CLINICAL TRIALS - Need for Accessibility to Meet FDA Guidance for Decentralized Trials

By: Neil Vivian

Abstract: As decentralized clinical trials (DCTs) gain in popularity, regulators are pushing sponsors to make trial populations more diverse. Progress toward greater diversity has been uneven, largely due to factors such as the COVID-19 pandemic and the limited manageability of voluminous data generated via wearable devices. Nevertheless, advances in electronic data collection and analysis are helping to make DCTs more accessible to broader and more diverse patient populations. Further innovations, particularly in artificial intelligence technology, are expected to accelerate these trends.

The decentralized clinical trial (DCT) model received a significant boost in May 2023, when the U.S. Food and Drug Administration (FDA) issued a draft guidance encouraging the design and implementation of clinical trials conducted at the point of care, facilitated by the use of wearables and other technologies.¹ The guidance positioned technology-enabled DCTs as a means to help researchers become “more agile and efficient”2, emphasizing the following potential benefits:¹

• Improved recruitment, enrollment, and retention: The DCT model enables recruitment of more diverse patient populations, and avoids having to focus recruitment efforts around trial sites.
• Collection of patient data in real time: This capability is a vast improvement over traditional trials’ 7-14-day timeframe for entering patient data into a trial database.
• Reduced drug development costs and administrative burden on investigators and sponsors: The DCT approach eliminates the need for 100% source data verification (SDV).

The basic rationale for DCTs is that they can “bring clinical trials to the patient.” This approach enables the movement of prospective data collection away from the “brick and mortar” of the investigator site. By integrating data collected via digital technology (e.g., wearables, telehealth visits, online patient diaries, electronic informed consent [eConsent] programs, patient apps), DCTs allow sponsors to:²

• Gain access to expanded source evidence (e.g., labs, insurance claims, media reports)
• Encourage enrollment of more diverse patient populations within community settings
• Obtain data more representative of a “real-world” population to support more informed treatment decisions

DCT Policy & Planning Considerations

As further evidence of its advocacy of the DCT model, the FDA, as outlined in its May 2023 draft guidance, aims to operationalize goals to reduce on-site monitoring, maintain data integrity, and oversee patient safety and product efficacy using remote monitoring technologies.^1,3

The FDA’s DCT-related policies are informed by the following planning considerations:

• 15% to 20% of trials never enroll a single patient⁴
• Two-thirds of sites fail to reach enrollment goals^4,5
• 70% of potential trial participants in the U.S. live more than two hours away from the nearest study center⁶
• More than half of patients surveyed say they are more likely to participate in a clinical trial if home care is offered⁷
• Employing virtual/direct-to-patient services helps maintain patient retention rates above 95%⁵

The DEPICT Act: A Push for Greater Diversity

Meanwhile, the DEPICT Act (H.R.6584), introduced in February 2022,⁸ has sharpened regulators’ focus on increasing diversity in clinical trials. This piece of legislation aims to strengthen diversity through enhanced data reporting and increased resources for underrepresented communities. It requires Investigational New Drug (IND) and Investigational Device Exemption (IDE) applicants to report trial enrollment targets by demographic subgroup (e.g., age, race, ethnicity, sex). Those targets should be accompanied by a Diversity Action Plan outlining strategies for reaching enrollment goals and improving diversity.

The DEPICT Act also grants the FDA authority to mandate post-market studies when sponsors fail to meet diversity enrollment targets without sufficient justification. Additionally, it requires the FDA to publish an annual report analyzing data provided by sponsors on their progress toward improving diversity.⁸

Uneven Progress Toward Greater Access & Diversity

So, how successful have the FDA draft guidance and the DEPICT Act been in increasing access to and diversity in clinical trials? The answer thus far: not so much. To be fair, the uneven success of these regulatory and legislative initiatives is largely due to the COVID-19 pandemic, which had a major impact on new clinical trial starts, as vividly illustrated by a sharp downturn in the second quarter of 2020 (Figure 1). The pandemic left patients unable to travel to trial sites, resulting in delays or cancellation of new trials and suspension of ongoing trials. Presumably, earlier and more widespread adoption of the DCT model would have been far less disruptive to clinical research programs.

Additionally, the DCT model has run into an unforeseen obstacle: wearables generate more data than is needed for sponsors to enter into electronic data collection (EDC) systems. A potential solution to this logjam is to apply filters to wearables-generated data to limit the volume of returned data. The filters can be customized to focus on key values such as those that are out of a specified range, or those that reflect rapid changes in a patient’s condition.

Digital data collection also raises privacy concerns. These can be addressed by de-identifying data presented to an EDC platform to safeguard patient privacy.

Enhancing Patient Access

Facilitating patient access is crucial to promoting and increasing diversity in trial populations. DCTs and hybrid trials enable patients to be more involved as trial participants, as they allow direct entry of patient-reported data (e.g., via wearables) without having to travel to the trial site (Figure 2).

