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 raw data and its derived analytical results generated from the process. Process validation failure affects both patient safety and the economic success of the manufacturing company. Hence, data integrity is highly critical in this area. Regulatory agencies, such as the Food and Drug Administration (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, currently 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 backdating 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 road map for the development of production-ready tools, such as versioned database systems that natively interoperate with distributed ledgers. This will improve the trustworthiness of pharmaceutical manufacturing data by both protecting the intellectual property of the industrial company and improving the safety of the patients.

LAY ABSTRACT: In the pharmaceutical industry, economically driven manufacturing companies are regulated and controlled by regulatory agencies. The pharmaceutical manufacturing companies need to produce large amounts of process and analytical data to show that their products are safe for patients. As the decisions of the regulatory agencies rely on this data, manufacturing companies need to prove how their generated data can be protected from technical breaches or data manipulation.

As of today, the available technical solutions to provide data integrity are not working well enough. Regulatory agencies have published multiple documents highlighting the current data integrity issues.

In this contribution, we show how blockchain, a technology that multiple cryptocurrencies like Bitcoin rely on, can help to improve the integrity of manufacturing data and data science analysis procedures. Therefore, we combined a smart contract on the Ethereum blockchain with tools currently mostly used by software developers. The presented workflow shows how data integrity can be guaranteed on a technological level without the need for trusted third parties.

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