Increasingly, both sponsors and research sites are turning to various types of performance metrics to support risk-based management of clinical trials. But collecting and analyzing performance data after a trial has begun may not be the best approach; if data on site and researcher performance can be collected and analyzed while they are being trained on a protocol, for instance, sponsors have an opportunity to head off key risks before the first patient is enrolled in a study.

The research industry has been paying closer attention to use of performance analytics to improve the way trials are conducted. In 2017, for instance, ACRP launched an initiative with CRO Analytics to provide insight on performance analytics and how they might improve clinical research, including reductions in costs and shorter timelines.

Avoiding problems that put data at risk or cause adverse events, which could undermine a study; this requires vigorous risk management, or “the exercise of thinking in advance about study risks and implementing mitigation strategies,” Dawn Niccum, executive director of QA and compliance at inSeption Group, said in a 2021 issue of Bioprocess Online. “It demands stakeholders identify critical study processes and calculate risk associated with those processes.”

And in a 2020 issue of Clinical Researcher, Patrick Hughes, co-founder and chief commercial officer at CluePoints, noted that the ICH guideline on GCPs extends risk-based management to all aspects of clinical trial execution, an approach that “has opened a tremendous opportunity to plan and manage clinical research more effectively and efficiently.” The ICH E6(R2) guideline on GCPs outlines what an ideal risk-based quality management system should include, such as risk identification, evaluation, control and communication, among other features.

“The first step in proactive data monitoring is to identify what is possible to mitigate, eliminate, and accept,” Hughes wrote. “This all forms part of various plans, including those for data, training, monitoring, statistical analysis, safety, medical monitoring, quality, and other functional plans.”

In other words, performance analytics can help reduce risks and improve clinical research. But when are the metrics gathered that form the basis of those analytics? Ideally, sponsors would want to have that information as early in the process as possible. And protocol-specific training could offer the perfect opportunity to gather data on where critical problems—those that can impact data quality and patient safety—are most likely to occur.

And the earlier sponsors can get quality information on what is likely to happen at each site participating in an upcoming clinical trial, the more likely they will be to get everything right from the start. Getting that information up-front is a huge risk management effort.

 

The value of training-generated analytics

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Better use of analytics to measure and track how individual sites, as well as specific staff, are performing in terms of properly following the protocol can help sponsors better target their remediation efforts. Necessary retraining could be provided only at those sites and to those individuals that are having deviations, for instance. And that training could focus specifically on the deviations seen.

Furthermore, sponsors often may provide remedial training to all staff at all sites rather than targeting only the sites—or the individuals—making the errors.

And that’s not all. Sponsors can also find and address these risks during initial training if they plan well. Providing training that allows research staff to practice their roles and tasks under a given protocol before a study begins can allow sponsors to collect clear data on how well-prepared each site and its staff is to conduct the protocol correctly.

The right training can help identify these areas and better orient both sponsors and sites to mitigate these risks. The key is to identify metrics that will help identify where risks are more likely to occur and track the occurrence of risky actions and decisions by clinical research staff.

And among the primary risks that sponsors seek to avoid are protocol deviations, which can have significant impacts on clinical trials. The FDA reported in its annual BIMO metrics report covering 2021 inspectional findings that protocol deviations or failure to follow the investigational plan continue to hold the top spot among most-frequent Form 483 observations, a position it held in 2020 and for the last several years.

When crafting a protocol, sponsors generally take a prescriptive view of where they think problems may be likely to occur. For instance, procedures required under the protocol that differ from the usual standard of care could pose a risk of deviations due to physicians, nurses and other staff falling automatically into the more typical way they are used to doing things.

Performance metrics tracked and collected during initial training can produce analytics that allow sites and sponsors to identify and correct problems before it affects study participants, thus reducing the risk of protocol deviations, as well as risks that could directly affect patient health or data integrity. 

