Voluntary Clinical Research
Data Sharing

Learning from what other researchers have already done- both accomplishments and challenges- stimulates innovation and ultimately the delivery of lifesaving medicines. Share meaningful clinical research data while ensuring participant privacy.

Why Share Clinical Data Results?

The value of anonymized patient level data can go far beyond that of the original clinical trial. Enabling new research with the benefit of understanding prior research is a critical opportunity and one that amplifies the voice of the patient participation well beyond the trial they participated in. Improvements to public health rely on the ability to enable new research as efficiently and economically as possible. Further, as regulations continue to evolve it is becoming more clear that regulators will soon mandate the sharing of clinical trial datasets  (EMA Policy 0070 Phase 2).   

Some of the benefits of clinical data sharing include:

-Expanding value of new research faster by not repeating already accomplished conclusions.
-Sharing new research innovations to bring more rapid benefit.
-Providing the ability for patients and patient advocacy groups to gain new insights into diseases of interest

There are many critical considerations before the sharing of clinical data can begin. Top of mind issues include:

-Protecting the privacy of trial participants
-Protecting the confidential information owned by the trial sponsor
-Sharing data that maintains its clinical usefulness and is interpretable by the recipient

Protecting the Privacy of Trial Participants

Using empirical methods to analyze the trial datasets is a critical aspect of protecting participant privacy.
-Classifying the variables
-Determine and measure the risk threshold
-Anonymize the data
By adopting an anonymization process that incorporates these steps, the risk of re-identification is quantifiably reduced. This anonymization methodology results in generating clinically useful information leveraged for voluntary data sharing purposes, while balancing the risk threshold that was determined. This approach maximizes data utility, while inherently adjusting to identifiers that could compromise a participant’s identity (of certain study populations), using a variety of different anonymization techniques.

Protecting the Confidential Information Owned by the Trial Sponsor

Information within the trial data and accompanying trial documents that are considered confidential and proprietary must be protected to ensure the financial interests of your organization are considered. 

Examples of such information may be dosing values, manufacturing sites and methods, shipping conditions, storage temperatures and bioanalytical values. 

Developing internal processes to capture this type of information in a consistent and timely manner for each trial is a critical step in preparing your data for sharing.

Sharing Data that Maintains its Clinical Utility and is Interpretable by the Recipient

To maximize the value received from the shared data, it is critical to retain the most utility or “clinical usefulness” possible. Retaining the original meaning of the data while anonymizing and protecting patient level data allows secondary researchers and consumers of the information to benefit from the shared data. Guidelines for preparing the anonymization data are as follows:

-All transformation of data should be conducted for the sole purpose of preventing the disclosure of personal information;

-All data transformations should be limited to the variables that have an observed risk of re-identification (not to broad sections of clinical information)

-To retain its analytical value, example methods applied to transform the data are  pseudonymization, generalization, randomization and offsetting

For a more detailed review of the Life Sciences industry perspective on data sharing policies, please refer to the Clinical Research Data Sharing Alliance’s published document from September 2022, “Whitepaper: A Review of BioPharma Sponsor Data Sharing Policies and Protection Methodologies”. Download the White Paper (PDF).

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Our team is made up of passionate leaders in the fields of machine learning, natural language processing, clinical trials, data analysis and regulatory submissions. We help Pharmaceutical Sponsors and CROs focus on your primary business goals while protecting patient identity and company confidential information while maximizing data utility and adhering to regulatory requirements.
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