Panorama: Customized Thought Leader Data and Insights for Life Sciences Companies

One of the key factors in the success of a new medical product is how well-accepted it is among healthcare practitioners (HCPs) and patients, both during development and upon commercialization. Life sciences companies often rely on thought leaders—sometimes also called opinion leaders—to help both spread information about a new product and to better target development and marketing efforts for new drugs or medical devices. And to use these individuals to their best potential, companies need to be able to quickly and easily identify which thought leaders are most important for their particular products.

Healthcare thought leaders or opinion leaders can be a factor in both recruiting patients to participate in clinical trials and maximizing acceptance of new products after commercialization. Thought leaders are looked to for insight on new products or treatments by both HCPs and patient communities. They can play a key role in increasing awareness of new commercial and investigational products, educating their peers about when and how new products may best be used and providing a sense of credibility among both HCPs and patients.

Thought leaders generally are trusted and well-respected individuals with proven expertise in a particular field. They can include prominent physicians, hospital executives, health system directors and researchers. They also may include less well-known professionals that have close ties to a particular patient or disease community.

Digital thought leaders—who make broad use of social media platforms like LinkedIn, Twitter and others to engage with and educate HCPs and patients—are also growing in importance. These thought leaders can be particularly effective in helping to drive information to the most relevant audiences by making use of social media algorithms to reach both the broadest and most-well-targeted audiences.

Finding key thought leaders

Many developers, manufacturers and contract research organizations (CROs) have their own internal processes for maintaining information about opinion leaders that they either have tapped for expertise in the past or have been following in anticipation of seeking their help with future products. But these—typically gleaned from a variety of sources, like applications, websites or internal tracking documentation, among others—are likely to have gaps in actionable information on their thought leaders.

For companies that have not developed such an internal resource, database service providers do exist. But use of generic, one-size-fits-all database providers will likely lack the specificity needed to meet each company’s or product’s individual needs. A generic database may, for instance, fail to take into consideration the needs and nuances of a specific company’s or team’s organization, objectives and strategies. A company’s insight-gathering needs may also be dependent on a particular patient population, disease state or other factors that cannot be fully captured with a generic database service.

A customized approach is more suitable to life sciences companies that are developing a wide array or product types for a range of disease states. For instance, Panorama, a thought leader management application acquired by Pro-ficiency earlier this year as part of Compass Group Partners, includes a database that can be configured specifically for an individual company’s specific needs and organizational structure. It can be geared specifically to target and manage information on thought leaders most important a specific disease state or therapeutic area, as well as include all the elements involved in strategic thought leader engagement planning.  This negates the need for companies/team members to go to multiple data sources, as well as work in multiple documents where collaboration and version management are challenges. 

Key factors to customization

This customization is borne out of a deep dive to understand not only each organization’s information needs, but also how teams are structured and how they work together and communicate. The customized database is then structured so that the information most important to the organization is quickly and easily accessible via an intuitive, customized dashboard.

The easy-to-use dashboard allows users to easily find information based on a variety of filters, from therapeutic expertise to affiliation to geographic location. The goal is to ensure that the application is configured to make the information most important to the company readily available. This includes the ability to easily generate needed reports and any other functionality that each individual company needs.

Information on thought leaders needs to be extensive, including their specific areas of expertise, affiliations, publications and clinical trials they have conducted, if applicable.

Panorama provides customization based on a deep understanding of the company, the teams that will be using the database, what their objectives are and how progress toward those objectives is measured. Key factors in providing customization include understanding:

  • Brand or franchise objectives;
  • How the company or team is organized; and
  • The objectives and priorities for various levels of the team, which could include everything from providing updates on insights or engagement to senior management, to helping develop engagement plans with thought leaders.

And that level of customization doesn’t end with delivery of the product and training in its use. It’s equally important for sponsors to be able to modify the database over time according to business needs. Panorama is an adaptive platform, allowing end-users to add or subtract filters—such as disease state or geographical region—easily.

Panorama offers a true strategic partnership that includes ongoing support to ensure the tool can be used to its maximum capacity. This can include continual refinement of insight gathering and engagement plans and the ability to shift easily to capture evolving objectives with thought leaders, including advocacy development for commercial users.

Differing division demands

For clients that develop and/or manufacture therapies, the ability to differentiate between the needs and regulatory constraints of medical affairs and marketing teams is an important factor. Regulations for each of those efforts can be diametrically opposed. For instance, while marketing teams often develop advocates from thought leaders, medical affairs professionals are often prohibited from doing so.

Conversely, marketing is usually only allowed to talk about the approved labeling information for each individual product. Medical affairs staff, however, can be more speculative, while CROs, by their very nature, must discuss off-label exploratory uses of therapies.

This disparity means that most companies often end up using different platforms for clinical development, medical affairs and commercial marketing. But that means comprehensive information needed by each division may not be readily available.

Being able to rely on a single system or platform to access appropriate information for each of those divisions could streamline both development and marketing efforts.

Potential clinical applications

Although much work with opinion leaders is focused on commercial or near-commercial products, they can also play a role at the R&D and clinical development stages. 

Here, access to opinion leaders can boost a sponsor’s ability to accurately identify potential investigators. Some may themselves be sought-after investigators for clinical trials in their areas of expertise. Others may be experts in evaluating protocols.

Sponsors may also use thought leaders and their networks to help identify research sites with expertise in particular disease states and capacity to deliver sufficient patients from the target populations. Enrollment is always a top concern for new drug and device sponsors when developing a clinical trial protocol; being able to quickly identify sites and investigators with access to specific patient populations can avoid problems related to selecting a “wrong” site for a particular study.

For such purposes, understanding opinion leaders’ networks is especially important. Key information to be tracked can include who an expert has published papers with, where they have made presentations, where they earned their medical degree or gained a fellowship and what hospitals or universities they are affiliated with, which can highlight the degree to which they may interact with practicing physicians.

Bottom line: Access to the right thought leaders is crucial to the success of medical products. Sponsors need to not only identify opinion leaders, but also to understand what they do, where they do it and who they are connected to through their networks. Having a comprehensive, easy-to-navigate, adaptable database, like Panorama, at their fingertips will make that job much easier for them.

Visit to discover how Panorama’s KOL management capabilities can help your team.

Creating Quality by Committing to Compliance in Clinical Research

In the highly regulated world of clinical research, compliance is an ongoing concern, but can be viewed as an annoying and costly item to check off a regulatory to-do list. And it can cost a great deal of money, not to mention valuable staff time, to be compliant, especially at the front end of a study.

But establishing systems to ensure compliance up front can pay off in spades, primarily by removing most of the “noise”—glitches in operational systems that can make it difficult to quickly and easily determine whether there is a problem with an investigational product or if the problem stems from a systemic issue.

At its most basic, compliance is adherence to a set of standards or regulations. In the clinical research arena, compliance involves, broadly, performance standards and safety standards, for instance. Compliance with applicable standards and regulations is necessary to create a minimally viable product.

