Drug developers and their partners are constantly seeking new and innovative ways to bring treatments to patients as quickly and cost efficiently as possible. While just a sliver of clinical trial operations, study start-up impacts multiple downstream factors like cost and timelines, which ultimately determine how quickly patients can have access to these treatments. However, study start-up can often be filled with preventable issues like unstructured accountability, mismanaged expectations about risk management, and distracting new technology that can complicate the process.

Alternatively, a successful start-up mobilizes a global cast of performers who rapidly identify and activate the best possible sites that have access to the most appropriate patient populations. This article explores best practices in start-up aimed at rapid, efficient delivery of this critical component of the clinical trial process.

The site start-up process can best be described as conducting an orchestra. Depending on how well the musicians are coordinated, the orchestra may perform like a world-class symphony or like the first day of a primary school music class. In an orchestra, it is important to group the families of instruments and conduct them to play at specific points that best accentuate the music. This enables the instrument sections to understand their role in the symphony and how their sound blends with other instrument sections.

For study start-up, this starts with creating single points of accountability. With the ever-increasing complexity of studies, it is easy to fall into the trap of associating responsibilities for tasks across multiple teams and, as a consequence, diluting overall accountability. Although many individuals may be conducting activation tasks, it is critical to simplify lanes of communication and ownership by ensuring there is always a single point of ownership at the study and site levels.

At the study level, it is this individual’s responsibility to command the study start-up process and coordinate activation ramping, remove roadblocks, and align all the contributors to the activation process. This is important because at the study level it is already challenging to coordinate all these ancillary activities for every site across multiple countries, but it can quickly become confusing when the responsibility of these tasks is diluted across multiple teams.

Similarly, at the site level, it is equally important to have a single individual that has the accountability for ensuring all activities at the site are completed. Although many individuals may be conducting tasks to activate a site, one person should act as a partner who guides all site personnel through the complex activation processes and requirements. This is important because often roadblocks are site-specific, and one person should be the point of contact to address challenges.

In my experience, I’ve seen many teams defer start-up kick-off discussions until the protocol is final or after feasibility is conducted. Doing this puts your start-up team at a disadvantage because teams will focus on individual pieces, but most likely not have the full picture of the final outcome.

Don’t underestimate the value of a start-up launch meeting as soon as you are ready to begin work. Just as the orchestra always begins with a tune up and a review of the sheet music, your start-up efforts should always begin with an official launch. Use this as an opportunity to align on goals and milestones, highlight key decisions to make, ensure all of the team members understand expectations, and define what success looks like.

The myriad of technologies available to researchers is nothing short of amazing. However, it is important to remember that with each new system and application, it incrementally increases and complicates the cost, time, and effort it takes for sites and teams to deliver studies.

Invest in tools and technologies that bring multiple data sources together to give a holistic picture of the activation process to the teams tasked with delivering study start-up. In addition, look to minimize the number of tools and technologies your teams and sites use to find the information and data they need. Not only does this approach directly improve the efficiency of the start-up process, but, more importantly, it creates a single sheet of music that all of the teams can work from, resulting in a more timely and efficient approach to start-up.

Monitor and maintain the fidelity of the operations

If you’ve ever watched an orchestra perform, you have seen the conductor quickly identify and address instruments that have fallen out of tune or musicians that hit a wrong note. A keen conductor keeps an alert ear for any indicators that the piece may be going off track.

In this same way, it is critical that the conductors of start-up monitor objective risk criteria to quickly identify dimensions of the process that are not progressing as expected and have pathways and processes to succinctly articulate, escalate, and remove obstacles that may prevent activation to expectations. These characteristics include:

 As you are monitoring the performance of your project, look to identify a minimal set of key indicators that demonstrate whether you are on track to deliver expectations. Risk criteria should be simple and objective, while also providing a good reference point on whether your operations are on track. Clear risk criteria minimize subjective opinions that could make you tone deaf to how your start-up is progressing.

Create a culture that embraces root-cause assessment and mitigation recommendations paired with clearly articulated asks. Ensure teams understand that “red” is not a personal reflection of their performance, but rather highlight the urgency needed to resolve roadblocks.

Design escalation pathways aimed at appropriate use of chain of command. Escalation should be a mechanism to gain endorsement and action to remove roadblocks, not a complaint or awareness forum.

Many of the best musical works are defined by simple yet exquisite solos that take the piece to a whole new level. During the start-up process, this can be accomplished by forming the right partnerships with strategic research sites and service providers and looking for opportunities to leverage their strengths.

For example, strategic research sites are a critical component of maximizing start-up activation efficiency. Strategic research sites are ones where you have a strong operational relationship and the site consistently performs well on previous studies.

Creating operational relationships with these sites is critical to your study’s success as it brings mutual benefits through opportunities, operational synergies, and effective escalation pathways that remove roadblocks.

In addition, partnering with strategic service providers maximizes the efficiency of the activation process. Look to partner with service providers who understand your processes and bring tangible value. For example, PRA Health Sciences partnered with Advarra, a provider of institutional review board (IRB), institutional biosafety committee (IBC), and research quality and compliance consulting services in North America, to increase the number of sites relying on IRB review and streamline startup.

