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Applied Clinical Trials December 2022

Ukraine invasion tests the resiliency and quick action of CROs and sponsors

Mobilizing and Maintaining Clinical Trials in Midst of War

ACT's biennial Salary Survey takes a look at the future of industry following increased adaptation of decentralized technology 

Salary Survey: The Age of COVID

The Pistoia Alliance launched its freely accessible FAIR4Clin guide. The guide will help clinical regulators, biopharmaceutical and healthcare organizations to implement the FAIR principles (Findable, Accessible, Interoperable, Reusable) in clinical datasets. 

FAIR4Clin was co-authored by the Pistoia Alliance and experts in the field, including from AstraZeneca, Bayer, Roche, Genentech, Galapagos, The Hyve, Elixir, The University of Manchester, and Oxford University.

Read more about the guide and how to access it 

Articles

Guide will help clinical regulators, biopharma, and healthcare organizations to implement the FAIR principles.

Pistoia Alliance Publishes Freely Accessible FAIR4Clin Guide

Patient enrollment performance is a chronic challenge in clinical development. Three years of the COVID-19 pandemic has caused a number of investigators to back out from participating in clinical trials, and the war in Ukraine has reduced geographic coverage for trials in various indications. Moreover, a global economic downturn and intensifying global inflation have made already costly clinical trials more expensive.

In this report, we leverage site level patient enrollment data in Phesi’s Trial Accelerator platform to assess the number of investigator sites that have recruited only one patient, the impact from those sites, and possible methods to improve enrollment.

A total of 173 cancer clinical trials with site level enrollment data, the majority conducted in the past three years, are included in this analysis. Most of the trials severely impacted by COVID-19 are not included. Overall, cancer trials take at least three years to complete and publish results; the cancer trials started before or during the pandemic and affected by the shutdown do not yet have available enrollment data. In the dataset, there are 11,826 investigator sites that enrolled one or more patients, totaling 83,916 patients.

117 companies and organizations sponsored these trials. The top sponsors of these cancer trials are Hoffmann-La Roche, Novartis, Regeneron, Merck Sharp & Dohme Corp., and Pfizer.

These investigator sites are distributed across 57 countries globally. The top countries include the United States, Germany, Japan, and the United Kingdom.

Most of these trials are Phase III (81) and Phase II (51) trials. 169 of the 173 trials have 10 or more enrolling investigator sites.

Of the 11,826 investigator sites identified in the data, 2,298 enrolled only a single patient. By definition, these sites enrolled a total of 2,298 patients.

In other words, a total of 19% investigator sites (2,298/11,825) contributed less than 3% of the enrolled patients (2,298/83,916). In contrast, the top 16% of investigator sites contributed 54% of the enrolled patients.

 conducted by the Tufts Center for the Study of Drug Development (Tufts CSDD) which found that 11% of sites fail to enroll a single patient and 37% under-enroll.

Based on a $40,000 site activation cost and $3,000 per month to manage a site, a study running for 30 months with just one patient will cost $130,000. In contrast, the best performing sites operate at approximately $14,000 per patient for similar study durations—just over 10% of the cost per patient at single patient sites.

Single patient sites prolong enrollment cycle time in two ways. A high percentage of single patient sites lowers the overall enrollment rate. It also requires more sites to complete enrollment. This complicates the operating space and dilutes resources from a focus on higher enrolling sites, which also contributes to a lower enrollment rate.

We cannot easily assess the impact of the data quality obtained from those single patient sites. It is safe to assume, though, that there are clear statistical liabilities when 50% to 70% of sites contribute just a single patient. For example, there are usually a set of subjective disease measures in cancer or other disease trials. A single patient at a site means there is no comparison to be made, which would increase the risk of measurement deviation. In addition, there is a steep learning curve for new sites and there are likely to be higher deviations with the first few patients until the site becomes familiar with the study.

Single patient sites are a significant factor in enrollment challenges, which also includes sites enrolling zero patients. The same dataset reveals that the number of activated but “zero patient recruited” sites amounted to 27% of those sites that recruited one or more patients.

