The growing complexity of clinical trial protocols and diminishing operational feasibility of many of today’s trial designs is demanding that the industry rethinks the status quo. The introduction of the ICH E6 (R2) guideline last year is a key indicator of the types of changes that need to be implemented in the industry, and most notably it strongly advocates a risk-based approach, rendering the implementation of these principles a matter of GCP compliance. Although the industry now recognizes that Risk-Based Monitoring (RBM) is the way forward, many organizations still do not understand the incredible opportunity presented by this paradigm shift and must look beyond simple compliance towards the transformational improvements they can achieve across their clinical development franchise.
Introducing the ICH E6 R2 Guideline
The first significant update to the GCP guideline in over 20 years, the International Council for Harmonization’s (ICH) addendum to the ICH E6 Guideline for Good Clinical Practice (ICH E6 R2) has been introduced for a number of reasons, which are summarized in the Introduction section of the updated guideline: “Since the development of the ICH GCP Guideline, the scale, complexity, and cost of clinical trials have increased … Advances in use of electronic data recording and reporting facilitate implementation of other approaches. For example, centralized monitoring can now offer a greater advantage, to a broader range of trials than is suggested in the original text. Therefore, this guideline has been amended 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.”
A Challenging Landscape
As the scope and complexity of clinical trials continue to grow, so do the challenges. Protocols have more endpoints, procedures, eligibility criteria, case report form pages, and investigative sites, all of which is further complicated by the growth in outsourced services, globalization, publicized safety issues with marketed drugs and a slowing of innovation coupled with patent expirations. In this increasingly complicated environment, it comes as no surprise that the cost and duration of clinical development has also steadily increased while profit margins have fallen.
Since 2001, the number of procedures performed on patients during a study has risen by 50%, placing additional burden on both patients and investigative sites and inevitably adding risk to the quality and operational success of clinical research. This is significant as a review of all regulatory submissions to the US Food and Drug Administration (FDA) between 2000 and 2012 revealed that up to 32% of all first-cycle review failures (16% of submissions overall) were due to quality issues and the reliability of data being insufficient.1 These findings are highly concerning considering the investment in time, money and resources that is required to take a new product to market.1
The Quality Debate
The growing cost implications of 100% source data verification (SDV) has highlighted the inefficiencies of this traditional practice. Site monitoring contributes up to one-third of the total cost of clinical research globally and is the single largest driver of cost after investigative site payments, yet 100% SDV, which drives at least half of total site monitoring effort and therefore up to 15% of the total cost of clinical research, has never been dictated in GCP guidance.
Additionally, the alarmingly high rate of quality-related submission failures has undercut the argument that the high cost implications of SDV is a necessary investment to ensure data quality. An analysis on clinical data in 2014 from 1168 clinical trials showed that on average the practice of 100% SDV only drives corrections to 1.1% of site-entered clinical data, demonstrating that this exhaustive, manual, on-site review process is not only insufficient but ineffective too.
RBM Rooted in Quality by Design (QbD)
At its core, the ICH E6 (R2) guidance is not just about RBM, its roots emanate from QbD. Both RBM and QbD are two components of a single paradigm, endorsed not only by the ICH GCP Guidance, but in related guidance documents issued by FDA and EMA over the past five years. RBM and QbD have the same goal – to enhance the operational outcomes of clinical research and ensure ongoing assessment and mitigation of operational risk. QbD is conducted at the earliest stages of clinical research design and calls for risk assessment to be undertaken during the earliest phases of protocol design. The intent is to ensure that studies are designed to not only be based on the scientific merits of the clinical research, but with the aim of assuring operational feasibility and success.
The patient perspective, as well as the perspective of the research site, also plays a significant role in the QbD approach, looking at elements such as how burdensome and complex the study design will be for sites to administer and for patients to submit to. Considering the plight of both the patient and investigator will lead to a study design that benefits these parties, improving enrolment, retention, and overall compliance.
Following the finalization of the study protocol, QbD becomes RBM. At this point, risk assessment is carried out 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 establishes a more targeted approach to quality management in clinical trials, and a robust centralized statistical monitoring (CSM) and key risk indicators (KRIs) solution plays a fundamental role.
