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A sex-bias that significantly impacts the advancement of women’s health exists in both preclinical and clinical research.

Considering Sex as a Variable in Clinical Trials

Since 2016, the FDA has released various guidance documents intended to promote diversity in clinical trials—particularly regarding recruitment of trial participants—and the agency’s diversity commitments are only expected to grow. As such, entities sponsoring and designing clinical trials must be proactive in ensuring that protocol inclusion and exclusion criteria do not inadvertently exclude diverse populations (absent scientific justifications). 

Moreover, as technology advancements continue to reshape the clinical trial landscape, entities should increasingly explore the use of decentralized trial models, telemedicine, and remote technology for extended outreach and inclusion of diverse populations. This article thus highlights the key takeaways of several FDA diversity-related guidance documents from 2016 onwards; outlines the potential for decentralized models and digital health technology to expand diversity in trials; and informs sponsors on the need to be aware of future guidance documents that will be released over the coming years.

Individuals within in the United States differ by sex, age, race, ethnicity, location, economics, and many other characteristics, while different groups within these populations may respond to medications in different ways. For these reasons, the FDA recognizes that it is important that clinical trial inclusion criteria (explained in greater detail below) seeks representatives of the different groups who will use these medications to provide data on the safety and efficacy for these diverse groups.

The FDA’s commitment to increasing diversity in clinical trials is clear and evidenced by guidance it issued within the past decade. Indeed, since October 2016, the FDA has released various guidance documents intended to promote and increase diversity in clinical trials, and with a focus on the recruitment of diverse clinical trial participants.

The focus of the FDA’s diversity efforts is often on clinical trial participant eligibility criteria. In conducting a clinical trial, a sponsor must determine which individuals are “eligible” to participate, while determinations as to eligibility criteria are generally based on the purpose and type of the clinical trial to be performed and the investigational product. The exclusion of certain populations from a trial is often an unintended consequence of setting eligibility criteria, without scientific justification. Accordingly, FDA guidance over the years includes a focus on how to increase participant diversity.

October 2016 - Collection of Race and Ethnicity Data in Clinical Trials Guidance

In 2016, then FDA Commissioner, Robert Califf, MD, declared that 2016 was the “Year of Clinical Trials Diversity” and in October of that year, the FDA issued a guidance outlining expectations and recommendations regarding the standardized approach for collection and reporting of race and ethnicity data in clinical trials. The October 2016 guidance document, “Collection of Race and Ethnicity Data in Clinical Trials Guidance for Industry and Food and Drug Administration Staff,”

 was issued in response to the Office of Management and Budget (OMB) Statistical Policy Directive 15, Revisions to the Standards for the Classification of Federal data on Race and Ethnicity. The guidance set forth FDA expectations for, and recommendations on, use of a standardized approach for collecting and reporting race and ethnicity data in submissions for clinical trials.

Further, the 2016 guidance lists the OMB categories for race and ethnicity and describes FDA's reasons for recommending the use of the categories in medical product (drugs, biologics, and devices) applications. As later discussed herein, the FDA reaffirmed its commitment to diversity and inclusion, and with respect to standards for the collection and reporting of race and ethnicity data via a 2024 draft guidance, which is intended to replace the 2016 guidance.

November 2020 - Enhancing the Diversity of Clinical Trial Populations - Eligibility Criteria, Enrollment Practices, and Trial Designs

Continuing its focus on diversity in clinical trials, in November 2020, the FDA issued a guidance document titled, “Enhancing the Diversity of Clinical Trial Populations - Eligibility Criteria, Enrollment Practices, and Trial Designs,”

 which focuses on sponsors and provides four sets of recommendations that can be applied in clinical trial design to ensure participants are diverse.

In issuing the guidance, the FDA satisfied the mandate under section 610(a)(3) of the FDA Reauthorization Act of 2017 (FDARA) (21 U.S.C. 360bbb note). Consistent with the FDARA mandate, the guidance discusses: (1) broadening eligibility criteria and avoiding unnecessary exclusions for clinical trials; (2) developing eligibility criteria and improving trial recruitment so that the participants enrolled in trials will better reflect the population most likely to use the drug if it is approved, while maintaining safety and efficacy standards; and (3) applying the recommendations for broadening eligibility criteria to clinical trials of drugs intended to treat rare diseases or conditions. The guidance also notes that sponsors should design clinical trials in ways to achieve participant diversity.

