Brian Barnes

	After more than 20 years, the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) Harmonized Guideline was updated to ICH E6 (R2) in November 2016. The revision was implemented to modernize clinical trials and takes into consideration the evolution in technology and quality management processes that offer new opportunities to enhance efficiency, focus, and oversight on relevant activities.

 ICH E8 (R1) draft version was released in May 2019 and further supports a risk-based monitoring (RBM) strategy by providing general considerations for clinical studies.

These revised guidelines encourage implementation of improved and more efficient approaches to clinical trials, in such aspects as: trial design, conduct, oversight, documentation, and reporting to ensure human subject protection and reliability of trial results. Successful implementation of these guidance documents requires a well-orchestrated, collaborative, and cross-functionally supported effort between sponsors and their contracted vendors.

	Within ICH E6 (R2), “The sponsor should implement a system to manage quality throughout all stages of the trial process. Sponsors should focus on trial activities essential to ensuring human subject protection and the reliability of trial results. Quality management includes the design of efficient clinical trial protocols and tools and procedures for data collection and processing, as well as the collection of information that is essential to decisio- making.”

 While the guidance provides core recommendations, interpretation and implementation has varied greatly. ICH E6 (R2) highlights seven components necessary to manage quality through all stages of clinical trials. Those components are:

	An effective-but often overlooked-component of clinical trial oversight is risk communication. ICH E6 (R2) states, “The sponsor should communicate quality management activities to those who are involved in or affected by such activities, to facilitate risk review and continual improvement during clinical trial execution.”

 ICH E8 (R1) further supports that premise by indicating that “proactive communication of the critical to quality factors and risk mitigation activities will support understanding of priorities and resource allocation by the sponsor and investigator sites.”

	To address the possibility of overlooked risk communication, a basic set of factors relevant to ensuring study quality should be identified for each study. Emphasis should be given to those factors that stand out as critical to study quality. These critical to quality (CTQ) factors are attributes of a study whose integrity is fundamental to the protection of study subjects, the reliability and interpretability of the study results, and the decisions made based on the study results. The use of CTQ, such as critical data and processes, key performance indicators (KPIs), key risk indicators (KRIs), and quality tolerance limits (QTLs), presents an opportunity to proactively communicate CTQ factors and risk mitigation activities to support understanding of priorities and resource allocation by the sponsor and investigator sites.

	CTQ factors function as communication vehicles to ensure quality alignment across the study. In this way, CTQ, KRIs, and QTLs aligned with critical data and processes to facilitate the alignment of project teams and organizations early while supporting study and vendor oversight throughout the clinical trial life cycle. ICH E8 (R1) recommends quality measures and performance indicators be aligned with a proactive design approach. In this framework, CTQ factors are 

 is to be focused on, whereas KRIs and QTLs are 

 the CTQ factors are safeguarded to prevent or mitigate important and likely risks to investigation quality, including risks to human subject protection and data integrity.

	What follows within this article are practical methods for integrating CTQ factors within the operational execution life cycle of a clinical trial.

	Successful clinical trials begin with focus and cross-function alignment across departments and the third-party vendors that provide services, such as project management, clinical management, data management, biostatistics, medical monitoring, pharmacovigilance, and medical writing. Early risk management activities require project teams to have a strong understanding of the study endpoints and supporting CTQ factors. Those factors function as a compass to provide a common direction across the project team, helping them to focus not only on what is important, but, more notably, what is not important. Early identification of the critical risks that could affect subject safety or data integrity is paramount to driving further focus of the project team. In this way, early risk-management activities prioritize resources on the critical trial elements, impact the various functional/vendor trial plans (e.g., monitoring plan), align communication across organizations, and lay the foundation for downstream risk-based operational decisions.

	Once CTQ factors are identified, the shift from planning to execution begins. Risks that are associated to CTQ factors are assessed to determine if they can be eliminated or sufficiently reduced. For those risks that cannot be eliminated or reduced, mitigation plans are established. For example, if the primary study endpoint is associated with a laboratory sample collection, the risks associated with collection of samples cannot be eliminated. Therefore, the associated risks should be effectively managed to reduce the risk to subject safety and ensure data quality. As mitigation strategies are established, detection mechanisms are determined to quickly identify if the established mitigation strategies are effective.

	One method to monitor mitigation plans is via KPIs, KRIs, and QTLs. KRIs are metric indicators of the quality of study conduct in specific targeted areas. QTLs, introduced within ICH E6 (R2), “should be established, taking into consideration the medical and statistical characteristics of the variables as well as the statistical design of the trial, to identify systematic issues that can impact subject safety or reliability of trial results.”

 Detection of deviations from the predefined QTLs should trigger an evaluation to determine if action is needed. In this context, it is important for clinical trial teams to regularly analyze and properly align trial-specific KRIs and QTLs. These activities support continuous clinical trial quality improvement as well as driving focused decision-making communication and actions.