But traditional forms of training don’t provide a way to measure how well various research staff are able to perform their jobs under a given protocol. They don’t let sponsors see if risk has been mitigated until they start seeing deviations after a study has started. When that occurs, sponsors must engage in those costly and time-intensive remediation efforts. In addition to taking up sponsor time and money, these retraining efforts also can eat up a lot of site time, often without additional payment.

Simulation-based training, on the other hand, lends itself especially well to collecting and presenting this type of data. Pro-ficiency, for example, provides simulation-based training that lets sites practice all parts of a protocol in a consequence-free environment. Every decision users make during a simulation experience is tracked, collected, and presented in actionable performance and compliance reports. Moreover, these reports can provide valuable insights to sponsors, with the ability to identify which sites and which individuals are having issues with a particular part of the protocol before they affect study timelines or budgets.

 

This heat map dashboard is just one example of the reporting capabilities simulation-based training offers. From sites to individual investigators, these dashboards can be invaluable in promptly detecting problematic areas and providing proactive assistance before lagging performance leads to deviations.

Simulation-based training customized for a given study, for instance, can track performance at both the individual and site level. These analytics can help sponsors better identify risk areas related to deviation from the protocol and address them with targeted training before the first patient is enrolled.

Behavior-based performance metrics can help sponsors predict performance by sites and their staff. And these metrics, or analytics, can be used to identify weak sites, under-performing staff, or even potential pain points in the protocol itself. Sponsors can take this information and provide carefully targeted support to the individuals or sites that need it most, heading off risks of protocol deviations before they occur within the actual study.

 

Pretesting of staff decisions

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This type of training system can be used to determine staff’s first responses to instructions on how to conduct protocol procedures, and to make corrections if their first actions are incorrect.

When determining what metrics to track, sponsors should think through the elements of a study that will most impact its success and what the greatest impact of noncompliance could be. For instance, deviations like lack of an initial or signature on some paperwork are easy to fix, while deviations in dosing or patient procedures would cause more problems. Important considerations are whether lab techs and other staff are handling the investigational product correctly and if patient visits and tests are conducted correctly.

The analytics can help sponsors see what sites’ natural inclinations lie in areas of risk. For instance, is there a particular procedure that they tend to miss the mark on? This will help sponsors drill down to how staff are handling their protocol-specific roles and allow for highly targeted remedial work, if any is needed.

This information allows sponsors to tell which sites or coordinators struggle with correctly applying inclusion/exclusion criteria when enrolling patients, or which sites have problems with the dosing regimen under the protocol. Sponsors can then address each site’s specific weaknesses to uncover the root of the problem and provide additional training to avoid problems when the study begins.

For instance, a protocol might include a complicated preparation procedure for the investigational drug that states the product can’t be shaken, but must be undulated to mix – and if bubbles are seen, it cannot be used. If a researcher’s first response to practicing the procedure is to shake the product, see bubbles and set it down, that can indicate to the sponsor that this staff member did not fully understand the prep instructions. 

Analytics can help point out weak areas in a protocol. In the example above, if the investigational product prep procedure is a challenge at multiple sites, that could be a signal to the sponsor that extra effort is needed in this part of the training before the trial starts.

In short, customized simulation-based training that measures carefully selected performance metrics can provide analytics that allow sponsors to identify key areas of risks, particularly regarding protocol deviations that could impact patient safety or data quality and integrity. Not only does this reduce the risk of citations for protocol deviations once a study is underway, it also can save time and money that would be spent on re-training when deviations began occurring with real study participants.

Analytics allows for both sponsors and sites to understand the problem and make better plans to fix them, taking less time away from the clinical trial and reducing overall study risk.

 

To learn more about a training approach which integrates predictive analytics, visit http://proficiency1.wpenginepowered.com/prescriptive-analytics.

Protocol deviations can have a detrimental effect on new drug development, adding to costs and time to clinical trials and even putting the acceptability of data generated during a study at risk. Despite this, protocol deviations seem to be viewed as just part of doing business in the clinical research arena. And one question that arises is whether training in individual protocols is adequate, given the frequency with which deviations occur.

