Provable Data Integrity in the Pharmaceutical Industry based on Version Control Systems and the Blockchain

Valentin Steinwandter; Christoph Herwig

doi:10.5731/pdajpst.2018.009407

Abstract

In the pharmaceutical industry, process validation tasks are based on the generated process raw and derived analytical results. Risks to fail in process validation, affect both, the patient’s safety as well as the economic success of the manufacturing company. Hence, data integrity is highly critical in this area. Regulatory agencies, such as the FDA, reacted to past data integrity breaches, by publishing new guidelines on data integrity for the correct handling of data in the pharmaceutical context. In this contribution, we want to show how data integrity can be improved on a technological level, removing the need for trusted third parties and centralized systems for this task. Therefore, we implemented an approach that uses existing tools, today mostly used by software developers, and combined them with a new smart contract built on top of the Ethereum blockchain. In a case study, we test how data manipulation or back-dating of results can be easily detected and how regulatory agencies can audit the complete data flow, from the regulatory report back to the original raw data. The results of this contribution outline a possible roadmap for the development of production-ready tools, like versioned database systems that natively interoperate with distributed ledgers. This will improve the trustworthiness of pharmaceutical manufacturing data by doing both, protecting the intellectual property of the industrial company and improving the safety of the patients.

Received August 7, 2018.
Accepted January 30, 2019.

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