Beat Widler, PhD

	Endpoint adjudication is gaining importance in the industry, however, no guidance on endpoint adjudication exists. In order to shed light on endpoint adjudication, the 

 generated an Events Charter Template for endpoint adjudication to assist those in need of guidance.

	The Adjudication Committee (AC) Chair and Members submit their dated signature to ensure that they have read and approved of the following Charter and its contents.

2. Study Abstract/Proposal/Introduction Page

	Description of the Clinical Trial related to Adjudication, Study objectives (primary, secondary, exploratory) and the rationale behind the Endpoints Assessments adoption.

	The objective of an adjudication is that a well-recognized group of experts in the area of the <study indication> confirms that an event took place and that for each event it fulfills the per protocol definitions. The members of the committee are not participating in the trial as principal or coinvestigators and their review ensure well reported, unbiased, blinded to treatment, count of events. When an adjudicator also participates - directly or indirectly - in the study, due diligence needs to be in place by the sponsor to avoid either adjudication of self-reports and unintentional unblinding of that adjudicator. The process should take place on a continuous timely fashion. Source documents need to be submitted on time together with the report shortly thereafter.

	The Adjudication Committee is responsible for reviewing each event as defined in the protocol. Their work is independent and impartial. Such type of review is to ensure accurate counting, assessing, rating, etc. of protocol defined "events".

	Unless defined by the Charter and supported by the composition of the Committee review of safety signals or of benefit - risk assessments are out of the scope of the Adjudication Committee.

	Identification of the Committee Chair along with his/her required expertise and related experiences should be described in detail. Roles and responsibilities of the Committee Chair should be described.

	The chair should as a minimum write/update or, respectively, oversee writing/updating the Charter and the decision rules. S/he chairs the Adjudication Committee meetings, arbitrates, documents, reviews and approves meeting minutes, decisions and results, and communicates with the sponsor/Steering Committee and clinical sites, as appropriate.

	The Charter will include a list of the Adjudication Committee Members including their contact information (work address, telephone number, fax number or email address), credentials and experience qualifying them for their assigned role(s). Adjudication Committee members will sign a potential conflict of interests declaration.

	The roles of the Adjudication Members are to be summarized, including their responsibilities throughout the course of the clinical trial, timelines, and participation in the Adjudication Committee meetings.
	
	Procedures are to be in place in the event that it is necessary to replace a Committee Member. The Charter keeps on file the reasons for replacing an Adjudication Committee member, such as inadequate performance and lack of communication with other members, lack of participation in consensus meetings, or inability to meet the responsibilities detailed in the Charter. Decision and communication are to be kept internal but are made available to auditors and regulatory inspectors.

	An adequate description of the training processes for new members of the Committee to adjudicate clinical endpoints will include how system access controls and blinding of reviewers will be addressed. Training will include processes, provisions and measures to prevent intentional or unintentional unblinding of trial participants/data.

	A description of the Endpoint Adjudication software to be used throughout the life-cycle of the clinical trial including how systems' security (user ID, electronic signature, passwords to access), customization, and validation controls have been addressed.

	This section is to include the following elements:

		Endpoint definition(s); what constitutes an endpoint, methods of endpoint identification.

Note: an event can be an endpoint (e.g., classification of the severity of a cardiac event) or a measurement of a tracing (e.g., ECG) or an image (e.g., tumor size). In the following the term event will be used to describe both types of adjudication processes/tasks.

		Is the event a primary or secondary endpoint.

		What are the event sources, on what source documents will the Adjudication Committee deliberate.

		Event identification codes for making the events anonymous.

		Blinding provisions to clinical trial center team members and sponsors.

		Management of participants' identifiers and relation to allocation of treatment.

		A statement that adjudication of an event where the rater had any involvement is nullified.

		If used, the process for post-hoc analyses or data re-analysis using an adjudication process and how this will be managed within the study planning.

		The use of an adjudicated result will be clarified as to whether this is planned as the primary data analysis, is concurrent and in addition to or separate from analysis and publication of primary results or original results (such as intent-to-treat).

		Adjudication committee members' roles in authorship or acknowledgment in a publication is to be pre-specified and defined in the Adjudication Committee Charter.

	The Assessment process consists of the following steps:

		Description of the event submission procedure and rules applied for assignment to a specific reviewer.

		Provisions made to avoid adjudication of self-events.

		The coordinating center will ensure that each event is complete as a package including the reporting CRF and all relevant supporting source documents. This can be a paper or an electronic process. Packages are to reach the designated adjudicators independently via courier/or/electronic password protected workflows. Adjudicators might send back their decisions also by courier or register themselves in the electronic "adjudication space" especially created for that.

		The workflow shall include a process by which the rater can ask for additional information/data, e.g., a request form for the adjudicator to request. The complete package would then consist of all original information/data plus the supplemental information/documents/data).

		The workflow may support the raters with automated edit checks, fill-in instructions.

		Description of the procedures to handle Disagreements among Reviewers.