The following chart shows a correlation between the percentage of non-enrolling sites and percentage of single patient sites. Each dot represents a cancer trial. The key takeaway is that when the overall quality of investigator sites selected for a cancer trial is not satisfactory, the proportion of both non-enrolling sites and sites enrolling only single patient is higher.

There are some positive elements to be found in the analysis. Despite the high percentage of single patient enrolling sites, the median enrollment is four patients per site. This means half of sites enrolled patients at an operational cost per patient equal to 25% of those that enrolled only a single patient, or less.

Across all the analyzed trials, the percentage of single patient sites ranges from 2% to 76%. Of the trials Phesi analyzed, 37 trials, or 21%, managed to reduce single patient sites to less than 10%.

Over the past 10 years, the industry has made a significant effort to improve investigator site enrollment performance. Yet, we don’t believe enough has been done to minimize the number of poorly performing sites.

Typically, current investigator site selection has focused on past clinical trial experience, which is far from sufficient. Clinical operations/study managers should ask:

Are past experiences relevant to the current study?

Are they aligned with the academic focus?

What is an investigator site’s past enrollment performance?

Can we predict an investigator’s future performance?

Igor Bondarenko, MD, PhD, from Ukraine is one of the most prolific investigators among the 173 trials. He enrolled 113 patients for the 11 trials in which he participated. The median number of patients he enrolled is nine. There is no trial where he enrolled only a single patient.

While COVID-19 naturally impacted his level of involvement, the Ukraine war seems not to have stopped him from participating in clinical trials.

Bondarenko has broad coverage in various cancers but focuses mostly on solid tumors. From the type of candidates he has been involved in developing, we can deduce his familiarity with various biomarkers, which is increasingly important for precision medicine for cancer treatments.

*All results were sourced from Phesi’s 

, Executive Director and Professor, Tufts Center for the Study of Drug Development

Already existing enrollment challenges emphasized by single patient sites.

Phesi Report: Assessing Single Patient Investigator Sites in Cancer Clinical Trials

Clinical trials will continue to play a crucial role in the future of medicine. With the rise of the Millennial and Gen Z generations, it is important to consider how these demographic shifts will impact the design and execution of clinical trials. As technology advances and our understanding of medicine evolves, the way clinical trials are conducted is also changing. In particular, the future of clinical trials will likely significantly impact Gen Z and Millennials, who have grown up in a digital age and have different expectations of healthcare and research.

One key factor to consider is that Millennials and Gen Z are more tech-savvy and connected than previous generations. This means that they are more likely to be open to using digital tools and platforms for clinical trial participation, such as electronic consent forms and remote monitoring devices. Additionally, these generations are often more accustomed to engaging with health information online and may be more likely to seek out and participate in clinical trials advertised through social media or other digital channels (i.e., Google Ads). I’ve personally found that online advertising works very effectively at recruiting patients within that age group.

Another important consideration is that Millennials and Gen Z are more likely to value personalization and transparency in their healthcare. This means they may be more interested in participating in trials that offer personalized treatment options or provide detailed information about the trial process and potential risks and benefits in an easy-to-understand way. Additionally, these generations have a great interest in expressing their personal values, such as social impact, which may increase the likelihood of clinical trial familiarity and willingness to participate.

One of the biggest changes in the future of clinical trials is the shift towards decentralized trials (DCTs). While the concept is relatively new in the industry, it has gained ground, and 

regulators have written a recommendation paper

. Data collection methods typically used in DCTs can include using smartphones and wearables to collect data and telemedicine to monitor patients remotely.

The benefits of decentralized trials for Gen Z and Millennials are numerous. For one, they allow for greater flexibility and convenience for participants, who can participate in the trial from the comfort of their own homes. This can make it easier for people to participate in trials, particularly those who may have mobility issues or live in remote areas. Additionally, decentralized trials can also help to increase diversity among participants, as people from different backgrounds and locations can participate. All of these factors 

Another important aspect of the future of clinical trials and DCTs is the increasing ability to use artificial intelligence and machine learning due to data digitization. For one, they can help increase the speed and accuracy of data analysis, leading to better treatments and faster drug development. Additionally, AI and machine learning can identify new potential drug targets and predict which patients are most likely to respond to a particular treatment. Say goodbye to the tasks of conducting interim data analyses if you can visualize your study’s endpoints and predict them in real time on a dashboard.