Clinical research involves multiple parties, each with their own particular compliance responsibilities. For instance, drug and device sponsors must make investigational products in accordance with GMPs/QSR requirements, respectively, as well as meet regulatory requirements for submitting information generated during a study.

At the research site level, IRBs lay out guidelines and standards within their own communities of research sites. Sites also must adhere to strict ethical standards, requirements for specific grant-funded efforts and internal policies.

By complying with all such requirements, clinical trials are better able to ensure that they perform optimally, meet defined endpoints and deliver the investigative treatment in a safe manner, while ensuring patient safety.

Compliance vs quality

It’s impossible to discuss compliance without also considering quality; regulations and performance standards are intended, after all, to ensure a good quality product. But while the two concepts are linked, they are not the same.

Quality involves factors such as useability, durability, utility, affordability, accessibility and other things that influence how a product is experienced by the users. It’s possible to build a compliant product that is not of good quality. But without compliance. When it comes to clinical research, the notion of quality revolves around the patient experience. 

Compliance focuses on adherence to regulations and standards. Because those regulations and standards generally are written with the goal of product quality in mind, it’s harder to achieve important quality-related factors like reproducibility and consistency, without compliance.

It is, however, possible for a product or clinical trial to be compliant and still yield a poor-quality product or inadequate research in terms of those factors. This is usually due to a checklist approach to compliance.

Many in the industry tend to view compliance activities in that way, as an onerous task involving a lot of fussy checklists, paper work and documentation. In reality, compliance needs to focus on high-reliability systems that can meet all safety and other basic requirements, including patient needs. 

Without systems in place to ensure compliance with all pertinent regulations and standards, problems can occur during the trial that ultimately are more costly. These systems can include SOPs, templates, work aids and other tools that help researchers perform consistently both throughout an individual study and across multiple studies.

Noncompliance comes with costs

Noncompliance during a clinical trial can cause regulatory problems that up the cost of a clinical trial, as well as pose risks to patients and affect data quality. The time required to complete a clinical trial can be extended significantly in the face of noncompliance, whether that is regulatory, protocol deviations or amendments or other problems.

Failure to meet all regulatory requirements can delay time to new product approval. This applies to IRB requirements and other standards, as well. Addressing such problems—including finding the root cause—can add time and expense to a study. 

More than that, not all costs can be measured only in dollars and cents. Noncompliance can damage a company’s or research site’s reputation. And the ultimate cost of not following the rules in the medical field is risk to patient health and safety.

The cost of redoing something is always higher. This refers not only to money, but also to patient outcomes, regulatory or legal sanctions and corporate reputation. One of the goals of compliance should be to establish systems that allow early, accurate detection of problems, before harm comes to patients or data integrity cannot be assured.

Cutting through systemic ‘noise’

But a clinical trial built on a foundation of scrupulous compliance with all applicable regulations, policies and standards will fare much better when unexpected problems arise. Compliant systems will have redundancies and failsafes built in to help weather any disasters that may befall a study. 

One of the most important things good compliance systems provide is the ability to see when something isn’t right. If aberrant data is quickly visible, it can be addressed before serious risks to patient safety and data integrity develop.

For example, a device manufacturer that produces a stent on a limited, one-by-one basis will find it extraordinarily difficult to conduct that manufacturing within a quality system. In this sort of a system, QSR compliance and consistent manufacturing quality would be challenging. Such a company wouldn’t have anything to look back on within its compliance system to understand where the point of failure was when the inevitable problems cropped up; it would be difficult to determine if a device failure was due to an issue with the product itself or to problems in the manufacturing system.

A more systematic method of production, in compliance with the QSR, on the other hand, adds traceability into the design. And this helps clear out the extraneous noise so that any problems that occur are more likely to be completely separate from the systems.

And the ability to handle problems can be crucial during a clinical trial. For instance, many medical devices perform essential functions that affect a patient’s immediate health. If an investigational device fails, things can go south quickly and dramatically for patients. Even in areas like medical scanning or imaging, failures can mean inaccurate diagnoses and treatment paths for patients.

Under compliance systems like this, if something comes up that is wrong, it is very apparent. Without clear systems, it’s harder to see when something has gone wrong.

For example, systematic collection of data on the front end helps researchers to see aberrant or outlying data points quickly. When a problem originates in the investigational product itself, systematic deviations will appear within the compliant systems. In other words, any deviations in data can be assumed to be because of an issue with the product.

In this way, a focus on compliance can eliminate extraneous “noise” within the clinical trial system. When all the compliance underpinnings are in place, systems within the trial will work in a consistent, reliable manner. With these basics handled up-front, researchers and sponsors are then free to be more creative and more agile in responding to new challenges or needs.

Research staff must be trained to work within the established compliance systems, as well as to perform the study protocol correctly. Since different people learn in different ways, it’s important that training incorporate different senses. Simulation-based approaches, like that offered by Pro-ficiency, often do the best job of incorporating multiple learning styles while also allowing the opportunity to practice in a consequence-free environment. 

Pro-ficiency’s protocol analysis and training approaches, for instance, help take the noise out of the system by helping research staff understand clearly what has to happen and how it has to happen. 

In short, a focus on compliance from a systems approach means that researchers don’t have to think about every tiny step that is taken for every procedure or task required in a given protocol. They can, instead, focus on the central focus of the study, which must always be patient care and data quality and integrity.

The Power of Adaptive Learning

Effective protocol training is essential to the success of any clinical trial, but can be challenging due to the complexity of protocols, presentation of novel procedures and varied staff skill and experience both within and across sites. If training is to ensure optimal performance by all research staff, it must address those challenges. Adaptive learning approaches are uniquely positioned to overcome all these challenges, while also reducing the time burden placed on research site staff by training and re-training.

Adaptive learning is a data-driven approach to instruction that allows material to be adjusted and tailored to meet the individual needs of different learners, rather than a one-size-fits-all experience. This approach uses computer software to create customized experiences and materials based individual learners’ skills and experience level. It provides feedback and resources unique to each person. 

Adaptive learning is typically done using a basic “if A happens, then B happens” approach, a June 2022 article on the website explains. For instance, if a learner gives a wrong answer, the system would offer guidance and prompt them to retry; conversely, individuals may skim through areas where they already have mastered the material.

Originally introduced in education, adaptive learning systems have been making inroads into many types of business training systems, as well, including medical fields. In a 2017 blog post on its website, for instance, the New England Journal of Medicine (NEJM) pointed to several common scenarios where adaptive learning is shown to outperform other approaches.

For instance, when learning outcomes—such as performance of a particular medical procedure—have serious consequences, adaptive learning has been shown to better ensure proficiency when the employee performs that procedure on actual patients. It also outperforms other types of training when the intended audience is heterogeneous, with a variety of experience levels and skill sets, a situation that is common in clinical research.

Adaptive learning is also especially useful when time is of the essence. Clinical research staff often complain of being overburdened with administrative tasks like training. An adaptive learning system, with its ability to focus on knowledge gaps and build proficiency faster, can minimize the amount of time busy researchers must spend on training, while still ensuring top performance.