In its recent analysis of inspectional findings during 2021, the FDA said in its annual BIMO metrics report that protocol deviations or failure to follow the investigational plan was the most common observation listed on Form 483s after a BIMO inspection. This was also the most-frequent Form 483 observation during 2020, and has been at the top of the list for the last several years, the FDA noted.

And in its January/February 2022 Impact Report, Tufts University Center for the Study of Drug Development (CSDD) reported that protocol deviations rose in the 2018-2020 period compared to the 2013-2015 period, as have substantial amendments to protocols. According to the CSDD report, Phase 3 trials had the highest number of deviations per protocol, with an average of 118.5, which affected 32.8% of patients enrolled. Phase 2 studies saw an average of 75.3 deviations affecting 30% of patients, and Phase 1 trials had an average of just 8.7 deviations affecting 15.3% of patients.

Oncology trials saw a higher number of deviations, on average, compared to other areas of research, with Phase 2 and 3 oncology protocols having 30% more deviations compared to non-oncology protocols. Additionally, protocols outsourced to CROs had more deviations and substantial amendments per protocol, CSDD reported.

But despite the potential for negative repercussions, protocol deviations remain an ongoing challenge for researchers. As a matter of fact, in a June 2020 blog post, clinical trial platform provider Castor referred to protocol deviations as “the new normal.”

Precisely quantifying the impact of all of these protocol deviations on clinical research is difficult because of the variation among different areas of study and even among individual clinical trials. However, it is clear that deviations do affect trial progress and outcomes.

 

Industry seeking to change

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Despite these figures, however, researchers and sponsors appear dedicated to reducing or even eliminating protocol deviations. In fact, some research organizations use protocol compliance as one of the metrics by which site performance is measured. For instance, Diane Whitham et al., on behalf of the Site Performance Metrics for Multicenter Randomized Trials Collaboration, listed several metrics related to protocol compliance in an October 2018 Trials article, including:

• Percentage of randomized participants with at least one protocol violation;
• Percentage of randomized participants receiving allocated intervention as intended per protocol;
• Number of missed visits per number of randomized participants;
• Number of late visits per number of randomized participants; and
• Number of critical or major audit findings per number of randomized participants.
• And the entirety of a seasoned clinical research audience attending a 2021 webinar agreed that one key metric should define success for site training: zero important protocol deviations.

The message seems to be that the goal of zero deviations—or at least zero important deviations—can be achieved with the right strategy. The industry is clearly keen to avoid the potential blowback from protocol deviations, which can include additional time to complete a trial, the costs associated with extending a trial.

Protocol deviations can increase costs due to the study having to be extended, additional patients enrolled, replicated work and prolonged timeline for product development. Additional monitoring and retraining costs may be incurred, as well. Deviations also may have an impact on data quality that could ultimately have long-term implications on product approval.

In fact, the ICH E9 guidance, Statistical Principles for Clinical Trials, stated clearly that protocol deviations “always bear the potential of invalidating the trial results.”

And all protocol deviations require documentation and reporting, Laurie Halloran, president and CEO of Halloran Consulting Group, noted in the May 2, 2018 Life Science Leader, activities that eat up staff resources and can add to costs in that way. If an unreported deviation is discovered during a regulatory inspection, it is likely to result in penalties from the FDA or other regulators.

In some cases, deviations may lead to protocol amendments, which can delay trial completion, potentially costing $35,000 per day or more, according to a 2015 survey by Clinverse, a statistic still used for cost estimates. Amendments can add an average of 30 days—and associated costs—to the length of a study, according to a 2021 report from CSDD.

Protocol deviations—whether enrolling an unqualified patient, incorrectly performing a visit or procedure or failing to collect data necessary to interpret primary endpoints—can result in unusable data that requires additional time and resources to replicate. In its March/April 2021 Impact Report, CSDD noted that mid-study amendments typically require 30 days to complete before a study can resume, adding significantly to the time required to complete a clinical trial.

