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Improving clinical trial design with real-world data

Many clinical trials struggle to enroll patients, hindering meaningful results and delaying the delivery of therapies to patients. Real-world data (RWD) addresses this by overcoming barriers such as overly strict enrollment criteria and disconnects between research design and patients’ lived experiences.

Arnaub Chatterjee, Chief Product and Solutions Officer at TriNetX, highlights the significance of RWD: “With over 80% of trials failing to meet enrollment targets, RWD offers a pivotal opportunity to enhance trial feasibility and site identification.” 

By leveraging RWD, global clinical trials are transformed, enhancing patient engagement and improving regulatory decision-making. “We recognize this critical juncture in the industry, where the demand for trial participation is high, yet successful recruitment remains a formidable hurdle. RWD brings many opportunities to address these challenges head-on,” Chatterjee added.

Access to rich data enables researchers to understand diverse patient populations worldwide, identifying clinics and hospitals that directly serve these communities. RWD removes knowledge gaps by sourcing from various health care settings: hospitals, clinics, insurance claims records and patient-generated data. The result is a patient pool that better reflects the real world — people of different races, ethnicities, ages, medical histories and socioeconomic backgrounds.

RWD: Streamlining clinical trial complexity

Capturing health data outside beyond conventional clinical trials offers a raw, unfiltered view of how patients experience disease, respond to treatments and interact with the health care system in their daily lives. Within the digital records of doctors’ visits, lab results and treatment histories lies a wealth of information to advance clinical trial design and execution.

RWD can be used to evaluate trial-eligibility criteria, recruit potential research participants and streamline recruitment. It increases efficiency, leads to shorter timelines and improves patient access to research. Data-driven trials informed by RWD start with a stronger foundation, potentially avoiding mismatched enrollment, unexpected side effects and costly delays that plague traditional trials.

“We worked with a large pharma in the infectious disease space who desired a data-driven approach to identify new sites to meet enrollment targets. TriNetX translated a complicated protocol into a query within one day, including variables such as BMI and laboratory assays supported by rich global EHR​. We then identified 50 net new sites for potential outreach across the U.S., U.K. and Israel ​and recommended 27 Tier 1 sites,” Chatterjee said.

Traditional clinical trials often rely on relatively simple inclusion/exclusion criteria. RWD enables a much more nuanced approach. Researchers can pinpoint patients based on disease variations, previous treatment failures, comorbid conditions (presence of multiple illnesses), or even specific lab values and test results. Such precision reduces the risk of enrolling patients unlikely to benefit from the tested therapy.

Clinical trials must fit within a defined period. RWD provides a longitudinal perspective on diseases that evolve over years or decades. Analyzing long-term patterns in how patients respond to treatments or how their health needs change over time can shape trials that better align with the actual trajectory of chronic illnesses.

RWD illuminates gaps in current treatment options. For instance, if real-world patients switch therapies frequently or experience common side effects, it suggests that better treatment options are needed. For example, clinical trials have limited ability to detect rare side effects. Large-scale RWD can reveal patterns that might emerge slowly or only affect a small percentage of patients. Proactively monitoring RWD allows for identifying potential issues early and modifying ongoing trials to investigate safety concerns.

RWD drives inclusivity

Recent mandates diversity action plans in regulatory submissions for life sciences companies, requiring integrating RWD to enhance patient inclusion.

Historically, underrepresented populations have been sidelined in clinical trials. RWD can help reverse this. Researchers can identify disparities in health care access or treatment outcomes among different groups by analyzing demographic data alongside health records. This knowledge can help shape trial design to intentionally recruit more diverse participants.

Analyzing RWD alongside demographic data empowers researchers to pinpoint specific health care organizations serving diverse communities. This strategy avoids the pitfall of limiting trial locations to major academic centers, which often leads to limited diversity in participant pools.

Using RWD allows for streamlining site identification and accelerates outreach, ensuring trials reach patients from underrepresented groups. “Our vision is to be the end-to-end platform to enable trial design through patient enrollment. Through our direct connection to health care organizations, we can ‘tech-enable’ site activation and patient recruitment following successful feasibility and connecting biopharma to the trial sites on our platform,” Chatterjee explained.

TriNetX uses RWD to optimize clinical trials and expand patient access. Its unwavering focus on inclusivity and precision fuels the development of tailored treatments, ultimately leading to better health outcomes for all.

Learn how to use real-world data on the TriNetX platform to explore patient diversity, identify gaps and improve clinical trials TriNetX | Case studies, publications, and more for RWD expeditions