The Power of Real-World Data in Clinical Trial Planning & Execution

Real-world data (RWD) and real-world evidence (RWE) are more than just life sciences buzzwords. They encompass vast, complex areas with notable potential to impact clients and the industry overall across the clinical continuum.

“Leveraging real-world data in clinical trial planning and execution is critical to ultimately reaching the right patient and enrolling them in a trial,” says Ashley Schwalje, senior director, clinical solution consulting, Citeline. “Without RWD, a major piece of the clinical strategy ‘puzzle’ is missing. In most scenarios now, it is table stakes for true patient insights.”

What is RWD?

Real-world data is derived from several sources associated with outcomes in a diverse patient population in real-world settings, including but not limited to health insurance claims, lab data, electronic health records, and patient surveys. This data can include, among other information, patient demographics, diagnoses, procedures, treatments, lab results, and patient outcomes.

It’s important to remember that RWD and RWE are not synonymous:

• Real-World Data (RWD) is data obtained from many independent sources that follow healthcare outcomes in a diverse population. The FDA defines it as data relating to patient health status and/or the delivery of healthcare, routinely collected from various sources.
  
  RWD is mainly observational and pertinent to actual clinical practice, in contrast to strictly controlled experimental data acquired in randomized clinical trials. It is primarily sourced from real-world medical environments and reflects realistic healthcare scenarios. RWD examples include data derived from medical claims, lab test/biomarker results data, electronic health records/electronic medical records, social determinants of health, consumer data, and more.
• Real-World Evidence (RWE) is the clinical evidence about the proper usage, benefits, and harms of a therapeutic or medical device obtained from RWD. It is extracted from RWD to form an analysis for the potential clinical study, base rationale, and engineer proper trial infrastructure.

How can RWD be leveraged to support sponsors’ overall clinical strategy?

The real-world experiences of patients as they journey through their healthcare experience — interacting with healthcare professionals, visiting medical and treatment centers, and dealing with insurance companies — are not necessarily smooth and seamless. For drug manufacturers, it is vitally important that they deepen their understanding and continue to monitor the landscape and evolving market across the product life cycle. In doing so, they ensure they are bringing treatments to market for patients in need. This includes leveraging data assets to address myriad business-related strategy questions across development including:

• What are the top indications to target?
• What is the unmet need in the market?
• What are the benefits of this product over other available treatments, and what is the value proposition for key stakeholders? Patients? Physicians? Payers?
• What patient cohort should I target? Is my protocol design inclusive?
• Which sites and investigators have access to the right patient population?
• How can social determinants of health data inform my patient engagement strategy?

Access to timely real-world data that helps uncover these insights is a significant advantage to companies looking to ensure they are optimally positioned in the market. The specific indications or therapeutic areas will dictate the types of data most relevant and valuable to address any given business need. For example, some oncology-focused business needs could be addressed more thoroughly with Citeline’s oncology biomarker data linked with open claims data.

The ability to tap into unstructured data is another trend gaining momentum. Of particular interest are physician notes, which can provide even deeper insights into the patient journey and associated diagnosis and treatment paradigms.

To be impactful, real-world data must be cleansed and organized, as well as be comprehensive and timely. In addition, RWD becomes more valuable when integrated or linked with other data assets, extending visibility into the patient journey, and with deeper insights across other clinical needs. Like any other form of big data, there is little-to-no value without utility resulting in insights and actionable next steps.

What are some of the clinical use cases for RWD?

1. R&D strategy planning and clinical trial protocol design: Assessing indications to identify the greatest potential involves looking at several factors, many supported by RWD, including diagnosis and treatment rates, gaps in standard of care, and current patient journey/patient cohort analysis. Assessing the competitive landscape also is an important factor here, to help clients leverage deeper insights to converge their efforts with market evolution to be at the right place at the right time.
2. Clinical trial feasibility: RWD can be layered in with site and investigator data to gain understanding of an investigator’s patient population characteristics and lab test/biomarker results. It can also help locate non-investigator physicians in proximity to investigators to lay the groundwork for trial participant referrals. In supporting the success of one sponsor’s Phase 1 trial, Citeline employed its proprietary databases and RWD to help the sponsor understand the implications of the US clinical trial landscape for site experience, availability, and access to the right patient population.
3. Diverse patient identification and recruitment: Diversity in clinical trials is an area that can greatly benefit from RWD. Study teams can analyze RWD to identify areas where under-represented patients live and receive care. Locating nearby clinical trial sites would then address awareness, access, and trust issues. Teams can also use RWD to guide the creation of eligibility criteria that optimize enrollment and ensure representative study populations.
4. Monitoring outcomes: RWD can add further insights when monitoring study outcomes. For example, the Adaptable study, which compared how effective two different doses of aspirin were in preventing ischemic adverse events, combined RWD with in-person visits for recruitment and data collection. The study team also employed RWD to improve outcome measurements such as hospitalizations and deaths.¹

As the availability of RWD grows, it creates opportunities for sponsors to incorporate related insights into all aspects of the drug development process. With the right sources, sponsors can use RWD to obtain a truly representative picture of how patients navigate through their healthcare journey, shedding light on treatment patterns, disease progression, healthcare utilization, and patient outcomes in real-world settings.

Learn more about Citeline’s Real-World Data Solutions.