Kenneth Getz is a senior research fellow at the Tufts Center for the Study of Drug Development.

Kenneth Getz

During the COVID-19 pandemic, some have observed that principal investigators with minimal experience, limited infrastructure, and low study grant income have divested from clinical trial activity. Delays, and in some cases cancelled clinical trials, during the early stages of the pandemic made it difficult for these investigators to cover their operating costs and remain viable. Anecdotal evidence supports this observation but there is no hard evidence to confirm it and characterize the magnitude of these departures.

A recent analysis by the Tufts Center for the Study of Drug Development (Tufts CSDD) provides updates on the global landscape of FDA-regulated investigative sites that will serve as a useful baseline for comparisons. The results of this analysis show that this global landscape remains very fragmented with a disproportionately high concentration of low-volume principal investigators. But the data also suggests that—even without the effects of the pandemic—the landscape is scaling and maturing with a growing proportion of higher-volume principal investigators now operating in North America compared to 10 years ago.

Consistent with past studies, Tufts CSDD analyzed data from the Bioresearch Monitoring Information System (BMIS) maintained by FDA’s Center for Drug Evaluation and Research (CDER). The Tufts CSDD team extracted data on investigators filing form 1572 between 2010 and 2020. A unique identifier based on last name, first name, and country was used–instead of the Reviewer ID—to avoid counting duplicate records inadvertently created by slight variations in variables due to typos and alternate spellings.

For this analysis, investigator productivity is defined as the volume of clinical trials associated with each unique identifier. Turnover rates are defined as the percentage of unique identifiers who filed at least one 1572 form in a given year but had not filed another 1572 form within the subsequent four years. Past research conducted by Tufts CSDD has demonstrated that if an investigator does not file a new 1572 form within four years, it is highly likely that they will never file again.

To assess investigative site landscape changes, Tufts CSDD considered using ClinicalTrials.gov, as it is becoming a more valuable and reliable source for data. However, for our purposes, use of ClinicalTrials.gov is problematic. It lacks data on individual clinical investigators, instead providing a less granular view at the facility level that cannot determine investigator-level changes. It cannot detect, for example, if a site network loses a clinical investigator but remains listed as active due to involvement by other investigators at that facility. Dedicated sites and site networks may engage individual investigators located in distinct geographic locations, yet the ClinicalTrials.gov filing may only list the facility’s central address.

Slowing growth, especially among low-volume investigators

There were 32,077 active principal investigators operating worldwide in 2020. This number continues to grow but at a slower overall rate of 1.5% annually during the most recent 10-year period compared to 4.6% annually in the prior decade.

The least productive principal investigators—those filing only one 1572 in 2020—make up the highest proportion (66%) of the global site landscape. Approximately one in four (23%) investigators filed two to three form 1572s in 2020 and 11% filed more than four form 1572s last year. But growth in the least productive principal investigator segment has remained flat during the past decade and the segment share of the total has been declining steadily. This compares to 3.2% annual growth for this segment during the previous 10-year period.

The most active principal investigator segments have been growing at a much faster rate: the segment comprised of those who filed between four and six form 1572s each year has grown 5.2% annually since 2010; those who filed seven or more form 1572s have grown 8.6% annually during that same period.

The distribution of FDA-regulated principal investigators remains highly global but the movement away from North America observed 10 years ago has now reversed direction. In 2020, 63% of all principal investigators were based in the US and Canada; 19% in Europe; and 18% in the rest of the world. This compares to 57% in North America; 20% in Europe; and 23% in the rest of the world a decade ago.

The rest-of-world segment—which includes the highly populous areas of China and India—has lost the largest share of total FDA-regulated principal investigators. The shift is due in part to drug development sponsors having difficulties dealing with legal, regulatory, and health authorities and limited oversight and investigative site infrastructure there. The growing proportion of investigators based in North America, and the sustained proportion in Europe, confirms sponsor and CRO preference for placing clinical trials in more mature and established regions during the past decade.

The principal investigator segment in North America is scaling as site selection practices dictate engaging study conduct providers with more experience, infrastructure, and patient diversity. In 2010, the proportion of low-volume, single-form 1572 filers was 63%. In 2020, the proportion had declined to 55%. During this period, the higher-volume, more experienced principal investigator segment grew from 11% to 17%. In Europe, the reverse has occurred: whereas in 2010, 84% of principal investigators were low volume filers, in 2020 that proportion grew to 91%. In the rest of the world, the proportion of low-volume, single-form 1572 filers declined modestly from 82% in 2010 to 78% in 2020.

Turnover rates among FDA-regulated principal investigators remain high but they have been improving during the last 10 years. In 2010, 40% of all individual investigators who had filed form 1572s four years earlier failed to file again. In 2020, that proportion had declined to 35%. Turnover rates have improved during the past decade in North America, but they have worsened in Europe and the rest of the world. Whereas in 2010, 48% and 46%, respectively, of all individual investigators in Europe and the rest of the world who had filed form 1572s four years earlier failed to file again, in 2020, the proportions increased to 56% and 50%, respectively.

And similar to that observed 10 years ago, turnover rates among the least-active principal investigators—those filing a single 1572 form each year—are the highest, with approximately half choosing not to file again.

As we continue to move into a post-pandemic operating environment, new benchmarks and measures will inform trends in the global investigative site landscape. Once data from 2021 and later years is published by the FDA, the fate of novice principal investigators can be quantitatively assessed. In addition, we look forward to documenting the ongoing impact of virtual and remote support on traditional clinical trial execution models. 

Articles

New benchmarks uncover a maturing and globally-shifting market.

