Data and AI Solutions for the Pharmaceutical Industry

We follow your quality management system and computer system validation procedures, and apply a risk-based approach consistent with GAMP 5 and Computer Software Assurance thinking. We help you determine GxP impact, document requirements, design tests proportional to risk and produce traceable evidence. Automated testing and infrastructure as code reduce the manual effort of revalidation when the solution changes. Your quality unit retains approval authority throughout.

Yes, with appropriate controls. Current regulatory thinking, including the European Commission’s draft Annex 22, emphasizes a clearly defined intended use, representative training and test data, explainability, human oversight and controlled change, and it limits dynamic or generative models in critical GMP applications. We assess each use case against applicable guidance, recommend where AI should advise rather than decide and design validation and monitoring accordingly. Non-critical uses such as document search usually face lighter requirements.

We integrate with common laboratory, manufacturing execution, process historian, quality management and ERP systems using their APIs, OPC interfaces, database connections or exports. A key part of the work is contextualization: linking process data to batches, materials, equipment and quality results so it becomes meaningful for analysis. Integrations are designed to be read-only toward source GxP systems unless write-back is explicitly required and validated.

We design for ALCOA+ principles: data that is attributable, legible, contemporaneous, original and accurate, as well as complete, consistent, enduring and available. Practically, that means immutable raw data storage, audit trails on changes, role-based access, controlled transformations with lineage and backup and retention aligned with your policies. We document these controls so they can be inspected during audits.

A focused analytics use case on an existing platform can reach validated release within about three to six months. Building a GxP data platform across several sites is typically phased, starting with one product or site and expanding. Validation and quality review steps are planned into the schedule from the beginning, which avoids late surprises and keeps timelines predictable.

Yes. Outside the GxP domain we build data platforms and analytics for commercial and medical teams, including customer master data, omnichannel engagement analytics, territory planning and medical information assistants. We apply privacy controls for healthcare professional and patient data and keep these environments appropriately separated from regulated manufacturing and quality data.