Clinical data management innovation needed to reduce mid-study updates

CROs need to improve trial data management according to analysis, which suggests disruptive mid-study database updates are increasingly common.

The finding comes from a study that examined data management “pain points” in trials by quizzing stakeholders in the contract research and pharma space.

Mid-trial updates – database amendments and post-production changes – were a “time intensive” concern. Around 56% of respondents said planned mid-study updates – those outlined in the study protocol – were a challenge.

Likewise, 48.4% of those asked said unplanned mid-study updates were their biggest data management pain point.

Data complexity

Growing concerns about mid-study updates illustrate the complex nature of clinical trials according to the researchers, who pointed out that modern trials draw data from an increasingly broad range of sources.

“The growing volume and diversity of clinical trial data is inevitable as drug developers look to gather data on more stratified patient populations, rely on more sources for clinical research and patient health data, and conduct more operationally complex protocols. At the same time, drug development timelines and efficiency continue to worsen.

“In response, the clinical data management function – in collaboration with clinical data solutions providers – is expected to evolve substantially to address these challenges and leverage the value of rich data. The pandemic has fast-tracked the adoption of decentralized trials, which translates to new patient engagement approaches and technology.”

The authors added that, “Mid-study updates are the most common pain point and the area where organizations are the least satisfied with the capabilities of their [electronic data capture] EDC solutions.”

Opportunity

Reducing the occurrence of mid-study database updates will require innovating in both EDC technology and data management according to the authors.

“Mid-study database updates are disruptive and present a major opportunity to accelerate cycle times and improve efficiency, particularly as protocol designs become more flexible and the diversity of data, most notably unstructured data, increases.”

They added that, “the clinical data management function—in collaboration with clinical data solutions providers —is expected to evolve substantially to address these challenges and leverage the value of rich data.”

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