AI-Powered Regulatory and HTA Review Simulation Services

This AI-powered service simulates regulatory and HTA review processes to identify risks, gaps, and likely objections before formal submission. It evaluates dossiers, evidence packages, clinical narratives, and economic models using multi-agent reviewer logic aligned with global agency frameworks, including FDA, EMA, NICE, CADTH, PBAC, and other international HTA bodies. The simulation highlights methodological issues, unsupported claims, and areas that may trigger clarification requests, enabling teams to strengthen their submission packages before agency review.

The service replicates real-world reviewer behavior by assessing evidence consistency, value claims, and alignment with agency expectations. All insights are generated using evidence-linked retrieval methods that ensure every observation is grounded in verifiable source material. Each simulation includes reviewer-style commentary, prioritized remediation guidance, and a traceable audit trail suitable for regulated environments.

Advanced analytics surface cross-market discrepancies, weak evidence linkages, and potential risks across clinical, economic, and value-based sections. This accelerates readiness, reduces downstream revision cycles, and improves cross-functional preparedness for global submissions.

AWS services support secure, scalable delivery of the simulation workflow. Amazon S3 is used for encrypted dossier and evidence storage, Amazon Bedrock and Amazon SageMaker support multi-agent orchestration and retrieval-augmented generation, AWS Lambda powers event-driven processing, and Amazon CloudWatch provides monitoring and operational visibility. All workloads run within secure, role-based AWS environments aligned with enterprise compliance requirements.