		Classification of disagreement (example: major or minor, event or not event) and respective resolution procedures. As mentioned in paragraph 8.1, if in doubt the rater needs to request more information to make an unequivocal decision.

		When a site re-submits an event and this has not been adjudicated yet, only the resubmission goes to adjudication.

		When the re-submitted event has been already adjudicated, the last information should be reanalyzed anew and the re-adjudication result superseeds any prior adjudication.

		The Chair can review the entire reporting, if deemed necessary.

	The following are examples of deliverables of the Adjudication Process:

		Format and content of the Adjudication Assessment Report by rater and consolidated finalized Adjudication Assessment Report as well as any periodic/final summary reports.

		Format of data and meta-data transfers/exports, e.g., as SAS, XML or other formats.

		Statement of preservation of blindness of sponsor and clinical trial center staff members, if applicable.

	A list of people involved in the adjudication process with their respective role (e.g., Adjudication Coordinator, Chair of the Adjudication Committee, Adjudication Committee Member), their responsibility and contact information will be maintained.

 is maintained to define upfront the following scenarios/requirements:

		Description of the situations that trigger an exchange of communication between sponsor staff and Committee Members, between Committee members, etc.

		It is recommended to develop and use communication templates such as standard meeting teleconference agendas and minutes that is as standard agenda items topics that are of particular importance to the adjudication process.

		The Adjudication status will be tracked by means of periodical reports, and according to the needs of the study, indicating, for example, how many of the total reported events have been adjudicated, how many were reported but are not complete yet, and number of refuted  from the completed ones.

	A description and flowchart of the Endpoint Assessment Standard Procedures and Workflows should be prepared upfront and these should take into consideration key study milestones such as submission and assessment timelines as well as any other milestones defined in the trial protocol.

	The sponsor's coordinator should actively manage these timelines and ensure that the adjudication process runs according to the agreed plan and, where required, issue reminders to the adjudication committee members.

13. Quality Control: Data Sources, Procedures, Analysis

	A complete list of data sources and their specified format is to be defined, for example the following aspects should be addressed:

		Data points where the CRF is the source of the entry, i.e., CRF is the source document.

		Option of .pdf upload of scanned data forms or .pdf upload of medical record elements, upload of CT or MRI imaging

		Roles and responsibilities in transferring adjudication information/assessments into the CRF or clinical database, i.e., is information related to adjudication entered into the CRF, a separate document, a separate data collection platform. Who performs these data entry tasks: sponsor representatives, adjudicators or who else.

		It is recommended to define media involved in the adjudication process (either as data capture or storage media), roles and responsibilities in entering data onto these media in a matrix table identifying explicit roles and accountabilities.

Articles

Endpoint adjudication is gaining importance in pharma today, however, no guidance on endpoint adjudication currently exists. The LinkedIn Endpoint Adjudication Community has generated an Events Charter Template to shed light on the subject for those in need of guidance.

Endpoint Adjudication of Events Charter Template: What Should Be Included?

About a year ago, TransCelerate began working on a clinical trial Quality Management Systems (QMS) initiative, and 

. TransCelerate recently published a few articles in the Therapeutic Innovation & Regulatory Science journal (DIA), with 

one publication specifically focusing on issues management in quality management systems

. In this Applied Clinical Trials article, we will summarize our interpretation of the findings from the DIA publication, and analyze the publication, and evaluate potential issues during QMS framework implementation. 	 	

	 	According to the authors, good QMSs define Key Risk and Performance Indicators (KPIs/KRIs), established documentation systems based on risk levels that are based on data, proper notification systems and plans, corrective and preventative action (CAPA) initiation and resolution capabilities, and analytics to track improvements in the QMS

.	 	The authors introduced another concept that seems to expand on 

TransCelerate’s definition of critical data

: triaging ‘issues that matter’ (i.e., problems that impact data integrity, patient rights and safety, confidence in ethical clinical trial conduct, and regulatory requirements

). By filtering issues that matter from issues that don’t, sponsors can enhance and optimize resource utilization and allocation during clinical program administration. Moreover, this model allows managers to quantify studies that exhibit high levels of risk based on issue category frequencies.	 	

	 	Another directive introduced in the publication involves pinpointing the issue, and preventing reoccurrence. Study teams must conduct a thorough root cause analysis, which requires setting proper documentation and impact analysis procedures on patient safety and data integrity assessments, and exercising investigative analysis to uncover other areas of impact.	 	The authors argue that while the intention of CAPAs are to eliminate issues that matter, the activity is insufficient without a ‘CAPA effectiveness check

,’ which basically ensures CAPA resolution and measuring its impact on eliminating issues that matter.	 	

