As the new calendar year approaches, organizations are beginning to look forward to understanding the impact of ICH E6 (R3) in the fourth quarter of 2021. Despite E6 (R2) being released just four years ago, the industry is still facing difficulties in adhering to these current regulations.

 and sponsored by Oracle Health Sciences in late summer addressed what organizations can do to prepare for E6 (R3).

The webcast featured insights from three industry leaders; Crissy MacDonald, PhD, Executive Director, Client Delivery, The Avoca Group; Andy Lawton, Consultant, Risk Based Approach Ltd, and Elvin Thalund, Director, Industry Strategy, Oracle Health Sciences.

E6 was originally released in 1996, creating the first guidance for clinical trial context. In 2016, revisions were made to these regulations for the first time in 20 years, forcing an industry-wide shift as it attempted to adjust. With another update to E6 expected in 2021, there will be a gap of just five years between revisions.

“What we’re seeing is a shrinking timeline of these regulatory guidance revisions, and it’s likely related to the rapid changes in technology’s clinical trial design approaches,” said MacDonald. “We need to become more adept at adjusting our internal policies and procedures to comply with these newly changing regulations.”

Lawton highlighted the revisions to E6, as well as the latest revisions to ICH E8, that will encourage greater use of quality tolerance limits (QTLs). “Quality tolerance limits give us that one perfect gift of avoiding perfection, because we write our plans as if we’re going to achieve perfection,” he said. “We can move away from that definition of perfection to a defined quality basis.”

Currently, organizations use a trial-reporting system that includes a completely separate process for quality checks after the fact. “There’s [currently] a whole secondary process, in this case a TMF (trial master file) process, where now the true regulatory quality is being assessed. The solution could be a system which considers quality from the very beginning. It would include training operational staff members on ICH regulations and implementing quality checks early in the process,” Thalundsaid.

“When you then start receiving them (documents), you can now ensure your quality control based on the quality you had defined from the beginning,” Thalund said. “That’s where you now have quality by design built into your system and process.”

The E6 (R3) concept paper states that R3 will be a full rewrite and reorganization of the GCP (good clinical practice) guidance with a focus on the applications of GCP principle to the increasingly diverse trial types and retaining concepts already present in R2.

While MacDonald noted the industry’s tendency to have a reactive approach to new regulations, when it should be more proactive. “[The industry’s reactive approach] drives a decrease in adoption because there’s concerns without a clear understanding of what those regulatory expectations are,” she said.

To address this, MacDonald referred to the Pharmaceuticals and Medical Devices Agency (PMDA)’s idea of “horizon scanning.” This concept will consist of “scanning the horizon” to find emerging technologies in order to proactively prepare and make the necessary regulations a priority.

Although the ICH E6 (R3) revision is fast approaching, models such as horizon scanning and streamlined operational processes should be able to help organizations adjust to the newest set of regulations.

is an Assistant Editor for Applied Clinical Trials. He can be reached at

Articles

Recent webcast addresses what organizations can do to prepare for the next revision of ICH E6.

E6 (R3) on Horizon

The imperative to prevent, treat, and cure the deadly COVID-19 virus altered clinical research and drug development priorities and regulatory oversight this past year as the research community devised new strategies for testing compounds with potential to mitigate the virus’ lethal affects. FDA issued guidance and advice on how sponsors could obtain necessary data through modified research programs, while federal agencies provided billions in financial support to accelerate drug and vaccine development and production.

At the same time, FDA faced challenges to its independence and credibility from often divergent demands from the White House. A central topic was how much clinical data FDA would require to approve Emergency Use Authorization (EUA) of experimental COVID therapies and vaccines. FDA’s fairly new commissioner, Stephen Hahn, a respected oncologist, but with little government experience, became entangled in these issues, raising fears about growing public “vaccine hesitancy” if companies and regulators took shortcuts to speed the development of COVID vaccines.

The debate came to a head in October as vaccine experts from leading medical institutions agreed with FDA staff on the need for sufficient safety and efficacy data prior to authorizing any COVID vaccine for administration to millions of individuals. Manufacturers backed FDA’s demand for two months of safety data following vaccination and at least 50% efficacy in a randomized controlled trial. A main question was the ethics and practical challenges of continuing controlled studies after finding one vaccine safe and effective.

The demand for greater access to information on research initiatives exposed the public to a wide range of usually confidential R&D and analytical information. In August, leading vaccine manufacturers began releasing detailed research protocols for Phase III studies, including enrollment goals for treatment and control arms, dosages, and number of COVID cases in each group needed for interim analysis and data safety monitoring board review.

While shifting many FDA staffers to COVID product development and review activities, FDA offices also worked overtime to meet schedules for vetting and approving new drugs and medical products to treat many other medical conditions. At the same time, pandemic restrictions raised challenges in conducting new and ongoing clinical trials, generating wider acceptance of decentralized trials, remote monitoring, streamlined enrollment processes, and updated standards for early termination and unblinding of trials. FDA also advanced policies for ensuring greater diversity in clinical trials, more effective use of real-world evidence in enrollment and data assessment, and use of master protocols and common control arms.

The pandemic slowed, but did not derail FDA initiatives designed to improve the regulatory process. The Center for Drug Evaluation and Research finalized the overhaul of its Office of New Drugs to have more review offices and divisions and a team-based, “integrated review” for assessing NDAs. Generic drugs and biosimilars continued to draw attention as important for managing drug shortages and for ensuring consumer access to affordable medicines.

The public debate on vaccine R&D also highlighted the critical role of FDA’s Center for Biologics Evaluation and Research (CBER) and its director Peter Marks, which issued guidance in June clarifying requirements for developing and testing new COVID preventives. In addition, CBER’s Office of Tissues and Advanced Therapies continued to cope with a surge in proposals for developing new cellular and gene therapies, many raising challenging and unique medical and technical issues.

FDA has approved more than 40 innovative medicines this past year and worked hard to meet user fee timeframes for prescription drugs, generics, and biosimilars–vital programs that face revision and renewal in the coming year. At the same time, officials note that researchers designed and launched more than a thousand clinical trials for COVID treatments, but most, unfortunately, appear too small and inadequately structured to yield any useful information. With COVID-19 again surging across the nation and the world as this historic year draws to a close, the only certainty is that both obstacles and opportunities will continue to challenge biopharmaceutical companies, regulatory authorities, and the research community in the months ahead.