Examples of FDA recommendations to sponsors on how to improve diversity include:

Sponsors should work to ensure that eligibility criteria serve the goal of having a representative sample of the population for whom the drug has been developed and examine each exclusion criterion to determine whether it is needed to help assure the safety of trial participants or to achieve the study objectives.

Sponsors should enroll participants who reflect the characteristics of clinically relevant populations with regard to age, sex, race, and ethnicity and can seek to do so via (1) inclusion of children and adolescents in confirmatory clinical trials involving adults when appropriate, (2) inclusion of women in adequate numbers to allow for analysis by sex, and (3) inclusion of racial and ethnic minorities and the analysis of clinical trial data by race and ethnicity.

Broadening eligibility criteria using enrichment strategies

 and should work to make trial participation less burdensome for participants. The FDA highlights use of telemedicine in trials and states: “During the study design phase, consider the recruitment challenges that may occur because of the planned visit schedule and difficulties with accessibility (including for individuals with disabilities) to trial sites: reduce the frequency of study visits to those needed to appropriately monitor safety and efficacy, and consider whether flexibility in visit windows is possible and whether electronic communication (e.g., telephone/mobile telephone, secured electronic mail, social media platforms) or digital health technology tools can be used to replace site visits and provide investigators with adequate real-time data. Consider the use of mobile medical professionals, such as nurses and phlebotomists, to visit participants at their locations instead of requiring participants to visit distant clinical trial sites.”

Adopt enrollment and retention practices that enhance inclusiveness. Sponsors should implement more inclusive strategies for public outreach and education, including incorporating patient-focused research into clinical trial design.

April 2022 - Diversity Plans to Improve Enrollment of Participants from Underrepresented Racial and Ethnic Populations in Clinical Trials

Following the November 2020 guidance, in April 2022, the FDA released the draft guidance titled “Diversity Plans to Improve Enrollment of Participants from Underrepresented Racial and Ethnic Populations in Clinical Trials Guidance for Industry.”

 The guidance recommends sponsors develop a Race and Ethnicity Diversity Plan to assist in enrolling underrepresented racial and ethnic populations in clinical trials.

Specifically, the draft guidance expands on the 2016 guidance and provides recommendations to sponsors on the approach for developing a Race and Ethnicity Diversity Plan “to enroll representative numbers of participants from underrepresented racial and ethnic populations in the United States, such as Black or African American, Hispanic/Latino, Indigenous and Native American, Asian, Native Hawaiian and Other Pacific Islanders, and other persons of color, in clinical trials.”

The draft guidance contains a table with suggested elements of a diversity plan and outlines the content of such plans, which includes:

Sponsors should define enrollment goals for underrepresented racial and ethnic participants as early as practicable.

The plan should describe the planned assessment of race and ethnicity.

The plan should outline the sponsor’s plan to collect data to explore the potential for differences in safety and/or effectiveness associated with race and ethnicity throughout the entire development life cycle of the medical product and not just during the pivotal trial(s) or studies.

Many of the recommendations in the April 2022 draft guidance are identical to the requirements set forth in the FDORA. At the end of 2022, as part of the Consolidated Appropriations Act, Congress passed the FDORA, which requires sponsors to submit diversity action plans to the Secretary of the Department of Health and Human Services (HHS) for any Phase III or other pivotal drug study and most device studies.

The requirement for diversity plans in the FDORA include identifying enrollment goals for subsets of the population by group, sex, racial and ethnic characteristics, rationale for these enrollment goals, and any relevant strategies on how the sponsor plans on how to reach those enrollment goals. Pursuant to FDORA, the FDA must issue updated draft guidance on Diversity Action Plans.

Recent FDA Guidance and Action – January 2024 Collection of Race and Ethnicity Data in Clinical Trials and Clinical Studies for FDA-Regulated Medical Products

In January 2024, the FDA released the draft guidance document “Collection of Race and Ethnicity Data in Clinical Trials and Clinical Studies for FDA-Regulated Medical Products Guidance for Industry.”