Other scenarios where adaptive learning outperforms other types of training, according to the NEJM blog post, include when training must be repeated over time, which can result in both new and old information being presented to the same individuals repeatedly, and when information is changing frequently, which is always the case in evidence-based medicine and clinical research.

This ability to essentially skip known material or to “test out” of some training where they already are proficient could be a particular boon in the clinical research arena. The time needed for training, particularly for re-training on the same material, is a frequent complaint, as indicated by a 2020 HealthStream survey on adaptive learning. This approach ensures that more skilled and experienced learners focus strictly on novel instruction.

Pick the right platform for adaptability

Taking advantage of the pluses offered by adaptive learning requires the right training platform. For instance, Pro-ficiency’s simulation-based training platform allows for adaptive learning in several ways. The system’s proprietary content authoring tool enables rapid construction and maintenance of branching logic, “choose your own adventure” learning modules (see Figure 1 below).

Figure 1: Branching Logic in Pro-ficiency’s Platform

In this way, all learners can take slightly different paths through the learning module, depending on their baseline capabilities and knowledge. The system will train individuals only when they make mistakes. When they make correct choices, they can quickly advance to the next challenge. This can reduce training time by up to 50%.

Further, each role on a study team has customized learning content in the system, based on job-specific target competencies. In this way, the platform adapts to the specific needs of each participant and team member of the study or internal sponsor team. This differs from video or slide training, where a one-hour training session will always take one hour, regardless of an individual learner’s baseline knowledge and skill sets.

The system also offers predictive analytics that enable detection of trends in performance data. This data can predict strengths and weaknesses in site staff, CRA and monitor competencies, allowing it to adapt smoothly to the needs of the entire cohort of learners.

Figure 2, below, provides an example of this capability. It shows performance results from three research sites that completed simulation-based training for a Phase 3 protocol. The vertical columns show the competencies while the horizontal rows represent the individuals who have completed the training. The trifurcation indicates the three separate sites. 

A grey checkmark indicates that the individual passed that challenge with no need for mentoring or training. Figure 2 indicates that the first site did very well across the board, as did the third site, except for the CRA three rows from the bottom. This information lets study leadership know that the CRA at the third site requires additional attention and training. The middle site, on the other hand, is struggling except for one individual; study leaders can leverage the high performance of that person to act as a champion to mentor and guide other team members.

Figure 2: Predictive Analytics Generated During Pro-ficiency Training
This performance data can also highlight areas of a protocol that may be more challenging. Figure 2 shows such a situation, with one particular competency that everyone struggled with, high and low performers alike. That competency will require more targeted remediation, which the system will provide.  

And the study team is not the only group that can benefit from this adaptive learning approach. Study participants can also experience similar training, via Pro-ficiency’s ProPatient product.

Because Pro-ficiency’s simulation-enabled performance management system is bespoke-built for clinical trials, it also offers capabilities to solve problems that most sponsors have not yet even identified. One of these is amendment management. Every protocol amendment increases complexity in the study by creating a new cohort within the staff for employees trained on A1 versus A2 versus A3, and so on. High staff and CRA turnover further add to this complexity.

The standard response to this challenge is to force constant retraining on affected sites or internal teams as amendments may require. The Pro-ficiency system, however, tracks exactly which competencies and which version each learner has completed. This allows retraining to focus only on new material, which dramatically reduces training burden on research staff.

`The final point concerning adaptive learning relates to how the data generated from the training system helps study teams adapt their monitoring plans. For instance, data like that shown in Figure 3, below, informs the study team as to which sites are more likely to generate study errors. This allows monitoring resources to be more effectively targeted—or adapted—to the riskiest sites at the beginning of the study. Sponsors don’t have to wait for problems to occur; they can address weak areas proactively.

Figure 3: Predicted Error Rates Via Pro-ficiency Training

This also extends to global considerations where culture, language or other country-specific issues may impact research staff performance. Pro-ficiency provides a dashboard that displays the predictive performance analytics in real-time and spread geographically according to the distribution of sites and teams.

Training in the clinical research industry will continue to pose a variety of challenges, including time constraints, ever-changing information due to protocol amendments or new scientific evidence, novel procedures that fall outside research staff experience and a broad range of skill level both within and across research sites. Any training program lacking the agility to handle these challenges is doomed to failure, leading to mistakes and delays in getting investigational products to market.

Adaptive learning offers a powerful solution to those challenges. By adopting training platforms with solid adaptive learning features, such as that offered by Pro-ficiency, new product sponsors can help ensure a faster, smoother path through the clinical research process.

To learn more about Pro-ficiency’s simulation-based training solution, please visit our  website:

Unlocking Clinical Site Efficiency with Simulation-based Solutions

The need for site efficiency is greater than ever in light of the ever-growing complexity of clinical trials and the requirements placed on-site teams. Unfortunately, the oversaturation of new solutions in the industry means that sponsors and CROs often invest in tools that cost them valuable time, money, and efficiency.

Outdated training methods, clunky system plug-ins, and lack of insightful analytics all place a large burden on sites and site teams throughout the trial process that could be vastly improved with solutions like those Pro-ficiency offers.

Protocol Training

While cheaper and more widely available, traditional didactic training methods are quite inefficient at actually training site teams. Oftentimes, the training consists of extensive and unengaging PowerPoint presentations that do not prioritize critical information, which means researchers are challenged to weed through mountains of information to remember key details. And these generic, one-size-fits-all trainings fail to address the challenges of constant staff turnover at sites. Without a targeted and efficient training methodology, site staff are left to shoulder the burden of inadequate and generic training programs, delaying the implementation of study-related actions. The result is typically more study deviations, re-training, and delays.

Pro-ficiency’s simulation-based protocol training uses virtual AI-driven methodology to simplify the protocol into key decision areas that an investigator has to make so site teams can train with the protocol hands-on and specifically target complex decisions they will need to make during the study. Combined with study tools like quick reference guides, job aids and patient visit guides, learners can improve their understanding of the protocol and increase their retention of vital information, reducing the number of deviations and delays – a much better solution to improving site performance than traditional methods.

Pro-ficiency’s prescriptive analytics also help to identify key risk areas and training issues proactively, so site managers can intervene where necessary. These performance-based analytics spotlight specific individuals struggling with training or specific topics posing issues for many people, allowing site managers to provide additional clarification and resources to the team. 

Workflow Integrations

The clinical trial technology landscape has an abundance of products, and due to the complexities of modern-day trials, site teams are working with dozens of these systems at once. According to Florence Healthcare, 42% of sites login to more than six platforms for an average study, and 40% say a lack of integrations prevents them from adopting new technology. Having to log in to each system individually not only poses a security threat but is also cumbersome and takes up valuable time. 

Pro-ficiency’s SSO and API solutions can integrate with any available system to further reduce the burden on sites and provide secure access with minimal disruption to the process. Additionally, Pro-ficiency’s newly released all-in-one training hub provides seamless access to educate, engage and enable trial sites to become more efficient.