Tracking Change in the Global Investigative Site Landscape

Since the release of the first ICH E6 Good Clinical Practice guidance in 1996, outlining international standards in the design, recording, and reporting of clinical trial data, technological advances in drug development have made it possible to conduct more clinical trial activities remotely and in patients’ homes. Although a revision to this earlier guidance was released in 2016 (ICH E6 R2), there has since been increasing adoption of decentralized clinical trials, as well as more use of technology given the COVID-19 pandemic. As investigative sites conduct more decentralized and hybrid trials, data collection is increasingly falling to the patient (e.g., wearable devices, smart phones). Stakeholders have expressed concerns about the impact of this trend on protocol complexity and patient participation burden during trials. The principles and guidelines in ICH E6(R2) influence the complexity of trial protocols and, by extension, the burden of data collection, validation, and reporting on investigative site staff and patients. Although the ICH E6(R2) guidance is meant to protect the “rights, safety, and well-being of trial subjects,” it does not sufficiently address the patient’s growing role or the roles of the many vendors and third parties that have entered the market.

The ICH E6 guidance is currently being revised (ICH E6 R3), and the industry has yet to see how this new iteration will approach oversight of these emerging external stakeholders. The goal of this study is to provide insight on ICH E6 revisions that could improve clinical trial operating activity by incorporating the patient’s changing role and those of the many stakeholders, including new entrants into the pharmaceutical industry.

The Tufts Center for the Study of Drug Development (Tufts CSDD) conducted a study in collaboration with MaxisIT, a technology solutions provider.* In early 2021, Tufts CSDD examined and identified areas in the ICH E6(R2) guidance document that fall short in accommodating the role of patients/study volunteers as partners in clinical data collection. To gather in-depth perspectives on these topics, Tufts CSDD facilitated three 2-hour virtual listening sessions in March 2021 among 20 clinical operations, data management, and regulatory affairs executives. A 2-hour virtual roundtable discussion was later held in mid-June 2021 to review the results of the listening sessions, gather additional insights from listening session participants, and add new voices and perspectives to the research. A total of 26 individuals attended the roundtable. Finally, Tufts CSDD interviewed six roundtable attendees during the summer of 2021 with relevant and extensive backgrounds in clinical trial regulation and development to expand upon the findings from previous discussions.

One pervasive issue that emerged during the interviews and discussions is the increased patient and study staff burden when unfamiliar technology is utilized for a trial. Although awareness and knowledge among the general public surrounding basic technology has grown exponentially in the last 10 years, patient and study staff burden can increase when the technology is sophisticated or has an interface that is unfamiliar. As a result, patient and study staff capabilities differ by trial, site, and geographic area, so the use and type of technology should be centered around the individual patient as well as the site capabilities.

One suggestion for decreasing knowledge-based patient burden when patients are oversight partners in a trial is adhering as much as possible to existing standards of care. For example, a diabetes patient participating in a diabetes-related clinical trial will have certain familiarity and capability around medical instruments and procedures more than a “healthy participant.” Whenever possible, responsibilities placed on the patient should adhere to the existing standard of care for the given disease.

Collecting feedback from trial participants and sites is another important way to prevent burden in future trials or improve the level of burden in ongoing trials. Some sponsors have struggled to effectively collect feedback from patients due to confidentiality concerns, or simply do not have feedback mechanisms available. A few participants from larger sponsor companies discussed channels in place for some trials that collect feedback from patients and sites during the study design process, throughout the treatment duration, and following the end of the trial. Such feedback channels can potentially decrease patient burden by adhering to what the patients believe is burdensome. However, these feedback channels have not been widely implemented and it will take time for sponsors to not only establish these mechanisms but also to learn to accurately interpret and cater to the patients’ needs.

A consistent theme surrounding patient burden and data collection is to only collect data that is critical to the trial and avoid extraneous protocol data collection. Although guidance in this area has been established, further clarity surrounding the restriction of extraneous data collection in ICH E6(R3) could decrease burden for the patient and the site. Other basic guidelines that currently exist may contribute to resolving this issue, such as ICH E8, which encourages patient feedback and input into study design.

During trials in which patients collect their own data and provide oversight, monitoring professionals still must review all patient activities and data. Discussions and interviews revealed concerns about how monitoring professionals can identify relevant data; validate the data; and integrate new technology in this process. Though we have yet to see how many companies will revert to on-site monitoring after the pandemic and how many will continue with decentralized models, multiple participants stated that they think many companies will return to on-site monitoring. Some of these are smaller sponsors without the technology to continue remote monitoring. Others might have a new system that relies on CRO partners, and internal staff may not be familiar with the technology. If on-site monitoring returns, the development of a remote monitoring process that allows monitoring professionals to overcome the challenges that accompany patient-collected data and patient oversight practices could be delayed until the use of decentralized trial models is more established among both large and small sponsor organizations.

Training and technological solution standardization were proposed as resolutions for decreasing burden on both patients and study staff and was discussed extensively throughout the listening sessions, roundtable, and interviews. Although there were mixed thoughts on the effectiveness of training in patient data collection and incorporating new technology systems, most participants agreed that training helps, but it should not be the only solution when confronted with these challenges. The simplicity and clarity of processes and systems, among others, are also important factors.

ICH E6(R3) should focus on data quality and patient engagement—in this case, patient engagement could mean patients have input into study design or aspects of data quality and verification. Additionally, throughout this study participants have discussed the detrimental focus on 100% SDV among sites. ICH E6(R3) should further highlight risk-based monitoring over 100% SDV, as monitoring and validating patient-collected data with 100% SDV would be difficult to carry out and would increase burden on the site and the patient.

Many participants discussed lack of system standardization across sponsors and its effect on the site’s ability to collect data and conduct trials quickly and effectively. Systems can also differ across sponsor organizations or departments within the same organization, creating confusion and additional burden for sites that have to navigate learning various systems for the same purpose. Although select vendors’ products are commonly used by most sites, there is rarely only one system that sites and patients are required to use.