View from Washington

Looking back on regulatory challenges created by COVID in 2020.

Pandemic Shines Spotlight on Clinical Trial Conduct and Regulation in 2020

The COVID-19 pandemic has brought new attention to clinical trials and is forcing the industry to rethink the best ways for patients to get involved. On Sept. 29, W2O announced the launch of Hū, a first-of-its kind Patient Activation Organization to accomplish just that.

In this interview, EVP and General Manager of Hū, April Lewis, discusses why the industry is seeing such a large drop in trial participation, how COVID is affecting trial operations, and what Hū is doing to better humanize trials.

You have 20 years of experience in the field of innovating trial operations. What do you think are the most valuable lessons you can take away from that time that are helping you in your current role?

 There are three things that I’ve learned that I carry with me. One, when we think about innovation, timing is everything; even the best innovations have to be met with a level of market readiness, adoption readiness, or maturity of a market in order to besuccessful.

The second thing is that data and evidence are only part of the story. As an industry, we’ve failed often because we look at data as the answer, when really it should be looked at as prescriptive guidance. I think data and evidence become most valuable when it’s balanced with experience and even sometimes instinct.

The third thing that I keep at the forefront of my mind is that patients aren’t waiting for us. If we stop and consider a trial, as we would consider a product, we have to think about whether or not that product is something that’s attractive. We take that approach with sites, so we often focus on whether or not a study is attractive, but we don’t take that same approach with patients. Thinking about what’s in it for patients is the thing that’s been missing.

The willingness to participate in trials has plummeted from 85% to just about 49% in the past year (CenterWatch). Why do you think we’ve seen such a such drastic drop like that?

 There’s copious amounts of misinformation around the pandemic, and that’s leading people into a state of paralysis and fear. I see it as a real opportunity for the collective R&D organizations to band together, change the narrative, and create a unified message.

Do you think that more literacy around trials will help people warm up to them and if so, why?

 Knowledge is power. Right now, people’s knowledge is wrapped up in a lot of noise. I truly believe we could fix that if we did a better job of providing resources to the general public around the value of trial participation. For example, what it means for our ability to future-proof care options by participating and some of the practicalities of participation, we’d really move the needle. However, this is a conversation that isn’t a one-size-fits-all, and requires us to not only combine forces as an industry, but to be consistent in our messaging, and keeping in mind that we need to personalize the conversation with patients in order to stay engaged.

How will Hū be utilizing social and behavioral evidence to increase patient participation in trials?

 We’ve built a model that predicts which patients have the highest intent to participate and it has shown high correlations. In addition, when we look at other industries, behavioral economics techniques have increased desired action by 41%. I’m not suggesting that we’ve been able to achieve that metric yet, but in other industries behavioral economics has been able to influence action and increase it to the desired state by 41%. So, we’re building out our tools and our techniques to leverage behavioral economics to provoke action in the same ways. For example, we are building out an innovative platform for gamified, scaled, digital patient insights. It’s a technique that’s going to highlight patient preferences and motivations that can be used by study teams in study design and delivery. This is a massive shift from the professional patient advisory board that gets used today. The third thing we’re using social and behavioral data for is working on a model to predict patient participation. This will allow us to predict what patients have highest interest or intent to participate, but the next step is translating that into enrollment rates. If we’re able to achieve that projection and prediction methodology, that will be a huge game changer.

What do you think are the most important elements for any company to consider when it comes to humanizing these trials?

 The most important elements start with listening and learning. We need to do a better job in understanding the patient lexicon; giving consideration to ethnic insights and the patient motivations. If we can combine listening with evidence and data, we can start to develop and analyze, get to a strategic goal, and have a strategic conversation that personalizes the way we engage with patients more effectively. The tactics are the last thing; by doing the upfront work and understanding the patient, adding in the evidence, and getting to that conversation blueprint, that allows us to build tactics that are going to have more meaningful effects on the ability to not only motivate a patient to participate, but to maintain that motivation throughout the trial.

How do you think that the pandemic has shed more light on the issue of the decreasing participation in trials?

 I think COVID has brought light to participation in clinical trials in general and has brought conversations about them to the table. I think that participation is a systemic issue and it requires a systemic response. We know, for example, if we think about diversity and inclusion in trials, there’s been under-representation of underserved populations for many years, but COVID has really brought this to light in particular. COVID has also brought to light the complexities and the reasons that are multifaceted; things like skepticism, lack of trusted relationships, and questionable data. Our approach at Hū is one that considers partnership as a balanced approach to not only civic and community engagement and partnership, but balancing that with medical and pharma partnership, as a means to take that systemic response.

EVP and General Manager of Hū, April Lewis, discusses why the industry has seen a decline in trial participation and what Hū is doing to combat it.

Industry Forced to Rethink Patient Participation in Trials

This year has been a busy one in the clinical trial disclosure and transparency space. The coronavirus pandemic has encouraged the rapid sharing of clinical data at a speed and scope that well exceeds regulatory requirements. It is unclear whether this broader and earlier data availability will eventually impact disclosure regulations, but it is no doubt shaping expectations and redefining what is possible.

On the regulatory front, 2020 has seen five significant developments:

In the US, a federal district court expanded the results disclosure requirements following a lawsuit brought against the National Institutes of Health (NIH).

The US Federal Drug Administration (FDA) published guidance on civil monetary penalties related to trial disclosure.

The European Medicines Agency (EMA) updated its plans for implementing its Clinical Trial Information System (CTIS), the EudraCT replacement system, by the end of 2021, bringing the Clinical TrialRegulation EU No 536/2014 into effect.

Brexit will change how clinical data are made public for trials conducted in the UK and require substantial organizational and process changes for UK and EU organizations.

Japan made the disclosure of protocol and trial results information mandatory on the JRCT registry.

Expansion of trial results disclosure requirements in the US

On Feb. 24, the US District Court for the Southern District of New York ruled that results for all trials applicable to the FDA Amendments Act section 801 of 2007 (FDAAA 801) must be disclosed on ClinicalTrials.gov. The disclosure deadline is no later than 30 days after the studied product is approved, licensed, or cleared (approval), even if that approval occurred after trial completion.

