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Stakeholders weigh in on big data at EMA forum

Posted 25 January 2021 | By Kari Oakes 

Stakeholders weigh in on big data at EMA forum

Effective use of real-world data and other data gathered outside the clinical trial arena requires a unified, big-picture approach, according to a new report from the first-ever big data stakeholder forum held by the European Medicines Agency (EMA).
 
The regulator’s report on the 15 December 2020 forum highlighted the importance of collaboration in addressing some of the challenges of bringing real-world data (RWD) into the drug development process. Some of these include data quality, the need for robust study methods, and “establishing the evidentiary value and regulatory accessibility of evidence generated.”
 
According to the report, stakeholders were pleased with progress made since a big data steering group was established in May 2020; the group also developed a work plan that was adopted in July. A key component in speeding effective utilization of large datasets, such as those generated from RWD sources, is the EU’s DARWIN project, which, according to the report, is “expected to improve health outcomes for all European citizens.”
 
That project should also help speed identification EU-wide of patients who are eligible for drug trials, accelerating evidence generation and making it easier for trialists to be flexible as circumstances change. “Stakeholders showed consensus in recognizing the value of RWD as a complement to clinical trials,” according to the report.
 
Going forward, stakeholders are anxious to see guidelines that set parameters around the use of data to ensure high-quality, representative information across “different data sources and use cases.”
 
Interoperability, attendees agreed, is key. “RWD can fill the gaps where evidence from clinical trials is lacking but can only deliver on this promise if national variations are overcome by adopting common standards on data quality and metadata,” noted EMA.
 
Ethical data protection within a governance framework is “essential,” according to the report. Stakeholders have to know “where data is kept, how it is used, and who is responsible for processing.”
 
The report highlighted particular comments and concerns from specific stakeholder groups. Patients prioritize “the ability to fulfill unmet medical needs,” as well as rational drug repurposing. However, patients are still concerned about confidentiality, and seek reassuring privacy and security standards.
 
Digital literacy was a challenge noted by both patients and clinician stakeholder groups. Though clinicians have high hopes that big-data techniques will have a positive impact on clinical outcomes, particularly in the areas of rare diseases and adverse events, concerns linger. According to the report, clinicians also worry about lack of standard data collection tools and lack of cross-EU harmonization for data analysis techniques. A final concern clinicians raised was the worry that “the increasing digitalization of the clinical space challenges a vital part of human care, namely the human touch, a requirement for trust.”
 
Researchers joined clinicians in voicing concerns about sampling bias and data completeness; both stakeholder groups noted that advanced analytic techniques could further widen economic disparities across Europe.
 
Researchers did note that the influx of “large amounts of quality data” would augment their efforts. They advocated for promoting transparency, independence, and standards as a 3-pillar foundation for big data efforts. A specific concern raised by researchers was the importance of not confusing data-driven research techniques – meant to find previously unknown associations – with causal inference. This distinction will require sophisticated epidemiologic and statistical methodologic approaches.
 
Academic stakeholders looked forward to the ability to make scarce resources stretch through data sharing, and emphasized the importance of research free from commercial bias.
 
For its part, industry also sought multi-stakeholder collaboration to work on problems of data quality, and offered insights from past real-world use cases.  
 
EMA
 
 

Tags: big, data, EMA, EU, RWE

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