Some participants in the roundtable and interviews did not see any resolution to the lack of standardization and vendor agnostic** solutions. The discussions clarified the different needs and operations across sponsors and sites, which has led to adoption of hybrid technology solutions. According to participants, implementing one system with the same capabilities across every site has not been feasible, as some level of customization is necessary for most trials. Participants expressed a need for integration and standardization of systems, however, and sponsors have not yet made the move to adopt or build centralized data platforms to improve their ability to maintain oversight and collaborate. Despite various limitations and evolving scenarios, standardization is still an important topic, and some steps can be taken to minimize the cost and time burden as well as potential risks resulted from delayed data that lack of standardization causes. One of these steps involves focusing on strategy or more efficient processes for using vendor agnostic technology when attempting to standardize systems. For example, sponsors could potentially standardize their processes so sites can more easily train for and adhere to methods across sponsors. Technology solutions should then be able to support these new methods. This process has occurred previously with GCP/ICH training, where study staff training with one sponsor can be applied to multiple sponsors across trials.

Participants did not think standardization was applicable to ICH E6, and in fact some were concerned that addressing this problem in the guidance could hinder innovation and make it more difficult for sites to operate. Standardization must occur among sponsor organizations with the focus of alleviating site burden. However, the guidance can help by implementing guidelines around topics such as third-party vendor oversight that encourage standardization of processes among sponsors, which could potentially lead to system standardization.

Leaving room for innovation in ICH E6 guidance

A common thread of conversation throughout the course of the research was maintaining simplicity and flexibility in the ICH guidance in order to be widely applicable across sites. However, a more general version of the guidance may result in variation of its interpretation among sponsors and sites. Some participants said that misinterpretation can increase burden because sites do not know what the regulator will look for during inspections. This confusion over the requirements influences the implementation of 100% SDV and other unnecessary and time-consuming tactics.

Regulators can prevent misinterpretations by providing transparency around the focus of inspections, making it easier for sites to adhere to these requirements. Additionally, industry groups and institutions can contribute to a general understanding of the guidance that will help those sites or sponsors struggling to achieve clarity in the interpretation.

The ICH E6(R3) guidance that is being developed is currently a collaborative effort with professionals from a variety of clinical trial fields incorporating their insights. This effort could contribute to a more widely interpretable document. Providing transparency on the guidance’s base principles while not being too didactic or restrictive can also leave room for innovation within the space of clinical research.

The main barriers to incorporating patients as oversight partners in clinical trials—and the acknowledgement of patients as stakeholders in the ICH E6 guidance—include the absence of technology standardization between and within sponsors and sites, protocols that overburden patients or require gathering extraneous data, and industry silos. The pharmaceutical industry is unlikely to adapt quickly to the needs of remote and hybrid trials and patients overseeing their own data collection because these barriers prevent quick turnaround. Therefore, it will take time and multiple research initiatives for the idea of patients as oversight partners to become commonly accepted and implemented throughout the industry.

ICH E6(R3), which is scheduled for release later this year, is expected to address the rapid innovations in technology and design that impact the conduct of trials. The guidance can also help encourage adaptation by considering the needs of sponsors and sites and allowing for flexibility in conducting trials. According to participants in this study, innovation is not driven by regulations. Instead, regulations create a minimum standard of quality and care in a clinical trial, and the more flexible regulations are, the more space there is for innovation among sponsors and sites.

Efforts to incorporate patients as oversight partners while addressing these potential drawbacks include training, collection of patient feedback, system standardization, vendor agnostic data platforms and maintaining an open channel of communication between the site and the patient. Although these solutions also contribute to mitigating the increase of patient and study staff burden, many sponsors have not, or state that they are not currently capable of, implementing them. Additionally, despite the higher use of digital processes and remote trial solutions during the COVID-19 pandemic, participants in this study anticipate that many sponsors will likely return to pre-pandemic standards as a result of lack of infrastructure and resources. Although patient oversight approaches have a strong place in the future of clinical trial technology, progress must be made before the industry is ready to adopt.

*This research study was funded by MaxisIT.

** In this article, vendor agnostic solutions/technology refers to a solution/technology that is generalizable, so it is interoperable among various systems.

Note: The authors would like to acknowledge Monique Garrett of PrismWorks for her contribution to this article.

Research Analyst, Tufts CSDD and School of Medicine Development, 

Professor and Associate Director, Tufts CSDD and School of Medicine Development, 

Deputy Director, Research Professor, Tufts CSDD and School of Medicine

Improving receptivity and response to the evolving nature of clinical trial patient oversight.

Assessing Sponsor and CRO Awareness

The remarkable speed in which sponsors have developed and delivered COVID-19 vaccines and treatments has intensified an already high interest among sponsor companies in compressing drug development cycle times. And there are numerous targeted opportunities in their sights—from protocol design and vendor and site identification to study start-up and patient enrollment; from clinical data management and study closeout through statistical analyses and dossier preparation.

Until recently, however, efforts to target and achieve speed and efficiency have focused on tasks and timelines within clinical phases. Now, more attention is being devoted to the breakdowns that occur between phases when clinical data and operations transition from one research phase to the next. These transitions—also referred to as “white space”—may be ideal targets for information technology, open collaboration, augmented analytics, and machine learning to accelerate program durations, improve performance, and lower costs.

Over the years many sponsor companies—some with assistance from consulting firms and contract research organization (CRO) partners—have measured the white space between their programs’ clinical phases. Regrettably, the results of, and insights from, these exercises have neither been shared publicly nor published.

Recently, my group at the Tufts Center for the Study of Drug Development (Tufts CSDD) was able to conduct a robust analysis based on all drugs and biologics approved between 2008 and 2018 (n=377). Although the transition time between Phase I and II could not be reliably measured due to wide variation in early-stage activity supporting development programs, we were able to measure transition times between the completion of Phase II and the start of Phase III pivotal trials. In our analysis, Tufts CSDD only looked at non-expedited review programs to remove the effects of an accelerated regulatory process.

Tufts CSDD found that for all non-expedited development programs approved between 2008 and 2018, 82% had between-phase transitions (white space) of 17 months on average; 18% had no white space as Phase II completion and Phase III pivotal trial timelines overlapped. Our study also found that white space durations have increased during the past decade. During 2008 to 2013, the mean white space duration was 12 months; between 2014 and 2018, the mean white space duration between Phase II and III pivotal trials nearly doubled to 21.6 months.