In less than two years, PRA was able to substantially improve the ratio of sites able to leverage the central IRB. In fact, as of May 2020, approximately 54% of sites were relying on Advarra as the central IRB and 37% relying on local IRBs (the remaining 9% were not tracked).

As a result, PRA was able to activate central IRB sites twice as fast as those sites only relying on local IRBs. Even sites that were required to have both central and local IRB review in the approval process were still faster than the local-only sites. This improved study startup timelines and saved money for PRA’s sponsor clients, ultimately speeding the drug development process and getting therapies to patients more quickly.

Study start-up has its challenges, but careful planning on how to manage accountability, outcomes, technology, expectations, and strategic partners can help structure the process into one that is rapid and efficient. While study start-up isn’t often viewed as the “star of the show,” it can be the quiet hero that leads your trial to the swift start it needs to deliver treatments to patients faster.

Executive Director, Global Study Start-Up, PRA Health Sciences

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Feature Articles

Similar to a world-class symphony, a curated site start-up model can accentuate its individual components and lead to swift starts for clinical trials.

Orchestrating Different Levels of a Successful Clinical Study Start-Up

At the outset of clinical trials—prior to enrolling the first patient—a considerable amount of work is done in planning and setting up a study for success. Collectively referred to as study start-up, these decisions can have a great impact on timelines and budgets. While the COVID-19 pandemic has slowed down the implementation of new trials, study start-up has the advanced technology necessary to overcome sucha large hurdle.

In this interview, Sujay Jadhav, global vice president, study start-up, Oracle Health Sciences, touches on how COVID has affected study start-up and what new perspectives it has forced the industry to have on its own challenges.

How did the pandemic affect study start-up in the beginning vs. study start-up about six months later?

 In March, not long after the pandemic was spreading globally, Oracle created a study start-up response team, which developed and released several COVID-19 specific application enhancements to help our customers:

Activate workflows were modified to allow certain tasks to take place simultaneously. This was a critical enabler for COVID-19-specific therapeutics and vaccine studies where operational time savings were critical.

We released a new organization-specific Analyze report to allow clinical trial teams to assess the impact of COVID-19-related delays at the study, country, and investigator level. This allowed pharmaceutical companies and CROs to better plan the revised schedules for studies and assess the resource and financial impact of the pandemic.

Oracle support teams immediately prioritized all support requests related to COVID-19 clinical trials to ensure expedited response.

In the present, six months after the outbreak of the pandemic in the U.S., we are seeing a resurgence in studies, which are either new, or previously placed on hold.

Do you think the pandemic has shined new light on challenges that may have existed in study start-up beforehand?

Yes. Study start-up is a continual focus because it has such an impact on clinical trials. Problems with start-up, more than any other phase of a clinical trial, have the greatest potential to increase timelines and budgets. Fortunately, technology for study start-up has advanced to the point that current solutions can do what Excel never will—automatically trigger workflows as a clinical trial unfolds.

It has also become possible to set and track milestones, improve communications among partners, act as a central repository for study documents, and integrate the flow of information from various data sources in a compliant manner—functions that are critical to successful site-activation processes as more clinical trials become global and complex.

Furthermore, companies with purpose-built solutions may have an advantage to monitor impact closely and accelerate the responses needed, where possible.

How can predictive analytics and effective study planning help CROs and sponsors run effective and accurate studies during these challenging times?

Machine learning is a quantum leap in the field of predictive analytics, helping ensure accurate and successful forecasting, more accurately and significantly earlier than humans do. It is these predictions that can help to drive planning and informed decisions.

It is this proactive planning that can mitigate mistakes that can impact overall product development costs.

For example, in the case of under-enrollment in studies, an entrenched industry problem, machine learning using leading indicators contained in the clinical development plan (e.g., indication, phase(s), key inclusion/exclusion criteria, etc.) can be used to help ensure that the required sites can be found, so enrollment success can be predicted, prior to the protocol being written and approved.

In addition to the machine learning capabilities embedded in Oracle’s Activate solution, the study planning tool allows sponsors and CROs to fully plan all of its study start-up milestones from protocol approval to activation.

Leveraging multi-plan comparison and visualization tools, users can scenario-plan to determine the best countries and sites to activate, based on the characteristics of the study, to hit enrollment goals in the fastest possible time.

What special programs or efforts around COVID-19 has Oracle made available for sponsors/CROs?

Many pharmas and CROs have pivoted quickly to develop and test potential COVID-19 treatments and vaccines—we at Oracle are working very closely with customers to support those efforts. As of today, the Oracle Cloud is running 93-plus clinical trials to test the safety and effectiveness of COVID-19 drugs and vaccines, across 53 different customers. These trials span many countries and hundreds of investigator sites.

Additionally, Oracle is supporting the National Institutes of Health’s Coronavirus Prevention Network (CoVPN)—formed to respond to the global pandemic with a goal of registering one million volunteers for large-scale testing of vaccines. As part of this initiative, Oracle developed and provided a Cloud System called the CoVPN Volunteer Screening Registry to identify and screen volunteers who want to participate in COVID-19 vaccine clinical trials.