 The guidance was mandated as part of FDORA regarding the collection of race and ethnicity data in clinical trials. Once finalized, this guidance will replace the 2016 FDA guidance regarding collection of race and ethnicity data.

The guidance provides that using standard terminology for race and ethnicity helps ensure that data are collected and reported consistently in submissions to the FDA. The agency’s recommended approach is based on the OMB Statistical Policy Directive No. 15 (Policy Directive 15) and was developed in accordance with section 4302 of the Affordable Care Act; HHS Implementation Guidance on Data Collection Standards for Race, Ethnicity, Sex, Primary Language, and Disability Status; and the 25 Food and Drug Administration Safety and Innovation Act (FDASIA) Section 907 Action Plan.

The draft guidance provides recommendations on: (1) meeting the requirements set forth in the 1998 final rule regarding presentation of demographic data in investigational new drug applications and new drug applications; (2) the collection of race and ethnicity data in biologics license applications and medical device applications; and (3) addressing the FDASIA Section 907 Action Plan to improve the completeness and quality of demographic data collection and reporting.

The FDA recommends that trial participants be requested to self-report race and ethnicity information, with participants being permitted to designate a multiracial identity. While such data may be available in a trial participant’s medical record, the FDA states that race and ethnicity should not be assigned by the study team conducting the trial and recommends that investigators and/or other clinical study staff verify the accuracy of the information provided in the medical record with the study participant.

With respect to participant self-reporting, similar to the 2016 guidance and to remain consistent with OMB Policy Directive 15, the FDA recommends using a two-question format for requesting race and ethnicity information, with the ethnicity question preceding the question about race:

1. Are you Hispanic/Latino or not Hispanic/Latino?

With respect to race, the FDA recommends the following, minimum, choices be offered: American Indian or Alaska Native; Asian; Black or African American; Native Hawaiian or Other Pacific Islander; and White.

 The FDA also encourages sponsors to provide detailed breakdowns when multiple responses are selected or at a minimum to note that “more than one race” was reported. Where appropriate, the FDA recommends using more-detailed categories by geographic region to provide sponsors flexibility in characterizing race and ethnicity.

Moving Forward: The Use of Decentralized Clinical Trials (DCTs) and Digital Health Technology

As the emphasis on encouraging diverse populations to participate in clinical trials increases, sponsors should use all tools available to them to help increase diverse recruitment. One such tool is the use of DCTs (either a wholly or partially decentralized model) for sponsors to help fulfill these obligations. In May 2023, the FDA released the draft guidance “Decentralized Clinical Trials for Drugs, Biological Products, and Devices - Guidance for Industry, Investigators, and Other Stakeholders”

DCTs are clinical trials in which some or all trial-related activities occur at locations other than traditional clinical trial sites. In the 2023 DCT guidance, FDA recognizes that use of decentralized elements, such as conducting follow-up visits in a participant’s home or via telemedicine, increases the convenience of such activities for research participants and can assist in diversity efforts.

A key element in the draft guidance centers around sponsor responsibilities for striving toward diversity and inclusiveness in their trial populations. The guidance specifies that sponsors engaging in outreach through local health care institutions may facilitate recruitment of participants in areas where there are limited or no traditional clinical trial sites that may increase diversity. 

The focus on diversity is highlighted by a press release announcing the guidance, which specifically highlights the value of DCTs in regard to enhancing diversity. In the release, Commissioner Califf stated:

"As we seek to improve our evidence generation system, decentralized clinical trials may enhance convenience for trial participants, reduce the burden on caregivers, expand access to more diverse populations, improve trial efficiencies, and facilitate research on rare diseases and diseases affecting populations with limited mobility."

Additionally, in the design of clinical trials, including DCTs, sponsors should consider the incorporation and use of digital health/telemedicine technologies in trials. The FDA has provided guidance on use of such technologies in clinical trials and notes their usefulness in reaching diverse populations previously not easily accessible.

Looking Ahead: What Sponsors Need to Know

Sponsors should be aware that the FDA’s focus on expanding diversity in clinical trials will not disappear any time soon. Instead, we expect the FDA’s focus on the issue to only intensify.