DCT and hybrid models also provide advantages to sponsors and sites, particularly in terms of better and earlier identification of at-risk patients, compared to traditional data-gathering methods. Other key advantages include enhanced patient safety and access to patient data in real time.

Achieving diversity in clinical trials is not easy and requires continuous collaboration between medical affairs teams and clinical research teams. These teams must avoid bias and improve clinical care quality for marginalized populations, and reduce barriers to trial access.

Anju’s clinical intelligence solution, TA Scan, enables sites to visualize global ethnicity data, socio-economic data, and site/principal investigator (PI) experience on a single map. It also filters data by age, gender, racial distribution, and average income. Perhaps the most unique feature of TA Scan is its capacity to visualize and analyze newly integrated European diversity data in addition to US diversity data.

Facilitating Informed Consent

 Informed consent issues were the number 3 reason for FDA Form 483 findings in 2017 and 2022.⁹ However, total informed consent issues declined from 10.7% of 483 findings^* in 2017 to 5% in 2022.⁶ The decline appears to reflect more widespread adoption of eConsent, a technology-enabled patient engagement tool that can improve site/patient discussions and clinical trial efficacy.

^*An FDA Form 483 is issued when an inspector(s) has observed any conditions in possible violation of the Food Drug and Cosmetic (FD&C) Act and related Acts.

A key advantage of eConsent is that it leverages advanced technologies (e.g., video/audio, pictures/diagrams, electronic signature, materials in different languages) to facilitate provision of consent (Figure 3).

eConsent also allows for greater consistency and regular updating of materials to ensure use of the most recent versions. Moreover, eConsent is extremely convenient; it can be deployed remotely, allowing patients to access consent materials from home via portals; eConsent also allows patients to review eligibility criteria earlier in the screening process, potentially facilitating more informed decision-making.

The pandemic encouraged more widespread use of eConsent, and adoption of this tool continues to increase, but the adoption rate is slow, reflecting the conservatism of the industry. Institutional review boards (IRBs) have been a major stumbling block, particularly when a trial involves multiple IRBs. Nevertheless, guidance from the FDA and other authorities has eased some IRB-related roadblocks. As a result, IRBs are now generally more open to eConsent.

Another key advantage of eConsent is that it can help to accelerate trial activation. Speed is vital in all clinical trials. Many trials require rapid turnaround due to disease severity, a factor that can make data management needs more complex and slow to implement. The best EDC systems deliver flexibility and adaptability in the design from the beginning. For example, Anju Software was recently involved in a trial in which its EDC system, TrialMaster, was activated in two weeks, compared to the industry standard of approximately 4-12 weeks.

Streamlining Electronic Data Collection & Analysis

Recognizing the need to speed up efforts to enhance patient access, numerous vendors have developed intuitive EDC suites with built-in eConsent, electronic patient-reported outcomes (ePROs), and electronic clinical outcome assessment (eCOA) software. These offerings enable collection of medical histories and medication information from patient diaries, surveys, and validated questionnaires. They empower patients to enter data directly into the system in real time, using their own devices, yet do not require source data verification. Additionally, these tools allow real-time evaluation of compliance and outcomes, and enable flagging of patients who may benefit from a check-in call, follow-up visit, or other timely intervention.

One notable trend is the development of intuitive, web-based, clinical business intelligence platforms that apply rules to large volumes of data to analyze trends of interest. Such platforms can be used to mine data from extensive global databases of clinical trials, investigators, publications, and other sources and variables. These platforms thus enable the analysis, measurement, and ranking of trial and site data, including key opinion leader and principal investigator experience and involvement.

Notably, some of the newer business intelligence platforms can help sponsors find sites that can meet enrollment needs by recruiting participants from a trial’s target population. This feature can help sponsors meet diversity goals, and can also provide justification for DEPICT Act exemption from the FDA.

Some of the more advanced platforms include a feasibility module, whereby the sponsor enters trial parameters, target countries, the desired number of patients, and other key variables over a defined period of time. The module thus facilitates identification of countries and/or regions to consider or avoid, based on competitive trial activity (or lack thereof) in those geographic areas. Incorporation of Monte Carlo simulation can enable modification of parameters to help determine whether a study is feasible in a specific location. In case of underperforming sites in an ongoing trial, the module can identify alternate/backup sites.

Future Directions: Leveraging AI to Facilitate DCTs

As in many fields, artificial intelligence (AI) is increasingly used in medical research, particularly in the development of new antibiotics targeting drug-resistant bacteria. The utility of AI and machine learning in drug discovery and development lies in their ability to screen thousands of potential compounds to isolate a handful that may be druggable.