 

Addressing deviation risks with training

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There are myriad reasons behind protocol deviations. Ever-increasing protocol complexity could be one factor that contributes to protocol deviations. CSDD noted that protocols have been steadily increasing in complexity since 2009, with increasing numbers of endpoints and distinct protocol procedures. Those increases provide more opportunities for investigators or research staff to make mistakes.

Sometimes a change in procedure may be made to ensure patient safety, as in the case of emergency treatment, Halloran said.

And social distancing requirements during the COVID-19 pandemic spurred some protocol deviations, such as replacing in-person site visits for patients with remote or telehealth visits. The FDA in August 2021 updated its guidance, Conduct of Clinical Trials of Medical Products During the COVID-19 Public Health Emergency, recognizing these necessities and clarifying what protocol deviations due to COVID would be acceptable with appropriate reporting.

But these relatively innocuous reasons are not the only causes of protocol deviations. For instance, deviations may occur because the protocol is hard to understand or allows different interpretations at different sites. And they may occur because study teams have not been trained adequately or because knowledge isn’t transferred well during staff turnover. In addition, Insufficient performance-based tracking throughout site training makes it difficult for proactive actions to be taken to address high-risk areas for protocol deviations that may result from site error.

All of these causes can be addressed with the right type of training. Thorough, protocol-specific training can help ensure that investigators, coordinators and other research staff fully understand how to perform all tasks included in the protocol. And properly designed training will develop mental muscle memory so that researchers can perform correctly under pressure or when substantial time has passed since training. Besides developing participants’ comprehension, proper training should track performance and allow sponsors to identify and correct potential problems before they impact a study’s budget or timeline.

For instance, protocol simulation-based training can mimic realistic scenarios and guide research staff through each step, including making the right decision when problems occur, like:

• A patient takes a restricted medication just before the randomization visit;
• A temperature excursion occurs for the investigational product; or
• A patient misses a dose or a visit where a procedure was to be completed.

Ideally, the training allows the learner to critically think through preventive actions. The simulation scenarios should not only model what can go wrong and assess potential corrective actions, but more importantly, how the issues can be prevented. When users make decisions in a simulation experience it can be tracked, collected, and presented in performance and compliance reports. These reports provide invaluable insight that can identify and address individual or site-wide weak points before a protocol deviation occurs. In contrast to traditional training, simulation-based training aims to ensure study training is consistent, intense, and proactive.

Simulation-based training in particular allows research staff to practice a protocol and all its nuances in advance of applying it to real patients and real data, with the associated real potential risks. And in addition to identifying and addressing protocol deviation risks, the designed scenarios can allow research staff to learn how to prevent the issues that lead to deviations before they arise.

And this practical approach to training can help sponsors and researchers reduce the incidence of protocol deviations and avoid the additional costs—in both time and money—associated with fixing those deviations.

 

Contact us to discover how our simulation-based training approach can reduce protocol deviations across studies.

As a former CRA, I have spent the better part of my career mentoring, teaching, and helping CRAs become competent at monitoring clinical trials to ensure compliance with protocol and GCP. In light of this experience, I urge all CRAs and monitors to STOP THE MADNESS of having CRAs reconduct site training at site initiation visits (SIVs). Instead of retraining sites across all topics, I propose that SIVs focus on retraining sites in their weakest areas.

 

A focus on evaluating protocol-specific training already conducted at a research site could hold a key to better focusing site initiation visits (SIVs) on critical factors and reducing the amount of time spend on these meetings.

The SIV is used to confirm that a site has hit several milestones needed to be ready to start enrolling patients. These milestones include:

• All staff have been property trained and qualified;
• Any necessary equipment—from e-diaries and electronic data capture (EDC) systems to special equipment like ECGs—is in place and working properly;
• Staff that must use the equipment has appropriate access and is able to use it correctly; and
• The study drug is on-site, properly documented and stored, and in sufficient numbers for the expected number of patients.