Proactive Efficiency

Very often, research teams are unable to identify gaps and deviations in trial design until the trial has already begun, causing further delays and increasing expenses. To combat this challenge, Pro-ficiency’s protocol optimization methodology translates a complex, scientific, and regulatory protocol into a visual simulation of the patient journey and site operational flow for the trial. This allows site teams to understand the full reality of the trial, see potential inconsistencies, anticipate resource and operational requirements, and make adjustments prior to finalization. 

This solution is most valuable at study start-up, though has value in mid-study implementation for better communication and comprehensive operationalization of a protocol’s time-sensitive steps.

Pro-ficiency’s value of site efficiency guides the innovation of every product and is part of our commitment to providing a better experience and better outcomes to our customers.

Click here to learn more about Pro-ficiency’s commitment to increasing site efficiency and reducing the burden on sponsors and site teams.  

Rethinking Training: Achieving Competency in Less Time and With Better Results

Training for clinical research staff that focuses on complete comprehension of a protocol and its goals can be a key factor in avoiding errors and protocol deviations during the course of a study. In fact, training, if done right, offers a unique opportunity to predict potential problems and address them before they occur.

At its foundation, training provided to research site employees is intended to ensure competency. Competent staff are less likely to make errors, meaning that the risk of protocol deviations goes down as site employee competency goes up. And reduced deviations can help to avoid study delays and keep costs—which have been trending upward, as have trial timelines—under control.

So it may seem self-evident that training provided to staff at clinical research sites is a critical opportunity to ensure peak performance and prevent protocol deviations that can derail a study.

But the clinical research industry traditionally has viewed the need for training as, at best, an item to check off a list in order to get a study off the ground and, at worst, a burden to sponsors and research sites alike.

This outlook has developed over years of a push-pull dynamic between sponsors’ need to comply with regulations that mandate training on study protocols and GCPs and sites’ desire for shorter training that poses a lesser burden to research staff. For instance, CenterWatch reported in August 2020 that training was a growing pain point for research sites, which were overwhelmed by growing administrative responsibilities, including undergoing GCP and protocol-specific training.

The FDA requires that all research personnel be adequately trained for their roles. The agency is largely focused on GCP compliance, as well as adhering to the protocol. And sponsors often focus on training as a risk mitigation exercise to ensure that they can demonstrate to the FDA that they have met their regulatory obligation in this area. In other words, it’s not uncommon for a sponsor or CRO to create training programs designed to do nothing more than check the “training” box on FDA paperwork.

And in an effort to cover all training bases, sponsors and/or CROs tend to provide training materials that are both massive in volume and overly generalized. One reason sites view training as a burden is the massive amount of information—often in slide decks numbering in the hundreds—sponsors tend to dump on researchers, rather than engaging with different roles and clarifying what is most important for a particular study.

A better approach would be to develop training that truly provides opportunity for individuals in clinical research to acquire, retain and apply knowledge.

Boost competency, reduce errors

Sponsors need sites to execute clinical trials as close to perfect as possible. In order for this to happen site employees need to consume content that will help them understand. But that is not enough to achieve the goal of optimized performance. Research staff also need to have enough understanding to ensure that they consistently make good decisions.

And that can’t be achieved through a slide deck, lecture or webinar. Research staff must be engaged with the content and provided an opportunity for “perfect practice,” where errors are caught and corrected before real-life stakes are in play.

Providing training in a simulation format can help solve these problems in several ways. Simulation-based training, such as the program offered by Pro-ficiency, provide research staff with hypothetical situations similar to those they will face during the study. They are then able to actually practice key tasks and procedures required under the protocol, getting guidance throughout the process to help ensure they make decisions correctly, in compliance with the protocol.

Additionally, the immediate feedback on mistakes that is built into Pro-ficiency’s method avoids the risk of staff developing “muscle memory” that is incorrect for performance of critical tasks. This can be particularly important when a protocol requires procedures that are different from the standard of care a site is used to practicing.

The dashboard of results like that provided by Pro-ficiency can highlight any weak areas to both sites and sponsors, allowing additional concentration on the troublesome areas—whether a tricky procedure or a less-experienced site or individual—and address problems before they occur in a real-life clinical trial. When training provides these types of analytics, sponsors can track where mistakes are most common and take appropriate action.

Actions available to sponsors in these cases can include providing an additional training module on a particular procedure or giving extra help and training to struggling sites or individuals.

It’s impossible to take a one-size-fits-all approach to competency management. The goal is to reduce errors as much as possible. But when they do happen, each situation should be evaluated independently. Additional training can solve some problems, but in other cases, a sponsor may be looking at a wrong investigator or site, for instance. In other words, improving human performance can save money and time.

This approach to training also lets research staff move at their own speed, whizzing through tasks in which they already are proficient and spending more time on novel, protocol-specific procedures.

But a high error rate is not always a negative during training. For instance, one Pro-ficiency client applied training for a highly complex protocol that was challenging for sites. When employees initially participated in the training, the analytics indicated a high error rate. However, once the study began, deviation rates were not high. This would seem to indicate that the training allowed them to safely make mistakes, correct them and better learn how to execute the protocol properly.

And for particularly complex or novel procedures, training can be repeated for research physicians or others responsible for those tasks. For example, the sponsor of a study where the protocol required novel needle path planning opted to provide the training for that procedure early to allow ample time for physicians at the research sites to become comfortable with the new method. Analytics showed that errors were common as sites went through that training the first time.

But the sponsor re-presented the same training just before the first patients would need to undergo the procedure. And at that point, the errors were significantly reduced, and performance during the clinical trial much improved.

And those two factors—an opportunity to practice the protocol in a consequence-free environment and getting real-time coaching during the training—are central to effective training that boosts staff competence, avoids protocol deviations and checks the regulatory “training” box.

Timelines for clinical trials are growing longer and costs are getting higher. Protocol deviations can be a major contributor to increases in both cost and time. Moving the needle toward fewer errors and deviations by even just 10% could make a significant difference in the resources needed to complete a clinical trial. And well-developed, well-applied, simulation-based training, while it can’t guarantee the perfect study, does offer the potential to alleviate some of these expense factors later on.

To learn more about Pro-ficiency’s simulation-based training solution, please visit our website:

Measuring Training ROI in Clinical Research

Clinical trials are vital to the future of medicine and pharmaceuticals. Many of them are literally matters of life and death, studying the effect of potentially life-saving drugs or researching the impact of devastating diseases. So, why is it that the training of study moderators and site teams is treated so nonchalantly?

The traditional methods used to train these teams are extremely outdated, inefficient, and ineffective. This leaves site teams unprepared for the realities of the trial, increases protocol deviations, and drastically increases the overall cost of the study.

But many sponsors don’t even measure the ROI (return on investment) of the training they administer to determine how it’s impacting their trials and bottom line. Unfortunately, CRO-managed studies actually benefit from increased deviations because they are also tasked with fixing them, which lengthens the study and makes them more money. Recent data from the Tufts Center for the Study of Drug Development revealed that a typical phase three trial has 120 protocol deviations affecting 30% of the study subjects, but CRO-managed trials have 64% higher protocol deviations affecting 70.8% of the study subjects. This is not a coincidence. Each amendment made to a trial costs approximately $500,000 to correct, so there is little incentive for CROs to optimize training and reduce errors despite the high stakes of many clinical trials.

