This article was co-authored by James Canterbury, EY Global Life Sciences Risk & Compliance Leader.
Pharma companies have complicated supply chains and manufacturing operations that are closely regulated by health authorities such as Food and Drug Administration (FDA) and Medicines and Healthcare products Regulatory Agency (MHRA). There has recently been a significant increase in the volume of regulatory findings around data integrity issues, which can also be viewed as a lack of trust in digital records. While the lack of trust can stem from many places, it is often traced back to two primary drivers:
- Inconsistent data across multiple sources over time
- False data (either accidental or fraudulent) that was not detected and corrected in a timely manner
Blockchain offers the prospect of designing a data structure from the perspective of the product, which means that, in a single chain, all vital data about that product can be captured directly at the source of origination and maintained in an immutable audit trail.
The time-stamping function of the blockchain, in conjunction with the audit trail, provides an accurate record of who, what, where and when a product might have been changed over a given period of time. The current status or location of any given product is available by examining the current state of the block.
The cost of data integrity and availability
The real cost of data integrity and availability is the amount of effort an organization puts forth producing data they can trust. If we imagine a world where all data is trustworthy and at our fingertips, then the efforts around data would be limited to affirming that it accurately reflects our real-world transactions and processes, and in interpreting the data to make better business decisions. Any time or resources spent on trying to locate, verify and conform data is a sunken cost that yields little return.
Yet this cost is significant. In July 2016, the FDA issued a draft of their proposed Request for Quality Metrics; the Federal Register notice (80 FR 44973) gave an estimate of 667,800 hours annually to collect and respond to their 15 proposed metrics. A follow-on study conducted by the International Society for Pharmaceutical Engineering (ISPE) in June 2016 determined that the actual effort would be at least three times that amount, just to collect and prepare data on three of the metrics.
And these up-front costs are just a drop in the bucket when compared with the cost of getting it wrong. From an FDA perspective, the inability to rely on data will create major obstacles in new drug approvals and can result in warning letters, which may lead to injunctions. These trends in data integrity issues have been so obvious that in April 2016, the FDA issued a draft guidance — Data Integrity and Compliance with CGMP.