The process of evaluating these areas—often including both completion of a feasibility questionnaire and an on-site qualification visit—can eat up as much as 30% of a clinical trial’s timeline, according to a March 2021 blog by Clinical Research IO (CRIO).

Traditionally, all of these areas have been reviewed during an in-person meeting, the SIV. And often, this meeting, in order to check off all of the above boxes, has included long lectures about how to conduct the trial in accordance with the protocol. However, sites, along with some sponsors and CROs, have recently begun to question whether this approach is the most effective and efficient method of confirming a site’s readiness to begin a clinical trial.

And this is spurring some sponsors to question the value of the SIV in its traditional form. A better approach, many sites, sponsors and CROs agree, could be to replace the rote SIV with a more targeted and customized approach.

 

Why re-conduct training?

A particular area of focus has been in the training of clinical trial staff. Some research sites are pushing back against long, drawn-out SIVs that include a repeat of training their staff have already completed. Many sites believe they gain nothing from this process; rather, it is a box that is being mindlessly checked off.

In theory, if the staff have already been to the investigator meeting and already done online training, this should not need to be re-done. No site staff should need training in the protocol at this point.

And the training provided at the SIV—typically a lecture-type presentation with a slide deck—may not add anything of value to staff capabilities and understanding. A one-size-fits-all lecture by a CRA who is not a trainer is unlikely to correctly target any site-, protocol- or job-specific areas where weaknesses may legitimately exist.

A better approach would be to provide site-specific training only as needed for identified knowledge gaps. The goal must be to make sure that any problems are addressed before a site begins enrolling patients for a new clinical trial. And rote checking off items on a broad, overly generalized to-do list is probably not the best way to accomplish that goal.

 

Insight available from training metrics

Training systems that use simulation can offer a great tool for sponsors and CRAs to streamline the SIV. For instance, Pro-ficiency’s training approach generates metrics that show how well each participant did during the training and highlights weak areas that may warrant addressing in an SIV. Because the training walks staff through actual protocol scenarios, the metrics can easily flag areas where the protocol may not be well-understood, or where certain staff skills need to be upgraded.

For instance, if the metrics provided show that the PI didn’t understand or struggled with something during training, or that no-one at a given site understood some aspect of the simulation, this information can be used to develop highly targeted training as part of the SIV. In such cases, the SIV could offer an opportunity to run through any specific problematic scenarios again, narrowly targeting only training gaps.

Conversely, if all staff at a site passed their training simulations with flying colors, the sponsor or CRA could correctly conclude that no additional training needs to be included in an SIV.

Metrics like this can act as valuable inputs for creating a customized SIV for an individual site. Anyone with administrator privileges can run reports on Pro-ficiency training results and review the metrics to see who did or did not do well in the training, and where they had difficulty. A CRA can request that information to help determine whether training should be part of a SIV. And if sponsors or CROs have any training concerns, they can ask the CRA to discuss those concerns.

Another approach could be to change the training portion of an SIV from the usual lecture to an opportunity for the site to ask questions based on their experience with the already-completed training. Savvy sites are already doing this, developing lists of questions based on “day-in-the-life” mock runs through the protocol for each position. Many sites may reach out to the sponsor or CRA independently with these questions.

The point is that the focus shifts from the sponsor to the site. This is appropriate, because under GCP requirements, the PI—not the sponsor—is responsible for the quality of the trial, including staff oversight, competency and training.

 

Focus on site-specific needs

An important consideration is what an SIV is intended to accomplish. In many cases, some of these goals can be achieved using other mechanisms. If that is the case, it makes sense for these things to be done outside of an SIV.

When developing SIVs for individual sites, sponsors and CRAs should strive to do away with anything perfunctory and anything that can be verified otherwise. If a particular site has unique needs, such as specialized equipment, customized program planning or another need, addressing that in an SIV could have value. However, even in those cases, much of that work could be done remotely.

