Clinical Data Sharing: Why It's Important To Share Clinical Results

Clinical data sharing plays a crucial role in advancing scientific knowledge and improving patient care. 

1. Transparency and Scientific Advancement: Data sharing allows researchers to access clinical trial data, fostering transparency and enabling scientific advancements. Pharmaceutical companies have recognized this importance and committed to sharing participant-level data, study-level data, and protocols¹.
2. Reducing Research Waste: By sharing data, we can avoid duplicative efforts and reduce research waste. Access to existing clinical trial data helps researchers build upon previous work, leading to more efficient resource utilization.
3. Patient-Centered Care: Data sharing contributes to better decision-making for patients and healthcare professionals. When data is accessible, clinicians can make informed choices based on evidence from a broader pool of studies.
4. Challenges and Commitment: Implementing good data sharing principles requires resources, time, and commitment. Despite challenges, enhancing data sharing remains essential for scientific collaboration and patient well-being.

This particular Blog will focus on advancing research - how the sharing of participant level data with qualified researchers can accelerate novel research and inform the design of future clinical trials, some examples of successful sharing initiatives and an outline of common challenges associated with data sharing.

Transparency and Scientific Advancement

1. Transparency and Open Science:
   • Clinical trial data, including participant-level data, study protocols, and results, are valuable resources. When researchers share this information openly, it promotes transparency.
   • Transparency is essential for scientific advancement. By allowing others to scrutinize and build upon existing research, we accelerate progress.
   • Open science practices, such as pre-registering studies and sharing raw data, enhance credibility and reproducibility.
2. Collaboration and Replication:
   • Data sharing encourages collaboration among researchers, institutions, and disciplines. It fosters a sense of community and collective effort.
   • Replication studies become feasible when data is accessible. Replicating findings ensures robustness and confirms or challenges initial results.
3. Pooling Data for Insights:
   • Combining data from multiple studies (meta-analysis) provides statistical power. Researchers can draw more accurate conclusions about treatment efficacy, safety, and adverse events.
   • For rare diseases or conditions, pooling data across trials is especially valuable.
4. Challenges and Solutions:
   • Challenges include privacy concerns, data governance, and intellectual property. Striking a balance between openness and protecting sensitive information is crucial.
   • Initiatives like the FAIR principles (Findable, Accessible, Interoperable, Reusable) guide responsible data sharing.
   • The Clinical Research Data Sharing Alliance (CRDSA) is a multi-stakeholder consortium that services the clinical data sharing ecosystem with a shared goal of accelerating the discovery and delivery of life-saving and life-changing therapies to patients by expanding the research value of the data collected through the clinical development process

Some examples of successful clinical data sharing initiatives include:

1. PhRMA/EFPIA Commitment (2013):
   • In 2013, the Pharmaceutical Research and Manufacturers of America (PhRMA) and the European Federation of Pharmaceutical Industries and Associations (EFPIA) endorsed a commitment to share participant-level data, study-level data, and protocols from clinical trials of US and EU registered medicines with qualified researchers. They also aimed to provide public access to clinical study reports (CSRs) or at least synopses from trials submitted to the FDA, EMA, and EU Member States².
2. Advancements in Drug Development:
   • Successful data sharing has led to tools that optimize drug development. These initiatives help bring new therapies to patients in need by accelerating the research process and improving decision-making³.
3. Clinical Research Data Sharing Alliance (CRDSA):
   • The CRDSA focuses on sharing patient data generated from clinical trials. By doing so, they transform the trial process itself, improve the patient experience, and deliver life-saving and life-changing therapies faster and at a lower cost to society⁴.

Data sharing comes with certain challenges that are often faced by researchers.  

1. Cultural Shift
   • Challenge: Establishing a culture where data sharing is the norm requires overcoming traditional practices and concerns.
   • Recommendation: Stakeholders should foster an environment where data sharing is expected and commit to responsible strategies⁵.
2. Timelines and Compliance:
   • Challenge: Meeting deadlines for sharing various types of clinical trial data (e.g., full analyzable datasets, metadata, and analytic datasets) can be demanding.
   • Recommendation: Sponsors and investigators should adhere to specified timelines for data sharing⁶.
3. Sensitive Data Risks:
   • Challenge: Sharing sensitive clinical trial data while protecting privacy and managing risks.
   • Recommendation: Implement operational strategies like data use agreements, independent review panels, and transparency⁷.
4. Organizing and Presenting Data:
   • Challenge: Researchers struggle with organizing data in a useful and presentable manner.
   • Recommendation: Providing clarity on copyright, licensing, repository options, and metadata standards can help⁸.

Remember, addressing these challenges is essential for advancing scientific knowledge and benefiting patients.

Real Life Sciences specializes in data anonymization for regulatory compliance and voluntary sharing.