	 	Another concept introduced in the article involves the ability to incorporate clinical IT systems to enhance QMS oversight. For example, incorporating the planning, and execution of the QMS through technology-based workflows and forms allow management to collect data, generate visualizations to better pinpoint the types of issues that arise, and evaluate the effectiveness of the QMS over time.	 	Additionally, the incorporation of workflows through clinical IT systems empower management to assign stakeholders, which allows for accountability, bottleneck identification, and stakeholder performance assessments

	 	The authors write that TransCelerate is developing tools to support the above process. Further clarifications of the process are certainly needed. For instance, the publication does not give any definitions on how to perform the triage on the basis of objective criteria and not subjective assessments. Moreover, the term ‘materially impact’ needs a clear definition. The three examples provided on Page 2 of the publication are all severe, however, they are not comparable in their nature: to elaborate, in two cases, a grave mistake has already been made (informed consent issue, and the changes in the database) whereas in the other example, there have not been any negative consequences for patients and data, even though not sending the Serious Unexpected Adverse Reactions (SUSARs) to the sites is a grave mistake.	 	In addition, to standardize the Root Cause Analysis and the use of Clinical IT in issues management processes, more details about the processes need to be provided and guidance should go beyond the examples that have been offered.	 	Furthermore, the proposed QMS infrastructure does not consider incorporating self-improving QMSs through the use of clinical technology at study sites. One of the largest investment assets in clinical trials is operationalizing the study site. Incorporating quality feedback systems (fueled by clinical technology) that enhances communications between Sponsors and sites, facilitate site staff to automatically resolve quality issues as they arise, rather than depending on one-off engagements with CRAs. Moreover, a self-improving QMS not only saves a tremendous amount of resources, but it also enables the Sponsor to ameliorate quality oversight, and extends stakeholder accountability all the way down to site personnel.	 	Finally, the important area of vendor oversight is not addressed at all. Deficiencies in vendor oversight often lead to compliance issues and is now becoming both FDA and EMA inspector priorities. 	 	

	 	While the publication has proposed a solid and comprehensive issues management methodology via a QMS, there are general complications that sponsors must consider during execution. Specifically, defining and interpreting KPIs/KRIs can result in reporting inaccuracies, or misfires that would impact the quality of management analytics and visualizations of the QMS program. For example, Sharon Reinhard, President of Clinical Compliance indicated 

 that issues interpretation varies vastly when a CRA looks at an issue versus an auditor; 

a CRA can completely miss a protocol violation, whereas an auditor would capture it by questioning unusual data during an audit

. Accordingly, it could be a challenge to properly quantify clinical program risk due to the subjective nature of GCP, and ‘issues that matter’ interpretation.	 	

	 	The TransCelerate paper offers plenty of robust discussion on issues management, however, the process needs to include specific details and enhanced methodologies in order to comprehensively cover all aspects of a solid QMS. We are excited to see how the TransCelerate tools will develop.	 	Moe Alsumidaie, is a regular contributor to and member of 

 Editorial Advisory Board. Beat Widler, PhD, and Peter Schiemann, PhD are Managing Partners at Widler & Schiemann Ltd.	 	 	

		Susan Callery-D’Amico, BSN, RN, Leslie M. Sam, BA, Timothy H. Grey, BS, and Daniel J. Greenwood, MS 

TransCelerate’s Clinical Quality Management System: Issue Management 

Available at http://dij.sagepub.com/content/early/2016/07/21/2168479016657129.full.pdf?ijkey=zz1ebAKYemDCZXQ&keytype=infinite. Accessed September 6, 2016.

TransCelerates work on their clinical trial Quality Management Systems (QMS) initiative began about one year ago. This article summarizes findings from a recent DIA publication about the initiative and evaluates potential issues during QMS framework implementation.

Discussion on TransCelerate’s QMS Initiative

	The biopharmaceutical industry is starting to adopt TransCelerate’s Risk Assessment Categorization Tool (RACT) in order to identify risks and plan a comprehensive clinical trial risk mitigation strategy. We recently wrote about the 

, and the advantages of using such systems. Some of these advantages include the ability for study teams to evaluate R&D portfolio risks by collecting and analyzing RACT data in aggregate. In this article, we will leverage industry-wide RACT data (provided by Cyntegrity) to see what are the most common study-related risks that people choose. 

	In October 2015, Cyntegrity launched @RACT, a free cloud-based RACT tool that has been deployed across the industry. Over the span of seven months, the @RACT database collected 2,185 RACT data points from 28 RACTs from about 20 small and large pharmaceutical companies. It is important to emphasize that this data cannot be used as a reference for a particular trial, it demonstrates only the global trends in risk assessments, and may not truly represent actual study risks; it is highly advisable for study teams to evaluate their own study risks by completing their own RACTs.
	 

	If you are new to the RACT, the tool essentially analyzes risk from 13 categories (Figure 1), and helps study teams uncover critical study risks in a simple, structured, and standardized way.

	Study teams are required to assess Impact, Probability and Detectability measures from a variety of questions from each category in the RACT, in order to generate a risk score for that category. Figure 2 demonstrates that clinical trial Endpoints, Complexity, and Blinding posed the highest risk scores (in red) compared to other categories.