Issued in 2016, the Final Rule clarifying and expanding FDAAA 801 had revised the requirements for disclosing results of applicable clinical trials completed before the rule’s enactment on Jan. 18, 2017. Under the Final Rule, results for applicable trials were only required if the product was approved (or the device cleared) for any use before the trial’s completion date. Previously, FDAAA 801 required disclosure of results for applicable clinical trials within 12 months of the completion date or 30 days after the product approval, whichever came later, irrespective of whether the product was approved or cleared before or after the trial completion date. The ruling by the Southern District of New York invalidated the Final Rule results reporting exception for trials of products approved after the completion date.

On July 28, the NIH accepted the ruling, requiring results disclosure of applicable clinical trials studying a drug, biological, or device product approved by FDA within 30 days of the approval. If the disclosure deadline has already passed for trials affected by the ruling, results are due as soon as possible.

FDA final guidance on civil money penalties relating to trial disclosure

The FDA has issued the final guidance related to financial penalties for noncompliance with US trial registration and results disclosure regulations. Following is a summary of the steps the FDA will take in issuing financial penalties for noncompliance with 402(j) of the Public Health Service Act (PHS Act) and 42 CFR part 11:

 identify a violation through the FDA’s Bioresearch Monitoring Program (BIMO) or based on complaints received by the agency.

The centers will send the responsible party a Preliminary Notice of Noncompliance (Pre-Notice) Letter, which describes the potential violation and requests that the responsible party take any necessary actions to address the possible violation within 30 calendar days of receiving the letter. Failure to comply with the requirements relating to applicable clinical trials may result in further regulatory action by the centers, including the issuance of a Notice of Noncompliance, civil money penalties, injunction and/or criminal.

30 days after issuing a Pre-Notice letter, the centers will follow up on the violation if the submitter fails to submit the required certification to the FDA or knowingly submits a false certification. In that case, the agency intends to issue a Notice of Noncompliance to the submitter, giving the sponsor another 30 days to remediate. The Notification of Noncompliance will be made publicly available on the agency’s website and ClinicalTrials.gov.

Failure to remediate the issues identified in the Notification of Noncompliance within 30 days means the centers intend to seek civil money penalties, taking into account the type of noncompliance and the circumstances associated with the lack of remediation.

Disclosure practices are under considerable scrutiny by transparency advocates and patient groups. Noncompliant organizations are identified publicly, with their trials listed with the potential fines that the FDA could be collecting. While the final guidance on civil money penalties describes a fairly lenient process where the FDA provides organizations with time to address noncompliance, the public naming and shaming can have serious reputational impacts. Industry sponsors with large portfolios of trials tend to be highly compliant with the disclosure regulations. However, more than 60 % of trials conducted by smaller sponsors are noncompliant, creating significant regulatory risks that may affect valuations and create challenges during a future acquisition.

Organizations should conduct an internal disclosure audit of all trials posted to ClinicalTrials.gov to identify potential issues, including trials of acquired products or companies. At a minimum, these trials should be reviewed on the FDAAA TrialsTracker to confirm compliance with the Final Rule, though this will not help assess compliance with the original FDAAA 801.

The EMA has shared its plans for implementing the new CTIS, replacing the current EudraCT system used to submit and manage Clinical Trial Applications (CTAs) and trial results in the EU. The CTIS will support a centralized procedure for submitting CTAs and is now expected to go live in December 2021, provided the independent audit scheduled to start in November 2020 does not uncover significant issues. Six months after the European Commission publishes a notice confirming the full functionality of CTIS following the independent audit, the EU Clinical Trial Regulation (Regulation EU No 536/2014) will go into effect.

For the first 12 months after the CTIS go-live, sponsors and investigators may submit new CTAs to either the current EudraCT system or the new CTIS. After the first year, new CTAs must be submitted to the CTIS, and 36 months after go-live, all ongoing trials must be available in the CTIS, including those initially registered in the current EudraCT system.

Since the CTIS will change the processes and data layout for submitting CTAs, and the flow of communication with competent authorities, plans to adjust SOPs, work instructions and stakeholder communication should be in development. While the use of the CTIS is not mandatory for the first 12 months after go-live, it is recommended to identify at least one or two trials to submit through the new system in 2022 to prepare for the mandatory use in early 2023.

Because the United Kingdom is part of the European Union, protocols and results for trials conducted in the UK were made public on the EMA’s EU CTR. Sponsors initiating trials after the UK exits the EU on Dec. 31, 2020, will be required to register trial protocols and results for interventional trials on alternate public trial registers such as the ISRCTN registry or ClinicalTrials.gov according to the Make it Public strategy published by the National Health Service (NHS). By the end of 2021, around the time that the EU CTIS system goes live, the UK expects to make a new clinical trial data hub available to support UK patients and researchers.

The UK will recognize ethics and regulatory approvals for clinical trials that were granted through the current EU processes before Dec. 31, 2020, but any trial starting after 2020 will need local UK approval.

For trials that are ongoing after Brexit with locations in the EU where the Medicines & Healthcare Products Regulatory Agency (MHRA) is the Reference Member State (RMS), the sponsor will have to find a different Concerned Member State (CMS) to take over the role of the RMS. Also, while trials conducted in the UK after Brexit will be made public on registries other than EU CTR, any trial conducted in the UK that completes by Dec. 31, 2020, will require results posting on EU CTR, even if the disclosure deadline is after Brexit. Although sponsors have options where they chose to disclose UK trials statring Jan. 1, 2021, the recommendation is to use ClinicalTrials.gov as it is the most comprehensive global registry with currently around 360,000 trials publicly available. However, trials that also have locations in EU member states (other than Phase I trials without pediatric participants) will be publicly available on EU CTR.

Following Brexit, sponsors of clinical trials will have to ensure they have established appropriate local representatives in both the UK and the EU, including the Qualified Person for Pharmacovigilance (QPPV), the QP to certify compliant product manufacturing, and a local Market Authorization Holder (MAH). Unless the EU and the UK come to an agreement, sponsors will also need to establish batch control testing sites in both regions.

Sponsors and investigators in Japan have had the option to publicly disclose clinical trial information on one of three registries, UMIN CTR, JMCATT CTR, and JapicCTI. Posting trial information on these registries was not mandated by Japanese regulations, though ethics committees, industry associations and organizational commitments may have required registration. However, Ministry of Health, Labor, and Welfare regulations now require the registration of all Phase I-IV

 interventional clinical trials on the jRCT for studies that started on or after Sept. 1, 2020. The protocol registration is due before the start of enrollment and is submitted in Japanese and English. Sponsors must disclose the results of registered trials within 12 months of study completion. However, it may be possible to delay results disclosure until 12 months after product approval or sale in any country.

