ACRP Clinical Researcher
ICH E6 R2 – Miracle Pill for the Clinical R&D Industry
Steve Young, Chief Operations Officer, CluePoints
Publication of the long-awaited ICH E6 (R2) Guideline this year finally makes it official. A risk-based approach to clinical trial quality management – commonly referred to as risk-based monitoring or RBM – is now a codified GCP expectation for the industry. Many sponsor and CRO organizations that may have previously delayed implementation of RBM methodology are now poring over the updated GCP guideline to determine what is needed for compliance. Here, CluePoints’ Chief Operations Officer Steve Young highlights the key changes in the mandate and explains why organizations should shift their mind-set away from simply ensuring compliance, and towards embracing the tremendous business opportunity offered through an effective roll-out of RBM.
Why Change?
To fully understand the origin of the new ICH E6 (R2) update, we need to go back a couple of decades. The 1990’s was a time of relative economic health for the bio-pharmaceutical industry, but that suddenly evaporated at the turn of the century. While the internet technology bubble was bursting on Wall Street, drug makers also began feeling pressure from multiple directions. This included highly publicized safety issues with marketed drugs, a slowing of innovation coupled with patent expirations, and a continual increase in the complexity of clinical trial designs. All of this meant that the cost and duration of clinical development was steadily increasing while at the same time profit margins for the industry were dwindling.
This was – and to a great extent continues to be – a true crisis for the industry. First, the increasing complexity of trial designs has added significant risk to the operational success of research, both in terms of attracting and retaining patients and in generating reliable results that support ultimate marketing approvals. A review of marketing submissions to the FDA between 2000 and 2012 revealed that about one-third (32%) of all first-cycle review failures – or 16% of submissions overall – were driven by quality issues. This is an alarming statistic, given the tremendous investment in time, effort and money needed to take each new investigational product through clinical development. It is apparent that our traditional methods of managing clinical trial quality are not sufficient for research in the 21st century – and perhaps never were.
Exacerbating these serious concerns with operational quality has been the ever-increasing cost and duration of clinical trials. And as organizations more closely scrutinized the drivers of cost in the previous decade, site monitoring quickly came into focus. Site monitoring contributes up to one-third of the total cost of clinical research globally and is the single largest driver of cost next to investigative site payments. Additionally, the traditional practice of 100% source data verification (SDV) drives at least half of total site monitoring effort by most estimates. Thus 100% SDV, a practice adopted broadly by a conservative industry but never dictated in GCP guidelines or regulations, has contributed about 15% of the total cost of clinical research.
You Get What You Pay For?
One might offer at this point that while the cost of comprehensive SDV is indeed quite high, it is a necessary investment we must continue to make in order to ensure requisite quality in clinical research. Put more simply: You get what you pay for. However, the alarming rate of quality-related submission failures clearly indicates that this practice has not been sufficient. And there is a growing body of evidence to confirm that this exhaustive, manual on-site review is not only insufficient but ineffective as well. An analysis conducted in 2014 on clinical data from 1168 clinical trials showed that the practice of 100% SDV drives corrections to only 1.1% of site-provided clinical data on average. This is quite a modest return on such a large investment of time and money!
The Case for RBM
RBM as a concept has gained steadily increasing interest and attention over the past 8 to 10 years, specifically as a potential solution to these industry challenges. RBM is, at its core, the operational analogue to Quality by Design (QBD). Both of these methodologies have the same fundamental goal in mind – to improve the operational success rate of clinical research. Success in this context certainly means higher quality, but it also means shorter timelines and greater operational efficiency. QBD and RBM are also linked together by methodology, as they both call for ongoing assessment and mitigation of operational risk. In the case of QBD, this risk assessment is conducted starting with the earliest stages of clinical research design. The purpose is to ensure that clinical studies are designed from the beginning not just with the scientific merits of the research in mind, but just as importantly with operational feasibility and success in mind. For example, the perspective of prospective patients should be considered (a.k.a patient-centricity), along with that of investigative sites. How complex will the study design be for sites to administer and how burdensome for patients to submit to? Are there ancillary, non-critical procedures or assessments that can be removed for the study?
Once a study protocol has been developed and is considered stable or final, QBD becomes RBM. Risk assessment is once again performed on the completed design by a cross-functional study team. Remaining operational risks are identified, prioritized, and risk mitigation plans established to guide all downstream operational study management plans. This results in a more thoughtful, targeted approach to quality planning and management.
QBD and RBM are then fundamentally basic concepts, and not specifically new concepts either. For those of us who have worked in clinical operations over the past two decades, how often have we lamented about the mad scramble to achieve first patient enrolled by a certain target date, only to realize afterward that we forgot to consider a dozen different pitfalls that we now have to urgently address? QBD and RBM can be thought of as welcome reminder to the industry: Think before you act!
Strong Regulatory and ICH Endorsements
ICH E6 R2 was preceded by RBM guidance documents from both FDA and EMA. The FDA guidance, finalized in August 2013, provided not just a very nice framework for considering a risk-based monitoring approach – it was a very strong endorsement of this paradigm. The following excerpt provides clear evidence of this:
“There is a growing consensus that risk-based approaches to monitoring, focused on risks to the most critical data elements and processes necessary to achieve study objectives, are more likely than routine visits to all clinical sites and 100% data verification to ensure subject protection and overall study quality.”
The EMA Reflection Paper on RBM, released just a few months following the FDA guidance, provides a similar call-to-action for the industry and in fact offers even broader context and guidance that goes beyond site monitoring to encompass overall quality management.
