Unlocking the vast potential that exists in combining and repurposing clinical trial data has advanced due to technological developments, but there is still hesitancy from many organizations as they weigh up the effort involved in harmonizing the datasets and concerns around protecting the privacy of participants. Many in the industry recognize that the technological advances that have made it possible to combine datasets more easily are also inadvertently providing the means to potentially re-identify trial participants. The growing influence of the GDPR in new legislation outside of the EEA and the associated fines and other sanctions that comes with it necessitate caution.
Various data protection methodologies (anonymization or strong pseudonymization) have been used by Sponsors to safeguard privacy and comply with relevant laws and regulations. However, certain variations in approach can render the resulting data difficult and time-consuming to use and, in some cases, greatly reduce data utility, especially in the context of cross-study analysis. The issue can be further compounded by a lack of transparency in describing the specific privacy safeguards that have been applied, making it difficult to determine whether the data are fit for an intended secondary purpose.
The vision for the Privacy Methodology for Data Sharing is to greatly improve transparency and reduce the variability in the methodology applied by companies to protect personal data in ways that facilitate secondary reuse of data. This proposed model approach would reduce the complexity associated with using the data within the DataCelerate modules and better facilitate cross-study analysis.
Additionally, the initiative aims to provide educational tools that study sponsors can use to help clinical trial participants better understand the levels of personal data protection measures that will be applied to their personal data, including an educational tool and a Frequently Asked Questions document.
Adoption of the Privacy Methodology for Data Sharing deliverables will facilitate:
- Faster scientific insights and reduced participant burden through easier reuse of studies.
- Greater transparency for clinical trial participants in the privacy safeguards applied to data resulting in increased data utility.
- Better transparency for patients as to how their privacy is protected in clinical trials and subsequent reuse of data.