About NexGen GxP AI
We are the first company purpose-built to close that gap — not by slowing AI down, but by building the validation infrastructure that lets it move at the speed of discovery.
The pharmaceutical industry's greatest bottleneck in 2026 is not drug discovery. It is not clinical trials. It is the validation of artificial intelligence for GxP environments — the processes that govern manufacturing, batch release, quality control, and regulatory submission.
Every major pharma and biotech company has AI initiatives underway. Most of them are stalled — not by technical failure, but by the absence of a compliant framework to operate within. The regulatory requirements exist. The AI capability exists. The bridge does not. That is what we build.
NexGen GxP AI deploys autonomous, fully-validated AI architectures that accelerate therapeutic development and manufacturing while ensuring absolute regulatory integrity. Headquartered in Boston and serving the global market, we provide the first audit-ready agentic ecosystem for the future of medicine.
The regulatory landscape for AI in pharmaceuticals is undergoing simultaneous change across every major jurisdiction. The window to establish validated AI infrastructure is now.
FDA's 2022 CSA guidance moves from prescriptive IQ/OQ/PQ to risk-based critical thinking. AI systems must demonstrate intended use documentation, audit trails, and human oversight. Simultaneously, FDA's AI/ML Action Plan extends Total Product Lifecycle (TPLC) requirements to manufacturing AI.
The revised Annex 11 draft introduces explicit AI/ML requirements: §4.8 requires documented validation of model training data and output thresholds; §7.1 classifies agentic systems as complex computerised systems requiring vendor audits; §9 mandates immutable logging and chain-of-custody for training data.
PIC/S harmonization with Annex 11 adds AI-specific requirements: validation of model performance across representative populations, change control triggered by retraining, and periodic review against pre-defined acceptance criteria. The forthcoming AI addendum will extend these requirements further.
We are intentionally focused on the therapeutic areas and manufacturing environments where GxP AI validation is most complex — and most consequential.
Commercial-scale cell therapy manufacturing is data-intensive and under-automated. Batch release decisions, real-time release testing (RTRT), and chain-of-identity tracking all represent AI validation opportunities under the highest regulatory scrutiny.
Biologics manufacturing requires AI-driven process analytical technology (PAT) and continuous process verification (CPV). Validating these systems against FDA Process Validation Guidance and Annex 11 requires a framework built for manufacturing complexity.
Companies transitioning from clinical to commercial-scale chemistry manufacturing face pressure to deploy AI for process optimization and quality. We bridge computational excellence to GxP-validated deployment under ICH Q10 and Q12 lifecycle frameworks.
If you are responsible for AI governance in a GxP environment, we would like to understand your specific situation. No sales process — a technical conversation between practitioners.
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