To supplement our data analysis, Tufts CSDD interviewed clinical operations, regulatory, and data management executives. The sponsors interviewed widely agree that white space inefficiencies have represented a persistent challenge for decades and that attempts to compress phase transition time have been elusive.

They point to four primary causes of between-phase inefficiencies:

The time-consuming back and forth with regulators and health authorities.

Mistakes sponsors make in gathering inappropriate and incomplete inputs into decision-making late in the process.

The failure to anticipate downstream needs (e.g., manufacturing of clinical trial supplies).

The inability to build the appropriate level of internal consensus and alignment around key decisions.

Most companies acknowledge that they expend substantial resources and time in administrative activity preparing, submitting, and sharing results with regulatory authorities. They also note the inefficient and time-intensive internal process, and post-regulatory meeting, of finalizing the Phase III pivotal trial protocol. One sponsor estimated that they spend on average four to five months of time on this back-and-forth alone.

White space durations are extended during protocol planning when external inputs—from scientific leaders, regulatory agencies, and health authorities—are insufficient, incomplete, and require second-guessing. Misunderstanding of global regulatory environments and the uncertainty around reconciling multiple and diverse scientific and regulatory inputs contribute significant time inefficiencies and delays.

Several executives interviewed believe that to mitigate risk, sponsor companies seek more-than-necessary input from, and spend too much time on relationships with, regulatory agencies during phase transitions.

Sponsor companies also suggest that whereas they generally know their program’s objectives extremely well, they fail to obtain the necessary inputs and insights from Phase II data to optimize critical Phase III decisions. Several sponsors note, for example, the critical and often inadequate role that Phase II data plays in informing primary Phase III endpoint(s), dose-finding, and dose-selection decisions. One executive observed that the failure to properly interrogate and leverage Phase II data is a common problem that ultimately forces sponsors to amend and expand later-stage clinical trial activity to make up for these shortcomings. She suggested that more flexible and adaptive designs may play an important role here.

Many of the executives interviewed suggest that despite the high volume of data collected during Phase II clinical trials, white space inefficiencies are partially caused by collecting the wrong—or an insufficient amount of the right—Phase II data.

Most sponsors note the opportunity to shorten white space by anticipating where problems will occur, developing contingency plans, and responding proactively. Doing so permits companies to make faster decisions and cues up organizational resources to handle situations as they unfold.

Several interviewees, for example, mention the importance of anticipating and coordinating ethics committees and boards of health dispersed widely around the globe. Some acknowledge the importance of planning the commercial formulation of the investigational drug or biologics before initiating later-stage pivotal trials. As one sponsor explained:

“It’s essential that large, treatment-testing studies utilize a commercial formulation of a drug so there’s no question about bioequivalence. But manufacturing that formulation—especially like the complex ones that are becoming more commonplace—can take months or even years to scale up.”

Given high growth in the volume of Phase II data collected, there is wide consensus among sponsor companies that data and analytics—enhanced by artificial intelligence (AI) and open collaboration models—can play a key role in accelerating white space timelines. Another recent Tufts CSDD study found that the typical Phase II protocol generates 2.2 million data points today, up from 378,000 data points 10 years ago. This is nearly a 500% increase and the highest area of growth in data volume per protocol per phase.

Several sponsors go even further and argue that machine learning and other AI-enhanced analytics, combined with information hubs and collaboration solutions, represent a clear and essential approach to best leverage protocol data volume and limited human capacity and competency. In this vein, several months ago, 10 major pharmaceutical companies announced that they had formed a new corporation—Accumulus Synergy—to support collaboration between industry and health authorities. The new non-profit entity will utilize a cloud-based platform to compress the white space caused by the back-and-forth between sponsors and regulatory agencies. The founding companies anticipate substantial acceleration through real-time collaboration, cross-agency harmonization, data exchange, and submission.

In the transition between development phases, there is no defined timeline in which key decisions have to be made. White space inefficiencies represent a unique opportunity for sponsors to accelerate development timelines because they are a function of administrative, project management, information processing and exchange. The efficiencies between phases may be easier to achieve as they rely far more heavily on internal team expertise, collaborative effectiveness, and their interaction and exchange with regulatory authorities. Within-phase efficiency gains rely heavily on improvements in relationships with a large and growing number of external service providers—a more complex, fragmented and difficult area from which to consistently glean speed improvements.

As we imagine opportunities and solutions that are now available to accelerate drug development timelines, the possibility of compressing white space may finally be within our grasp.

Compression between phases to accelerate cycle time.

Characterizing White Space in the Quest to Drive Development Speed

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.

As early as this past April, Pew Research reported growing public support for the pharmaceutical industry. This could not have come any sooner. Only eight months earlier (September 2019), Pew Research reported that the pharmaceutical industry was the most poorly regarded of all industries, having finally received the lowest rating of all those evaluated. Many may recall a Pew Research study published several years ago showing that the pharmaceutical industry’s reputation had fallen sharply putting it on par with the oil and used car industries.

In July 2020, the Harris Poll conducted among several thousand Americans noted that 54% gave the pharmaceutical industry positive ratings. This was a remarkable 22 percentage point increase above the results that Harris had reported in February 2020, one month before widespread lockdowns went into effect. Harris noted in its report that pharmaceutical companies were “… the only industry to sustain reputation gains through the pandemic. While other industries—such as grocery, retail, technology, consumer products and financial services—also rose during the spring and summer, most spiked in May and have since flattened or dropped back to typical pre-COVID levels.”

And a global poll conducted by Caliber Research in September 2020 reported that public perceptions of the pharmaceutical industry had improved measurably around the world. The poll solicited responses from more than 13,000 people. Caliber noted that “COVID-19 is playing a very important role in reminding people of the [pharmaceutical industry’s] importance and relevance, especially in markets like the U.S. where the pandemic’s positive reputational impact has so far been the greatest.”