Industry sponsors that have made their trial data public on JapicCTI in the past must now post their trial information on jRCT instead and recognize the need to register Phase I trials (other than bioequivalence studies) before enrollment starts. The mandatory registration and results disclosure may necessitate updating standard operating procedures (SOPs) as well as agreements with clinical research organizations (CROs) or investigators.

There are over 40 trial registries globally with an average of two new registries starting each year since 2000. These registries make data publicly available for trials run in well over 100 countries, based on a broad range of local regulatory requirements. With increasing public scrutiny and the inspections by national health authorities, organizations conducting multinational trials must have the regulatory intelligence and tracking capabilities to keep up with the evolving requirements. Sponsors may choose to dedicate internal resources to disclosure or outsource this function to vendors with a specialization in disclosure. In either case, 2021 is expected to bring significant additional changes that will require organizational resources and expanded investment in disclosure and transparency.

Center for Drug Evaluation and Research (CDER), Center for Biologics Evaluation and Research (CBER) and Center for Devices and Radiological Health (CDRH)

Disclosure of bioequivalence studies is not required

Feature Articles

Spotlight on clinical trials created by COVID-19 pandemic has forced regulatory officials around the world to expand disclosure requirements on results.

Top 5 Global Clinical Trial Disclosure Changes in 2020 Amidst Pandemic

In March 2018, FDA placed ICH E6 (R2), a revision to Good Clinical Practice (GCP), in the federal registry. This regulatory update made explicit the responsibility of the sponsor to understand the risks to quality in clinical trials via the use of a Risk-Based Quality Management (RBQM) approach. Consisting of a variety of required components–including but not limited to quality risk assessments, a written Quality Risk Management Plan, and strategic, centralized data reviews–the revision underscores the importance of a robust RBQM framework to ensure clinical trial execution in compliance with GCP.

In the months since ICH E6 (R2) was adopted, a global pandemic has impacted clinical trial operations. However, even before the pandemic, many companies were still working to become compliant–and while COVID-19 has introduced its share of roadblocks to the industry, it has also prompted sponsors to intentionally embrace the adoption of a RBQM framework to new and ongoing trials.

In this article, we will examine the overall value of ICH E6 (R2) to sponsors, as well as how COVID-19 has and will continue to influence sponsors’ consideration of risk-based monitoring as a key component of clinical trial operations.

Benefits to ICH E6 (R2) and an RBQM framework

Early, targeted risk assessment tells you where you need to look and watch. In other words, to adopt a RBQM framework means to focus more on what matters most: the critical data/processes and potential risks unique to each trial. As the foundation for a targeted, risk-based approach to monitoring, RBQM helps sponsors first identify and understand their trials’ most critical risks before choosing the monitoring strategy that provides the most value.

So, what exactly does ICH E6 (R2) ask of sponsors, and what benefits does it offer in return for the time invested in making the transition? As it currently stands, ICH E6 (R2) requires sponsors to implement the following:

Quality risk assessments, starting at protocol development and ending with database lock

A written RBQM Plan and demonstration of plan execution

Strategic data reviews throughout the clinical trial

A robust RBQM framework and approach to ensure regulatory compliance

While these additional assessments and reviews may seem overwhelming at first glance, it is important to consider these requirements alongside the benefits they provide:

Improves the likelihood of a high-quality clinical trial

Ensures clinical trial execution in compliance with GCP

Focuses on data and risks critical to trial endpoints and patient safety

Provides quick access to data insights across clinical sites and patients

Potentially reduces the amount of on-site monitoring needed

In efforts to adapt the ICH E6 (R2) revision, many companies have encountered difficulty transitioning to a risk-based approach and adaptive monitoring strategy. However, the potential risks that could result from foregoing an RBQM framework far outweigh the transitional period.

For sponsors still weighing the necessity of adopting a RBQM approach, it is important to recognize that the decision to skip proactive, risk-based monitoring brings a risk to safety, data integrity, and even primary endpoints, any of which could drastically impact trials if not monitored appropriately.

Likewise, clinical trials characteristically produce massive amounts of data for study staff to sift through. However, if they have not proactively identified key data and processes that could bring potential risk, they run the danger of getting “lost in the weeds” and overlooking risk factors that later breached tolerance limits and resulted in issues that had some level of impact on the study and its results.

Employing the expertise of a CRO is an option for sponsors to help alleviate the work and time commitment required to adopt a RBQM process on their own. At Rho, we consider a robust RBQM framework to include dedicated quality risk managers, RBQM templates to assist with creating the plans required by ICH E6 (R2), a strategic approach to data review, among other components.

COVID-19, ICH E6 (R2) and a risk-based future

The global pandemic is a major risk in and of itself, and it has certainly revealed the extent of its negative impact on a variety of industries, resulting in closures, layoffs and more. When observed through a clinical research lens, COVID-19 is the type of risk that should be accounted for proactively–ideally via an RBQM approach. However, the reality is the shocking and surprising onset of the pandemic did not provide the clinical research industry–or any industry–the foresight to prepare for every single roadblock presented by a pandemic of this scale.

For many ongoing clinical trials, when the pandemic hit, sites stopped seeing patients in-person, encountered issues with enrollment, along with other delays. This required sponsors to pause and identify what risks COVID-19 could bring about to potentially impact the future of the trial. Arguably, this situation has forced sponsors to look at their trials through an RBQM lens and adopt this process or encounter the risk of halting their trials altogether.

On the other hand, those in the planning phase have the privilege of incorporating pandemic-related mitigations into their programs up front.

During this stage, an early adoption of RBQM provides the opportunity to proactively determine what can be monitored centrally or conducted remotely via on off-site visit or very limited on-site visits to safeguard patient and staff health and safety.

