts. A clinical study report section (e.g., Section 10.1, Patient Disposition) must remain a coherent chunk. Splitting mid-section loses the regulatory context.
Every retrieved chunk must carry the CTD module, section, document name, version, and page number as metadata. A page number alone is not sufficient for a regulatory professional to navigate to the source.
Clinical study reports reference protocols, amendments, and appendices. The ingestion pipeline extracts these cross-references and stores them as navigable links, so a query can optionally retrieve linked documents alongside the primary match.
Systems touching regulatory workflows require IQ/OQ/PQ validation. The audit trail, access controls, and system validation documentation are part of the project deliverable, not optional add-ons.
The ingestion pipeline parses eCTD submission packages, preserves the CTD module and section hierarchy, and chunks at section boundaries. Each chunk carries the full CTD path, document name, version, and page range as metadata. The pipeline handles PDF, Word, and Excel documents within the same submission.
The ingestion step extracts document cross-references (protocol citations, amendment references, appendix links) and stores them as an explicit graph. Queries can optionally traverse the graph to retrieve linked documents, with the link type shown in the result.
First-pass retrieval returns 20-30 candidate chunks. A cross-encoder reranker trained on biomedical and regulatory text re-scores them. This step is critical for regulatory documents where the relevant section may contain dense statistical tables that keyword models underweight.
Every query is logged with user ID, timestamp, query text, retrieved document identifiers with similarity scores, and the generated answer. Access is controlled by role-based permissions. The audit table is append-only. Validation documentation (IQ/OQ/PQ) is produced as a project deliverable.
Before deployment, we test the system against representative FDA information request scenarios. You see precision and recall numbers against real queries, not a product demonstration. The benchmark is a written deliverable.
Describe your submission dossier, the types of FDA information requests your team receives, and any GxP validation requirements. We reply within one business day.