Outside of training, SIVs are used to confirm equipment readiness and correct supply and handling of the investigational drug.  If a site is proven to have all of the equipment and drug supplies needed and is ready to start enrollment, it might even be possible to eliminate the SIV altogether and allow that site to begin. And since much of this should have been addressed in training already, the training metrics can be used to identify gaps in these areas.

Both the training portion and the SIV are more effective and valuable if they involve a conversation, rather than someone talking at site staff. This is more easily accomplished by discussing identified problems from previous training in the protocol or on equipment versus subjecting staff to a PowerPoint presentation and lecture that may cover things in which they already are competent, and could also miss areas where confusion does exist.

Even when a formal SIV is warranted, sponsors and sites need to consider whether an in-person meeting is necessary. Many things, even demonstration of equipment availability and staff competency in using it, can be done remotely and involving only the specific personnel necessary.

Another advantage to the selectively targeted SIV approach is how well the process lends itself to being done virtually. For instance, access to systems can be confirmed by checking as an administrator that the necessary people are logged in; this demonstrates the ability to access the necessary systems for data entry and management, communications and other purposes. Similarly, a virtual call via Zoom or other approved platform can be used to view the pharmacy and confirm the presence of necessary equipment.

And the industry seems to be shifting in that direction to some degree. The CRIO blog also indicated that many sponsors and CRAs are increasingly moving to technology to allow more aspects of the SIV process to be conducted remotely.

Virtual meetings can even be used to demonstrate that equipment turns on and functions properly, and to troubleshoot any problems noted. Personnel can even demonstrate proficiency in use of equipment via a virtual call.

Ultimately, it’s important that the SIV process change from a rote, one-way, box-checking approach to a more conversational, interactive, focused and targeted approach that sets sites up for success.

Sponsors and CROs trying to achieve better enrollment in clinical trials often overlook the most essential stakeholder in the process — the investigative sites that implement the trials and interact with the patients throughout the process. At any given moment, tens of thousands of clinical trials are running across the globe. Given the number of studies currently underway, it is unsurprising that patient enrollment has become a top priority. Ineffectively recruiting patients often delays research, potentially compromising sponsors’ timeline and prompting a dreaded “study rescue” situation. When enrollment is lacking and potential subjects are being excluded left and right, the first thing to determine is whether the study’s protocol is the root of the problem. Sites suffer the most from overly complicated protocols, often putting enrollment, data collection and study fulfillment at risk. Throughout a recruitment process, potential subjects moving through the pre-screening and screening process may be disqualified for unnecessary reasons along the way. Poorly written protocols create unnecessary challenges for sites, confusing investigators and leading to investigators disqualifying ideal subjects, or spending valuable time and resources screening unsuitable candidates. Doing a deep dive diagnostic evaluation of the way your protocol is describing the eligibility criteria, and the way you are teaching your sites how to identify and evaluate the ideal subject for the study can go a long way in preventing and overcoming enrollment challenges. Here are some strategies for improving existing and developing protocols:

 

1. Perfectly describing the eligibility criteria – Segmentation strategies

Lets face it, protocols may never be perfectly executed, but they can be perfectly written, at least from an inclusion / exclusion criteria standpoint. Split out composite or multi-part criteria vs. lumping things together. If you can’t answer a simple yes or no to each part of your criteria, then the site won’t be able to determine if a potential subject is in or out. There is no shame in having a few more easily-understandable criteria. Lumping things together or worse, describing end of study procedures along with an eligibility criterion creates unnecessary confusion. Segmenting the criteria into the pre-screening vs. screening (post-consent) stages can help optimize the site’s workflow to quickly rule out subjects who have permanent exclusions. Clearly articulating the time-based criteria will help sites to understand how long they have to wait before re-evaluating a potential subject.