Between April and October 2020, news coverage of coronavirus drug development activity appeared several times per week. Beginning in early November, however, daily coverage became the norm as preliminary results of late-stage COVID-19 vaccine trials, funded by Operation Warp Speed, were publicized. Pfizer-BioNTech was the fist to announce in early November followed by Moderna in mid-November and AstraZeneca-Oxford University later in the month. In December, regulatory agencies including the FDA’s Center for Biologics Evaluation and Research (CBER) will begin making decisions with regards to EUAs. Through the Operation Warp Speed program, drug and biologic development will be more than 80% faster than the typical clinical duration for vaccines.

A number of nongovernmental committees and panels are providing input and expertise to inform emergency access and approval, as well as vaccine distribution and logistics decisions. These committees include the Vaccines and Related Biological Products Advisory Committee (VRBPAC), which provides input into EUAs and approvals of vaccines. The Center for Disease Control’s (CDC) Advisory Committee on Immunization Practices (ACIP) provides input into the distribution of vaccines and their use. In partnership with these committees, CBER and the CDC have far greater public transparency.

Collectively, these agencies and committees now face the difficult task of facilitating unprecedented development and commercialization speed while reassuring the public that no corners have been cut and that these treatments and vaccines are in the most competent and capable hands.

Operation Warp Speed leadership has yet to clearly indicate publicly how COVID-19 vaccines will be allocated. And although ACIP, the CDC, the National Academies, and outside consultants have all been meeting to discuss prioritization of COVID-19 vaccines when they are available, lack of clarity and simple messaging tailored to the lay community has contributed to speculation in the media and ultimately public confusion and concern. At the outset of the pandemic, public confusion and concern began mounting—and has not abated—with the poor availability and apparent mismanaged distribution of personal protective equipment and the antiviral medication remdesivir.

The majority of the public worldwide supports vaccines. But a vocal minority—very often without rational or scientific basis—is against vaccination. Concerns over a link between vaccines and autism, for example, persist despite scientific evidence to support it. Public confidence in vaccines varies by country and by communities within a given country.

The media tends to exacerbate the problem. They report adverse patient conditions and/or patient deaths associated with the time of a vaccination, but not the results of investigations into the cause of death. These investigations, completed long after misinformation has been in circulation, typically show that the condition and/or death was unrelated to the vaccine.

For COVID-19 vaccines to be widely embraced and to deliver on their promise, they must engender public confidence and trust. Clinical research and healthcare professionals must ensure that their messages about vaccines and their distribution are balanced and transparent in depicting risks, benefits, and uncertainties. Messages must also be customized to the community that they target. Plain, non-technical, tailored communications in the mass and social media will go far in helping to build this balance and transparency. Consistent and simple—but not oversimplified—communication is essential. Creative communications developed by a collective of major advertising agencies will be highly valuable input here.

Media briefings will also prove helpful as many reporters have little to no background in medical research and healthcare. Partnerships with patient advocacy groups will also help ensure that communications reach a broader community via sources that are perceived as trusted and credible.

Producing and distributing plain language summaries of COVID-19 vaccine clinical trial results will also play a major part in building public and patient trust. At this time, the pharmaceutical companies leading Operation Warp Speed late-stage vaccine trials have signaled their primary intent to publish the results of their clinical trials in medical journals and on the NIH ClinicalTrials.gov registry. But this is not enough. These channels are primarily geared toward the scientific and medical community. Plain language summaries should be disseminated—simultaneously with the publication of technical summaries—to patients who participated in the clinical trials through public-facing healthcare communication channels, patient advocacy groups, mass media outlets, and digital and social media.

Despite unprecedented investments in vaccine development and distribution, public confidence in COVID-19 vaccines is hopeful but tenuous. This is due in large part to historical context, the lack of clarity and transparency from government agencies and the clinical research and healthcare professional communities. It is also due to the spread of misinformation since the pandemic began.

Global vaccination programs that rid the world of COVID-19 will succeed only if there is widespread belief and trust that these vaccines are safe and effective, that policies for prioritizing and executing their distribution are equitable and rational, that every individual has an important part to play. Translating the scientific progress and promising new vaccines into successful vaccination programs will require overcoming the significant challenge of building public trust and confidence through frequent, comprehensive, consistent, customized, balanced, and straightforward communication and education.

MBA, Deputy Director and Research Professor, Tufts CSDD; Chairman of CISCRP. Reach Ken Getz via email at 

Battle for trust ensues as vaccines are set for approval.

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

Of the more than 1,600 active clinical trials of treatments and vaccines for SARS-CoV-2 (COVID-19), four vaccine trials are in late stage (Phase III) activity. These promising candidates have received funding through the Operation Warp Speed (OWS) program from the US federal government. The primary aim of OWS is to rapidly develop and distribute a sufficient amount of safe and effective vaccine doses to immunize the U.S. population against COVID-19.

A look at the placement and conduct of these late-stage clinical trials offers insight into site engagement practices necessitated by global public health urgency. What do these site engagement practices tell us about sponsor confidence in meeting extremely aggressive enrollment timelines and demanding trial execution requirements? Do these practices signal a shift in where sponsors can be expected to conduct clinical trials in the future?

This article summarizes the results of a study that we have performed to answer these questions. Our goal is to assess COVID-19 site placement practices and to compare them with historical practices.

