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

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(DCT) model received a sig­nificant boost in May 2023, when the U.S. Food and Drug Ad­ministration (FDA) issued a draft guidance encouraging the design and implementation of clinical trials conducted at the point of care, facilitated by the use of wearables and other technolo­gies.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

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

• 15% to 20% of trials never enroll a sin­gle patient
• Two-thirds of sites fail to reach enroll­ment goals⁴,
• 70% of potential trial participants in the U.S. live more than two hours away from the nearest study center
• More than half of patients surveyed say they are more likely to participate in a clinical trial if home care is offered
• 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, 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. 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, 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).

Click image to enlarge

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.