How are new approaches (such as decentralized trials) changing the landscape of study start-up all together?

 Currently, studies which have pivoted to utilizing remote devices and/or virtual visits because of the pandemic, are following a traditional study start-up process. These studies have had their protocol amendments approved by the IRB/EC due to the immediate need to have these studies continue.

The industry expectation is that the use of decentralized clinical trials will continue at scale post-pandemic. This will require assessment and direction from regulatory agencies.

The adoption of decentralized clinical trials will have significant impact on study start-up, as the sequence of processes can change. For example:

Subjects can be found and enroll in trials before or separate from sites and primary investigators.

Devices and virtual tools must be validated prior to being deployed. It is still not clear if this is under the responsibility of the site/principal investigator (source data), or the sponsor/CRO (case data).

These impacts will first be realized when there is an option to run a trial using traditional visits and any regulatory risk has to be assessed.

In addition, digital transformation will also put extra emphasis on the site selection process. As a result, assessing site ability to leverage telehealth will be a factor in site selection.

Beyond what you already discussed, what else do you think the future holds for study start-up?

 In the near future, study startup will be significantly impacted by:

Regulatory changes: The forthcoming ICH E6 (R3) “Good Clinical Practice (GCP)” (draft scheduled for end of this year) will introduce quality by design (QbD) and associated metrics (e.g., QTLs). Quality, which must be ensured upfront in operational systems such as study start-up, instead of after the fact, in systems such as eTMF (electronic trial master file) and QMS (quality management system).

Decentralized clinical trials: As discussed, the pandemic has forced the use of decentralized clinical trials and this use is likely to continue post-pandemic.There may also be more emphasis on a site’s ability to leverage telehealth, as a key factor in the site selection process. We may also see an acceleration in the use of patient hot-spotting technology, which allows the ability to mine electronic health record (EHR) and electronic medical record (EMR) data in a de-identified way to identify a higher quality of patients.

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

Sujay Jadhav, global vice president, study start-up, Oracle Health Sciences, spoke with ACT on how study start-up has been impacted by the pandemic and what its future holds beyond COVID.

COVID-19 Puts Spotlight on Study Start-up

Life sciences companies are looking for ways to get clinical trials started and completed with greater speed and efficiency. The development cycle for a new product typically takes eight years, making clinical trials no quicker today than a decade ago.

 COVID-19’s disruption of clinical operations has made trial starts and execution even harder, delaying more than 1,700 studies.

There is, however, change underway as the industry adopts novel approaches to keep existing trials on track and get new studies up and running faster. As leaders rethink trial processes, study start-up is an area that is a significant accelerator.

Study start-up accounts for 61% of the time spent on a clinical trial

, likely due to delays in the early steps of research. As organizations look to fast-track study start-up, identifying areas for improvement, mapping processes, evaluating systems to find the right technology, and proactively managing change can help speed trials.

In a recent survey, 100% of sponsor and CRO respondents said they need to improve study start-up.

 Study start-up is one of the most time and resource-intensive areas in clinical research, and incremental progress can significantly impact how studies are run.

The teams executing study start-up processes can be key sources for innovation. At the 2020 Veeva R&D Summit, Amy Abernethy, MD, PhD, principal deputy commissioner and acting CIO of the FDA, said innovation happens at “the intersections” where “voices at the table represent different backgrounds, disciplines, and ideas.”

Bringing start-up teams and stakeholders in supporting areas together can drive new ways of working and help leaders prioritize which study start-up activities to optimize first. Study start-up impacts other clinical processes so including the teams doing the work every day in planning sessions provides insights to figure out what is effective and what is not quickly. Identifying areas for improvement is vital to streamlining processes and speeding up cycle times.

With insights into the causes of delays and redundant user tasks, organizations can evaluate end-to-end study start-up processes. The objective is to understand how each step fits together and impacts one another.

Sponsors and CROs cite that site identification, feasibility, and selection is one of the top challenges in study start-up (see Figure 1 below), causing delays and accounting for most of the cycle time in the start-up phase. New technology isn’t necessarily a quick fix. Mapping out the processes in these problem areas before evaluating solutions sets a foundation for change.

For example, examining the impact of the protocol authoring team’s processes on the site identification team and the triggers for identifying sites at the correct times can help uncover process issues. Looking at processes holistically helps teams and business owners identify opportunities to digitize or automate, simplifying study start-up.

Evaluate systems for new, faster ways of working

The processes and systems used to manage study start-up make it harder to speed execution. Heavy reliance on manual processes and general-purpose tools and systems leads to inefficiencies and lack of transparency.

Spreadsheets are the predominant way sponsors and CROs manage study start-up, and others use applications for clinical trial management systems (CTMS) and electronic trial master files (eTMF) (see Figure 2 below). Relying on manual-based processes and applications built for other areas adds complexity to early trial processes. These applications cannot handle the rigor or meet the requirements of study start-up.

The use of multiple applications to manage study start-up perpetuates a lack of visibility across end-to-end study start-up processes, causes delays that have a substantial downstream impact on investigative site activation and study conduct, and can prevent a trial from ever getting off the ground. The learnings from aligning teams and mapping processes can guide leaders to make informed technology decisions.