Overall, ICH E6 (R2) underscores the sponsor’s responsibility to evaluate and implement risk-based monitoring into their clinical trials, before, during and even after the era of COVID-19. We consider a risk-based future to consist of the following:

Site monitoring visits conducted based on tracking and managing risk at the site

Initial set of visits may be pre-planned but then visits are driven by findings–leading to a variable frequency of visits across the study and between sites

More findings or more severe findings leads to more visits and vice versa

Visit types (off- or on-site) driven by number, severity, and type of findings

It is important to note that the possibility of more on-site visits will likely be delayed as we continue to adapt and recover from the impacts of COVID-19. However, decentralized clinical trials provide a viable solution for this setback, as long as they are patient-centric, customized and rooted in a robust RBQM framework, per the ICH E6 (R2) guidance.

Arguably, the global pandemic has redefined our understanding of a “traditional” clinical trial, as more sponsors are implementing decentralized clinical trials to keep studies active during this time. Despite this shift, many organizations have still been slow to adopt ICH E6 (R2) and make the necessary updates. Future updates to ICH E6 (R2) will likely be driven by this need for more frequent adoption of the revisions, as well as pave the way for an easier industry-wide transition to a risk-based monitoring approach.

Associate Director, Clinical Management, Rho

COVID-19 pandemic forces compliancy within organizations following FDA’s 2018 revision of Good Clinical Practice in federal registry. 

Managing Risks in Clinical Trials During a Pandemic with ICH E6 (R2)

Issue PDF

Click the title above for a link to open the Applied Clinical Trials December 2020 issue in an interactive PDF format.

Applied Clinical Trials, December 2020 Issue (PDF)

The Michael J. Fox Foundation for Parkinson’s Research (MJFF) aims to speed clinical research by removing obstacles that stand in the way of drug development. In pursuit of this mission, the Foundation gathers insights from a wide range of stakeholders and uses these perspectives to enhance clinical trial processes from start to finish. In 

 Eye on Patient Advocacy series, we will share best practices and lessons learned from the field of Parkinson’s research that can be applied to clinical trials across disease states. In our latest column in this series, we explore the importance of addressing barriers to participation for historically underrepresented and marginalized groups.

Despite growing emphasis on increasing diversity in clinical research, the proportion of underrepresented groups (URGs; defined in this study as women and gender minorities, racial and ethnic minorities, individuals earning below a median household income of $57,000, a high-school education or less, and/or rural residents) in Parkinson’s disease (PD) research remains low, with as many as 91% of participants identifying as non-Hispanic Caucasian in various studies.1–3 Although some studies, such as the MJFF online PD research platform Fox Insight (FI), have been designed to reduce or eliminate research barriers for URGs, equitable representation in PD research remains elusive.4 Without diverse inclusion in these trials, estimates of PD disparities in underrepresented populations, which remain poorly understood, may widen.5–7

Although the barriers to PD clinical research among underrepresented populations have been well identified, it remains unclear whether suggested interventions from the existing literature will improve engagement of traditionally underrepresented populations in PD research. For these reasons, MJFF sponsored the Fostering Inclusivity in Research Engagement for Underrepresented Populations in Parkinson’s Disease (FIRE-UP PD) Study to 1) explore whether it is possible to identify best practices to engage URGs in PD clinical research, 2) to assess knowledge and attitudes toward clinical research designs, and 3) to increase participation of URGs to FI.

A request for proposals (RFP) was released for academic medical centers within the Parkinson Study Group research network to participate in FIRE-UP PD. Sites were instructed to identify a specific URG or geographical region to focus on, a specific barrier to PD research participation experienced by this group as categorized by the Picillo PD research barrier framework8, and a specified intervention as categorized by the Picillo et al. framework. Eight participating sites were selected, and were paired based on their proposed interventions and randomly assigned to either intervention or control conditions. Sites in Chicago, Boston, Denver, and Southern Florida were assigned to the intervention condition and were given $45,500 to execute their proposed design, whereas a second site in Chicago, the rural northern Midwest, the greater Seattle metropolitan area, and San Francisco were given $10,000 to serve as passive controls, maintaining their current recruitment workflow. Interventions included developing educational tools and surveys to engage community health centers in PD diagnosis (Boston), partnerships with local PD support groups to discuss PD research (Southern Florida), developing multi-stakeholder alliances and focus groups to create community-specific educational toolkits (Chicago), and recruiting community stakeholders to reimagine medical and research information for the community through a collaborative method called Boot Camp Translation (Denver).

The study was divided into three temporal phases for all sites: pre-intervention, to establish a recruitment baseline; intervention, to deliver a specified intervention or in the case of control sites, to continue passive recruitment activities, and post-intervention, to determine change from baseline. In addition to recruitment measures to FI, the FIRE-UP PD study was designed to collect survey responses from participants with regard to awareness and trust of PD research. Sites collected the Trust in Medical Research Scale (TIMRS), the Patient Engagement in Research Scale (PEIRS) and PD Research Participation Surveys, which assessed specific PD research designs and their impact on participation willingness. All sites also collected barriers to PD research participation, capturing reasons why URG individuals, who would otherwise participate in FIRE-UP PD, could not do so. All sites displayed FI recruitment materials as designed by MJFF and had a dedicated tablet device for FIRE-UP PD surveys and FI registration.

The FIRE-UP PD study enrolled 488 individuals across the eight sites (intervention n=295), while 230 individuals (intervention barrier n=101) faced insurmountable barriers to participation, outlined in 

Changes in trust, measured via TIMRS did not significantly improve for intervention sites relative to control sites, although a trend towards improvement emerged, t(382)=1.80, p=.073.There was no disproportionate change in patient engagement or in overall research participation willingness for intervention relative to control, all ts < 1. However, participant characteristics indicated that intervention site participants were significantly more diverse at both pre- and post-intervention with respect to race, ethnicity, income, and educational attainment.

Diverse accrual to FI (n=181) improved across all sites over the study period relative to sites’ own baselines, although intervention sites significantly improved diversity with respect to race, ethnicity, income, and educational attainment, while control sites improved race and ethnic diversity alone, as seen in 

The FIRE-UP PD study was designed to measure barriers, attitudes, and FI accrual for URG populations accessing PD clinical research. The study suggests that URG recruitment could have increased by as much as 50% if common participation barriers such as language, time, and the digital divide were addressed. Although sampling and selection factors obscured trends in the attitudinal surveys, intervention sites recruited a broadly diverse sample of participants to complete surveys as well as enroll in FI, despite intervention sites’ focus on a single URG. Notably, although control sites were instructed to continue their baseline recruitment activities, nevertheless these sites yielded increased racial and ethnic diversity in FI. This suggests that while targeted interventions may yield substantial benefits to improved diversity of PD research participation, merely orienting to the problem of lack of study representativeness may alter even passive recruitment practices in subtle ways to promote more inclusive research participant cohorts. Developing detailed recruitment protocols that focus on particular URG populations as well as barriers faced by these groups may be a promising addition to PD research, although future studies will need to better understand specific mechanisms of efficacy and comparative effectiveness given similar site and study characteristics.

