Real-time algorithmic exchange and processing of pharmaceutical quality data and information

Herein, a modern method is proposed for exchanging and processing real-time medicinal product information using Health Level 7 International's (HL7) Fast Healthcare Interoperability Resources (FHIR (R)) standard, Application Programming Interfaces (API), digitization and artificial intelligence. FHIR is presently in use largely to facilitate interactions between patient-facing healthcare institutions, such as hospitals, doctor's offices, and laboratories, for electronic health record management and exchange. There are several ongoing efforts to adapt the FHIR standard for regulatory use cases to support the needs of the global biopharmaceutical industry, including the exchange of Electronic Product Information (ePI); chemistry, manufacturing, and controls (CMC) data; and adverse event reporting. Once in place, this new method of data exchange is expected to (1) improve efficiency by reducing the time and effort needed to manage regulatory information; (2) accelerate decision making; (3) encourage innovation in pharmaceutical manufacturing; (4) improve the ability and agility of in-formation exchange. Currently, the end-to-end timescale for the pharmaceutical regulatory workflow is measured in months and years. This new paradigm will use FHIR APIs and other supporting technologies to reduce the potential time for data exchange from months to days, hours, minutes, and eventually sub-seconds. With such drastic improvements in speed provided by digitization, automation, and interoperability, the bio-pharmaceutical industry can reach more patients, and more quickly than at any time in the industry's 100+ year history. The present work will focus on examining specific real-world implementation examples for using FHIR to support exchange of CMC information within and across the biopharmaceutical industry.

Automated summary

This article proposes a modern method for exchanging and processing real-time medicinal product information using the FHIR standard, API, digitization, and artificial intelligence. The method is expected to improve efficiency, accelerate decision making, encourage innovation in pharmaceutical manufacturing, and improve information exchange capabilities and agility.