International Clinical Trials Day: Data Centric Clinical Research

International Clinical Trials Day

In May 2005, the European Clinical Research Infrastructures Network (ECRIN) begun celebrating the International Clinical Trials Day. This celebration yearly brings together patients, health policy actors, health authorities, clinical researchers, health professionals and citizens from across Europe and beyond to discuss issues related to multinational clinical trials. This year discussions and presentations focus on data centric clinical research, emphasizing the central role of data at all stages of the research process. With the data revolution playing an increasing role in all aspects of clinical research, the focus on some of the impacts, benefits and challenges of the rise of data and technology are now an essential topic for discussion.

Data centric clinical research

Data-centric clinical research is elemental in the era of big data and precision medicine, where large datasets and complex analyses play a crucial role in advancing medical knowledge and improving patient care. By focusing on data as a core aspect of research, this approach aims to maximize the accuracy, efficiency, and impact of clinical studies. The integration of the new technical assets, eHealth, data science, and the data protection legislation are current points of debate that need an active consideration and collaboration from all stakeholders. Regulatory frameworks need to be adapted to accommodate these new technical assets; and the definition of priorities and proper funding schemes are vital to focus on our patient’s needs.

Some of the challenges of data centric clinical research

While highly beneficial, data-centric clinical research faces several significant challenges that can impact its effectiveness and efficiency. For example, differences in the real-world clinical practice between European Union member states and between health care systems, may affect the relevance of data sources. Patients in different types of commercial or government health care payment programs can differ in a range of characteristics, such as age, socioeconomic status, health conditions, risk factors, and other potential confounders. Various factors in health care systems and private insurance programs, such as medication tiering (e.g., first-line, second-line), formulary decisions, and patient coverage, can influence the degree to which patients on a given therapy in one health care system might differ in disease severity, or other disease characteristics, from patients on the same therapy in another health care system. It is also important to identify whether the data sources cover all populations relevant to a specific clinical study and if those data sources can be used to examine the clinical study hypothesis.

In the case of data that comes from electronic health records and medical claims because these are collected during routine care and not according to a prespecified clinical research protocol, there are struggles for sponsors to be able to demonstrate in a clinical trial setting that the information needed to address the protocol questions for all exposures and outcomes of interest is present and doesn’t lead to an excessive exclusion of patients due to deficient records.

Conclusions

Addressing these challenges will require careful planning, and the adoption of new methodologies that can facilitate the efficient, secure, and ethical use of such data sources Overall, data-centric clinical research has the potential to significantly transform healthcare delivery, making it more efficient, personalized, and patient-centered, leading to better health outcomes and improved patient satisfaction. The journey is complex, but it has the ability to redefine our patient’s health.

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