CLINICAL TRIALS AND REAL-WORLD DATA

Written by: Amencefs CRO
Published on: December 24, 2022

There is an increasingly innovative focus to gain further insights into vital information about subjects enrolled in clinical trials and the trials products by linking clinical trials data with information from other sources. 

Subjects enrolled in clinical trials, irrespective of the study phase, may differ in their characteristics, ranging from varying health status to palpable degrees of disabilities, living conditions, and other social determinants of health, etc., depending on the targeted population and the intended outcome of such intervention. These characteristics are often present in the real world from Electronic Medical Records (EMR), laboratory records, administrative, insurance, and billing claims, disease registries, medical devices, etc. These diverse features are usually present in the larger population of the eventual users of the intervention, especially after market access, and may not be feasible to be fully characterized in the protocol that guides the study implementation. Moreover, this critical information is often not accessible to the investigator(s) and may impact the study outcome, and consequently limit the information needed to accelerate compelling evidence for such novel intervention.

A simple definition: Real World Data (RWD) by the FDA “are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources”. The sources include Electronic Medical Records systems (EMR), medical claims reports, disease, and vital statistics registries, etc. Clinical trials is a type of clinical research intended to test an intervention for human use. You can read up the basics of clinical trials to understand and familiarize with the basics and     the inter-usage of terminologies.

Generally, the aim of clinical trials is to find more effective ways to prevent, diagnose and treat a disease or a condition. The drive towards improving existing interventions before the commencement of a trial is usually informed by the disease epidemiology, burden, associated costs, and the unmet medical needs for the condition under consideration. These factors which inform the design and feasibility of clinical studies are gotten from multiple data sources in the real world which is critical before the study start-up in guiding the design, and even in recruiting study participants. Access to other medical data sources for a prospective participant could further strengthen the inclusion criteria that seek to eliminate any form of bias that could impact the trials’ outcome by acting as supplement information, and even validating enrolled subjects reported information and medical histories.

Subjects recruited in a trial may by chance be engaged in off-trial events, like exposures to factors that could be confounding to the trial medicine. An example is taking an over-the-counter medicine, or population-specific lifestyle, a subject’s daily routines, etc. Real-world data could provide useful insight into subjects’ off-trial happenings and even inform reasons for dropout of study which could result in a higher retention rate.

After trials and marketing approvals for the use of an intervention, sponsors and regulatory agencies focus on outcomes data in the general population, ranging from product value, use patterns, and safety. Post-marketing safety surveillance (PMS) detects rare and long-term treatment effects and informs product stay. Through RWD, sponsors can follow subjects beyond the lifespan of the trial to detect long-term effects that could result from the product and other outcomes-related measures. Outcomes data could facilitate the coverage of a medicine for use in population sub-groups (elderly, pregnant, children, etc.), and in certain co-morbidities.

Although the FDA uses Real World Evidence (RWE) generated from the analysis of RWD to inform clinical and regulatory decisions, the nature of data and the increasing reliance on randomized interventional to nonrandomized interventional and observational studies has led to a number of FDA guidance on the use of RWD and RWE to ensure that a strong scientific rigor is maintained and to avoid misclassification of outcomes.

RWD and RWE during the fourth phase of clinical trial give insight into what way and use pattern of a medical product, and may predict the likelihood of other indications beyond the regulatory approved indication for use. However, sponsors are tasked with ensuring regulatory compliance in addition to the conventional randomized controlled trials by ensuring that the data sources are standardized with data elements exchange formats that are capable of representing similar data elements or data domains. In addition, access to a subject’s medical records requires continual consent, and assurance could be achieved through tokenization.

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    There is an increasingly innovative focus to gain further insights into vital information about subjects enrolled in clinical trials and the trials products by linking