Wendy Tate

Today, it’s estimated that it can take over 180 days to activate a clinical research study—time meticulously spent on site selection, project managing, and training. Unfortunately, when you couple these factors with the rise of a global pandemic, these once cumbersome tasks have become even more painstaking, with safety concerns and remote/hybrid procedures creating new operational hurdles to the clinical trial activation process.

Yet, in this era of unprecedented complexity, clinical trials have experienced a renaissance of digital efficiency borne out of the rise of new trial technologies and, perhaps most importantly, metrics.

Ask anyone in the clinical trials space and they’re likely to say the same thing: Metrics “make the world go round.” From initial protocol development to the execution lifecycle stage, metrics and performance data have grown to become critically important indicators, not only of a site’s performance, but also of a trial participant’s progress at every step of the way.

Thanks to the advent of breakthrough digital technologies, from e-consent forms, to clinical trials management systems and more, clinical trial sites and sponsors alike have been able to garner metrics that provide a much more holistic picture of a clinical trial process from start to finish.

That said, site staff then become responsible for ensuring that participants know how to use whatever technologies are needed for the clinical trial. For example, they should be well-versed in troubleshooting, acting as product support, as well as training on the technology. So, from an operations perspective, it is important to know how much additional effort is necessary to manage these types of studies and this newer procedure type.

Below, please see three key insights about clinical trial advancements made possible by the advent of metrics—the backbone upon which all future clinical trials will be built and operated.

When you’re dealing with multiple therapeutic areas, each with their own set of investigators and staffing considerations, operational execution becomes mission critical to ensuring you’re always moving forward in the most efficient way possible. Accordingly, before even starting your clinical trial, you want to be sure you’re deploying the right resources for the right reasons at the right time – which starts with metrics.

Leveraging cutting-edge algorithms, clinical trial sponsors are now able to compare historic performance with internal systems and internal processes to ensure they’ve got an accurate level of resources being applied to the trial in question. In doing so, sponsors can uncover answers to critical questions such as: How many sites are needed to enroll the needed number of subjects? In what order do we approach sites to be most efficient?

Sites also can leverage extensive amounts of performance data to address trial resourcing questions such as: How much time does it actually take to get consent? How much time does it take conduct a visit? And how much work do our coordinators have and how can we maximize their productivity? If, for example, a coordinator is found to be at 80% capacity, that means we can add X number of studies to meet that white space.

From an operations standpoint, metrics have empowered trial sponsors and sites to identify the highest throughput teams and allocate resources accordingly—streamlining efficiencies and, consequently, speeding up processing times. For example, some of the most commonly seen metrics include time to activate a trial at a site, time to enroll the first participant after opening a study to accrual, and one of my favorites (minor but powerful)–how fast does the other “side” (sponsors for sites and sites for sponsors) respond to requests, especially during budget and contract negotiations.

Unlocking a holistic view of patient care

In many ways, advancements in wearable technologies have completely blown the roof off of our original perception of quality data collection. Take the six-minute walk test, as one example. When researching mobility, site operators may seek to observe a participant’s ability to walk across a flat hospital floor for six minutes—a useful, but limiting, view of a patient’s mobility in the real world. When you move this process to a wearable, however, the depth of your metrics intensify. In real time, you can actually see their mobility patterns come to life, including up-to-the-minute details such as elevation, exhaustion and more.

Of course, from a research perspective, it’s worth noting that more data isn’t always better. Accordingly, it’ll be very important that trial organizers leveraging wearable technologies define what they’re measuring prior to embarking into the trial process. Equipped with a clear vision for their analysis, sponsors and site organizers alike can unlock new frontiers in data collection that make it easier and faster to conduct clinical trials.

Improving the site / sponsor relationship

Over the past 18 months, the COVID-19 pandemic has catalyzed profound transformations in the way we conduct trials processes, and one important aspect that’s applicable to our conversation today is transforming the site / sponsorship relationship. Historically, relationships between sites and sponsors have been built upon the protocol or drug level, which, while effective in many respects, overlooks the big picture of a site’s research overall capabilities. With resource prioritization increasingly taking center stage, however, trial sponsors are quickly realizing that there’s true value in taking a more macro view of a site’s capacity at a portfolio level. You may have a top-10 NIH funded site that’s publishing directly in your area of expertise, but you’ll never know if you don’t look. This is where metrics come in.

Indeed, by leveraging publicly available information surrounding a site’s enrollment and patient population data, sponsors can maximize the probability of success in their pipeline by ensuring that their trial sites can efficiently and effectively meet their needs—all before a trial even begins. In doing so, trial organizers can build lasting partnerships with sites that are primed to bring potentially life-saving therapeutics from bench to bedside.