	A method of communication that reinforces CTQ factors is regular project team meetings. These meetings should be held in conjunction with dedicated cross-functional risk review meetings and become frequent quality check-ins for analyzing KPIs, KRIs, and QTLs to assess if established mitigation strategies remain effective and if existing or new risks are emerging (see Figure 1; click to enlarge).

	Following a continuous process improvement model, such as those of Six Sigma, Lean, and Total Quality Management, ongoing improvement is achieved through incremental and breakthrough improvements. As demonstrated within Figure 2, the more often the project team evaluates performance based upon established parameters (KPIs, KRIs, and QTLs), the greater the resulting quality becomes.

	Coinciding with continuous process improvement is documentation to recreate the environment present when key decisions were made and what specific actions were taken as a result. These activities support ICH E6 (R2) recommendations for sponsor oversight and are included within the risk management section of the clinical study report. An example of questions project teams should consider when evaluating process improvement are:

		What are the downstream actions caused by the findings?

		Does the project team have evidence of study team members changing processes?

		Can the project team demonstrate they’ve made meaningful change?

	As demonstrated within this article, KPIs, KRIs, and QTLs provide an opportunity to proactively communicate CTQ factors and risk mitigation activities to support ongoing sponsor oversight activities across vendors throughout the clinical study life cycle.

 is Director of Risk-Based Monitoring, PPD; 

is Executive Director of Centralized Services, PPD

	1. International Council for Harmonization. 2016. Integrated Addendum to ICH E6(R1): Guideline for Good Clinical Practice E6(R2), 

www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Efficacy/E6/E6_R2__Step_4_2016_1109.pdf

	2. General Consideration for Clinical Studies E8(R1) Draft version Endorsed on May 8.  2019, 

https://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Efficacy/E8/E8-R1EWG_Step2_DraftGuideline_2019_0508.pdf

Articles

Amid the recently released ICH E8 (R1) draft guidelines further supporting RBM strategies, practical methods for integrating critical-to-quality (CTQ) factors within the operational execution life cycle of a clinical trial are presented. 

Risk-Based Quality Management: The Importance of Risk Communication

With recent reports noting that R&D returns in the biopharmaceutical industry have fallen to their lowest levels in nine years,

 life sciences companies need to evaluate the current R&D model and the way clinical trials are designed and implemented. One possible innovation to enhance R&D efficiency is master protocol studies. In FDA draft guidance issued in October 2018, a master protocol is defined as “a protocol designed with multiple sub-studies, which may have different objectives and involves coordinated efforts to evaluate one or more investigational drugs in one or more disease subtypes within the overall trial structure.”

	Common types of master protocol studies include:

		Basket trials, a single investigational drug or a drug combination in multiple disease populations.

		Umbrella trials, which include multiple investigational drugs in a single disease population.

		Other trial designs that may include a combination of design features both of basket and umbrella trials.

	Master protocol studies can provide potential opportunities to shorten R&D timelines, reduce R&D costs, and improve the probability of success-if designed and implemented properly. The uniqueness of the master protocol design is that it starts from a more open beginning and gradually adjusts the design to the direction where there is a higher probability of success. For instance, adding new treatment arms, changing the standard of care arm, adding or removing disease populations, and changing eligibility criteria. These are achieved by utilizing more frequent interim data reviews and decision-making that relies significantly on data currency and data quality. However, the master protocol design has dramatically increased implementation complexities because of the frequent substantial protocol amendments and/or protocol adaptations. As a result, the questions about what, why, when, where, who, and how have become critical to answer.

	Master protocol studies usually are large global studies and involve numerous countries and investigational sites that have different requirements and processes for reviewing protocols. The sites also have different processes and systems in place for patient data, labs, contracts, finance, etc. Besides sponsors and contract research organizations (CROs), many vendors are used in the study for clinical supplies, lab sample processing and analysis, and imaging data review. Sponsors, CROs, and vendors also use many different systems for data capture and analysis. Because of the numerous entities involved, these processes and systems may have significant data overlap and lack the necessary integration.

	A master protocol study can constantly change. It is reflected in the downstream work activities conducted by various parties, including regulatory affairs, ethics committees, institutional review boards (IRBs), sponsors, CROs, vendors, and sites, all of which ultimately impact the patient. In the current R&D model, all of these activities are performed by different companies and organizations using different processes and systems. As a result, interoperability needs to be assessed, with protocol development and any amendments handled by the sponsor or a sponsor-contracted company or consultant.

	To ensure data consistency and an integrated process flow, various process plans, data transfers, and reconciliation agreements are established, which takes significant time and effort to develop and implement at the start-up stage of a trial. In a master protocol study, the development and setup activities need to be conducted again whenever there is a protocol amendment and adaptation that impact the critical process and data identification. That can make it even more challenging than at the initial setup because enrollment is ongoing, and/or a high number of patients are still active in the study.

	Compared to a master protocol study’s innate flexibility and adaptability, a traditional protocol model can seem inflexible, slow, and unclear. In this context, an orchestrated cross-functional, risk-based approach to implement master protocol studies address many of the concerns with a traditional study methodology. The principles established within ICH E6 (R2) provide opportunities to effectively address these challenges, while ensuring human subject protection and reliability of trial data are maintained throughout the life cycle of the clinical trial.

