Pharmaceutical companies today are well-advised to view transparency as an opportunity to enhance their reputation in the marketplace and earn trust with stakeholders, which can ultimately benefit their competitive position.
Clinical trial transparency measures can be regulated, with requirements across a multitude of jurisdictions. Regulation aside, a trial sponsor can of course choose to adopt discretionary transparency measures, such as voluntarily sharing data to enable secondary research.
Perhaps the greatest benefit that can accrue to a trial sponsor from adopting transparency best practices is trust – earning trust with the public, other sponsors and regulators through greater openness and collaboration.
The value of trust
It’s a common refrain that people are often reluctant to enroll in clinical trials. They simply don’t trust industry-sponsored trials and fear participating. Transparency is widely regarded as an effective means for the approval system as a whole to earn the public’s trust and encourage participation in trials for both pharmaceuticals and medical devices.
This need to build trust also extends to the broader research community.
“By making clinical trial data available to other researchers, we believe we are honoring participants of the study by giving data new life, beyond the original purpose of the study,” Dr. Joanne Waldstreicher, CMO, Johnson & Johnson, said during a round table published in the May 2018 issue of Pharmaceutical Technology.
A robust transparency program enables a trial sponsor to build trust and its standing among its peers. This contributes to a number of benefits for the approval system as a whole:
- Avoided Duplication: An understanding of what other similar work has already been done, to ensure a trial is necessary and not a needless duplication of effort
- Patient Access: Greater patient access, to help them better understand their options for enrolling in new trials and encourage their participation
- Better Decisions: With more complete information available from trials, better medical and other decisions can be made by those with access to this evidence
- Higher Quality: By expanding the pool of quality data available to the broader scientific community, new secondary research can be conducted, quality of care can be improved and any data gaps identified
Privacy measures are a must
This emphasis on transparency and disclosure has also put the spotlight on privacy. Publication of trial results – whether it’s in the form of documents or structured, tabulated data – cannot come at the expense of any single trial participant’s privacy.
That’s where things can get sticky if a trial sponsor doesn’t have an effective privacy program in place to support its transparency goals.
As transparency leaders know, to protect privacy, participant data must be anonymized. Regulators mandating the publication of clinical study reports have also emphasized this privacy imperative. They favour an anonymization approach that protects patient privacy while also preserving the utility of the trial data for other research purposes.
Instead of traditional blunt methods of redaction or masking, this preferred approach relies on statistical analysis. The goal is to reduce the risk of re-identification below a threshold acceptable to a regulator, without eroding the value of that data for further research.
Striking the right balance
For example, say we have a study participant identified as “Subject 899-456 – a 34-year-old female with a medical history of coeliac disease.” Published as is, the subject may be re-identified using the information disclosed about them in the study document.
But if we redact, we end up with something that is useless, either for further research, or to achieve the goal of transparency: “Subject _____ was a _____-year old ______ with a medical history of _______.”
With statistical analysis, we take a risk-based approach to transform the data just enough to sufficiently protect privacy without distorting the data to such an extent that its utility is lost. For example: “Subject 454-994 was a 32-year-old female with a medical history of autoimmune disorders.”
In this case, we use a different direct identifier for this participant, keep her gender, generalize her age but keep it within the range of her demographic, and replace her specific medical condition with the general classification of disease in which her condition fits. Privacy is protected, data value is preserved and transparency goals are met.
This defensible proof of privacy with transparency enables a trial sponsor to earn trust with both the public and the broader research community.
Learn more with Sarah Lyons and Vivien Fagan
The value of anonymization extends far beyond mere regulatory compliance to also support discretionary data sharing for secondary research, internal innovation whereby older trial data can be used for purposes beyond the original uses, and to sourcing and combining real-world data in a safe manner for other valuable insights.
Trial sponsors are well advised to view transparency as much more than just a box that has to be checked off. But transparency and privacy regulation is a complex and dynamic field. Clinical trial sponsors must arm themselves with the right tools and expertise to remain at the forefront of transparency and to reap the benefits that can result.
To learn about how transparency best practices and the regulatory environment have evolved, how they continue to change and how a trial sponsor can rise to the challenge with statistical anonymization, we invite you to listen to our recent webinar at FDAnews. (Please advised that paid subscription access is required.)