Classifying Phase III COVID-19 vaccine trials site segments

For this assessment, we have included all locations where Phase III COVID-19 vaccine studies, under Operation Warp Speed, are actively enrolling patients as of October 8th. Sponsors who were engaged in studies fitting these criteria are Moderna, Inc., Janssen Pharmaceuticals (in partnership with the Biomedical Advanced Research and Development Authority or BARDA), Pfizer, Inc. (with BioNTech), and AstraZeneca (with Oxford University).

 to identify the investigative sites participating in each of these four active Phase III COVID-19 vaccine trials. Although investigative sites in these trials continue to change, this study examines all sites that were actively enrolling as of October 8th. Data from ClinicalTrials.gov was supplemented by press releases, news articles, and other publicly available information to segment investigative sites into five categories based on the following definitions:

Site Networks (SN): defined as a collective of independent sites that derive the majority of their income from clinical research grants.This includes dedicated independent sites that are permanently part of, or affiliated with, a network. Sites within this category are generally for-profit organizations;

Academic Medical Center (AMC): defined as any site which has a major affiliation with a teaching institution. This includes any site that is a member of the Association of American Medical Colleges as a Medical School Member or a Hospital/Health System Member. Sites within this category are generally not-for-profit organizations;

Health System: defined as any entity that is, or is affiliated with, a system that includes a hospital. Sites within this category are both for-profit and not-for-profit entities. Some for-profit health systems have established not-for-profit entities within themselves for the purpose of carrying out clinical research, a factor that makes this segment difficult to classify;

Independent Medical Practice (IMP): defined as any community-based, independent clinical care provider that is not part of a larger health system. Sites within this category are generally for-profit organizations;

Government Entity (GE): defined as any site that is funded and administered by the federal government. The two major types of government entities include Veterans Affairs organizations and Indian Health Service affiliates. Sites within this category are not-for-profit organizations.

Sites supporting AstraZeneca and Oxford University’s COVID-19 clinical trial were not named in ClinicalTrials.gov; in the US, only the zip code and city name were provided.To identify and classify these sites, we used not only press releases and local news articles, but also cross-referenced the AZ site locations with sites participating in the other three sponsors’ studies.

Overall, we found that approximately half (53%) of Operation Warp Speed (OWS) clinical trials are placed within site networks; one-third (34%) of clinical trials are placed within academic medical centers; 5% within health systems; and the remaining 8% are roughly evenly placed within government entities and independent medical practices (see Table 1 below).

With the exception of Janssen’s late stage COVID clinical trials, site networks and academic medical centers operating in the US were the dominant two settings. SNs and AMCs combined to account for almost 90% of all clinical trial settings for AZ, Pfizer and Moderna programs; these two segments together account for 75% of sites conducting the Janssen clinical trial. For-profit site networks were the largest category in every clinical trial except for those sponsored by AstraZeneca, where AMCs comprised the majority.

Site networks made up at least two-thirds of both Moderna and Pfizer’s study sites; whereas they only accounted for about 40% of sites in Janssen and AstraZeneca’s clinical trials. The similar site placement patterns observed in Moderna and Pfizer’s clinical trials may in part be due to their use of the same contract research organization (PPD).

Academic Medical Centers account for over half of AstraZeneca’s sites (52%), making them the only sponsors to have engaged more AMCs than SNs.

Janssen has almost five times as many government entities as the next closest sponsor with 10% of all clinical trials being placed within federally-funded institutions. This is in part due to Janssen and BARDA’s higher relative utilization of Veterans Affairs offices.

Table 2 below shows that Janssen’s COVID-19 clinical trial is the most evenly dispersed across for-profit and not-for-profit organizations. Moderna and Pfizer are the most heavily weighted toward for-profit investigative site settings (68-70%) vs. not-for-profit settings (24%-28%).

Comparing COVID-19 trial placement to past placement practice

The most striking observation in this study is the remarkable consistency of placement practices over time including those testing new treatments and vaccines for COVID-19. In 2013, a study from the Tufts Center for the Study of Drug Development (CSDD) noted that “53% of all global FDA-regulated clinical trials are now conducted by independent, community-based principal investigators”.

 This 53% share of the total site landscape is identical to the share captured by site networks in COVID-19 vaccine trials.

Academic medical centers have held on to a more modest share of industry-funded clinical trials. In a 2007 report, Tufts CSDD noted that “today, only one-third of all industry-funded clinical trials are placed within academic clinical trials offices”.

Our study found a similar percentage —34% — of late stage COVID-19 vaccine clinical trials are being conducted within academic settings.

Academic medical centers have not been alone in their inability to increase market share of industry-funded clinical trials. Government entities — such as Veterans Affairs offices — have captured an even smaller share of this market. This is due in part to the protracted contracting, negotiations, and bureaucracy that historically contribute to slower study start-up times there when compared to that of site networks and dedicated investigative sites.

 Academic medical centers have leveraged their experience, prestige, infrastructure, and patient volume to maintain their market share. The VA setting, on the other hand, has been a consistently less attractive place for industry-funded trials.

 During the pandemic, with increased interest in public-private collaboration, the VA setting for industry-funded clinical trials will likely receive greater visibility.

Comparing sponsors of late stage COVID trials, those companies most closely collaborating with government and non-profit partners (e.g., AstraZeneca and Janssen) have placed their clinical trials in a higher relative percentage of academic medical centers. In the case of AstraZeneca, this decision is consistent with the company’s historical site placement practice: In 2007 AstraZeneca’s R&D director Ellis Wilson remarked that, “by mitigating bottlenecks on the critical path, academic sites are becoming more attractive and may even start to account for a growing proportion of trial placements. The pendulum is swinging back in their direction. And pharmaceutical companies want to be their partner of choice".

In the past, sponsors have relied on independent, for-profit investigative sites when speed and efficiency are paramount. In today’s COVID-19 vaccine landscape, the same holds true. Moderna and Pfizer’s studies, with their heavy reliance on for-profit sites, are moving the fastest in the race to prove the safety and efficacy of their vaccines.

Given the consistency observed in investigative site placement practices, we can assume that there will be a similar consistency in sponsor experience with participant diversity and inclusion for their COVID-19 trials. We can expect to see the same levels of proportional representation by participant demographic subgroup: White and Asian participants will be overrepresented, and participants from minority communities — most notably those of Black and African descent — will be underrepresented. This is particularly concerning given the higher observed rate and severity of COVID-19 cases among minority communities. Indeed, a lack of diversity has already been documented in both the NIAID Adaptive Covid-19 Treatment Trial (ACTT-1) and the Gilead-funded remdesivir study.