Features that can simplify study start-up include automated workflows, imbedded process knowledge, and reports and visualizations that help prioritize critical start-up activities. Technology with digital document management and filing can also lessen the burden on sites and speed document collections and submission. A modern study start-up application can help eliminate data and workflow silos, making it easier for start-up teams to do their jobs.

Proactive change management to ensure user adoption

Closely collaborating with the people doing the work, simplifying processes, and selecting the right technology, companies can speed study start-up. The final step is training users on new processes and solutions.

A proactive training and change management approach is critical to ensure people are proficient with new solutions and processes. Identify change champions within your team early on to be the go-to person for questions. Provide training sessions that showcase what will be changing, how changes will make the users’ job easier, and what is not changing.

FAQs and videos can also help teams understand how modernization efforts impact their roles. Provide a clear path for users to submit feedback, such as successes and key learnings. By asking people to provide comments on their experience, companies can build knowledge over time to further improve processes for faster study start-up.

Speed study start-up to accelerate clinical research

Study start-up presents a significant opportunity for the life sciences. This area is especially important now that the industry is looking for ways to keep existing trials running, speed new studies, and prepare for a major wave of post-COVID-19 trial starts.

Sponsors and CROs are leading the shift to innovate early trial processes and speed clinical research. The path to modernizing study start-up begins with identifying areas of improvement, mapping out processes, evaluating systems, and implementing change-management techniques proactively. Taking this holistic approach can position organizations to accelerate study start-up from site identification to enrollment.

PhRMA, Biopharmaceutical Research and Development: The Process Behind New Medicines, 2015.

The Grey Literature, Clinical trials stopped by COVID-19, 2020.

Veeva Systems, Study Start-up Pulse Report & Accessing Post COVID Readiness, 2020.

Veeva Systems, 2020 Unified Clinical Operations Survey Report, 2020.

Senior Director, Vault Study Startup, Veeva Systems

With a major wave of post-COVID trial starts on the horizon, the industry’s need to accelerate clinical research through study start-up is intensifying.

Fast Tracking Study Start-Up from Site Selection to First-Patient Enrollment 

The COVID-19 pandemic is shifting the framework for thinking about medicines development in so many ways and in so many places that it is difficult to keep pace with the immediate changes, and harder still to foresee all the implications for the future. In Europe, deep concerns have been raised about the arrangements granting immunity from liability for the half-dozen manufacturers that have forged supply deals with the European Union for vaccines they have in development, and the still-confidential aspects of these deals leave many unresolved questions for the coming months and years. At the same time, new flexibilities introduced in EU regulations for COVID-related products—notably in absolving manufacturers from the customary prior environmental impact assessment of GM-derived medicines—could be harbingers of a more pragmatic approach when tough realities confront regulators.

Another area where circumstances are demanding novelty of response is conditional authorization. The U.K.—which is going about it more or less alone in its COVID regulation, since the transition period linking it with the EU expires at the end of December—is now finalizing its plans for modifications to its human medicines regulations to support the rollout of COVID-19 vaccines. These are essentially detailed changes—driven by some tough realities—which will cover conditional authorization and other issues. But a public consultation on the plans provoked nearly 200,000 responses, illustrating clearly the sensitivity and degree of concern over many of the planned amendments. Regulators—and drug developers—are likely to face not only the new evident challenges in innovation to combat COVID, but also new levels of public scrutiny and skepticism over the operations of the medicines sector.

The U.K. aim is to strengthen existing regulations that allow for the temporary licensing of medicines and vaccines, on an exceptional basis, pending the grant of a full license. The intention is also to extend the current immunity from civil liability to companies producing the vaccine, rather than just healthcare workers and manufacturers, so as to protect them from legal liability in civil cases (although the U.K. authorities insist that this does not give them blanket immunity from civil liability). At the same time, a wider range of trained personnel will be authorized to administer COVID-19 or flu vaccines, with a view of ensuring that vaccines and treatments for specific types of public health threat, such as a COVID-19 vaccine, can be promoted as part of national vaccination or treatment campaigns. The changes will also make short-term provisions to ease the swift and safe transfer of COVID-19 and flu vaccines under NHS arrangements by providing an exemption from the need for a wholesale dealer’s license.

Explaining the changes to the many anxious respondents to its consultation, the U.K. government’s formal response observes that many of the concerns expressed were not about the new provisions for a temporarily authorized vaccine, but about the very concept of conditional authorization. “The existing Human Medicines Regulations contain a provision (regulation 174) that enables the temporary authorization of the supply of an unlicensed medicine (including vaccines) in response to a public health emergency,” it says. “Many respondents to the consultation expressed concern about this existing provision, rather than the proposal we consulted on, which is to clarify that conditions can be attached.”

The government also notes concerns that temporary authorization meant fast-tracking a vaccine and, therefore, bypassing necessary processes to uphold safety standards, as well as concerns that methods for shorter and smaller clinical trials need consultation and review. Some respondents sought clarification about how long a temporary authorization of an unlicensed vaccine would last.