 

2. Job aids

Site-wide comprehension of your eligibility criteria can be improved with one, cost-effective tool – a well crafted I/E criteria checklist. And no, we don’t mean copying and pasting the criteria as written in the protocol. We mean converting this into an easy-to-use checklist that clearly segments out the component parts of the criteria by stage (pre-screening / screening) and by permanent exclusions vs. time-based or temporary exclusions as described above. Make it simple for site staff to easily walk through the criteria in a way that allows them to quickly rule out subjects who don’t warrant further attention from those who should be put on a watch and wait list. The addition can be incorporated into any on-going study without any additional adjustments.

 

3. Use visuals!

Improving total protocol comprehension across sites does not always require a complete overhaul of the written document, but don’t shy away from flow diagrams or decision trees. If you can map out a process in the protocol, or visualize the steps a site will have to take, you can more clearly describe this in understandable terms in the protocol. These simple infographics enhance understanding with little added effort to the protocol writer. Visually representing key parts of the protocol ensures the important steps are easily translated across sites, and greatly reduces site errors.

 

4. Site Training

When sites struggle to recruit randomized subjects and the protocol wording is not to blame, it is time to reassess your site training approach. The majority of site training is unoptimized, and a missed opportunity for sponsors and CROs. Effective clinical site training prevents deviations by giving users the chance to learn from the known challenges from earlier studies and other sites. Site staff are not all created equal in terms of their experience so a “one size fits all” approach is a surefire way to set your study up for failure. Pro-ficiency’s Simulation-based online training provides users with training tailored to their individual needs. With Pro-ficiency’s superior clinical site training and analytics to track performance, sponsors can ensure sites are prepared and understand their protocol sufficiently to maximize enrollment and minimize deviations. Preparing site staff by providing them training that guarantees true and total protocol comprehension is the safest way to ensure that a poorly written protocol won’t come in the way of your enrollment and study timelines.

Visit http://proficiency1.wpenginepowered.com/our-approach/ to discover a better way to train clinical sites.

As part of our series covering all the do’s and don’ts surrounding protocols, I wanted to call attention to one of the greatest urban legends in clinical research…the requirement to include endless footnotes (in size 6 or 8 font no less!), at the end of the schedule of assessments in the protocol.  I have searched high and low for regulatory guidance documents that mandate such a practice, to no avail.  Common protocol templates created by organizations and industry collaboratives vary on their use of footnotes within the templates, but nowhere have I found that this is a requirement to get a protocol approved.  Yet, it is a common practice and one that contributes more to non-compliance than just about any other facet of the protocol.

It is not uncommon to see upwards of 21 footnotes in a typical Phase III study.  In one recent protocol I evaluated there were 17 footnotes, 6 “*’s” and 8 “notes” provided as part of the schedule of assessments.  I confess that I wasn’t sure what the differences were between these and what prompted the decision to use three different formats for conveying the procedural requirements versus just using footnotes.  But what I was sure about, is that the sites would have difficulty understanding and complying with the requirements.

The solution is simple.  Just add an extra column to the schedule of events with the content of the footnote.  Rather than the site having to hunt around for an important footnote that might appear several pages later in the protocol, the information will be readily available and easily readable right next to the required procedure.

Instead of this…

*Be sure to do this procedure prior to the morning dosing on days with fasting labs*

 

Do this…

A coworker recently mentioned to me that Elon Musk’s claim to fame has been challenging the norm.  The willingness to ask “why are we doing it this way?” has led to some of his innovative discoveries and his success.  So I was inspired to ask the hard question for all you protocol writers out there:

“Why are you creating more unnecessary confusion for your sites by using footnotes instead of adding in an extra column to the schedule of assessments?”

It costs nothing but potentially saves hundreds of protocol deviations.  

While you may not be rewarded with the billions of dollars that Mr. Musk has acquired for his inventions, challenging the norm when you write or review your next protocol will reap even greater rewards….happy sites….cleaner data…safer subjects.  Now that’s what I call a great return on investment!