Nevertheless, as sponsors evaluate all elements of their clinical research, there is a reliable method for determining the ROI of their training.

The Kirkpatrick Model

The Kirkpatrick Model was developed in the 1950s by Donald Kirkpatrick, a professor and training specialist, to accurately measure training effectiveness. There are four levels sponsors can use to evaluate their training methodology:

  • Level 1 – Reaction
    The degree to which participants find the training favorable, engaging, and relevant to their jobs. The current training in our industry is severely lacking, consisting of mind-numbing powerpoints and lectures that don’t do anything to engage the participant.
  • Level 2 – Learning
    The degree to which participants acquire the intended knowledge, skills, attitude, confidence, and commitment based on their participation. Current training methods are very ineffective at building retention, leading to higher rates of protocol deviations during the trial.
  • Level 3 – Behavior
    The degree to which participants apply what they learned during training when they are back on the job. If they are prepared with adequate training, site teams will be able to retain information better and act more appropriately in situations, reducing errors across the board.
  • Level 4 – Results
    The degree to which targeted outcomes occur as a result of the training and the support and accountability package. This is the level where ROI can be measured.

Unfortunately, sponsors don’t often measure the ROI of training at all. In fact, they barely test site teams for retention after training is administered. The only standard sponsors are required to meet by the FDA is simply to administer the training, not determine how well it works.

But deviations can have tremendous impacts on the bottom line of a trial and on the well-being of the patients involved, so even without calculating the exact ROI, it’s obvious that improved training would be of benefit to sponsors in the end, even if it calls for higher initial investment.

The ROI of Simulation-Based Training

Take the Boeing 737 Max, for example. Normally, pilots are required to complete thousands of hours of simulation training to fly, but they were not required to do so for this new aircraft due to the high cost. But when faced with emergency crash situations, the pilots were unable to perform basic procedures that would have shown up in simulation training and could have saved hundreds of lives.

Sure, it would have cost Boeing several hundred million dollars to train these pilots in a simulator, but what is that compared to the cost of those devastating crashes?

Why then are clinical trials, often testing life-saving procedures and putting patient health at risk, treated differently? Well, many sponsors don’t even know it’s possible to measure the ROI of training, and simulation-based training is a larger upfront cost without an immediate return, which deters many from utilizing it.

Nevertheless, the industry is slowly changing to adopt simulation-based training more broadly as the ROI is discovered. Good training should result in about a 5,000% ROI, and in fact, we estimate that Pro-ficiency’s simulation training solutions will save $1 – 10 million per study by better preparing site teams, reducing deviations, and mitigating the need for costly amendments to be made mid-study.

All training should be designed to have a positive business impact. The more that sponsors adopt simulation-based training, the more data they will be able to gather and analyze, allowing them to realize the tremendous ROI associated with training their site teams using real-world scenarios.

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Business Expansion in the Digital Age

No business or industry has gone untouched by the widespread impact of COVID-19. Whether it was business development, talent acquisition, or company culture, every organization had to adapt in some way to weather the storm. In fact, many organizations were still reeling from the effects of the omicron variant just a few months ago in early 2022.

But now, as we look back on the past three years from the post-COVID era, there are many lessons to be learned and many opportunities to take advantage of as businesses seek to recover, grow, and thrive moving into the future.

Our industry and the industries we serve, for example, have faced several challenges over the past few years. From a business development perspective, there was a sudden reduction in trade shows and in-person events a few years ago, impacting our ability to make connections with customers and forcing our sales team to adapt virtually. On a larger scale, the life sciences industry as a whole is struggling with talent deficiencies and increasing costs, all of which impact outside partners like Pro-ficiency. Studies are harder to staff, sponsors are struggling with manpower, and business expenses are going up tremendously.

When we think about the strategies and tools businesses can use to make the most of this unique environment, a few things come to mind…

Focus on Customer Satisfaction and Innovation

Focusing on customer satisfaction and bringing innovative offerings to the table can mitigate gaps caused by a dip in new customer acquisition. In a world where business expenses are skyrocketing, sponsors/CROs are more than ever on the lookout for cost-cutting strategies. And at Pro-ficiency, we strive to provide such a valuable experience to customers that they always come back to us for their next study.

To ensure our customers’ satisfaction, we invest heavily in our technology and our team to provide customers with tools that provide undeniable value to their business. Most recently, we expanded our sales team, acquired a product development team for updating and creating new products more rapidly, and launched the use of avatars to help improve throughput and capacity for building simulations. We also have a whole series of product initiatives in the works to facilitate payments, improve analytics, and allow study participants to more easily connect – all expected to roll out in 2023.

By investing in the right priorities, we are able to deliver for our customers and make future acquisitions easier.

Embrace Virtual

Pro-ficiency has always been a lean and virtual organization, so we were well-positioned to tackle the pandemic from day one, needing to make much fewer adjustments than other larger businesses that operated primarily in person. Now that we are on the other side of the pandemic, it’s obvious that virtual is the way forward. For the sake of business development and company culture, embracing this reality has proven to be better at reducing costs, maintaining employee satisfaction, and delivering results than even the old pre-covid way of conducting business.

With the right tools and structure, employees can be much more efficient, product development can be streamlined, and building your team from a much larger pool of candidates can offer unlimited opportunities.

Invest in Company Culture

Building a meaningful company culture where a team can thrive is more important than ever as employees have unlimited options at their fingertips. Making this a top priority will pay off tenfold down the road as companies look to expand and grow.

At Pro-ficiency, we’ve been very fortunate to attract top-shelf talent. A lot of that is because people want to be involved in what we do. Being part of the solution to accelerate therapeutics for a rare disease is very noble work, it’s meaningful. We also work to create a positive day-to-day environment for our team by connecting personally with virtual tools, sending regular updates on company progress, and getting together in person whenever possible. All of these efforts go towards creating a culture that will allow Pro-ficiency to grow in this new world.

Overall, businesses that adapt to the new digital landscape and prioritize customer satisfaction, innovation, and company culture will be well-positioned to thrive in the post-COVID era.

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Analyzing Protocol Deviations Before Retraining

Protocol deviations can cause significant problems during clinical trials, forcing sites and sponsors to direct time and resources toward investigating and addressing them, potentially delaying completion of the study. And failure to address a deviation properly can lead to recurrences, costing the study more time and money.

What constitutes addressing a deviation properly? Any corrective and preventive action (CAPA) plan aimed at a deviation must be founded on a thorough root cause analysis, a step that the research industry seems prone to skip. Instead, a common response is to throw more training at the problem in the interest of checking a box on a form and moving forward quickly.

But taking a pause when a deviation occurs, performing a root cause analysis to identify the real source of the problem and tailoring a CAPA response specifically to that problem or set of problems will serve sites and sponsors better than just retraining site personnel on autopilot.

Root cause analysis is considered to be an integral part of overall quality principles, and is addressed in regulatory guidance. For instance, the FDA noted in a 2013 guidance document that a sponsor should have a “Processes to ensure that root cause analyses are conducted where important deviations are discovered and that appropriate corrective and preventive actions are implemented to address issues identified by monitoring.”