To dampen these concerns, the government says that COVID-19 vaccines “are being developed in a strategic and coordinated way that allows some stages of the process to happen in parallel to condense the time needed, but it does not mean steps and the expected standards of safety, quality, and efficacy have been bypassed.” It also says that the existing regulation makes clear than any such authorization must be temporary—suggesting that “one of the conditions that could be applied to an authorization could be a specific time limit.” In any event, the government goes on, “we expect an authorization using regulation 174 to be short term, kept under review, and to automatically cease when the product is granted a full license.”

Responding to arguments that a temporary authorization of an unlicensed vaccine should only be used in exceptional circumstances where a licensed alternative is not available, or even that only licensed products should be used, it offers reassurance that “the government’s preferred route to enable deployment of a COVID-19 vaccine remains through the usual licensing routes available. A decision to temporarily authorize the sale or supply of an unlicensed vaccine or medicine will be rare and only in exceptional circumstances.” A product will only be supplied once the relevant government minister is satisfied, in light of advice from the Medicines and Healthcare products Regulatory Authority, that robust evidence demonstrates safety, quality, and efficacy. To appease some of these anxieties, the new rules will now require a public review within a year of the first use of regulation 174 to evaluate the whole process.

The dilemmas are multiple—and the stakes high. Most obviously because of the pressing urgency of successfully developing effective and safe therapeutics to combat COVID—and that is challenging enough for developers and regulators. But because public perceptions of the issues relating to medicines innovation are so heightened by over-ambitious hopes of miracle cures and magic protections, any underperformance or adverse effects of the products that are likely to be rolled out over coming months will receive massive attention. It has often been said that COVID is giving drug innovation an unprecedented, if unfortunate, opportunity to demonstrate its value to society. But it is becoming increasingly clear that anxiety-fueled public expectations are rising to an extent that makes the credibility of the entire medicines sector fragile if expectations are not met.

 is a freelance journalist who specializes in European health affairs and is based in Brussels, Belgium

View from Brussels

COVID-19 pandemic shifts traditional process for medicine development in Europe.

COVID-Related Changes Have Implications for Public Acceptance of Innovation

The much-anticipated meeting of FDA’s Vaccines and Related Biological Products Advisory Committee (VRBPAC) last month addressed a number of critical issues related to testing and approval of vaccines to prevent COVID-19 infection, including policies and data requirements for determining that a pandemic vaccine can be considered safe and effective, particularly when based on more limited, early clinical trial data. A main goal for FDA officials was to reassure the public that it will take all precautions to ensure the safety of any vaccine approved under an Emergency Use Authorization (EUA).

The deliberations may have been shaped by halts in two major vaccine trials at the time due to unspecified safety issues. While studies sponsored by AstraZeneca and Johnson & Johnson’s Janssen unit resumed soon after the meeting, the study pauses were described by researchers as a sign that clinical trial safety systems were working as intended, as the analysts determined the adverse events were unrelated to the test vaccine candidates.

FDA standards for documenting vaccine safety was an important topic for VRBPAC review. The agency’s Center for Biologics Evaluation and Research (CBER) specified in its recent guidance document that it expects an EUA application to provide two months or more of safety data for at least half of the participants in a 

 following completion of the full vaccination regimen (see: https://bit.ly/36azRXc). As most serious side effects appear within six weeks of individual vaccination, this timeframe was designed to provide a sufficient period for detecting rare events such as vaccine-induced enhanced respiratory disease and to distinguish such conditions from COVID-19.

A particularly challenging issue for the advisors was how granting EUA status to an initial product could interfere with further assessment of the vaccine’s safety and with ongoing trials for other preventives. FDA and the expert panel advised that the sponsor of an authorized vaccine should continue blinded follow-up assessments for months following an initial authorization. The aim is to gain further information on vaccine efficacy and side effects, including rare adverse events and fuller comparisons among patient groups with differences in age, sex, comorbidities, and ethnic characteristics. And because information on how long immunity will last will be limited in initial data, both manufacturers and regulators look for additional guidance on determining what data needs to be collected further to indicate when boosters or additional vaccination would be advisable.

However, sponsors raised concerns that it may be unethical to retain trial participants in a placebo arm following EUA approval, raising an important consideration for the research community and health authorities.

At the same time, unblinding a trial could hinder continued development of alternative vaccines, as it would be difficult to enroll new subjects in randomized trials after a vaccine comes to market. Scientists and vaccine developers emphasize that it’s vital for research to continue on multiple preventives, as certain products may affect certain populations differently, and varying formulations may be more suitable for distribution in certain regions.

Most analysts, moreover, expect that some vaccines likely to gain approval in subsequent months may be more effective or provide stronger protection than the early products.

While randomized, placebo-controlled clinical trials are necessary to understand the true effects of a medical product on larger populations, individual participants may gain limited benefit and added risk in the face of a lethal pandemic where the risks are more stark.

An alternative research approach may be to use a newly authorized vaccine as a control in testing subsequent preventives, as a form of noninferiority trial. Such studies may take much longer and cost more to produce results, but could reduce the need for large placebo control arms that deny treatment for thousands.

View from Washington

FDA’s Vaccines and Related Biological Products Advisory Committee addresses issues related to testing and approval of potential COVID vaccines.