	Factors impacting Study Endpoints include endpoint data collection methods, and whether the study is event or outcome driven. Factors affecting Study Complexity include uncommon procedures beyond usual standard of care, subject burden, Adverse Events (AEs) requiring adjudication, and the number of sites and subjects. Factors impacting Blinding involve blinding setup, assignments, where blinded IP is created, and risk of unblinding.

Patterns with Probability, Detectability and Impact

	The rating system of the RACT requires study teams to categorize risk in each of the questions by Probability (how likely a risk is going to happen), Detectability (how easy it is to detect a risk), and Impact (extent of damage/consequences of a materialized risk).

	Figure 3 illustrates the effect of Probability, Detectability and Impact (risk measures) on average risk scores. Figure 3 shows that Probability has the highest impact on risk scores. However, it is important to delineate two observations; (a) each risk measure has a different effect on risk scores; for example, Low Probability is associated with the lowest average risk score, and vice versa for High Probability, and (b) the slopes differ for each risk measure.

	Analytical trends with this phenomenon introduces variability in risk score measurement, and this might be explained by the notion that the structure of RACT design suggests subjectivity in its assessments by allowing study teams to come to their own conclusions and interpretations of certain risks in specific risk categories.

	One weakness of the RACT is that many answers to the questions are left to the judgment of the individual and if you have two different teams complete the RACT on the same study, you would most likely get two different risk assessment outcomes.

	TransCelerate’s RACT was initially developed with the intention for study teams to identify risks at the beginning, or during study set up and during study conduct. RACT was designed with project management requirements in mind, as the categories are focused primarily on study operations. This approach is not wrong, however, it is easy to lose focus on the requirements of a risk assessment that regulators would want to see. To elaborate, when one looks at the safety section, it is clearly visible that the authors have given this a lot of thought, nevertheless, essential questions are missing, such as, "does the protocol contain clear definitions of adverse events and clear guidance on safety reporting?" or "how often does the study team plan to reconcile the clinical trial database against the serious adverse event database?" In addition, no quantitative reference is asked for but assessments are made on the basis of merely subjective – team driven – criteria. Further, questions about disclosure are missing.

	There are more examples, which show that project management requirements regarding timelines, meeting endpoints and budget were drivers of this RACT design rather than compliance. Nonetheless, the structured risk assessment does cover many aspects of compliance pertaining to data integrity and patient safety.

	An initiative that can standardize risk assessments (integrated into @RACT), was developed by PPH plus (questionnaire “RACT plus”), which includes tangible criteria on better defining Impact, Probability and Detectability for each of questions in RACT. This clarification tool is aimed to reduce subjectivity during the risk evaluation.

	Moreover, it is important to consider including fixed analytical weights to each question and category, since certain categories are always more important than others. However, leaving RACT scoring and weighting up to individual teams opens the door to inconsistency and hampers protocol / project to protocol / project reproducibility. Henceforth, the most consistent way for weighting may involve linking the weights to historical successes and failures for each trial, retrospectively. Cloud-based solutions enhance the ability to conduct aggregate assessments.

	In summary, RACT provides the first essential step towards the standardization of risk assessments in clinical trials. However, the analysis in this article demonstrates that the structure of RACT questions infers subjectivity. 

	Standardized criteria for defining “low”, “medium” and “high” for each risk measure, “Impact”, “Probability” and “Detectability” in the assessments as well as fixed analytical weighting can enhance the consistency of risk assessment outcomes.

	While the global risk assessment trend demonstrates that study personnel tend to give higher risk assessment scores to categories, such as “Endpoints” and “Complexity,” and “Blinding,” these risk categories may not properly reflect actual study risks due to subjectivity, and more data is needed in order to see consistency in categorical trends. 

	On the way to future perfection, it is important for the industry to evaluate risks that regulators pay particular attention to, such as disclosure, safety reporting, and clarifying AE detection. In addition, a section on outsourcing and vendor oversight would be a reasonable addition, as well as ethics and regulatory questions.

	While the RACT has created advancements in allowing study teams to interpret risk, it still has a long way to go and needs to undergo continuous transformation and real-world testing in order to generate consistency in identifying study risk outcomes. 

The biopharmaceutical industry is starting to adopt TransCelerate’s Risk Assessment Categorization Tool (RACT) in order to identify risks and plan a comprehensive clinical trial risk mitigation strategy. We recently wrote about the RACT moving to the cloud, and the advantages of using such systems. Some of these advantages include the ability for study teams to evaluate R&D portfolio risks by collecting and analyzing RACT data in aggregate.

Data from Global RACT Analysis Reveals Subjectivity

	GCP Addendum Review and Embracement Plan

	The new upcoming GCP E6 (R2) addendum has the potential to reform clinical monitoring and clinical trial management. What changes does it bring to all of us? What does this mean for a pharmaceutical company, for a Contract Research Organization (CRO) and for an investigator in terms of changes to the processes of trial oversight, data collection and reporting and trial design and planning? In this article, you will find a structured summary and critical review of the new addendum, and as well as ideas on how to prepare for these regulatory changes.