Similarly, ICH guidelines, Good Clinical Practice: Integrated Addendum to ICH E6, include specific requirements for a root cause analysis to be conducted in the event of a protocol deviation.

A frenzy often surrounds occurrence of a protocol deviation, focused on checking off the corrective action box and filling in the right forms. For many sponsors and research sites, the knee-jerk response to a protocol deviation is to retrain the erring staff member. This is an easy cause to address; site staff can be retrained and this is easily documentable. But retraining may not work to prevent the same problem from recurring.

But lack of training isn’t always the right answer. And if the problem recurs after retraining, one of two conclusions can be drawn: Either the problem wasn’t rooted in insufficient training or the training was ineffective. While inadequate or poorly understood training can contribute to deviations, it is not always the root cause. Other possibilities include issues with a process, with the technology used, or with communication among personnel, for instance.

In some cases, there may be multiple factors contributing to deviations; each of these must then be addressed effectively.

Applying the five whys

Thus, research sites and sponsors would be better served to pause and consider before moving to the easiest option—often retraining. But the preventive part of CAPA is just as important as the correction part; pausing and taking the time to conduct a root cause analysis can mean the difference between recurring deviations that must continue to be dealt with and a complete solution that forestalls future problems.

The only way to determine for sure that a deviation is rooted in training or another problem is to map out the process in fine detail. In this way, sites and sponsors can rule out potential causes and zero in on the real reasons behind a deviation.

A variety of methods may be applied. One of the most widely used approaches is the “five whys” method. By asking the question “why” of each stage of deviation evaluation, sites and sponsors can gradually work down to the root cause of the problem.

For example, the deviation may be that a site is not consistently performing protocol-required EKG assessments at patients’ baseline visits. The five whys approach can be used to dig down to the true reason these assessments have not been done, starting with the simple question: Why don’t sites comply with this requirement?

A possible answer is that the site doesn’t understand the measurement criteria, an answer that leads to the question: Why doesn’t the site understand? If the answer is that the site hasn’t been trained, that also begs a “why” question.

More often, training has been provided, but it hasn’t proven effective in ensuring the site’s understanding of how to perform the EKG assessment. When “why” is asked to that answer, several possibilities arise, including:

  • The training was so long ago that site staff forgot the instructions for this assessment;
  • The training didn’t focus on how to conduct the measurement;
  • The training approach wasn’t effective; or
  • Site staff simply weren’t paying attention during the training.

Depending on the answers at this level, the site and/or sponsor continue moving forward, asking “why” until it is no longer applicable. It may not always be necessary to go five layers deep. With regard to the potential answers above, for instance, the first issue could be addressed by providing job aids to jog staff memories when doing the EKG assessments. The last three points are common problems associated with traditional slide-and-lecture training that is too broad, not engaging enough and lacks feedback on absorption of information.

Additionally, root cause analyses also need to look beyond an individual incident. They must look at patterns and trends. This focus may reveal that a deviation was a one-off issue at a single site with one or a few employees. Or it could show that a given site has certain problems and root causes, or one particular region or sites working with a specific CRA. All of these situations must be handled differently to correct the current deviation and prevent future ones.

When is more training needed?

In some cases, insufficient training can be the root cause of a problem. Even in those instances, however, effective correction and prevention of future incidents should not rely on simply re-doing the same training. It’s important to make sure the right training is targeted to the right people in the right format at the right time and in the right way.

When considering whether training really is the root cause of a deviation, there are several considerations, including how the training was done and who conducted it. Some types of training can be more effective than others. The traditional slide-and-lecture approach to training may not be the most effective way to ensure correct performance of all protocol-mandated tasks, for instance. A simulation-based approach that guides staff through real-life scenarios may be more effective.

Who conducted the training may also be a factor. It’s not uncommon for a CRA to provide training, but this individual likely lacks training skills or credentials. A qualified trainer or team can mean the difference between training being well-absorbed or forgotten.

Use of a training matrix, to help develop effective, simulation-based training modules for clinical trials, can help guide development of effective training programs for both initial training and retraining that might be needed to address deviations.

And in some cases, the training may have been on point, but if a significant amount of time has elapsed between the training and start of enrollment at a site, staff may struggle to recall perfectly how some tasks are to be performed, particularly any that may differ from standard of care. In such cases, retraining might be helpful, as might job aids that staff can refer to when conducting the clinical trial.

Additionally, it’s important to consider root cause analysis to be a continuous process, not just a one-time event that’s done and checked off. Sites, sponsors and monitors must monitor that a corrective action worked to effectively fix the current deviation, and that preventive measures are able to keep similar deviations from happening during the study. And that means there must be methods for measuring the performance of the training or other intervention.

In the case of training, for instance, a simulation-based approach that provides both immediate feedback to research staff about their performance and a dashboard of information showing sponsors and site leadership how well staff perform in various areas can provide that means of measurement.

Developing a training strategy

All of this should be incorporated into a risk management strategy that includes an up-front risk assessment for each protocol. Part of a proactive risk strategy should include going through the exercise of anticipating where a protocol is likely to see deviations. This information can be gleaned from previous work, from questions posted by sites during feasibility assessments and from a thorough mapping of the entirety of the protocol, such as that performed as part of Pro-ficiency’s Pro-Active Protocol service. And this information can help to identify where training can be focused to prevent deviations.

Many sponsors don’t really have a training strategy. They tend to look at it as a box on a list that needs to be checked off, so they conduct training, but don’t really think about strategy. But this can lead to ineffective, one-size-fits-all training. A better approach would be to parse out who the specific audience is and what they need for each training effort. This includes whether a site is experienced—in the area of study, with clinical research generally and in working with the specific sponsor—or not; training needs will be different for a site new to clinical research versus one that conducts several trials each year.

This type of training assessment can be supported by creation of a training matrix that looks not only at site experience, but also at global regions, where language and cultural differences can cause confusion, and at specific roles within a clinical trial. A PI will have different training needs than a pharmacist, for instance. Targeting potential areas for misunderstanding up front can be more effective.

Sponsors can perform this work themselves or engage a company like Pro-ficiency to thoroughly evaluate the training needed, including focused modules for different staff. Coordinators, pharmacists, interventional radiologists, investigators and research nurses, for instance, will each be responsible for specific protocol tasks and procedures; focused modules for each position that simulate real-life scenarios relevant to each role can be most effective in ensuring that all positions fully understand how to perform protocol tasks.

And sites need to own their own quality systems, including thorough analysis of deviations and CAPA procedures. Sponsors can provide support via training and resources.

A similar approach can be applied to re-training, if that is needed to properly address a deviation. The focus should be on what problems the training is meant to solve, who needs that training and how it should best be presented to enhance understanding and avoid future deviations.

This takes time and effort and also means that existing training must be adjusted. But if the work isn’t put in up front, it will need to be put in later, after deviations have occurred.