Early Vaccine Authorization Raises Ethical and Logistical Challenges for Trial Sponsors

For many years, it’s been discussed that FDA is a barrier to change…mostly related to a change in process or a change of technology. Though regulators would routinely come forward to reassure the industry that their guidance documents supported change, fear and insecurities still abound. It does take time to change, but the FDA really does support advances in clinical trials. But every so often, it is reassuring to hear it in the agency’s own words, especially now with talks of decentralized trials and patient participation. Recently, FDA has been asked about ongoing changes in clinical trials from the point of decentralization and participation.

Last month, Amy Abernethy, MD, PhD, principal deputy commissioner and interim CIO for the FDA, gave the opening keynote for the Veeva Systems R&D and Quality Summit. As a hematologist/oncologist and palliative medicine physician, and internationally recognized clinical data expert and clinical researcher, she shared her compelling views on those discussions. She set the stage by saying the practical reality of clinical trials features two important responsibilities, (1) keep study participants safe and (2) generate a high-quality data set that will answer the question at hand.

For that, Abernethy stressed that the “site is critical to that entire set of activities.” And specifically for decentralized clinical trials, she said: “I think about a series of solutions that help physicians or other healthcare providers involved in the clinical trial process and keep patients safe. It also allows us to be able to have, even if it’s virtual, eyes on the person receiving care to make sure that we know how the patient is doing.”

Abernethy continued, “I think that from the perspective of the site investigator involved in decentralized clinical trials, they still are going to continue to have this incredibly important central function—even if it’s a decentralized clinical trial—of continuing to lead that focus of patient safety, and then also contributing to the clinical trial in alliance with the study protocol.”

At a closed event, a member of FDA declared that “Participating in clinical trials is an imposition on people. If we can move to trial designs that are more pragmatic, with less burden and allows for more participation…” that would be a plus.

There was also the hint that the speed with which FDA issued guidances in the early pandemic could become the norm; the process would shorten to release with a more fluid approach to alterations or changes as needed.

The FDA is moving with the times, and with speed. It will be up to some in the industry to respond in kind.

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

From the Editor

The FDA hints that their increased speed in issuing guidances during the pandemic could become the new norm.

FDA Reassurances Always Go a Long Way

Issue PDF

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

Applied Clinical Trials, November 2020 Issue (PDF)

Syneos Health acquires emerging-biopharma-focused CRO Synteract

Syneos Health, a fully integrated biopharmaceutical solutions company combining a contract research organization (CRO) and contract commercial organization (CCO), has agreed to acquire Synteract, a full-service CRO focused on the rapidly growing emerging biopharma segment. Synteract has built a solid reputation in this space, providing deep therapeutic expertise in oncology, rare and orphan diseases, neuroscience, dermatology, and pediatrics. The company’s client base comprises primarily pre-revenue companies, a segment in which Syneos Health has growth opportunities. Synteract’s 700 employees across North America, Europe, Asia Pacific, and Africa have supported more than 4,000 Phase I-IV clinical trials across 26,000 sites in more than 60 countries.

The acquisition will enhance Syneos’ position in the marketplace, particularly for serving customers across the small to mid-sized (SMID) category. According to industry estimates, funding to the biotech sector has shown no signs of slowing down, remaining near all-time record highs.

Health-management information company SomaLogic, Inc. has struck an agreement with FDA’s Division of Applied Regulatory Science to evaluate the use of large-scale analysis of proteins (proteomics) for the identification of biomarkers that may be useful in demonstrating biosimilarity of a proposed biosimilar to a reference biologic.

The collaborative project will use data generated on the SomaLogic SomaScan Platform, which makes 5,000 protein measurements simultaneously in small samples of blood, to compare changes in circulating proteins following treatment with FDA-approved biologics. The protein measurements from an FDA-approved reference biologic could then be compared to those generated by a candidate biosimilar drug.

Advarra, a provider of institutional review board (IRB), institutional biosafety committee (IBC), quality and compliance consulting services, and research technology solutions has acquired IntegReview IRB, an AAHRPP-accredited central IRB. As a market player in early phase clinical research, the addition of IntegReview enables Advarra to continue its expansion of comprehensive review solutions capabilities in North America.

The Austin, Tex. headquarters for IntegReview will become the first Advarra office in the southern US.

According to a report by Bizwit Research & Consulting, the worldwide DNA sequencing market garnered a valuation of $4.7 billion in 2019 and is projected to record a year-over-year growth rate of 11.3% during 2020-2027. Increasing demand for DNA sequencing in biological research applications and across various medical fields such as virology, biotechnology, medical diagnosis, forensic biology, and biological systematics is expected to augment the industry growth in the upcoming years.

The rising prevalence of cancer, the report notes, serves as a major growth impetus for the global DNA sequencing industry. Nearly 18.1 million new cancer cases were recorded in 2018 and the number is expected to climb to 27.5 million by 2040, the report says, citing data from the International Agency for Research on Cancer.

eGenesis, a biotech using gene editing technologies for the development of safe and effective human-compatible organs, tissues, and cells to address the global organ shortage, has initiated a research collaboration with Duke University School of Medicine. The arrangement will encompass evaluation of gene-edited pancreatic islet cells in non-human primate recipients as a prerequisite to advancing to human clinical trials. This collaboration is in addition to an existing eGenesis partnership with Massachusetts General Hospital, established in 2017.