Implementing data to help drive clinical trial processes

It’s important for users to first determine what’s important to them to measure. If there is a specific process or step that is of interest to ensure a goal is met, then it should definitely be measured. After the goal is identified it must be defined. For example, what measurable items go into knowing whether a goal has been met? If it’s a turnaround time, what is the start time and stop time? How is it measured (hours, business days, calendar days, weeks, months)? And if it is a quantity, at what point is the count increased? For example, for accrual, is a person accrued if they are consented or when they have met eligibility or when they go on treatment?

You can’t quantitate metrics if you are not collecting the data—however, you don’t need a fancy system to collect data (although sometimes it helps quite a bit). The key is to identify a systematic and consistent process to collect and store that data.

Finally, communication is paramount. If you collect data and quantitate metrics, it does absolutely no good if the information is not communicated out and acted upon. How are you going to use that data to assess and better processes? Make sure that the data is used for strategic decision making. This ensures that there’s real value in the time and effort needed to collect the data—and the overall clinical trial process is improved and streamlined.

When speaking about digital advancements, we in the clinical trials space so often view “technology” as a singular umbrella term, when the reality is far more complex and far more exciting. With each breakthrough, we get a little smarter, a little faster and a little more agile. With each new metric, we find a new piece of a critical research puzzle, allowing us to learn more about the complex diseases we treat and consequently address significant unmet patient needs. Admittedly, we may not have all the answers; however, equipped with improved operational decision-making, holistic patient monitoring and a strengthened site / sponsor relationship, I’m confident we’ll at least know where to find it.

, Senior Clinical Research Strategist at Advarra

Articles

Three key insights about clinical trial advancements made possible by the advent of metrics

A Critical Piece of the Research Puzzle: How Metrics Have Transformed Clinical Trials

	Three Dog Night wasn’t singing about clinical research when they sang “One (is the Loneliest Number)," but just like love, one is the loneliest number in clinical research. Why? Because more often than not, you do not want to accrue only one participant to a clinical trial.

	You may be reading this thinking that I’m wrong, your counterargument being that it is worse to accrue zero patients. However, I am here to propose that recruiting one subject is worse than no subjects at all.

	When a study does not accrue anyone, it can close at any time. Staff can close the study out with the sponsor, conclude the study with the IRB, and move on to the next project. While not the best use of an institution’s resources, it is (hopefully) a short commitment with no long-term requirements. However, when one subject is enrolled, the study must remain open. The subject must complete the study treatment and required follow-up. Even after they are off-study, ongoing study requirements, such as survival follow-up and monitoring commitments are necessary, as well as the completion of regulatory requirements, such as protocol amendments, submission of IND reports and continuing reviews. This results in an investment of both monetary and human resources that could have been directed to a more productive study. If multiple studies only accrue one subject, it drains the resources of the clinical research enterprise.

	It is unlikely that the study opened to only accrue one person, so additional time was dedicated to screening and recruiting patients that ultimately did not enroll in a trial because they do not exist or refuse to participate. This is demoralizing to the clinical research professional, as well as a drain of human resources that could be used to recruit to a successful protocol.

	When multiple subjects are enrolled, there are economies of scale. The same forms, procedures, and physical resources (e.g. laboratory supplies) are utilized. Study staff is working within the protocol regularly. They know the requirements and procedures better. It is possible to assign several staff members to the protocol for coverage. It is likely that fewer compliance issues will occur, as the study is better known to the staff and investigators. This is not possible with a study that has only one subject. It is not prudent to assign multiple people to the protocol, or if multiple people are assigned, they have other assignments that split their attention with competing commitments and often lead to workplace stress and dissatisfaction.

	However, as with most rules, there is an exception. Systematically designed case studies, known as “N of 1” studies, are of great value. These data-driven trials are still conducted under a protocol, with a specific order of procedures and requirements to be followed. They are another mechanism for studying precision, or individualized medicine. While not utilized often, these studies can provide incredibly helpful data when a larger, randomized controlled trial is not feasible (such as in the case of incredibly rare disease and/or a more common disease that refuses to react to regular clinical treatment).

	Nevertheless, outside of the n=1 study design, my recommendation is that a study should not be allowed to enroll only one subject. If a study has been recruiting for a period of time and has no accrual, cut your losses and close the study. Do not wait for the opportunity for one subject to appear. While it may benefit the one subject in the short-term, the long-term result is that productive studies that can help numerous people at your institution cannot be conducted due to a lack of resources.

Why? Because more often than not, you do not want to accrue only one participant to a clinical trial.

Wendy Tate

Articles

A Critical Piece of the Research Puzzle: How Metrics Have Transformed Clinical Trials

One IS the Loneliest Number