Protocol deviations will happen. Companies can reduce the risk of deviations by taking a risk-based, proactive approach to training that includes a well-thought-out training strategy. Application of carefully targeted training modules that provide performance feedback to both research staff and study sponsors can help ensure that all employees get exactly the training they need to fully understand their roles in enacting the protocol.

And when a deviation does occur, a careful root cause analysis must be prioritized above a fast, knee-jerk response. Failure to conduct this analysis and craft CAPA plans tailored to address the true causes of the deviation means that researchers will end up chasing the same problems, treating symptoms rather than the true cause. Retraining may be part of the issue, but all other potential causes must be considered and dealt with.

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Preemptive Protocol Analysis: Reducing the Need for Retraining

When things go wrong during a clinical trial, retraining of staff is often the go-to response to correct the problem. But rather than using training as a band-aid for every protocol deviation that occurs, organizations would be better served by investing up-front in protocol analysis to anticipate areas where protocol deviations or other problems are likely to occur, and then designing training that will trouble-shoot those issues in advance.

While staff retraining is the knee-jerk reaction to a protocol deviation or problem, training is not always the root problem. There could be issues with a site’s operational process, technology or communication, among other things.

If done properly, training can be designed that anticipates these potential problems and focuses its efforts on ensuring that challenging parts of a protocol are fully understood. This depends upon a thorough protocol review, with specific input from patients and research sites to identify anything that is unclear or impractical.

This information can then be used both to refine the protocol into something difficult to misinterpret and to develop a training program that truly meets site’s needs, along with job aids where it makes sense to support research staff in making the correct decisions with every patient and every procedure.

Correcting protocol deviations can be a costly and time-consuming process that leads to study delays, extra costs and potential impact on study data. And deviations are far from uncommon. According to a study published by Tufts Center for the Study of Drug Development (CSDD) last year, Phase 2 and 3 protocols have a mean of 75 and 119 protocol deviations, respectively. And the FDA’s most recent BIMO metrics report lists protocol deviations or failure to follow the investigational plan as the most common observations listed on Form 483s after a BIMO inspection.

But deviations aren’t the only issue of concern. Protocol amendments can add significantly to the cost and duration of a clinical trial. CSDD has estimated that a single protocol amendment to a typical Phase 3 protocol can add three months of time and more than $500,000 in cost to a clinical trial, on average.

And amendments are on the rise. CSDD data indicates that the frequency of protocol amendments is increasing. During the 2018-2020 period they increased significantly compared to the 2013-2015 period. Nearly 78% of Phase 2 and 69% of Phase 3 protocols had at least one substantial protocol amendment; total amendments per protocol averaged 2.7 for Phase 2 and 3.3 for Phase 3.

Both protocol deviations and amendments potentially impact patient retention, investigative site commitment and the completeness, accuracy and reliability of study data.

But none of this data means that protocol deviations and amendments are just part of doing business for the clinical research industry. Rather than the traditional reactive response to problems arising during study conduct, sponsors could take a more proactive approach and trouble-shoot problems before a trial even begins.

Communication, analysis, then training

And this does not begin with protocol training. The first step to avoiding deviations and amendments is a thorough analysis to understand what a day in the life of a patient or research site would look like under the protocol.

For instance, many logistical issues can become major pain points for research sites and patients when it comes to putting the written protocol into action. The time window required for drug administration or patient visits is one example. A protocol may provide a window of 10 minutes to administer a drug, but that window may not be workable for all sites. If a particular site has patient visits occurring on one side of a large campus while the research pharmacy is on the other side, for instance, that 10-minute period may be insufficient.

If a drug takes 45 minutes to thaw before being provided to a research nurse to administer, that will add to the time needed to prepare each dose for each patient. Further, if the pharmacy is at a distance from the clinic, the time to deliver that drug also must be considered. Other factors include the time needed for the nurse to prepare the patient and prepare the drug in an infusion bag. The whole process could take well over an hour.

Similarly, the amount of time and effort required to attend visits and otherwise participate in a clinical trial can have a big impact on patient willingness to enroll. Protocols that include lengthy visits for tests and treatment can put patients off, as can lengthy or frequent trips to the clinic. Remote visits may ease some of that resistance for some patients, but not all; some may be unwilling to have strangers coming to their homes.

And on the staff side, long or frequent visits can raise questions about when staff must be available.

In essence, a protocol analysis needs to consider what is practical for patients and for the sites that will be conducting the clinical trial. This sort of analysis requires input from both patient groups and the enrolling sites. While it’s becoming more common for sponsors to include patient advocacy groups input into protocol design, that is just the first step. They also need to get feedback from the sites that will implement the protocol to learn what is and is not operationally feasible.

With that operational input, including what parts of a protocol may be burdensome or impractical for patients and sites, a sponsor can refine its training to fully address any areas that might differ from a site’s normal standard of care or otherwise be open to interpretation.

Solutions such as Pro-ficiency’s Protocol Optimization methodology can be used to get a thorough interpretation of a protocol, identify potential problem areas or pain points and provide a visualization that helps make clear what the journey through a clinical trial will look like for patients and research sites.

The mapping out of tasks and timelines in the protocol is especially important. Without that visualization, it is easy to miss all the steps that have to happen with each procedure or patient visit. It also helps to uncover any inconsistencies that might exist in the protocol. A visual mapping of a study’s operational flow, on the other hand, will easily reveal any issues.

If that process flow is animated, as provided by Pro-ficiency’s Protocol Optimization solution, it can become even more clear. In essence, a sponsor can see in a few minutes the whole of the study experience for the sites and patients in a way that will have a visceral impact and better enable both refinement of the protocol and development of effective training.

By approaching protocol optimization in this way, sponsors can ensure that training reflects perfectly the experiences research staff will have in implementing a given protocol.

And this effect can be expanded by incorporating simulation-based training. Any novel or unusual procedures can be more carefully illustrated and explained to avoid misinterpretation; job aids can also be provided to guide researchers’ decision-making in real time. The training can likewise walk researchers through not only the steps, but the timelines needed to complete patient visits and other key tasks.

Training, in this way, becomes a tool for proactive troubleshooting, reducing the need for after-the-fact procedures to address protocol deviations.

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Bringing Protocols to Life to Reduce Site and Patient Burdens

In a world where clinical trials are growing larger and protocols more complex, it’s increasingly important that study sponsors make sure to get their protocols right from the start to avoid unwanted delays or cost overruns due to mistakes, deviations or even just failure to correctly forecast the time, money and resources needed to conduct a study. 

And that means that the art and practice of protocol optimization, utilizing input not only from target patient groups, but from potential site partners, as well, becomes ever-more important. 

Protocols are getting more complex for many reasons, such as regulatory demands, expansion into more challenging indications like rare disease and immunology, adaptive study designs and trying to get as much data from one study as possible. A 2021 study by the Tufts Center for the Study of Drug Development (CSDD) noted that protocols have been growing increasingly complex since 2009, with no end in sight to that trend. For instance, the CSDD report said that Phase II and III protocols as of 2020 generally had about 20 endpoints, with an average of 1.6 primary endpoints, up 27% since 2009. And the mean number of distinct procedures required for a typical protocol rose 44% during the same timeframe.