However, there are also risks associated with decentralized trials, particularly regarding data security and privacy. As more and more personal information is collected and stored digitally, DCT companies may become the target of hackers and data breaches. Additionally, there may be concerns about the accuracy and reliability of data collected through remote monitoring devices and apps, which could lead to inaccurate results and false conclusions. Furthermore, decentralized trials can make it easier for professional trial participants to participate in multiple trials simultaneously, especially if there is no database to track multiple trial participation.

There are also risks associated with using AI and machine learning in clinical trials. One of the biggest concerns is that these technologies may perpetuate existing biases and disparities in healthcare, as they are only as unbiased as the data they are trained on. Additionally, there may be concerns about the transparency and interpretability of the results these technologies generate, as it can be difficult to understand how they make decisions and predictions, especially for people who need to be trained in data sciences.

In summary, the future of clinical trials will likely significantly impact Gen Z and Millennials and will look very different. Decentralized trials and the use of artificial intelligence and machine learning are likely to become more prevalent, bringing many benefits such as convenience, flexibility, and increased diversity among participants. However, there are also risks associated with these changes, particularly regarding data security and privacy, as well as the potential for existing biases and disparities in healthcare.

, MBA, MSF, is a thought leader and expert in the application of business analytics toward clinical trials, and Editorial Advisory Board member for and regular contributor to Applied Clinical Trials.

Recent industry advancements such as DCTs, AI, and machine learning are shaping the future of clinical trials.

Clinical Trials in the Millennial and Gen-Z Era

Curebase has announced the release of its integrated software and services package for digital therapeutics (DTx) trials. Available now, the new offering includes a DCT platform bundled with site and trial execution services for the DTx market.

New offering includes a DCT platform bundled with site and trial execution services for the DTx market.

Curebase Launches Software Package for DTx Trials

Precision for Medicine has announced the strategic acquisition of SolveBio by QuartzBio. SolveBio's technologies and enterprise data management platform has integrated into QuartzBio's suite of SaaS solutions, providing a single, scalable solution supporting clinical sample inventory management and biomarker data management for the biotech and pharmaceutical sectors.

SolveBio's enterprise data management platform has integrated into QuartzBio's suite of SaaS solutions.

Precision for Medicine's QuartzBio Acquires SolveBio

Elligo Health Research® has introduced Data

 Connect, a new data and technology platform that will enable data-driven clinical research. Data

Connect creates efficiencies across the clinical study workflow—reducing human error and digesting patient data to accelerate clinical trials.

Introduces new platform which will reduce human error and accelerate trials.

Elligo Adds AI-Driven Clinical Research Study Technology

On January 31, 2023, the use of the Clinical Trials Information System (CTIS) will become mandatory for new clinical trials applications and will serve as the single-entry point for submission by sponsors and for regulatory assessment. The EMA reiterated this deadline and updated the community on the current status of the system, which has been in transition for one year. 

EMA reminds the clinical trials community that the Clinical Trials Information System will be mandatory at the last day of this month. 

One Week Left for CTIS Mandatory Use Date

Peter O'Donnell is a freelance journalist who specializes in European health affairs and is based in Brussels, Belgium.

By now, some of the dust is beginning to settle on the controversial refusal by the European Union to extend its Jan. 31 deadline for compliance with its new Clinical Trials Regulation, and attention among the clinical trials community is gradually turning toward other challenging issues.

But a rankling sense of resentment inevitably remains, both over this specific piece of legislation, and over the broader issues of the quality of the legislative process in the EU. Despite a mid-January admission by the European Medicines Agency (EMA) that some 20% of the arrangements for the operation of this radical shift in clinical trials approval were still not in place, EU officials had insisted that going ahead was, nevertheless justified because of "recent improvements introduced in the system and progress made to prepare for mandatory use."