As a result, we recommend sponsors do their best to comply with FDA recommendations outlined in this article and in the FDA’s guidance documents. Even though the recent FDA documents are purely draft documents, sponsors should aim to comply with these recommendations so they are better prepared to comply with the final guidance when it is released.

Finally, sponsors should be aware that additional final guidance is likely to be announced over the next few years, including final guidance regarding diversity action plans. Sponsors must be ready to quickly implement these recommendations.

1. See FDA Guidance Document “Collection of Race and Ethnicity Data in Clinical Trials Guidance for Industry and Food and Drug Administration Staff “ October 2016”; 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/collection-race-and-ethnicity-data-clinical-trials

2. See FDA Guidance Document “Enhancing the Diversity of Clinical Trial Populations — Eligibility Criteria, Enrollment Practices, and Trial Designs Guidance for Industry” November 2020; 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/enhancing-diversity-clinical-trial-populations-eligibility-criteria-enrollment-practices-and-trial

3. Enrichment is a trial design strategy in which there is a targeted inclusion of certain populations, with the goal of more readily demonstrating the effect, if any, of the drug. See Id.

5. See FDA draft Guidance “Diversity Plans to Improve Enrollment of Participants from Underrepresented Racial and Ethnic Populations in Clinical Trials Guidance for Industry” April 2020; 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/diversity-plans-improve-enrollment-participants-underrepresented-racial-and-ethnic-populations

8. See FDA draft Guidance “Collection of Race and Ethnicity Data in Clinical Trials and Clinical Studies for FDA-Regulated Medical Products Guidance for Industry” January 2024; 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/collection-race-and-ethnicity-data-clinical-trials-and-clinical-studies-fda-regulated-medical

13. See FDA draft Guidance “Decentralized Clinical Trials for Drugs, Biological Products, and Devices - Guidance for Industry, Investigators, and Other Stakeholders” May 2023; 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/decentralized-clinical-trials-drugs-biological-products-and-devices

14. See FDA Guidance “Digital Health Technologies for Remote Data Acquisition in Clinical Investigations” December 2023; 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/digital-health-technologies-remote-data-acquisition-clinical-investigations

; See FDA Digital Health Technologies (DHTs) for Drug Development, 

There is significant potential in decentralized models and digital health technology to expand diversity in clinical trials.

An Overview of FDA Diversity-Related Documents for Clinical Trials

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DVCR is Designed Differently

Today, clinical trial data collection faces increased complexity due to data duplication between research systems and electronic health records (EHRs), particularly in oncology studies. Manual processes, such as data entry, consume significant time and resources. Over 50% of clinical trial data is duplicated between research systems and hospital EHRs, with around 20% of total study costs typically allocated to data duplication and verification.

The number of data points collected in oncology trials has surged dramatically over the past decade, driven by advances in genomic technologies, digital health tools, and personalized medicine. While this increase in data volume enhances our ability to understand and treat cancer more effectively, it also presents significant challenges in data management and analysis. In typical Phase III oncology trials, approximately 10,000 data points are collected per patient. However, in trials incorporating genomic and digital health data, this number can multiply ten to a hundredfold.

As a result, study sites, particularly clinical research coordinators (CRCs), face increased workloads, complex data management tasks, and the need for specialized training, leading to higher personnel costs. Sponsor companies incur additional expenses due to investments in advanced data management tools, extended trial timelines, and source data verification (SDV). To mitigate these challenges, sites and sponsors must explore innovative solutions, collaborate with stakeholders and vendors, and ensure regulatory compliance to improve efficiency, reduce costs, and enhance cancer treatment outcomes.

EHR to electronic data capture (EHR-to-EDC), or eSource technology and processes, offers a promising solution, delivering significant time and cost savings by streamlining data transfer.

The European EIT Health-supported EHR2EDC project estimated a total time of three minutes per data point in oncology trials, demonstrating substantial efficiency gains.

This paper presents a use case from Memorial Sloan Kettering Cancer Center (MSK), emphasizing the critical role of CRCs. It highlights the burdensome nature of current double-entry processes and supports the three-minute-per-data-point estimate. Additionally, it revisits the value generated for investigational sites and sponsors by introducing this technology, exploring the transformative potential of eSource for future clinical trials.

