Managing data effectively can be challenging in any industry. But it’s especially difficult in pharmaceuticals, which faces especially stringent data management, privacy and security needs.
In pharma, much of the data that businesses work with – such as personally identifiable information (PII) in patient records and information from the supply chain involved in the production of medications – is highly sensitive. It’s also subject to data privacy regulations in many cases.
On top of this, the consequences of making mistakes when working with pharma data are especially serious. In most other industries, the worst thing that could happen from mismanagement of data is ineffective business decisions or information security risks – which are bad, to be sure, but which are not matters of life and death. In contrast, data management errors in pharma could lead to issues like the inaccurate tracking of medication expiration dates, with severe consequences for human health and safety.
For these reasons, pharma companies must develop especially sophisticated data management strategies. Those strategies should start with basic data management best practices, like validating data quality and implementing processes to track data throughout its life cycle. But they must also include extra steps that address the unique challenges of pharmaceutical data management.
Key data management challenges in the pharma industry
Effective data management in pharma can be tough for two main reasons. The first is that, again, pharma data is often highly sensitive. In cases where data managed by a pharmaceutical company includes PII, the information may be regulated by data protection laws like the GDPR, which restrict how pharmaceutical companies can collect, analyse and store data associated with consumers.
In addition, pharma data may include sensitive business information, like the status of a drug currently in development. This information isn’t typically regulated by compliance laws, but it’s nonetheless highly sensitive data that businesses don’t want to expose to competitors – which means that this type of data, too, must be managed in ways that maximise data security and privacy.
The second fundamental data management challenge for pharma companies is that mistakes can have dire consequences. In addition to regulatory fines triggered by compliance violations, failing to manage data accurately could lead to issues like the sale of expired medications, causing harm to patients. Likewise, businesses involved in the pharma supply chain must also ensure that they can accurately trace the origins of drug ingredients and products so that they can recall tainted medications when necessary.
Read the article in full here.