It is interesting to note the very low percentage of investigative sites from health systems and independent medical centers participating in these late stage COVID-19 clinical trials. Although these segments offer access to a large volume of patients within clinical care settings, combined they account for less than 10% of total sites. Similar to pre-pandemic conditions, these entities have been less attractive settings when compared to site networks and academic medical centers that offer larger numbers and more dedicated personnel; higher levels of experience and competency; and substantially greater research infrastructure.

 Hospitals and independent medical centers were also the slowest to respond during the early stages of lockdowns throughout the US, and these sites were among the most likely to suspend their clinical trials at the outset of the pandemic.

Community hospitals often find themselves being passed over during site selection in favor of academic medical centers which boast experienced investigators and specialized researchers.

 This is another reason why new investigators and health systems are not participating in COVID-19 clinical trials: sponsors place a high value on prior experience rather than total potential for accessing and attracting a large and diverse patient population. This fact makes it difficult for new investigators and sites to get their foot in the door for new clinical trials, and nowhere is this trend reflected more than in this research. Sponsors and CROs are choosing to place their study sites within entities that have proven track records, and the result is that site networks and AMCs account for over 85% of late stage COVID-19 vaccine trial sites.

Some independent medical practices and health systems are turning to partnership as a way to win and participate in more trials. The integrated research organization (IRO) is an emerging model that is allowing multi-specialty practices and community health systems to be involved in clinical trials as a research care option for their patients. Privia Health, Tryon Medical Partners in Charlotte, North Carolina, and the AMC of Wake Forest University Health, for example, are benefitting through partnership with IRO Javara Research to participate in COVID-19 vaccine trials which other health systems in the same geographic areas in some cases have not managed to secure. We can expect to see these integrated research partnerships become more common as other health systems and medical practices recognize the high-profile COVID-19 studies that IRO partners have been able to win.

In the race against time, during a pandemic that has, to date, claimed nearly 250,000 lives, sponsors and CROs are placing their COVID-19 clinical trials in the same places that they have been doing so for decades. Site networks and academic medical centers continue to dominate- and the majority are based in the US. Independent medical practices, health systems, and government entities are playing a relatively small role in late stage COVID-19 clinical trials. Sponsor company site placement practices may likely contribute to participant disparities by race and ethnicity typically seen in pre-pandemic clinical trials unless remedial and innovative approaches are utilized.

https://www.appliedclinicaltrialsonline.com/view/principal-investigators-take-lead-fda-regulated-studies

Getz KA. Industry Trials Poised to Win Back Academia. Applied Clinical Trials. 2007; 0(0) para. 3, 22. Retrieved October 8, 2020, from 

https://www.appliedclinicaltrialsonline.com/view/industry-trials-poised-win-back-academia

Getz KA, Lamberti MJ, Chakravarthy R. Assessing Practices & Inefficiencies with Site Selection, Study Start-Up, and Site Activation. Applied Clinical Trials. 2016; para. 4. Retrieved October 8, 2020, from 

https://www.appliedclinicaltrialsonline.com/view/limited-boosts-study-start

Salzman S. The VA Gets Real on Reform. Applied Clinical Trials. 2019; 28(9): para. 3. Retrieved October 30, 2020, from 

https://www.appliedclinicaltrialsonline.com/view/va-gets-real-reform

Chastain DB, Osae SP, Henao-Martínez AF, Franco-Paredes C, Chastain JS, Young GN, et al. Racial Disproportionality in Covid Clinical Trials. The New England Journal of Medicine. 2020; 383(9) e59-e59. Retrieved October 30, 2020, from 

https://www.nejm.org/doi/full/10.1056/NEJMp2021971

Paulsen E, Practice-Based Clinical Trials: Benefits and Barriers. Duke Health. 2016. Retrieved October 30, 2020 from 

https://physicians.dukehealth.org/articles/practice-based-clinical-trials-benefits-and-barriers

Kaplan GA, Weaver R, Cloud B. Clinical Trials: Insights from the Inside. Applied Clinical Trials. 2020; para. 13. Retrieved October 30, 2020, from 

https://www.appliedclinicaltrialsonline.com/view/effect-covid-19-clinical-trials-insights-inside

Glabman, M. Community hospitals branch out to clinical research. ACP Hospitalist. 2008; para. 8. Retrieved October 30, 2020, from 

https://acphospitalist.org/archives/2008/12/research.htm

, Tufts Center for the Study of Drug Development

Comparing late-stage COVID-19 vaccine trials to historical practices.

Investigative Site Placement Practices to Support Operation Warp Speed

New drugs and biologics approved in 2018 signal an exceptional period of change and opportunity in global drug development. This past year, the FDA approved 59 novel small-molecule (NDAs) and large-molecule biologic (BLAs) therapies-the highest number in history (see chart below). 

	This is a remarkable achievement, particularly in light of the anemic number of annual approvals that we saw in the 2005 to 2010 period. At that time, several industry watchdogs and prognosticators cautioned that the industry had exhausted its ability to develop truly novel and innovative therapies. They could not have been more wrong.

	What is most notable about 2018’s approval volume is not only the scientific innovations that produced them, but also where they originated, how they were funded, and the operating models, services, and technology solutions that supported them throughout the R&D process.

	One revealing feature that sets the 2018 class of approvals apart is the fact that 73% were approved under “priority review” status, meaning they were recognized by the FDA as important, truly novel treatments warranting an accelerated regulatory process. They are therapies targeting medical conditions for which there is no available treatment on the market or they offer substantial improvement over current therapies, including a standard of care.

	One-third of all new approvals in 2018  are first-in-class offering a novel mechanism of action-a new way of treating a particular disease. This is another record achieved by last year’s approvals. They represent exciting, truly novel breakthrough therapies, including next-generation vaccines, new antibiotics for drug-resistant infections, combination therapies, nanomedicines, microbiome or bacteria-based treatments, and gene therapies. 