Similarly, AI/machine learning has great potential in the clinical trial setting, although their use in DCTs is still in its infancy. Sponsors are exploring the use of AI to streamline various aspects of DCTs including identifying eligible patients. AI can also be useful in reviewing and analyzing voluminous data that are currently stored in data warehouses; the technology can be deployed to detect trends in ePROs, medication/protocol adherence, and other drug-related data.

Additionally, as sponsors respond to intensifying demands to make trial populations more diverse and reflective of the general population, AI may prove valuable in identifying medications and other interventions that are effective in specific patient populations, whether stratified by age, sex, ethnicity, geography, disease variant, or molecular makeup.

The nascent field of AI is just one example of technological advances that are expected to make DCTs more accessible to broader and more diverse patient populations. The next few years will be a crucial time to observe how quickly and thoroughly such advances are adopted in the DCT setting.

Sidebar: TA Scan

TA Scan is Anju’s web-based clinical intelligence platform that analyzes, measures, and ranks trial and site data, including key opinion leader (KOL) and investigator experience and involvement. Designed to support the entire clinical study workflow, TA Scan can facilitate trial planning and benchmarking by helping sponsors:

• Understand the competitive landscape
• Estimate patient enrollment benchmarks
• Identify sites with capacity to recruit and that support diversity strategies

TA Scan can pinpoint specific patient populations on a global or local scale by browsing the literature to identify relevant publications, producing a citation list with PubMed links to each article, along with semantic linking of data types to enable assessment of trial results. It can also quantify the number of trials in a specific disease subtype over a defined time period, sorted by phase and geographic area (Figure 4).

TA Scan yields intelligence on currently recruiting trials, regulatory lag, and number and experience of sites and investigators, with built-in Gantt charts to facilitate comparison of competitive trial timelines (Figure 5).

TA Scan’s site inference algorithm unlocks undisclosed site data, with an unbiased investigator scoring system based on clinical or scientific footprint. The platform’s site capacity calculator enables assessment of a site’s ability to accommodate additional trials; sites with sufficient capacity can be layered on a diversity distribution map to streamline site selection and diversity strategy.

In summary, TA Scan is an all-in-one tool that collects, aggregates, and analyzes clinical, publication, and congress data, with integrated analytics modules for quick and easy analysis. Its features include weekly data updates, exportable graphical outputs and reports, a self-driven and intuitive user interface, and dedicated customer support covering all time zones.

References

1. Decentralized Clinical Trials for Drugs, Biological Products, and Devices: Guidance for Industry, Investigators, and Other Stakeholders. U.S. Food and Drug Administration; May 2023. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/decentralized-clinical-trials-drugs-biological-products-and-devices.

2. Wechsler J. FDA policies support shift to decentralized clinical trials. Applied Clinical Trials. 2019 Feb 8. https://www.appliedclinicaltrialsonline.com/view/fda-policies-support-shift-decentralized-clinical-trials.

3. Combs KB, Levine GH, Peloquin D, Purcell MJ. FDA guidance clarifies approach to decentralized trials. Ropes & Gray; 2023. https://www.ropesgray.com/en/insights/alerts/2023/05/fda-guidance-clarifies-approach-to-decentralized-clinical-trials.

4. Lo C. The numbers game: boosting clinical trial enrollment. Pharmaceutical Technology. 2014 Feb 5. https://www.pharmaceutical-technology.com/features/featurethe-numbers-game-boosting-clinical-trial-enrolment-4171654/?cf-view&cf-closed.

5. Sweeney M. Direct-to-patient clinical trials: strategies for success. Applied Clinical Trials. 2018 Nov 29. https://www.appliedclinicaltrialsonline.com/view/direct-patient-clinical-trials-strategies-success.

6. Anderson D, Fox J, Elsner N. Digital R&D: transforming the future of clinical development. Deloitte; 2018. https://www2.deloitte.com/us/en/insights/industry/life-sciences/digital-research-and-development-clinical-strategy.html.

7. Amengual T, Adams H, Mink J, Augustine E. Rare disease clinical research: caregivers’ perspectives on barriers and solutions for clinical research participation (I8.001). Neurology. 2016;86(15 suppl). https://doi.org/10.1212.WNL.86.16_supplementI8.001.

8. H.R.6584 – DEPICT Act. Congress.gov; 2024. https://www.congress.gov/bill/117th-congress/house-bill/6584.

9. Inspection observations. U.S. Food and Drug Administration; 2024. https://www.fda.gov/inspections-compliance-enforcement-and-criminal-investigations/inspection-references/inspection-observations.

Neil Vivian is Senior Director of Business Solutions, Anju Software. He provides technical support to the Business Development group and positions Anju Solutions and Services to potential and existing clients. His Product Manager responsibilities include providing guidance and high-level business requirements for new product features based on his industry experience and understanding of new emerging Regulatory Guidance. He has over 43 years’ experience in the software industry built from a solid foundation in the Defense Industry, 29 of those focused on Life Sciences. He has a BSc in Physics and Engineering Science and MSc in Information Technology.