A recent update for Health Canada and EMA’s data anonymization program included instructions for filling out the new clinical template and a more granular look inside the harmonized Anonymization Report (AnR). Further, the goal of this regulatory harmonization program is to make EU and Health Canada identification of specific patients from characteristics in the data set as highly unlikely as possible.
What is Data Anonymization?
Data anonymization is a method for presenting research data in a way that reduces our ability to identify the individuals who participated in the clinical study. Best practices for Clinical anonymization commonly target how to protect the trial participant’s data and clinical trial drivers, such as:
- Device manufacturer
- Drug manufacturer
- Device trade name
- Drug trade name
Patient data and re-identification can also be linked to outlier conditions to be considered:
- Protocol design vs. advanced methods
- Special populations
- Rare disease state
- Ultra rare disease state
Finally, consideration must be given to small trial populations that can limit the intended scope of patient disclosure. For example, since there are fewer patients in the trial, any form of incomplete anonymization often leads to an increased risk of re-identifying a trial participant.
Regulatory Compliance
Two unique regulatory standards are being used as guidance for drug sponsors & data anonymization clinical teams:
- Health Canada
- Public Release of Clinical Information (PRCI)
- EMA
- Policy 0070 Clinical Data Publication (CDP)
Finally, an important benefit of anonymization is the ability to proactively distribute scientific data to reduce duplicate clinical trials. Building public trust in products coming to market is often accomplished by increasing the awareness of clinical successes. The healthcare industry’s ability to scrutinize the data against both standards to be durable, reliable, and anonymized over time will help researchers improve clinical outcomes.
Drug Sponsors
The regulatory process will now include drug sponsors submitting only one anonymization report for both Health Canada and EMA regulatory submissions. The updated report format for both Health Canada and EMA uses a mix of predefined, multi-choice questions and verbatim response questions. Additionally, the format is optimized for clinical data sharing between each regulatory body to improve transparency and product efficacy.
A drug sponsor’s anonymization methodology would include a risk assessment that shows either a qualitative or quantitative calculation (or a combination based on clinical strategy). Redacted copy options include both Personal Information that satisfies Health Canada regulatory and Protected Personal Data for the EMA regulatory format. Finally, direct identifiers of both the clinical report signatory and principal investigator should be listed with the rationale for each clinical approach used.
Adverse Events (AEs)
Indirect identifiers are anonymization report categories often about clinical data specifically related to the trial (or product used in the clinical trial). This information is not enough to stand on its own in terms of independent study variables. Instead, the data analysis is dependent on the clinical trial to connect the differences between patient information and an actual participant.
All adverse events (and terms related to the adverse event) should be recorded in these formats:
- Summary level
- Tables and/or descriptive summaries
- Participant level
- Written patient narrative based on AEs
Special Populations
Select clinical trial participants may fall under the anonymization category of special populations. These participants often include a sub-set audience that is impacted by either the patient’s life events or stage of life while participating in the clinical trial. Special populations often warrant a different level of clinical segmentation that should be documented and analyzed in the final reporting submission.
Further, their current health condition may warrant creating a clinical subset of participants for regulatory approval, such as:
- Trial specific examples:
- Pediatric
- Geriatric
- Patient specific examples:
- Pregnant women
- Breastfeeding women.
In the context of anonymization, these special populations may need a unique reporting strategy since they often do not share all key characteristics of the trial population.
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