	“When the facts change, I change my mind,” Winston Churchill once said. When regulations change, it can change how people think across the entire industry. This article intends to systematize and critically comment on the primary new topics addressed in the ICH GCP addendum (GCPA) E6 (R2).

	The revision of the International Conference on Harmonization (ICH) Good Clinical Practice (GCP) guideline, and specifically its addendum E6 (R2), will presumably take effect in 2016. Industry experts already refer to it as an important milestone in driving adoption of Quality-by-Design and Quality Risk Management principles and methodologies in clinical development. The ICH Expert Working Group has decided to update the guideline, which has remained unchanged for 19 years. Since the last revision of the guideline, the environment in clinical trials has fundamentally changed. A few technological changes that were unknown or in their infancy when the E6 Guidelines were issued include: the Internet, smart phones, electronic data capture, real time review of clinical data, drug development as a truly global enterprise, etc. Technology progress is, however, counterbalanced by growing complexity and costs of clinical trials, creating pressure on sponsors – academic and commercial – whilst ethical and quality standards have become stricter. The regulatory environment for conducting clinical trials has not become any easier since the initial rollout of ICH GCP. Moreover, drug development is a global endeavor, requiring progressively greater division of tasks across multiple functional teams, organizations and locations. On the positive side for sponsors, evolving technology offers new opportunities. The new GCPA takes this evolution of technology into consideration and encourages sponsors to pursue innovative approaches for conducting clinical trials. Quality-by-design and risk-based quality management are now recommended as approaches of choice to sponsors of clinical trials. Additionally, the GCPA defines standards and procedures for the use of IT tools, as well as for the management of electronic records and essential documents.

	The new regulatory document adds new concepts to the existing current ICH GCP guideline. The addendum states the need for many well-established processes in order to align the GCP with reality (e.g., validation of computerized systems or centralized monitoring), in addition to adjusting and modernizing well-known processes and procedures such as clinical trial oversight. Despite the wide range of topics, the goal of the new addendum remains concise:

“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 data integrity.”

	Let us start our review with the sponsors’ responsibilities. Three main roles and responsibilities have been identified:

	The topic that was expanded upon the most in the GCPA document was quality management. GCPA fully embraces the quality-by-design and risk-based approaches. Quality Management (QM) hinges on the quality-by-design concept, which infers that the quality of a clinical trial must be ensured through careful and fact-driven planning. Efficient and effective trial designs must be supported by tools and processes that leverage past experience, real-life data, and so on, in order to eliminate from study protocols requirements (e.g., inclusion and exclusion criteria) and study procedures that are not realistic and would become the root cause of poor protocol compliance by investigators, in addition to eliminating avoidable protocol amendments.

	In the new GCPA, it is stated for the first time in the context of ICH GCP that QM is expected to be risk-based. The risk-based approach should be applied to QC/monitoring, as well as to QA/auditing tasks. The concept of risk identification and prioritization is the “logical thread” throughout the GCPA document to make clinical trial activities more focused on important clinical risks. The risk-based approach is based on the following criteria:

			Critical process and data identification

	The analytic part of risk evaluation occurs with the help of the three main risk properties:

 on subject’s safety, rights and data integrity and reliability

– extent to which such threats or errors are detectable

 The steps of risk control listed in GCPA are known from ISO 31000 (Risk Management) and now have been adapted to clinical trials. However, in the GCPA, reference is made to “Critical process and data identification,” which underlines the importance of clinical data as the main output of a clinical trial but does not match the “Risk Category Assessment” of the ISO norm. The motives of the ICH expert group for avoiding the risk categorization step are not clear.

	The GCPA is now incorporating terminology already used in the old ICH Quality Risk Management (Q9) guidance. According to the GCPA, quality management now includes:

			“Efficient design” of a trial, and thus delivering a strong message that many clinical trials are overcomplicating its design and reducing its efficiency. These problems are also mentioned in various publications (e.g. Ken Getz et al.

			Regarding data collection tools and processes, implicitly, it is advised to move away from paper-based CRFs and consistently use Electronic Data Capturing (EDC) systems for data collection.

	The call in the GCPA for capturing data electronically stems from the need to use trial information in real time to make informed decisions.

 The GCPA introduces the concept of traceability of decision-making. Collection of information is critical, but it is as important to describe and document who is defining what information is to be collected for making a decision, what level of accuracy needs to be reached, and how decisions are based on facts – a decision matrix rather than an individual or team’s subjective judgment. Along these lines, sponsors have to decide what minimum information is required to make an informed decision and how decisions will be reached on the basis of objective and verifiable facts and criteria. In addition, key decisions depend on the levels of risk that a sponsor is willing to tolerate. Risk levels should again be based on objective and verifiable criteria and not on “opinions”. Such limits will determine how and when alerts or risk communication must be triggered.