The study employs a qualitative structured interview guide to understand the data entry process during clinical trials. An in-depth, semi-structured interview was conducted with an experienced CRC to gather insights into workflows, challenges, and perceptions regarding data entry tasks. Open-ended questions allowed for rich, nuanced responses, capturing the complexity and variability of the process. The validity and generalizability of the interview outcomes were assessed and found to correspond well with CRC practices at MSK.

Gynet Santiago is a seasoned CRC at MSK, with 16 years of experience and involvement in over 50 clinical studies. She summarizes her role as, “I am responsible for collecting, extracting, and entering data for research projects, databases, and clinical trial protocols. This includes reviewing patient charts, existing databases, and other sources within a specific timeframe.”

The CRC is pivotal in executing clinical trials, with responsibilities spanning various trial phases to ensure compliance with regulatory requirements and ethical standards, while prioritizing patient safety and data integrity. During trial execution, CRCs manage participant recruitment, screening, and enrollment, ensuring informed consent is obtained. They accurately collect and document clinical data, monitor participants for adverse events, and ensure adherence to the trial protocol. CRCs act as liaisons between participants, investigators, and sponsors, maintaining communication and addressing issues. They also ensure regulatory compliance by maintaining accurate documentation and assisting with audits. These responsibilities are crucial for the smooth operation of trials, data integrity, and participant safety. Additionally, CRCs often manage multiple studies simultaneously, requiring efficient context switching throughout the week.

Navigating the complexities of EDC data entry

In clinical trials, EDC data entry is a multi-faceted process involving several crucial steps performed by a CRC (see Figure 1). This process, while systematic, is often challenging due to its time-consuming nature and the meticulous attention to detail required. 

The following is an overview of how a CRC manages the process of retrieving and manually entering data into an EDC system.

 One of the first tasks a CRC faces is finding and allocating time for EDC data entry. This often involves scheduling data entry activities around other demanding clinic responsibilities. For instance, a CRC might set aside Friday afternoons every two weeks for data entry once all other clinic activities have been addressed. Prioritizing EDC data entry among other tasks can be challenging, as the coordinator must balance immediate clinical duties with the time-consuming process of data entry. The irregularity and unpredictability of clinical activities can make it difficult to allocate consistent time slots for this purpose. Or as Santiago puts it, “Each day is based on what the priority is for that day, that’s how I know how to allocate my time. So, for example, if there’s a data lock coming up or an audit coming up for a particular study, that’s always going to be a top priority for me for that day or for that week.”

Patient information retrieval and manual searching for patient information. 

Once time is allocated, the CRC manually searches for patient information within EHRs. Unlike records specifically designed for clinical trials, these records are complex and primarily geared toward billing, with patient information spread across various locations, pages, and fields, including free-text entries. Confidence in the data source can vary, and locating the correct data points requires a detailed, page-by-page review, making this step particularly time-consuming.

The complexity of EHR systems presents additional challenges. Patient information is not always recorded in a standardized manner, which means that the CRC must have a thorough understanding of how different healthcare providers document data. This lack of standardization can lead to difficulties in finding specific data points, as information might be spread across multiple pages or hidden within lengthy notes. Santiago explains: “The way that EHR is set up is, once you open the records, it displays different categories of information in a particular folder, and it can be a challenge to locate the right data point because of the large amount of information that you must read through to find that correct data point.”

After retrieving the necessary patient information, the CRC logs into the sponsor’s EDC system using the appropriate URL and credentials. The next step involves navigating the EDC system to find the correct case report form (CRF) for data entry. This can be challenging due to the system’s complexity and the need to ensure that the information entered matches the patient’s records accurately. The CRC must be familiar with the EDC system’s layout and functionality to efficiently locate the correct CRF pages. It is a demanding process as Santiago explains: “It really is familiarizing yourself with the EDC. So EHR is one aspect of it where you’re able to know where it is. And now you must go to the EDC and confirm, okay, I’m entering this information in the proper place that it needs to be for the database.” And sometimes errors can multiply—“There’s challenges when you’re entering data into the EDC and inaccurate system queries require information that’s not always available,” adds Santiago.