	Immunotherapies have been one of the leading headliners (e.g., checkpoint inhibitors, CAR-T therapies, and other adoptive cell transfer drugs) and they top the list of breakthrough therapies receiving approval.  The first immunotherapy was introduced less than a decade ago; there are now nearly 2,000 cancer immunotherapies in small and large animal studies and in human testing. And immunotherapies that have already been commercialized to treat one form of cancer are now pursuing and receiving regulatory approval to treat many other cancer-related diseases.

	In addition to novel therapies, the FDA also approved the use of a record number of already-marketed drugs to treat new disease conditions and to be offered in new formulations that are more effective, accessible, and/or convenient to patients.

	In addition to notable areas of scientific innovation, new 2018 drug and biologic approvals also reveal a major shift in the composition of the drug pipeline and in the types of companies sponsoring drug development activity. Historically, the majority of new drug approvals targeted increasingly crowded chronic diseases affecting large numbers of people. Nearly 60% of approved drugs today target rare diseases that represent very small markets relative to those for chronic disease-or blockbuster-therapies.

	More than one-quarter (27%) of all new approvals are precision medicines. They rely on biomarker and genetic data to identify a far more targeted patient subpopulation that has a much higher likelihood of responding to a new treatment safely and effectively. According to the Tufts Center for the Study of Drug Development (Tufts CSDD), half of all drugs in the overall R&D pipeline-and about 80% of all drugs in development for cancer-related diseases specifically-now rely on biomarker and genetic data to target therapeutic agents.

	And whereas new approvals were historically dominated by the largest, top 50 pharmaceutical and biotechnology companies, today the majority of approvals are for drugs in development programs sponsored by small companies-many that are funded by private equity and venture capital. Sixty-percent of new approvals were from sponsors submitting their very first application to the FDA. This, too, is a record achievement.

	Small companies have unique needs, including a heavy reliance on outsourcing to support discovery, preclinical, and development activity; a proclivity to seek more open collaboration and data sharing models; and far more limited resources.

	In 2018, approximately $150 billion was spent on global R&D activity. Tufts CSDD estimates that R&D spending has been rising 6% annually since 2000. Nearly nine out of 10 drugs entering clinical testing fail, with wide variation in failure rates across different disease conditions. Investigational cancer treatment failure rates are among the highest. Drug development processes are highly complex and inefficient, with durations that have shown little to no improvement in more than three decades. And, on average, the typical drug generates a relatively low and declining return on its development investment, given the high capitalized cost-now estimated at $2.6 billion-to successfully bring a single drug through FDA approval.

	To remain viable, drug developers must transform long-standing R&D operating processes and practices that are largely insular and sequential, supported by redundant resources and personnel and that underutilize key assets and expertise. The growing prominence of precision medicines and treatments for rare diseases and targeted patient subpopulations-all requiring more complex clinical trial designs and longer durations to identify and recruit patients-intensify the pressure on drug developers to accelerate this transformation.

	Another revealing quality of the graduating 2018 class of NDAs and BLAs is that some are part of an emerging new paradigm that holds promise in delivering better quality, speed, and efficiency at lower cost. According to the Economist Intelligence Unit (EIU), during the past five years, an estimated 3% to 5% of clinical trials were “patient centric,” in that they included patients in clinical trial planning and design and they were executed with approaches that supported greater participation convenience (e.g., use of mobile technologies, transportation assistance, home- and work-based participation). The EIU found that patient-centric clinical trials had Phase II and III enrollment rates that were 40% faster. They also noted that drugs approved with patient-centric clinical trials had higher success rates and a greater likelihood of receiving formulary approval by insurers. Although the numbers are small at this time, we anticipate having more data on approvals in the coming years to further demonstrate the impact of this new operating paradigm.

	A growing number of new approvals are also being developed in an environment that favors more open, precompetitive data and information-sharing. New approvals also favor increasing use of external collaborations and service providers that offer scientific and operating expertise and operating advantages, smarter use of resources, and greater leverage of data and analytics to inform, manage, correct, and predict.

	During the past several years, we have seen massive investments by traditional R&D players and new entrants, consortia, the capital markets, and the public sector in data and data management capabilities and technology solutions and applications.  There is an enormous appetite currently for more sophisticated analytics, including machine learning and natural language processing to analyze a much higher volume of data from diverse sources (including clinical data and real-world evidence such as electronic health and medical records); to prioritize and target resources; to identify and interpret data patterns; to assess and mitigate risk; to manage complex logistical and manufacturing processes; to benchmark practices and, increasingly, to predict scientific and operating outcomes and performance.

	Patients and patient advocacy groups are playing a growing role in helping to direct and even fund drug development programs, to define clinically meaningful outcomes, and to push the scientific community to provide higher levels of relevance, convenience, flexibility, and transparency. 

	We are getting closer to being able to aggregate and look at data across the entire R&D and commercialization continuum. Components of an historically fragmented and disaggregated system within drug development and within the broader healthcare arena are becoming increasingly connected and integrated to share and make better use of scientific and operating data to support open and collaborative learning-what the National Academy of Sciences calls a Learning Health System-where every response a patient has with a commercially-available or investigational therapy informs personalized treatment as well as public health outcomes. As integration unfolds, we expect clinical research and clinical care to converge to drive efficiency through the removal of intermediaries and redundant fixed infrastructure and labor-intensive activity. And we expect patients, payers, and providers to play active roles in the development of new treatments.

	We have a long way to go to realize the full promise of this new operating environment and to navigate critical issues like data ownership, data privacy, data compatibility, and the gleaning and refereeing of insights in the data. But, as we revel in 2018’s new drug and biologic approvals, we are already seeing truly novel scientific innovations generated by a changing community of sponsor companies piloting and operating under an evolving drug development paradigm.

	There are now more than 11,000 active molecules in the R&D pipeline-a 5-7% year-over-year rate of growth across the span of two decades-to address unmet medical needs and improve patients’ lives. This is indeed an unprecedented moment.

, MBA, is the Director of Sponsored Research at the Tufts CSDD and Chairman of CISCRP, both based in Boston, MA. email: 

Record numbers point to new R&D operating environment, driven by a changing community of sponsors.