	Remarkably, the GCPA states the need to utilize lessons learned to optimize quality management in clinical studies by means of a risk review. This is not a new process but it has been mentioned for the first time in a regulatory document related to clinical trials. Drug developers must be aware that the risk-based approach cannot follow the pattern “get it done and forget”. It rather requires continuous improvement of each quality management process at the sponsor’s organizational level, as well as that of a clinical trial.

 is identified as a cornerstone of GCP and this concept is prominently discussed in the Monitoring and Data Handling sub-sections of the Quality Management chapter. GCPA emphasizes that whenever there is a change in the design, operations or set-up of a clinical trial or in a supporting process or system, data integrity aspects must be carefully assessed and possible risks minimized.

	The GCPA also identifies the role of training and SOPs as key elements of any QM system. Therefore, the on- boarding of a team and the training on a system and process are defined as requirements:

 “SOPs should cover system setup, installation and use, system validation and functionality, security, change control, data backup, recovery, contingency planning and decommissioning.”

	The part of clinical research process that will need to be significantly adjusted is monitoring. In the GCPA, the nature of monitoring is defined more clearly:

“The sponsor should develop a systematic, prioritized, risk-based approach to monitoring clinical trials. (…) A combination of onsite and centralized monitoring activities may be appropriate. The sponsor should document the rationale for the chosen monitoring strategy.”

	GCPA sets the standards defined in the FDA and EMA guidance concerning RbM and risk management.

 It is not surprising that the authors of GCPA have chosen a rather vague way to describe the combination of onsite and centralized monitoring activities. They state that such a combination “may be appropriate” without giving more detail or guidance related to what extent this combination is right and if this combination is needed at all. Indeed, a risk-based approach cannot be served by a “one size fits all” approach and regulators’ acknowledgement is welcomed regarding the sponsor’s responsibility to determine the optimal approach to study oversight and not mandate any given strategy.

	Taking into account that the rationale of the chosen monitoring strategy should be documented, the ICH assumes that every sponsor would know the advantages of this or the other monitoring strategy and will be able to choose the right levels of application of these strategies. This is not always the case. In this sense, the FDA Guidance for Industry Oversight of Clinical Investigations

 describes in more detail what techniques relative to the verification of informed consent, site records, and source data require a higher or lower extent of onsite and centralized monitoring. The implementation of risk-based monitoring (RBM), with the consequent adjustment or reduction of onsite monitoring visits and source data verification (SDV), can only succeed after establishing an appropriate risk-based QM system. The monitoring management team should know and understand the rationale for use of the chosen monitoring method. The monitoring strategy cannot be risk-based if risk management does not exist. The authors of the GCPA included a stern warning: regulators will not accept onsite monitoring reduction under the pretext of RBM without demonstrating on how oversight is exercised. A common pitfall relative to this is an RBM approach that is neither holistic nor data driven.

	As a part of RBM, centralized monitoring is defined as 

"the remote evaluation of ongoing and/or cumulative data collected from trial sites, in a timely manner."

	Here, it is important to keep in mind that the outcome of any verification through centralized monitoring processes and tools should be reported and documented as to its nature and impact – together with any corrective and/or preventive actions taken – like any other monitoring activity. What does this mean for a sponsor? Mostly, it means that the findings, decisions, and actions resulting from any centralized monitoring process should be captured, audited and archived throughout a trial. In addition, because of its systematized and repetitive nature, assessments of centralized monitoring reports and actions taken on the basis of these should be based on objective decision-making criteria and not left to the discretion of an individual.

 If the decision is left to an individual – as competent as the person may be – the risk is that the same observation or “signal” is considered to be acceptable in one case but not in other cases. When this happens, centralized monitoring approaches do not lead to better oversight but add a quality and compliance risk because decisions are made in a haphazard manner.

	As the main tools for centralized monitoring, ICH experts advise routine review and statistical analyses. Routine review infers identification of missing data, inconsistent data, data outliers or unexpected lack of variability and protocol deviations. Such detection allows for identifying significant errors during data collection, such as data manipulation or integrity problems, or inconsistent data collection practices, such as rounding-up/down of values.

	The application of statistical methods for identification of data trends, such as the range and consistency of data within and across sites, has undergone significant progress in recent times. There are companies offering RBM platforms for such analyses. According to GCPA, two main objectives could be achieved with this approach:

			Analyzing site characteristics and performance metrics

			Selection of sites and/or processes for targeted onsite monitoring

	It is not a surprise that with regard to such approaches, GCPA is aligned with the FDA’s guidance,

 which refers to targeted monitoring as a strategy of RBM.

	A monitoring process, in general, and a monitoring plan, in particular, should be “tailored to the specific human subject protection” priorities, guarantee data integrity, and include actions preventing risks to patients and data integrity that might materialize in a clinical trial. Monitoring plans and reports are interrelated. A report should contain sufficient detail to allow for verification and documentation thereof, so that all measures of verification and actions laid down in the monitoring plan have been complied with.