After entering the data, the CRC reviews it for accuracy and resolves any discrepancies. This review process might involve understanding the data’s meaning, consulting with other study team members, and performing self-quality assurance checks to ensure data integrity. Ensuring data accuracy is crucial, as any errors can lead to significant issues in the trial’s results and regulatory compliance. Therefore, the CRC must be diligent in verifying that the data entered the EDC system accurately reflects the information in the patient’s medical records. Santiago highlights one common issue: “Sometimes the same data is being entered into different places in the EDC. So, I’m always pushing back and saying, why are we entering the same data in multiple places?”

Query resolution and collateral time efforts. 

Queries from the sponsor or contract research organization (CRO) can arise weeks or months after initial data entry, requiring the CRC to spend additional time for resolution. This involves revisiting medical records to locate specific data points, often repeating original data retrieval steps. If significant time has passed, the CRC may need to refamiliarize themselves with the patient’s records and data points.

Managing queries is time-consuming and demanding, often due to double data entry. As Santiago explains, “Query resolution is part of the role. I would say 50% is data entry, and 50% can be query resolution, especially if a study is active.” Queries can be frequent and complex. Adds Santiago: “Queries can be raised weekly or even daily, and sponsors usually require them to be resolved within one or two weeks.” This process involves thorough research, confirming data accuracy. During this process, the CRC may also need to check or verify with other study personnel to address the query. Monitoring visits by sponsors or CROs are crucial for ensuring data quality and protocol adherence. These visits involve reviewing data entered into the EDC system and verifying its accuracy against source documents. The CRC may also implement process improvements based on queries and share these with the broader study team.

The interview highlights the multifaceted role of a CRC, including data entry, patient information retrieval, and managing queries. The CRC must navigate systems such as EDCs, clinical trial management systems, and EHRs, often facing challenges such as locating specific data points and handling system queries. Effective query resolution is crucial, often consuming as much time as initial data entry, underscoring the need for efficient processes and tools to streamline these tasks.

Three minutes and 5,000 hours: A significant investment of time

During the European EIT Health-sponsored EHR2EDC project from 2018 to 2020, AstraZeneca and Sanofi collaborated on a retrospective analysis to estimate the average total time spent per data point per patient in a Phase II-III oncology study. The combined analysis determined that local study personnel spend at least three minutes per data point. This time encompasses all the tasks we covered in the interview, including data searches, manual entry, checking, reviewing, and resolving queries.

To put this in context, for an oncology study involving 10 patients, each with 10,000 data points, this equates to about 5,000 hours of work. Scaling up to an ordinary Phase III study with over 200 patients, the time and associated costs increase exponentially (see Figure 2).

Based on the MSK use case, we can conclude that straightforward data points can be entered within three minutes total time if the data is normal. However, complex data points, such as those involving adverse events or abnormal lab values, can take significantly longer. Santiago explained that query resolution is a significant part of her workload, often consuming 50% of her time. Queries can range from simple confirmations to complex requests requiring additional information from treating physicians or further investigation. She noted that resolving queries can be particularly challenging and time-consuming when dealing with historical data. She agreed that the estimation of three to five minutes per data point is reasonable for straightforward cases but emphasized that overall time varies. Santiago also highlighted the potential for eSource technology to streamline data entry and reduce manual processes and query resolution, potentially saving more than 50% of the current time required. This underscores the variability and complexity of data management in clinical research.

What is eSource technology and what can it do?

EDC-to-EDC, or eSource, is a streamlined process specifically designed to transfer routinely collected EHR data relevant to clinical research, particularly data collected at investigator/hospital sites during clinical trials (including randomized controlled trials). This transfer occurs with patient consent, meeting regulatory eSource requirements, into either an EDC system or the sponsor’s study database. It’s important to emphasize that EHR as eSource does not involve replacing staff or vendors for data entry at sites, duplicative data capture, or extraction of datasets from the EHR.

In the case of the “eSource data flow” and the transfer of mapped study data from EHR to study data base, it will always be in the control of the CRC, who will have oversight and final say of data transfer. In this perspective, the eSource technology should be viewed as a “virtual research assistant.”