	The implementation of a master protocol study starts with the development of a sound integrated quality and risk management plan (IQRMP) to de-risk the complexity by answering the questions about what, why, when, where, who, and how in relation to an evolving protocol. The IQRMP defines the actions each functional group and party will take to proactively identify, assess, and manage risk throughout the life of the master protocol and each sub-study. As important as predefined actions are to identified risks, an IQRMP also should have the agility and flexibility to adapt to the speed and frequency of the changes with master protocols since it’s impossible to foresee all the risks when the study is initiated. Therefore, rather than trying to predict a fixed future, the IQRMP serves as a tool to understand the data that will be available at each point to make real-time decisions as the study evolves.

	The initial step in the development of an IQRMP is the risk assessment using an instrument such as the risk assessment categorization tool (RACT). The RACT requires the identification of critical process and data identification based upon the protocol and its endpoints and objectives. Those evaluations will evolve as the protocol design advances and connects with functional oversight plans, processes, and systems residing with various parties and stakeholders. This creates an ideal venue to orchestrate the cross-functional and cross-party changes using a risk-based approach. The risk assessment process also ensures that ongoing risk reviews are performed throughout the life cycle of the study.

	These regular reviews offer an opportunity for orchestrated and cross-functional engagement to safeguard important protocol direction decisions with ongoing risk reviews and mitigations. Due to the complexity of master protocol design, it can be valuable to separate out each sub-study from the master protocol while critical processes and data identification are collected as a component of the risk assessment. Once risks are identified for each sub-study, the data is consolidated to identify similarities and prioritize those risks that bring greatest impact to the overall master protocol. Another approach is to “break” the protocol based on what is certain and what is subject to change, then identify the associated critical data and processes according to these “time zones” to help prioritize, while remaining agile and flexible.

	Addressing challenges: Centralized monitoring, RBM

	As previously noted, to achieve the purpose of a master protocol study, data must be entered and cleaned in a timely manner. Data currency and quality directly impact the timeliness and quality of these important study direction decisions as well as the trial’s overall success. However, it’s extremely challenging to maintain high data currency and quality in such fast-paced, complex, large global studies. To help address the related challenges, ICH E6 (R2) allows for varied approaches with a focus on centralized monitoring.

	Centralized monitoring is valuable for master protocol studies due to the speed of study execution, the frequent study adaptations and amendments, and the scope of changes in study implementation. Potential data integrity and subject safety concerns must be identified and investigated promptly. Centralized monitoring, inclusive of advanced data analytics, allows for large volumes of data to be reviewed more quickly than the traditional 100% onsite source data verification (SDV) monitoring approach. Focused, targeted monitoring activities can promptly identify data anomalies for additional root cause analysis and corrective actions by clinical research associates (CRAs).

	A risk-based monitoring (RBM) approach also brings enhanced quality control to master protocols via the use of key risk indicators (KRIs). KRIs are alerts at specific sites, or at the study level, in the form of atypical patterns of data that indicate potential risks related to the conduct of the study to ensure the defined risk-mitigation techniques are effective. Establishing these alerts in a master protocol study provide a just-in-time mechanism to identify the signals and trigger appropriate action plans. Due to the constantly changing nature of master protocol studies, it’s also important to ensure agility and flexibility are built into the KRIs and reviewed at more frequent intervals than traditional protocol designs. These RBM approaches help to align precious time and resources more intelligently in accordance with the evolving protocol design and ongoing risk assessment.

	The protocol’s path: Continuous navigation

	In the evolving journey of the master protocol study, from its initial version to its final iteration, there are many interim timepoints at which data is reviewed and protocol direction decisions are made. An orchestrated risk-based model provides opportunities at these timepoints to establish cross-functional engagement and safeguard these important protocol direction decisions. Its structured framework embedded in the life cycle of the study helps de-risk the inherent protocol complexity and navigate changes. This model provides clarity to the earlier questions about what, why, when, where, who and how, and establishes a continuous model that can be reused as needed in the study duration in its full or partial version.

		“Unlocking R&D Productivity – Measuring the Return from Pharmaceutical Innovation 2018.” Deloitte Center for Health Solutions and GlobalData. 

https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/life-sciences-health-care/deloitte-uk-measuring-return-on-pharma-innovation-report-2018.pdf

		“Master Protocols: Efficient Clinical Trial Design Strategies to Expedite Development of Oncology Drugs and Biologics.” Guidance for industry, FDA. October 2018. 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/master-protocols-efficient-clinical-trial-design-strategies-expedite-development-oncology-drugs-and

 is Director, Risk-based Monitoring, PPD; 

 is Associate Director, Project Management, PPD

Using a risk-based model to navigate the inherent changes and fluctuations in master protocol studies-and help maintain data integrity throughout.

Brian Barnes

Articles

Risk-Based Quality Management: The Importance of Risk Communication

De-risking Master Protocol Implementation