	Since all monitoring activities should be traceable and documented, the adjustment of monitoring reports to a risk-based approach might not be simple. Apart from the systematized recording of monitoring activities, the automatization of reporting procedures and related communication systems, including issue escalation, must not be overlooked. Prioritization of data to be included in monitoring reports must be aligned with the criticality of the monitored processes and data.

	Concerning Contract Research Organization (CRO) oversight, GCPA is very concise, only defining it as a sponsor responsibility.

“The sponsor should ensure oversight of any trial-related duties and functions carried out on its behalf.”

 Rightly, GCPA does not mandate how oversight of third parties must be exercised; however, more detail about minimum elements and actions of oversight would also be useful from a public perception perspective. Recently, the media have given the impression that sponsors walk away from their responsibilities by transferring clinical trial tasks to CROs, and more clarity about minimum oversight responsibilities could help to correct such perceptions. For instance, clarification about the following aspects would be welcome:

			Are regular self-reports by the CRO enough or should there be a deeper look into the CRO’s trial activities?

			How should one act when a CRO does not fully disclose the nature of a process or the root cause of data deficiencies?

			How can an objective assessment of the work delivered by the CRO be established?

			What key performance metrics should be used?

			How do the sponsor and CROs’ QMS interact and how are the interfaces managed?

	Without any guidance or setting of minimum standards, there is a risk that different sponsors come to different conclusions, and as a result, apply different criteria. This may lead to a misconception of the sponsor’s responsibilities. The sponsor must set the rules for the sponsor–CRO interface based on clear definitions of roles, duties and procedures, including monitoring, to be followed by both organizations. Duplicated oversight efforts come at a price, so that the most efficient CRO oversight strategy must be carefully chosen based on objective criteria, such as previous CRO cooperation, e.g., the CRO’s experience with the sponsor’s procedures, systems, specific therapeutic area, quality of the CRO SOPs, etc.

	Other meaningful additions that appear in the GCPA cover computerized systems, electronic media, records, resources, non-compliance and validation of computerized systems. In the context of computerized systems, GCPA refers to validation process:

“Validation should ensure accuracy, reliability and consistent intended performance, from design until decommissioning of the system or transition to a new system.“

	In the data recording section, GCPA states that the “source document should be maintained and changes should be traceable.” GCPA states that trial data systems must ensure data integrity, particularly with changes and software updates. They are supposed to be guided with special training and, very importantly, be supported with SOPs, covering system setup, installation and use.

	Investigator responsibilities are described in more detail, particularly the following duties:

 – This requires the investigator to supervise those team members to whom she/he delegates study tasks and to ensure that the team members are qualified to fulfill the assigned tasks.

Source data should follow minimum quality criteria defined in the GCPA as: 

attributable, legible, contemporaneous, original, accurate, 

– Investigator should maintain a record of the location of essential documents.

	If non-compliance occurs, the sponsor must follow the following procedure:

			Initiate and execute appropriate corrective and preventive actions

			Inform regulators, where warranted by local regulations

	The GCPA requests a formal corrective action preventive action (CAPA) process for ensuring clinical trial management improvement following a case of non-compliance. Thus, quality management is boosted by quality-by-design and adaptive risk-based approaches, together with continuous improvement of the overall QM processes.

	What actions should a sponsor or CRO plan now in order to efficiently embrace the GCPA?

			Plan the change to a risk-based quality management approach for the QA and QC functions

In this article, you will find a structured summary and critical review of the new addendum, and as well as ideas on how to prepare for these regulatory changes.

ICH GCP Goes Risk Based

	In a previous article, we discussed details on how to define clinical trial data quality.  The aforementioned article emphasized that a reduction in data quality ultimately leads to enrolling more clinical trial subjects in order to maintain equivalent statistical power.  In this article, we elaborate on three categories impacting clinical trial data quality.

	Environmental factors typically relate to the protocol’s design and the scope of study visit interventions, such as devices and human methods that measure and generate study data. These study measurement origins can create levels of data variances.

	For example, measuring the circumference of a lymphedema patient’s arm with measuring tape may vary from one coordinator to another; one coordinator may measure the arm with slack in the measuring tape, whereas another may compress the tape around the patient’s arm, both of which yield variances in data measurements; this can be risky if you have more than one coordinator taking the same measurements on one patient.  Another scenario can include differing brands of imaging devices which generate varying data formats, noise frequencies and imaging quality that can be interpreted differently by a medical reviewer. 

	How to mitigate study design risks:  Think about the protocol design and how you can standardize data measurement across the study. If you plan to use a medical device to conduct study measurements, investigate the device’s standardization specifications to uncover potential differences in data quality and frequency. If the measurement technique requires human intervention, consider implementing training programs that delineate appropriate measurement techniques, and limiting the amount of coordinators taking measurements per patient.  Minimizing data variances will likely reduce the required clinical trial sample size.  

 provides an example of standardizing and managing medical device use for measuring outcomes in clinical trials.