Very much encouraging an RBM approach as well, the ICH E6 R2 states that, “the sponsor should develop a systematic, prioritized, risk-based approach to monitoring clinical trials. The sponsor may choose on-site monitoring, a combination of on-site and centralized monitoring, or, where justified, centralized monitoring.”1 The sponsor should ensure that all aspects of the trial are operationally feasible and should avoid unnecessary complexity, procedures and data collection. The guidance also recommends that the approach taken must be controlled and systematic for the lifecycle of the study, and sets clear expectations for appropriate monitoring methodologies and documentation, all of which make the case for an RBM approach. These include:
- Critical process and data identification: processes and data that are critical to ensure human subject protection and the reliability of trial results should be identified during protocol development
- Risk identification: sponsors should identify risks – at both system and clinical trial level – critical to trial processes and data up front
- Risk evaluation: researchers must carry out risk assessment/critical data identification before the study to characterize risks through risk evaluation, looking at the likelihood, detectability and impact of those risks. They should then put together a quality oversight plan that is a targeted approach to operational quality management, specifically focused on the biggest risks to operations
- Risk control: the sponsor should decide up front which risks to reduce and/or to accept. Predefined ranges within which various quality measures will be accepted should also be established, to identify issues that can impact subject safety or the reliability of trial results. Detection of deviations from these predefined limits should trigger an evaluation to determine if action is needed
- Risk communication: quality management activities should be documented and communicated, to facilitate risk review and continual improvement during study execution
- Risk review: risk control measures should be reviewed intermittently to check that the implemented quality management activities remain effective and relevant
- Risk reporting: reporting should include a description of the quality management approach taken and review key deviations from the predefined quality limits, and any remedial actions taken
Operational Lynchpin: Centralized monitoring
The ICH E6 R2 also indicates that the implementation of RBM, and more specifically using centralized statistical monitoring (CSM) as a core component of clinical trial execution, is recommended due to its ability to provide, “additional monitoring capabilities that can complement and reduce the extent and/or frequency of on-site monitoring and help distinguish between reliable data and potentially unreliable data.” 1
CSM uses statistical methods to identify unexpected or unusual patterns in clinical trial databases, driving better quality outcomes. CSM ideally comprises two complementary components, which we will refer to here as key risk indicators (KRIs) and data quality assessment (DQA).
KRIs are pre-designed metrics used to monitor for emergence of known operational risks across all sites in a study, typically identified or confirmed during the pre-study risk assessment exercise. Commonly used KRIs include the rate of protocol deviations, rate of adverse event reporting, timeliness of data entry, and rates of queries or data errors. All are designed to identify sites that are deviating significantly from an expected norm.
CSM on the other hand employs a large number of statistical tests that are executed against all of the patient data in the study, with the purpose of detecting unusual data patterns within particular sites, patients, or countries that may be indicative of quality issues. Unlike KRIs which are targeted to monitor for specific pre-identified operational risks, DQA is a more comprehensive vetting of all study data that results in a “leave no stone unturned” approach. If done effectively, it can expose important quality issues that may not have been anticipated during pre-study risk assessments. The combination of KRIs and DQA provides for a very powerful, comprehensive approach to operational quality and risk monitoring.
When considering design and implementation of KRIs, the focus should be on KRI quality and not quantity. Early adopters of RBM have had a tendency to over-engineer various aspects of the process, and this includes trying to implement many dozens of KRIs. Use of more than 20 KRIs on any given study should give you pause, as it is more than likely that some of those KRIs are redundant – monitoring for essentially the same area of risk. What’s more important is to select KRIs with discretion and to configure them to ensure they are both reliable (i.e., minimizing unnecessary false signalling) and proactive in detecting emerging risks.
Using ICH E6 R2 to support a transition to RBM
Clinical research organizations tend to be very conservative with respect to trying new technologies and new paradigms, and RBM is no exception. It’s interesting that even the ringing endorsements of RBM from both FDA and EMA have not been enough to motivate most organizations over the past four years. However, the introduction of ICH E6 R2 means that waiting and watching is no longer an option from a GCP perspective. And while this is medicine that some still don’t want to take, in reality it is a miracle pill for the industry. Rather than fearing the change, organizations should embrace the updated guidance the new RBM paradigm as a huge opportunity. If someone told you that you can significantly improve quality, shorten study timelines and do this all at significantly lower cost, you would likely roll your eyes and walk away. Well, whether you choose to believe it or not, this is the clear and present proposition with RBM.
It is important for organizations to know that RBM strategies can actually be relatively straightforward to implement, providing they work collaboratively with the correct study partners to identify and implement the right tools that will help them manage this change in the most effective way in order to reap the advantages as soon as possible.
Once implemented, it’s crucial to make RBM stick and study teams can do this by ensuring clear communication with all involved in the change, creating an environment of openness where discussion about the new approach is encouraged, avoiding information overload, and continuously checking understanding to ensure correct processes are being followed.
Final thought
The updated ICH E6 R2 guidelines have been introduced to encourage implementation of improved and more efficient approaches to clinical trial design, conduct, oversight, recording and reporting while continuing to ensure human subject protection and reliability of trial results. Far from being considered a hurdle to overcome, the ICH E6 R2 should be seen as a positive step forward and exciting opportunity for more efficient clinical research and development, with significantly better outcomes.
An effective centralized monitoring solution can help sponsors and CROs manage this shift, meet the new regulatory guidelines, and improve the data integrity and success rates of their trials, and is critical to operational quality monitoring in the new paradigm.