The first independently accredited Trial Master File University (TMF University) is getting ready to launch its inaugural training series on Jan. 11, 2021. TMF University engages students with a combination of high-quality virtual instruction along with standardized educational competency requirements to prepare internationally qualified TMF experts. It is being facilitated by LMK Clinical Research Consulting and has received accreditation from the International Accrediting Organization for Clinical Research (IAOCR).

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A compilation of recent notable news developments that pertain to the clinical trials industry.

News Notes (November)

Developed in the 18th century by the Reverend Thomas Bayes, the essence of the Bayesian method is to update our beliefs about hypotheses as data accumulates. This approach allows every new piece of data to serve as evidence to update a hypothesis. Bayes’ rule then consists of a “prior” either based on evidence already collected, or scientific findings in the case of early-phase trials (i.e., a prior can be both informative and non-informative). A rule then explains how to update these priors in order to make sense of newly collected evidence. A “posterior” is then the result of the prior being updated in light of this new evidence.

Touted for their ability to create flexible trial designs and accelerate learning while doing so, Bayesian methods have played a key role in transforming clinical research in therapeutic areas from oncology and rare diseases, where they protect patients by efficient modeling, to medical device trials, where the gains in effectiveness can be quickly calculated using Bayes’ rule. Bayesian methods are also popularly used for interim analyses, where Bayesian predictive power calculates the probability of reaching a specific trial outcome based on the data at hand. They can also be used in a variety of ways for performing meta-analyses, for integrating historical data into a trial, and for combining insights from multiple data sources. They have also begun to play an important part in infectious disease trials for epidemics and pandemics like Ebola and COVID-19, where the demand for fast learning and flexible designs comes together.

This article reviews the main Bayesian methods used in clinical trial design. After a short history of Bayesian and Frequentist methods, we delve into Bayesian methods for early-phase and late-phase designs. We highlight the fact that Bayesian methods can be useful for trials that have both Bayesian and Frequentist designs, and that ultimately the decision to use Bayesian methods depends on the specific context of the trial in question. Sound trial design requires understanding the specific research question, and having a sense of the program-level strategy as necessary to drive scientifically rigorous conclusions under resource constraints. There is no firm rule on when to use Bayesian and Frequentist methods, but knowledge of both can result in informed decision-making about a specific trial’s design in order to generate sound statistical results under resource- and time-constraints.

Brief history of the status and uses of the p-value

Bayesian statistics have a much older history than Frequentist methods, but their use within the clinical development setting has taken time to establish. Frequentist methods became the norm for drug development in the 1960s and ’70s, mostly because it was easier to undertake the calculations and computations necessary for Frequentist statistics without the use of fast or powerful computers. Even today, the number of simulation and modeling tools necessary to perform Bayesian computations requires statisticians to be well- resourced technologically.

As, historically, Frequentist methods have been easier to use, this has resulted in the widespread use of Frequentist concepts like p-values and type 1 error rates as industry norms for measuring statistical rigor. Unlike Bayesian probabilities, which aim to tell us the probability of a statement or hypothesis given the data, the Frequentist p-value tells us the likelihood of seeing the data before us if a certain hypothesis were not true. A low p-value then means it would be highly coincidental if the hypothesis were false while the data that appears to confirm the hypothesis is true. The type 1 error rate then conveys the probability that we rejected a null hypothesis when it is true (false positive).

Frequentist designs can often require higher sample sizes than Bayesian methods, and are considered by some to be less flexible and less intuitive. Others point out that the decision to use Frequentist or Bayesian designs is a matter of context. Both methods have particular strengths, in varying situations. Therefore, this paper considers both Bayesian methods used for Bayesian trials, as well as examples of how Bayesian methods can strengthen insights of trials that are Frequentist.

Bayesian designs are frequently used in early-phase trials due to their flexibility and efficiency. For example, as participants in what are typically first-in-human trials, there is very little known about the response of a drug within the human body, especially regarding toxicity. Therefore, patients and sponsors benefit from a trial design that enables frequent interim looks, opportunities for adjusting doses, and stopping for futility when required.

Popular Bayesian dose-finding approaches like the continual reassessment method (CRM), the Bayesian logistic regression method (BLRM), and the modified toxicity probability interval (mTPI) employ Bayesian methods, modeling, and decision making to achieve two goals: proper patient allocation to safe and efficacious doses during the trial and efficient estimation of the maximum tolerated dose (MTD) at the end of the study. Parametric Bayesian models, with or without a dose-response curve, provide the foundation for statistical inference in these designs, which increase the probability of finding the MTD as well as assigning patients to better doses.

After dose-finding, Bayesian designs can be applied in Phase Ib expansion cohort trials and Phase II trials with one or more treatment arms. Recent developments in oncology drug development have provided great opportunities for Bayesian designs, such as MUCE, to improve the Phase Ib multiple expansion trials.

 Phase II Bayesian designs using hierarchical models allows basket trials to efficiently assess the efficacy of a therapeutics in multiple disease indications.