	Have you ever asked a clinical trial patient whether excessive sweating was an adverse drug reaction?  Most likely they’ll think excessive sweating is unrelated to medical product use. According to 

an analysis of FDA’s Adverse Event Reporting System

, adverse events are largely underreported.  Additionally, T.J. Sharpe, a cancer patient said 

, “before I started participating in clinical trials, I never paid attention to or worried about reporting adverse events of FDA approved medications.”   

	Oftentimes, inexperienced clinical trial participants will neither pay attention to, nor recognize the  importance of reporting adverse drug reactions in clinical trials.  Further, the doctor-patient barrier introduces risks associated with AE noncompliance; “Healthcare professionals aren’t out there to detect adverse events, and I had issues with the dialogue between healthcare professionals,” said Sharpe.  AE noncompliance can contribute towards increasing data variances (which reduces statistical power, requiring more patients), and lead towards generating non comprehensive AE profiles.

	How to Mitigate AE Noncompliance risks: Implement communications programs with patients and their families to instruct them on how to detect and report adverse events, and to remind them about the importance of timely adverse event reporting; verifying timeliness can reduce statistical variances associated with expected AEs).  You may also want to consider establishing AE reporting systems (i.e., call in centers, or web forms), and incorporate 

WHO’s guidelines for successful AE reporting system implementations

	As much as we would like to think that patients are honest and truthful, the aforementioned comments by Sharpe demonstrate that compliance requirements in medical settings pressure patients, and they subsequently become untruthful, or exercise misconduct. For example, a patient may indicate that they adhered to investigational medical product regiments, however, patient vitals and reported outcomes data would confirm nonadherence; 30% of patients either throw out or do not take investigational medical product in clinical trials.

forget to take investigational medical  product, and double dose thinking they’re catching up, however, such activities lead to increased toxicity levels, and can result in overdose-related adverse drug reactions; coupled with patient untruthfulness, medical adjudicators can, subsequently, draw irreconcilable conclusions.  Other forms of nonadherence include a lack of patient involvement in the trial, such as not adhering to patient reported outcomes requests and not appropriately following study visit procedures. 

	Nonadherence leads to inconsistency, inconsistency leads to larger statistical variances, and subsequently, enrolling more patients.  The causes of patient nonadherence can range from mental stability/health, race and language barriers, access to transportation, financial issues, to name a few,

 but, it is important to recognize that patients are people with busy lives, and researchers should not expect patients to be 100% adherent.

	The case study above demonstrates that while communications programs can assist with improving adherence, mobile technologies cross many barriers (including cultural and language) and are proven to work.  Multinational mHealth studies in Asia, for example, have shown that regular engagement through patient mobile devices have improved medication adherence, reduced nonadherence related symptoms, and even minimized the number of nonadherence related adverse events compared to control groups in healthcare settings.

Mitigating Nonadherence with Protocol Optimization, Patient/Investigator Centricity and mHealth:  Midata Case Study

 will elaborate on how protocol optimization techniques, patient involvement and mHealth can mitigate patient nonadherence while improving data quality:

	Involve patients in clinical trials! Not just as a “patient,” but as a stakeholder and “active participant.” Ask patients to help with designing protocols that meet their needs (especially in long-term studies), make patients understand that the data they are providing will lead to better 

medicines, offer them  smart apps and other tools to support study execution, and include them in clinical trial training programs.  Involving patients may take more time, but the outcome will outweigh the time invested.

	There is an ongoing pilot that is evaluating patient involvement in trials at The Department of Neurology of the Zurich (Switzerland) University Hospital with technical support from the Swiss Federal Institute of Technology (ETH-Z, Eidgenössische Technische Hochschule) Zurich.

		The concept of this innovative approach to clinical trials involves the following main elements:

		The study protocol is written with direct patient advocacy group input to ensure patients’ priorities are addressed.

		Through this approach, advocacy groups share protocol summaries (in lay language) with prospective patients.

		If interested, patients are asked to join the Midata Cooperative – a non-profit– and consent to offering the capture of all of their trial data.

		Through the Midata platform, subsequently, patient eligibility is evaluated, and if eligible, the patient is invited to ask his/her treating physician to become an investigator.

		Sophisticated baseline assessments, such as MRIs, will be conducted at the University Clinic while routine assessments are left to the treating physician to minimize patient burden.

 patients will receive push and pull information to drive compliance to the treatment regimen and to clarify gaps or “oddities” in the clinical data.

		Real time communication between sponsor and patients is enabled through the Midata platform.  The firewalled platform is fully compliant with data privacy and protection laws and regulations, and it allows the sponsor to submit queries to anonymized trial participants, and to resolve those data discrepancies and queries without bothering the investigator with trivia while the investigator is also kept in the loop as s/he has access to the section of the Midata platform that is related to the trial.

		Centralized monitoring tools enable the sponsor to conduct data integrity assessments and verify outliers.  If gaps or discrepancies are discovered the sponsor can follow up directly with the patient, reducing investigator administrative burden.

The aforementioned article emphasized that a reduction in data quality ultimately leads to enrolling more clinical trial subjects in order to maintain equivalent statistical power.