Schneider MG, Swearingen CJ, Shulman LM, Ye J, Baumgarten M, Tilley BC. Minority enrollment in Parkinson’s disease clinical trials. 

. 2009;15(4):258-262. doi:10.1016/j.parkreldis.2008.06.005

Mainous AG, Smith DW, Geesey ME, Tilley BC. Factors influencing physician referrals of patients to clinical trials. 

. 2008;100(11):1298-1303. doi:10.1016/S0027-9684(15)31508-X

Eskandar EN, Flaherty A, Cosgrove GR, Shinobu LA, Barker FG. Surgery for Parkinson disease in the United States, 1996 to 2000: practice patterns, short-term outcomes, and hospital charges in a nationwide sample. 

. 2003;99(5):863-871. doi:10.3171/jns.2003.99.5.0863

Jang M, Vorderstrasse A. Socioeconomic status and racial or ethnic differences in participation:web-based survey. 

Svenson LW. Regional disparities in the annual prevalence rates of Parkinson’s disease in Canada. 

. 1991;10(4):205-210. doi:10.1159/000110271

Winter AC, Rist PM, Buring JE, Kurth T. Prospective comorbidity-matched study of Parkinson’s disease and risk of mortality among women. 

. 2016;6(9). doi:10.1136/bmjopen-2016-011888

Chan AK, McGovern RA, Brown LT, et al. Disparities in Access to Deep Brain Stimulation Surgery for Parkinson Disease.

. 2014;71(3):291. doi:10.1001/jamaneurol.2013.5798

Picillo M, Kou N, Barone P, Fasano A. Recruitment strategies and patient selection in clinical trials for Parkinson’s disease: Going viral and keeping science and ethics at the highest standards. 

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, all with CARE Research Center-Massachusetts General Hospital; and 

MJFF and Dr. Jackson would like to acknowledge the following individuals for their contribution to the research presented in this case study: Dr. Michael Schwarzchild (Co-I), Dr. Angie Sanchez (Research Fellow), Ms. Helen Hemley (Project Manager), and the site principal investigators: Dr. Mitra Afshari, Dr. Pinky Agarwal, Dr. Michael Aminoff, Dr. Meagan Bailey, Dr. Katelyn Bird, Dr. Stephanie Bissonnette, Dr. Michelle Fullard, Dr. Tarannum Khan, Dr. Danielle Larson, Catherine Wielinski, MPH, and Karen Williams, MS.

The MJFF Research Engagement Team includes 

, Research Partnerships Officer at The Michael J. Fox Foundation in New York, NY. To contact the MJFF Research Engagement Team email: 

The Systemic Synuclein Sampling Study (S4) was a multicenter, cross-sectional, observational study sponsored by MJFF. The primary objective of this study was to better understand the progression of Parkinson’s disease (PD) by identifying the optimal biofluids and tissues for measuring the protein alpha-synuclein outside of the brain as a potential biomarker in individuals with PD. The secondary objective of the study was to create standard operating procedures for the collection and assessment of multiple tissues and biofluids to better understand alpha-synuclein’s potential as a biomarker for PD.

In January 2017, MJFF launched a survey to assess the need for transportation infrastructure at clinical trial sites. Data from the survey was used to inform the design of a transportation intervention that was tested via the Parkinson’s Disease Trial Recruitment Innovation (PD-TRI) project, an MJFF-funded pilot study aimed at reducing barriers and enhancing facilitators to clinical trial recruitment.

Patient retention is an important element of the Parkinson’s Progression Markers Initiative (PPMI), a landmark, longitudinal, observational study sponsored by MJFF. PPMI aims to find reliable and consistent biomarkers for PD progression by studying cohorts of Parkinson’s patients, populations at risk for PD, and controls without PD.

Building a Physician Referral Network: A Case Study

General practitioners often are not involved in the recruitment strategy for clinical trials. Historical barriers have made engagement with physicians challenging. They may fear losing care of patients to clinical trial site providers, be unfamiliar with the trial and principal investigator (PI), or have concerns about jeopardizing the doctor-patient relationship. One approach to building trust and overcoming these obstacles is for research institutions and PIs to actively engage with community physicians.

Eliminating barriers to engage underrepresented populations.

Importance of Diversity in Parkinson’s Research

As clinical trials grow in complexity, clinical operations (ClinOps) professionals are finding it challenging to keep pace and fulfill their oversight responsibilities. Their workloads are increasing like never before, and their resources are not helping them keep pace with a tsunami of data, much of it unstructured. One of the central areas of data requests come from their internal company colleagues in regulatory, for data that regulatory bodies will eventually require, as well as data requests from regulators themselves.

Mike McLaughlin, Associate Director of Clinical Operations at Dermavant Sciences, Inc., says the major ClinOps issue is dealing with large amounts of data and a lack of standardization. “It was much simpler when we dealt with paper files and not electronic data,” he says. “Now we have to sift through and streamline the data and find the data that provides the most value.

“Different companies collect data in different formats. For example, there’s a recommended DIA file structure and format for the TMF, but not all companies file documents using the same file structure,” McLaughlin explains. “It is more difficult to review the TMF if the documents are not structured and formatted correctly. Time-consuming manual labor is needed to correctly structure and format the documents. Software could speed this task.”

Karen Roy, Co-Chair of the DIA-founded Trial Master File (TMF) Reference Model and Chief Strategy Officer at Phlexglobal, a technology and services organization for clinical and regulatory matters, continued: “I think the biggest challenge is that the regulators want to see the detail behind the documentation, including the different systems and audit trails that back up the documentation and (ClinOps) activities. It’s no longer just a matter of providing a few documents to review. This has made the TMF much bigger because people don’t know exactly what they should be collecting or presenting to regulators. They collect way more than they used to, and sometimes more than what’s needed. Mandates have made it harder to keep up from a regulatory perspective.”