Calling for CSM
CSM uses statistical methods to identify unexpected and unusual patterns in clinical data. It has been strongly endorsed by the ICH E6 (R2) addendum as a core component of operational risk detection, and thus positioned to be key to the operational success of any RBM implementation, and for effective oversight of quality in general. This is highlighted in the addendum, which notes that CSM provides “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.”2
CSM is ideally comprised of at least the following three components:
- Statistical Data Monitoring (SDM): The purpose of SDM is to identify atypical data patterns that may represent operational risks, such as fraud, study equipment malfunction, site sloppiness and training issues, through the use of a well-designed, robust set of statistical tests. These are to be used on all clinical data in a study. This has been very effective when identifying risks that may not have been considered during pre-study risk planning.
- Key Risk Indicators (KRIs): KRIs represent a set of metrics designed to provide an early signal of increasing operational risks across all sites in a study. A few examples of commonly- used KRIs include:
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- The rate of protocol deviations
- The rate of adverse event reporting
- Timeliness of data entry
- Rates of queries or data errors
- Screen Failure rate and Early Termination rate
- Rate of missed procedures – especially key efficacy or safety procedures
- Quality Tolerance Limits (QTLs): QTLs are similar to KRIs, in that they represent metrics designed to monitor for specific operational risks, however, the focus is on more systematic issues which, according to ICH E6 (R2), “can impact subject safety or reliability of trial results”. Although the industry is still developing an appropriate interpretation of this new ICH language, QTLs should generally be thought of as monitoring for specific thresholds beyond which the study would likely be considered an operational failure.
In a time of considerable change for the industry, CSM represents a vital new era of quality management and oversight in clinical trials and builds on traditional centralized reviews, such as clinical data management and medical safety reviews.
A key factor to successful outcomes is the effective implementation of CSM. If statistical tests and KRIs have been poorly designed, this may lead to researchers being unable to identify risks in a timely fashion, and/ or a high rate of false risk signalling. False risk signalling often results in unnecessary risk remediation activities that run counter the actual intent.
By effectively using a combination of SDM, KRIs, and QTLs, sponsors can build a very powerful, comprehensive approach to operational quality and risk monitoring, not only driving significantly better quality outcomes but doing so with much greater operational resource efficiency. This enables a significant reduction in the reliance on SDV and related on-site monitoring reviews.
Conclusion
The introduction of ICH E6 (R2) has driven a fundamental shift in the way that clinical trials are run, meaning that there is no other option than for sponsors to take steps forward and embrace the opportunity to achieve improved and more efficient approaches to trial design, conduct, oversight, recording, and reporting. Although it is driving change in the industry, organizations are still in the process of interpreting the guidance into tangible operating practices and must look beyond simple compliance to recognize the benefits a risk-based approach can provide. The most beneficial aspects include:
- A reduced reliance on 100% SDV and on-site monitoring, resulting in significantly less costs in clinical development.
- Improved enrolment and retention rates and more efficient database lock processes, resulting in shorter study timelines
- Significantly higher study and data quality, resulting in higher marketing approval rates.
Now is the time for organizations to explore the difference between simply complying with regulatory guidance and fully embracing effective RBM. Since rolling out RBM activities, organizations have already reported significant cost efficiencies, and many that belong to the TransCelerate consortium are observing significant improvements in key quality measures.
The introduction of ICH E6 (R2) has raised a lot of questions, but it is also supporting sponsors and CROs in bringing improvements to the quality of their data and achieving real, measurable benefits from taking a centralized, technology-based approach to risk management. By reducing costs, offering real-time identification of risk trends across investigative sites and access to trial-wide views, organizations are readily equipped to capture best practices for their future trials.
References
- http://jama.jamanetwork.com/article.aspx?articleid=1817795
- Evaluating Source Data Verification as a Quality Control Measure in Clinical Trials, Therapeutic Innovation & Regulatory Science 2014, Vol. 48(6) 671-680