"More than 80% of the blocking issues and related workarounds have been resolved, with activities remaining on track to deliver a system with no blocking bugs on core functionalities by Jan. 31," said EMA in a Jan. 18 statement. It invoked its "commitment for the system to be functional for Jan. 31, 2023, and in compliance with the relevant Clinicals Trial Regulation provisions from this date." Yet as recently as October, the agency had itself been admitting that the problems presented by the new system were leading to some users needing intensive support. Across Europe, the uptake reported in many countries during 2022 was slow, with repeated indications of serious "teething problems" encountered by sponsors. In November, broad swathes of the German clinical trials community stigmatized the new system as "largely unmanageable for all those involved," and issued a firm call for the deadline to be postponed. Their complaint over the complexity of registering new clinical trials was echoed across Europe.

The sense of exasperation is all the more intense because this was not an unforeseen difficulty, given the well-recognized tendency of new IT systems to over-run on time and budget and to reveal unexpected misfires. The Clinical Trials Regulation was adopted as long ago as 2014—long enough to get everything in place before pressing the "go" button, many critics argue, and strong arguments for deferral if the "go" button is not ready. Salt has been rubbed in the wound by the EU's recent decisions to defer—twice—deadlines for compliance with another major piece of health legislation, covering 

 devices and diagnostics, in response to widespread complaints that neither the sector nor its regulators were ready.

All this is conspiring to reinforce existing concerns that EU legislators are becoming over-optimistic—and even cavalier—in their design and implementation of new rules. The unhappy experience with rules on clinical trials and medical devices is itself disheartening enough (and it is remembered with no satisfaction that the "new" Clinical Trials Regulation emerged only a decade after the EU's first attempt to legislate on clinical trials proved to be so misconceived and full of errors that it had to be replaced). But everyone working in clinical trials in Europe is also well aware that the even more influential 2016 rules that the EU rushed through on data protection were so badly drafted and finalized that the legislation continues to be an obstacle in health research.

The greater concern now is that the wave of new legislation that it is scheduled to hit the EU as from 2023 will turn out badly. And the wave that is gathering is huge. One element is on the table since mid-2022—an ambitious proposal for sharing health data, which is already being criticized for imprecision. But by the spring of this year, the EU is expected to be starting formal debates on updating the principal pillars of EU pharmaceutical law. The proposals, currently scheduled to appear in March, will spell changes to the conditions for applying for and obtaining marketing authorization for medicines, and for incentives for research and development—particularly into rare diseases and paediatric medicines. The preliminary discussions among EU officials as they work toward finalizing their proposals have not been entirely harmonious: an early draft was turned down flat during the summer by one of the legislative watchdogs in the EU hierarchy, and officials were told to do their homework again.

This doesn't mean that the new laws will necessarily lead to catastrophe. As is the case with the clinical trials rules, the legislators' intentions may be constructive. It is obviously important that EU rules are kept up to date with advances in science and technology, and views among officials and across the health sector coincide that there are plenty of areas in need of regulatory improvement. But the risk is that good intentions may not be enough to avert unintended consequences. And recent experience has not inspired confidence. The stakes are high. Getting it right could boost research, development, and patient care in Europe. Getting it wrong could hasten Europe's decline in global health innovation.

The issues engulfing compliance with the Clinical Trials Regulation signal that even the best  intentions with these types of laws may not be enough to avert unintended consequences.

Get it Right Next Time? EU Legislation Under Critical Review

Dr. Harsha Rajasimha, Founder and Chairman of IndoUSrare, discusses the emotional reason behind founding the non-profit, programs they offer that are helping rare disease parents/patients, rare disease research in India, and much more.

Podcasts

IndoUSrare: Purposeful Clinical Research For Rare Diseases In India

DM Clinical Research has opened its first research location in the Boston metropolitan area and Massachusetts. The company also announced it will soon start enrolling patients in Moderna's CMVictory Trial studying mRNA-1647, an investigational vaccine, to understand whether it can help the immune system protect against cytomegalovirus (CMV).

Read more about the new site and partnership 

National site network continues expansion, partners with Moderna on CMVictory Trial.

Featured Content

Applied Clinical Trials December 2022

Mobilizing and Maintaining Clinical Trials in Midst of War

Salary Survey: The Age of COVID