Amendments are also increasing. CSDD noted in an early 2022 report that the mean number of protocol deviations and substantial amendments—another cost and time driver—have increased across all clinical trial phases. The typical Phase 3 trial has 119 deviations, the CSDD report said. More amendments mean more operational burdens for sites, longer cycle times and more chances for deviations.

And about 30% of patients in Phase 2 and 3 studies have deviations; more deviations can lead to poorer quality data and outcomes. But many amendments, as well as deviations, can be avoided by better planning up front, especially in the face of more complex protocol designs.


Feasibility should be a conversation

Protocols typically are written to meet regulatory obligations, not to help research sites efficiently operationalize them. This leads to a disconnect when it comes to operational feasibility. At most, sites will check off a feasibility form that indicates whether they do or do not have particular equipment and access to desired patients.

But operational feasibility needs to be viewed as more of a process or a conversation, not just completion of a simple form. And protocol optimization is the means by which operational feasibility can be built into the study design from ground zero.

Protocol optimization can be viewed as an in-depth examination of the who, what, where, when, why and how of what it will take to conduct a successful clinical trial. In most cases, protocols do a good job of explaining what must happen when—in other words, detailing the procedures to be followed and the schedule. But questions often arise around the who and the how of protocol implementation.

The who is generally viewed as the target patient population. The protocol must define this group very clearly, explaining how the patients are characterized and defining specific inclusion and exclusion criteria.

Sponsors generally do a good job of defining the patient population they want to target with different clinical trials. However, the way they communicate this information in the protocol is rarely optimal. For example, most protocols include numerous inclusion and exclusion criteria, but provide them in a random order. Some may be copied from previous protocols or from a corporate template. But rarely are the criteria written with consideration of, for instance, how sites will go through potential patients’ medical records. 

A better approach would be to provide some sort of organization of the criteria that aligns well with normal site workflow. For instance, inclusion/exclusion criteria could be organized by body systems, medications used or time restrictions, among other categories.

This sort of enrollment optimization can make the protocol more easily understandable—and thus, easier to execute correctly—for both patients and research sites. And that means fewer enrollment issues and reduced chance of deviations related to patient recruitment, enrollment and informed consent.


A site-centric approach to better explain the ‘how’

The other area in which protocols tend to need optimization is in explaining exactly how, in sufficient detail, protocol activities are to happen. And this is an area where early input from target sites themselves can be invaluable.

Patient-centricity has become a buzzword within the clinical research industry, with sponsors, sites and even regulators emphasizing the importance of providing a positive patient experience to aid in recruitment and retention of study participants. This can include factors like schedule flexibility and use of decentralized features or technology to increase convenience for patients.

In order for that to happen, patient-centricity must be built into a protocol from its inception, using real-life input from patients and advocates about the real needs and preferences of the target population, as Mike Lang noted in a blog post on the Pro-ficiency website. And that means that protocols need to be optimized with an eye toward real-life patient needs and preferences, usually by getting input from patient groups during the protocol design stage.

But patient centricity can be difficult to achieve if sites are not fully capable of delivering an optimum experience. What is often missing is a site-centric approach to determining what is truly feasible, as well as what time, equipment and human resources are realistically needed for a protocol to be viable. In some ways, the emphasis on patient-centricity has led to less consideration of operational feedback from sites.

And in reality, one of the most patient-centric actions sponsors can take is taking a site-centric approach to optimizing their protocols. Sites interact with patients and are responsible for implementing protocols in a patient-centric way, so making the protocol more organizationally feasible for sites will ultimately add to patients’ experiences.

And this type of information can only come with early feedback from sites. If protocols are not absolutely clear on the ‘how’ of implementation, down to the smallest detail, that leaves sites with room for interpretation based on their individual capabilities, set-ups and standard practices. The end result? In essence, a study could have 200 sites around the world applying their own interpretations to protocols. This can lead to cost overruns due to under-estimating staff or equipment needs, or protocol deviations or mistakes due to unplanned glitches in operations.

For instance, protocols often use footnotes or separate operational manuals to provide precise instructions on how to carry out various activities. A protocol may state that sites need to take patients’ blood pressure at visits on a certain schedule. And sites may take this information to estimate the time needed for each visit, as well as estimating the associated person-hours that must be funded. But if a footnote or manual then mandates that the measurement be taken standing for a certain amount of time and sitting for a certain amount of time, this can throw off the estimated visit time needed and drive up time and costs.

Similarly, a protocol may mention pharmacokinetic sampling requirements at certain visits. But the supplemental information might stipulate widely different timing relative to the study drug dose at different visits.

Even facility layout can pose a challenge, if the pharmacy is supposed to prepare a sensitive treatment within a certain timeframe but the distance from the pharmacy to the clinic is too far to allow that timeline to be met.

This can be further complicated if there are errors or inconsistencies in any of the supporting documents or footnotes. And that issue is exacerbated by the need to maintain version control and accuracy of all these parts if one is updated.


Visualizations help bring the protocol to life for sites

But sponsors can work with sites to avoid many of these problems and prevent confusion that can lead to errors, deviations and delays. It comes down to operational feasibility. Factors that are most important to sites are those that involve what they must do, when they must do it and how they must do it.

It’s not enough for a site to check off that it has access to patients or certain equipment or facilities. These basic qualifications may not tell the whole story of how easy or difficult a protocol may be for a given site to implement. For instance, a site may have broad access to diabetes patients, but may not have many that meet all 70 inclusion criteria listed in a particular protocol.

Sponsors cannot provide this information to sites unless they look at the protocol through the lens of the staff that must implement it. And in order to do this, it’s important for sponsors to get complete and accurate evaluations from sites so that the protocol writers can incorporate that feedback into the finished protocol. Not all sites are structured the same, so some consideration may be required for variation among sites that they want to include in a study.

All parties must fully understand the study design and timeline so that they can see clearly how complex it will be in real life. It may be helpful for some sponsors to work with outside protocol optimization experts to ensure that they cover all their bases from the inception of each study protocol. Pro-ficiency’s proprietary optimization methodology, Pro-Active Protocol, can help achieve that goal by applying simulation to visually represent the operational flow of a clinical study.

For instance, visual mapping can be done to show, step-by-step, how drug preparation must be conducted, rather than forcing sites to figure out how to implement that part of the protocol without having to piece together information from multiple documents. Sites can then see clearly how those steps would work within their own organizational structures.

This ability to help sponsors and sites visualize the information contained in disparate documents is a key value of services like Pro-Active Protocol.

In this way, sponsors and sites can experience a “day in the life” of a planned study, looking at it from both a site organizational and patient experience view. This insight will prove invaluable. Not only will it allow sponsors to incorporate feedback from sites and patients into the protocol design, but the simulation can be used later to let sites and patients understand in mere minutes exactly what participation in a study will entail, including possible curve balls like patient relapse.

This can aid enrollment by letting patients understand viscerally how study participation will fit into their lives. And it can aid in site selection, preparation and training by giving sites a clear view of what study participation will demand of their organizational structures and procedures.


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