 Other usage of Bayesian designs includes the Bayesian continuous monitoring in single-arm Phase II trials, as well as Bayesian dose-ranging designs for non-oncology drug development.

 A recent review can be found in Tsimberidou, Müller and Ji (2020).

Bayesian methods in early-phase Frequentist designs

While several Bayesian methods exist for early-phase trials, Bayesian tools can also be used to prepare or augment trials that make use of Frequentist designs. When designing a Frequentist trial, the use of historical data has become much more common as a starting point for developing hypotheses, estimands, and designs. Historical data may also be useful when a concurrent control is not feasible for ethical or practical reasons. A variety of approaches to using historical data exist, through which data from an external source can be incorporated into the analysis of the current trial and act as a guide to update the current data.

The initial step in such approaches involves the identification of relevant data from previous or ongoing studies. These data must be selected carefully, and one must determine whether they are exchangeable with data from the current trial. They are rarely exchangeable at the patient level, although exchangeability at the aggregate data level may be more realistic. Common methods for the incorporation of historical information include commensurate priors, power priors, meta-analytic predictive (MAP) priors, and others.

The latter MAP approach derives a prior distribution from a random-effect meta-analysis of historical data via Markov Chain Monte Carlo (MCMC) algorithms. The prior distribution is represented by a parametric mixture whose components are determined by the use of an expectation-maximization algorithm. One can also increase robustness of the parametric MAP by adding a weakly-informative prior component to the mixture derived from the previous steps. The degree of how informative the MAP prior is can be assessed with its effective sample size, which provides a rough guide of how much the sample size can be reduced when using the respective frequentist power calculation as a reference.

At the program-level or portfolio-level, Bayesian model-based meta-analyses can also play a role to determine which of many candidate therapies ought to proceed to the next stage of clinical development. They can also anticipate what data will be needed for later stages of trial design, making them invaluable for seamless studies or strong Phase III trials.

A further use of Bayesian methods involves the calculation of benefit-risk profiles, usually conducted after safety studies are complete. When making such a calculation, the ethical standard should take into consideration every piece of data available at our disposal, from historical data from other trials, to the effects of the current therapy on various endpoints. Bayesian methods enable trial sponsors to collate these various forms of data into one benefit-risk calculation.

Recent publications in medical literature have illustrated several advantages of Bayesian methods for designing and analyzing confirmatory trials. The recently published case study redesigning the Phase III OSCAR (High Frequency OSCillation in Acute Respiratory Distress Syndrome (ARDS)) trial using Bayesian methods showed that the Bayesian sequential design could shorten the trial duration by 15 to 40 weeks and recruited 231 to 336 fewer patients.

Authors of another trial illustrated that by using Bayesian designs, the trial could have declared adrenaline superior for 30-day survival with 1,500 fewer patients.

The advantages of Bayesian analysis have also been shown by post-hoc Bayesian analysis of two recent high-profile trials, EOLIA and ANDROMEDA-SHOCK. Both studies demonstrate a large clinically important mortality difference but failed to reach p-value ≤ 0.5.8 These analyses show that the Bayesian analysis helps inform interpretation of the study beyond Frequentist’s binary “positive or negative” delineation.

Bayesian methods help optimize trials at several levels. Optimizing interim monitoring by enabling more efficient and informative decision-making as early as possible is one of the key advantages. Within the Frequentist framework, interim analyses usually evaluate the treatment benefit based on completed patients. However, a more relevant question to answer at interim analysis would be whether a trial is likely to reach a definitive conclusion by the end of the study. Futility is inherently a prediction problem and, therefore, best addressed by predictive probability than by p-value.

Bayesian methods also offer advantages for efficacy monitoring. The predictive probabilities formalize the decision to stop accrual in a manner consistent with the decision process of the data monitoring committee (DMC). Another important advantage of Bayesian methods is the ability to incorporate partial data into the estimation of predictive probabilities, especially for trials requiring long follow-up periods.

 Although partial information would not be used for regulatory submission purposes, the use of incomplete information can help to de-risk interim futility or efficacy.

Here we have highlighted the need for more Bayesian methods employed in pharmaceutical development, both for design and analysis. The array of Bayesian methods is vast, and with computing power now more easily accessible to a wide range of statisticians, these methods are perpetuating the trial design space. From early-phase trials to late-phase development, utilizing Bayesian tools can expedite and/or de-risk trials, even when used to augment a Frequentist framework. They are critical for learning quickly and employ flexible strategies for sound scientific outcomes.

There are statisticians who insist that Bayesian methods are always an improvement on Frequentist methods, and vice versa. At a practical level, though, a knowledgeable quantitative strategist should be able to pick and choose methods from both these paradigms that serve the needs of a specific sponsor.

Therefore, it is always important to partner with a team that has strong working knowledge of both paradigms, along with regulatory knowledge of how to combine these methods acceptably.

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Vice President of Strategic Consulting, Cytel, 

Bayesian methods bring flexibility and speed to clinical trial design and analysis, and with increased access to the necessary computational power, are transforming today’s clinical research.

Applied Clinical Trials-11-01-2020