Contrasting traditional EDC trial with eSource-enabled trial

The eSource approach improves clinical trial conduct. By automating data transfer from existing EHR directly to EDC systems, it eliminates manual entry, reducing investigator site burden and enhancing data quality (see Figure 3). This automation minimizes transcription errors, improving data accuracy and streamlining and sometimes eliminating SDV, leading to cost savings and faster trial timelines. Furthermore, eSource fosters collaboration by integrating EHR and EDC systems. Sponsors gain valuable insights into site data collection processes, enabling the optimization of electronic CRFs to align with specific EHR capabilities. This collaborative approach ultimately enhances overall clinical trial efficiency.

Ongoing studies at MSK utilizing data from past clinical trials to simulate feasibility and outcomes with eSource technology have shown promising results. These findings strongly support the value generation as outlined in this report.

Consider an example: An industry-sponsored oncology trial includes three investigational sites, each with 10 patients. All sites meet the minimum eSource HCO requirements for early adopters, including EHRs with structured data and coding standards for data domains such as laboratory results, vital signs, and medications. They have adopted the FHIR® (Fast Healthcare Interoperability Resources) standard to ensure smooth information flow across platforms and organizations.

In this example, all sites are eSource-enabled, encompassing 300,000 data points (10,000 per patient) across the mentioned domains, accounting for over 50% of the entire study data. Implementing eSource technology in this study is expected to significantly reduce site burden, cutting site staff time by 50%, equivalent to more than 2.5 full-time equivalent months per site. Most issues from double entry and query resolution will be eliminated, leading to faster trial completion. There will be a significant reduction in SDV from the sponsor’s side and a notable decrease in study costs, estimated at $150.000 per site.

In the coming years, hybrid eSource-enabled trials will include more eSource-capable sites among traditional “double-entry EDC” sites. This hybrid approach may not immediately reduce the study database lock time, but it will enhance efficiency and reduce site burden at eSource sites. A transformational shift will occur when trials become 100% eSource-enabled. These trials will likely have fewer but larger super-sites, transferring over 80% of all study data as eSource. This shift will enhance value generation for investigational sites by reducing the total time per data point by over 90%. This improvement in efficiency and resource utilization will almost completely eradicate SDV and other time-consuming processes. Fully eSource-enabled studies are expected to reduce total study costs by over 20%, achieving database lock significantly faster.

This MSK use case highlights the significant benefits of eSource technology and corroborate time metrics in supporting CRC and site personnel during trial execution. The widespread adoption of eSource technology represents a paradigm shift in hospital clinical trials, optimizing processes, saving time, and reducing double entry. If innovations such as eSource, or EHR-to-EDC, were fully implemented, they could also enable research that might otherwise not happen, paving the way for the development of medicines that otherwise would never reach patients.

, PhD, is Industry Science Director, i-HD; 

 is a Clinical Research Coordinator, Memorial Sloan Kettering Cancer Center (MSK); 

Memorial Sloan Kettering Cancer Center (MSK)

1. Kalankesh, L.R.; Monaghesh, E. Utilization of EHRs for Clinical Trials: A Systematic Review. 

https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-024-02177-7

2. Passut, C. Oncology Trials Outpacing Rest of the Field in Complexity and Duration. CenterWatch. May 10, 2021. 

https://www.centerwatch.com/articles/25599-oncology-trials-outpacing-rest-of-the-field-in-complexity-and-duration-study-shows

3. Monira, S; Toral, M. Possibilities and Challenges for Digital Medicine in Oncology Clinical Trials.

https://acrpnet.org/2023/08/possibilities-and-challenges-for-digital-medicine-in-oncology-clinical-trials/

4. Parab, A.A.; Mehta, P.; Vattikola, A.; et al. Accelerating the Adoption of eSource in Clinical Research: A TransCelerate Point of View. 

https://pubmed.ncbi.nlm.nih.gov/32128701/

5. Garza, M.; Myneni, S.; Nordo, A.; et al. eSource for Standardized Health Information Exchange in Clinical Research: A Systematic Review. 

A use case by Memorial Sloan Kettering Cancer Center explores the potential of EHR-to-EDC.

Nicole C. Woitowich, PhD

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