“There’s pressure on clinical operations to produce data in a consistent, manageable, and compliant structure for their colleagues in regulatory affairs and operations to streamline submissions. But there are different mandates to follow, such as the Electronic Common Technical Document (eCTD) for the FDA. It’s challenging, especially when you have mandates within mandates creating duplicate work,” adds Jim Nichols, Co-Chair of DIA’s Regulatory Information Management Committee and Chief Product Officer at Phlexglobal. Roy and Nichols add that sometimes the mandates are not clear, leaving ClinOps in the lurch.

Paul Fenton, President and CEO at Montrium believes there has been poor compliance with registering metadata against documents because the process is very labor-intensive and ultimately, “We don’t fully leverage the metadata as an information source. We can scan documents using AI and identify a broader range of metadata that could be extracted from those documents and used to provide a richer base of information about particular types of documents, a particular trial site, or a particular process,” he states.

Several companies are developing AI solutions to recognize documents and metadata, make them more structured, and perform automated extraction on indexing of information. He expects to see these types of systems, which are much more integrated and process driven, with AI and machine learning tools built in, in the next two to three years.

In addition, development of a forms management solution, which would be part of the TMF, would allow companies to collect and add data in a much more structured way directly into a database, according to Fenton. “When you initiate a site, there are many forms that must be completed, which provide basic information about that site, like FDA Form 1572. These forms could be filled out electronically online instead of being uploaded as a document, which would make the data easier to integrate and exploit,” he says.

Fenton chairs a group which has developed a standard for exchange of TMF information between systems, eTMF Exchange Mechanism Standard that is a sub-group of DIA’s TMF Reference Model. They have started to define areas like standard metadata, which is a step toward having more standardized information about operational documentation.

“There’s a lot of variability in terms of the information we have to manage,” Fenton continues. “There are probably around 500 different types of documents collected in a TMF, which all have their own format, and formats can change from one company to the next. Standardization will help, and machine learning could help unlock the gold mine that all of that information represents.”

Jim Reilly, Vice President, Vault R&D, Veeva Systems, a provider of cloud solutions, said, “Why can’t we use AI in the form of natural language processing or machine learning to examine content as it comes into a TMF and automatically classify and attribute metadata to the documents so that we don’t have to spend much resource time reviewing material that’s already been received? This would be a tremendous cost and time saver.”

Although requiring more effort on the part of sponsors and CROs, McLaughlin thinks it’s important that the FDA wants more sponsor oversight and is placing more emphasis on quality. “The current guidance (ICH E6 (R2)) is more specific than in the past. They’re driving home quality and risk assessment to make sure that clinical trials are performed with care.”

In the guidance document, the FDA updates and further outlines responsibilities of institutional review boards (IRBs), investigators, and sponsors based on “evolutions in technology and risk management… to increase efficiency and quality.” The goal is to improve clinical trial design, conduct, oversight, human subject protection, and the reliability of trial results.

“Sponsors must review documentation on a regular basis, ensuring that CROs are following good clinical practice. As sponsors, we’re responsible for making sure that the obligations that you’ve transferred over to the CRO are being fulfilled,” McLaughlin notes.

“It’s incumbent upon sponsors to be accountable for their trial execution even when they outsource. So, it’s important for them to have a mechanism by which they can accurately receive information from their service providers. Technology can have a significant play here,” explains Reilly.

He thinks that technology needs to “up its game” and provide a consistent mechanism that enables CROs and sponsors to share and exchange information, driving better trial oversight. Part of this involves having better operational data standards and consistent data standards, but he also believes there is a need for technologies that have open connection points, and which are networked so data can flow between CROs and sponsors and be better understood by the receiver.

There is discussion of using artificial intelligence (AI)—as in many areas of pharma—to build quality into unstructured and structured documentation that becomes part of the TMF. “Regulators are increasingly supporting the use of Quality by Design principles (QbD) in clinical trials. Risk-based quality control is a key component of QbD,” Roy explains.

Addressing risk management and taking a risk-based approach pushed by regulators is important for Fenton. But clinical trials contain a lot of information.

“A clinical site might be higher risk because they’re recruiting a lot of patients, or there may be many safety cases at that site, or delays in providing information that can impact risk. We should be able to flag groups of documents or information that should receive additional scrutiny, QC, or verification because they’re considered an inspection risk. Machine learning could improve the risk models over time,” explains Fenton.

While AI can be used to check documentation for quality and to help with risk assessment, there also is a need to collect data from disparate sources more efficiently and to unify the data collection process. “Companies haven’t been the best at building quality into documentation from the beginning and putting processes, such as the ALCOA framework, into their systems,” states Roy. She suggests adding ALCOA and other quality processes to source systems and then using AI to analyze the documents and transfer them to the centralized TMF, which would bemore efficient.

It’s also important to map out what technology can do. Technology can bring things together and indicate knowledge and data gaps. But it won’t tell you which documents are needed, unless it is directed to that need. This is a skilled task that requires the expertise of the ClinOps team, or outside experts, adds Roy. And that subject matter expertise can be built into technology to essentially establish a risk-based approach to a process to check on documentation.

McLaughlin is hopeful that advanced software, such as AI and machine learning, will remove some of the burden from ClinOps personnel, for example by helping to structure any unstructured data, optimizing documentation in the TMF, and by helping trial participants remain compliant with their medications. But he thinks the technology still requires additional commercial exposure before it can fully demonstrate its usefulness in clinical trial settings.

“ClinOps people can do many tasks but they are struggling to keep pace with regulatory requirements,” Nichols explains. “Compliance is taking up more time and effort from trained people to do manual, repetitive tasks. These tasks are tailor-made for AI technologies, such as machine learning.”

To connect the dots of the ins and outs of the trial, including the many different study events, Fenton indicates a standard process model could be established that defines all of the processes that occur in a clinical trial, including the events that trigger them and the data required to describe them. This model would then be used to pull information from different sources.

“Technology can help by leveraging this model. But the model needs to be defined by people who know about clinical processes and by the regulations,” Fenton says. “We can improve the model over time by making connections between different processes and events as well as looking at historical data through machine learning and AI.”

Another related technology trend Alok Tayi PhD, Vice President of Life Sciences at Egnyte, sees is the emergence of natural language processing (NLP) in the clinical trial space. “NLP promises to automate rote tasks and improve data integrity by helping staff extract key data from study reports, CVs, and other documents,” explains Tayi. Recent advancements in NLP enable software to perform cognitive tasks, like document classification, data extraction, and even summarization. Tayi believes that these novel capabilities, integrated into the trial workflow, will allow trials to process quickly new data, check for inaccuracies, and extract insights quickly.

Reilly is encouraged by how the FDA and other regulators are piloting initiatives that can make the review process less difficult. The agency’s Real-Time Oncology Review Pilot Program aims to explore a more efficient review process which includes companies submitting top line results as they occur, speeding the review process.

“In many ways they’re pushing along the data directly to the agency rather than compiling it in a big package. Technology can help with modern submission tools and mechanisms where data can be compiled in a normalized sense and pushed into the regulatory system. A more hardened connection between clinical and regulatory can make a real-time submission process more efficient,” Reilly explains.

Tayi expects AI algorithms will help the industry address key data privacy issues. AI can help sponsors, sites, and CROs monitor their data for sensitive information and ensure compliance in an automated fashion. For example, technology can ensure that consent documents are properly classified, or that data managers are alerted to personally identifiable information (PII) embedded within the metadata of CT imaging. “But we need clarity on how to train the models to help identify data as well as very specific regulations to which we can tie the data,” Tayi notes. He also sees AI helping structure data and metadata for one’s TMF.

In addition, as sponsors and CROs consider running new types of trials, such as virtual clinical trials, data privacy risks are heightened. According to Tayi, institutions will need automation and AI software that ensures that the right people have access to the right data, without the overhead and burden to the team.

Clinical operations professionals, burdened by lack of data standardization, turn to technology in hopes of streamlining regulatory processes for the future.

Regulatory Data: How Technology Can Help ClinOps Survive

As we continue to keep our eye on decentralized trials advances, a recent survey released by Oracle, and detailed in a recent 

 showed that 76% of 252 industry respondents noted that the pandemic sped their adoption of decentralized clinical trial methods. The most common decentralization steps taken were patient-facing technologies or alternatives (64%), protocol redesign (63%), and investigator-facing technologies or alternatives (53%).

However, it is data issues and regulatory concerns that held most back from adopting decentralized trial methods—specifically, ensuring data reliability and quality and data collection. Also, to wearable and remote monitoring, the respondents’ top concerns are a different approach to review, manage, and interpret data (50%), expense (46%), and complicated regulatory considerations (41%). Additionally, from the 24% of respondents who reported that the pandemic had not accelerated their adoption of decentralized clinical trials, regulatory concerns (42%) were a top reason.

During Informa’s Clinical Trials in Europe virtual event, the panel discussion “The Future of Clinical Trials” was heavily weighted toward the many advances in technology used in clinical trials during COVID, and practices such as decentralized trials. Panel members Kenneth Getz, Deputy Director and Professor, Tufts Center for the Study of Drug Development, Tufts University School of Medicine, and Kai Langel, Director, Janssen Clinical Innovation, took a moment to discuss whether industry will continue with its advances post-COVID.

Langel reiterated that as a global experiment, aspects brought forward by COVID are working out and regulators are OK with many of the changes, and, therefore, what’s successful will remain. He suggested that protocol deviations during COVID were not perfect but we can learn from that. “There will be data points that worked extremely well, and those that will show how they could improve,” Langel maintained.

Getz admittedly offered a “somewhat cynical” perspective based on historical data. “I think a lot of change in behavior in response to the pandemic may be more of a short-term or one-time occurrence, even though it has facilitated much more widespread use of many approaches supportive of the remote and virtual clinical trial activity,”
he said.

Based on an audience poll around barriers to decentralized trials, Langel expressed surprise that no one pointed out costs related to decentralized trials, saying costs will go up. “Home nursing is an expensive service as opposed to asking patients to travel to site,” he said. “But in many studies, such as rare diseases, the research gets done faster and better, so that trade-off can be worth it.”

 is Editor-in-Chief of Applied Clinical Trials. She can be reached at 

From the Editor

Regulatory concerns remain despite industry's quick adaptation of decentralized trials.

Decentralized Trials, Pros and Cons

Throughout the pandemic, the global public has had a front-row seat in an emotional theater of drug development. Daily news updates and more in-depth profiles have covered scientific breakthroughs, new collaborations, commitments, clinical trial activity, and preliminary results from interim assessments. And, as a result, public awareness of the role and importance of the pharmaceutical industry has increased sharply and public perception has improved dramatically.

This is a unique moment and a rare opportunity for drug development stakeholders to hit the reset button and enter a higher level of partnership and engagement with the public and patient communities. But until now, the pharmaceutical industry has largely emphasized one side of the story. The focus-to-date has been inward—on the industry’s innovativeness, productivity, passion, and commitment.

With late-stage vaccinations in the process of receiving Emergency Use Authorizations (EUA), the clinical research community—in collaboration with public health officials and the clinical care community—needs to expand its focus outward to collectively engender trust and support for the great science that the world is witnessing.

In addition to conveying gratitude for study volunteers who participated in COVID-19 vaccine and treatment clinical trials, the clinical research enterprise must also demonstrate respect for the public and patients through complete transparency and disclosure, in plain language, of the results of its COVID-19 clinical trials; and it must provide consistent and easy-to-understand patient and public education focusing on the “last mile” between the availability of safe and effective new vaccines and the societal importance of, and obligation in, their uptake.

Battle for trust ensues as vaccines are set for approval.

Applied Clinical Trials-12-01-2020

E6 (R3) on Horizon

Pandemic Shines Spotlight on Clinical Trial Conduct and Regulation in 2020

Industry Forced to Rethink Patient Participation in Trials

Top 5 Global Clinical Trial Disclosure Changes in 2020 Amidst Pandemic

Managing Risks in Clinical Trials During a Pandemic with ICH E6 (R2)

Applied Clinical Trials, December 2020 Issue (PDF)

Importance of Diversity in Parkinson’s Research

Regulatory Data: How Technology Can Help ClinOps Survive

Decentralized Trials, Pros and Cons

Public Trust and the ‘Last Mile’ for COVID-19 Vaccines

The Ever-Changing Face of NICE Guidance on Drug Innovation

Investigative Site Placement Practices to Support Operation Warp Speed

Radiomics: What It is and What It Can Do for Clinical Trials

Gender Bias in the Clinical Evaluation of Drugs