through advances in risk-based

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1 Insight brief Quintiles is a market leader with >100 risk-based monitoring studies Quintiles developed solutions that bring as much as 25% cost reduction over traditional trial execution approaches Transform clinical development through advances in risk-based monitoring Quintiles has been delivering RBM studies across a wide variety of therapeutic areas, with numerous submissions and approvals to date Executive summary This paper shares the challenges of clinical development along with an approach to trial execution gleaned from years of executing trials with risk-based monitoring (RBM) policies and processes. This approach leverages the expertise and experience gained over years of delivery to reduce the risk of clinical trials, while improving patient safety and quality. By delivering trials more efficiently by using science, technology and global delivery, you can accelerate and expand your pipeline.

2 By reading this insight brief, you ll learn: How technology, integrated with expertise, is connecting insights to transform clinical trial execution How better design affects execution and produces better outcomes How near real-time data is providing insights for faster decision making How roles are changing for superior delivery How this approach delivers better outcomes faster and less expensively You can execute risk-based monitoring trials with greater confidence by leveraging Quintiles extensive RBM experience and best practices from years of delivering successful trials to lead the evolution and transformation of clinical development. Harness the power of risk-based monitoring to drive greater efficiency and lower costs The future of clinical trial monitoring is at a crossroads. Traditional methodologies still dominate, but a riskbased approach has emerged as the new way forward. It offers a way to facilitate more efficient trial delivery without compromising data quality or patient safety. By executing studies using risk-based monitoring policies and processes, Quintiles has developed Datadriven Trial Execution to help sponsors better mitigate a trial s highest potential risks by quickly identifying and responding to signals and trends that could affect patient safety and operational performance. Combining risk-based thinking, advanced data analytics and years of process refinement has enabled this evolution of risk-based monitoring to deliver greater efficiencies and more predictable trial outcomes at potentially lower costs. Overcoming growing challenges A risk-based approach, characterized by a clearly documented upfront and continuous risk assessment, and coupled with centralized monitoring and subject-level data review, has emerged as the future of clinical development. The approach is supported by the Food and Drug Administration (FDA), European Medicines Agency (EMA) and is consistent with industry consortium methodologies, such as TransCelerate has documented, as a new way to help mitigate potential study risks and bring efficiency and enhanced quality to clinical trial execution. Growing pressures leave biopharmaceutical companies with few options but to transform clinical development using this new approach. The industry faces familiar, and daunting, challenges: increasing development costs, heightened levels of trial complexity, greater regulatory scrutiny. These challenges, combined with current market realities such as decreasing reimbursements, dwindling pipelines and reduced chances of bringing a product to market, are driving the imperative for change. Move forward with better data and less risk Risk-based monitoring (RBM) can directly impact many of these challenges you face by facilitating more efficient trial delivery with the potential to enhance both data quality and patient safety. RBM involves identifying study-specific risks, implementing a process to mitigate and monitor those risks, and continually reviewing those risks throughout the study life-cycle. By targeting key data points and sites that require a higher degree of scrutiny, you can utilize on-site and remote resources where risk is highest. This optimized balance of monitoring resources also leads to greater efficiency, while centralized data surveillance using advanced technology permits enhanced scrutiny of trial data. Quintiles has experience using risk-based monitoring in more than 100 studies across more than 20,000 sites and more than 250,000 patients. Combining this experience with the industry-leading Quintiles 2

3 Infosario Clinical technology enables more agile decision making, thanks to a holistic view of integrated patient, site and trial data at every step. This approach delivers streamlined operations and a more predictable path to trial success. Get different results by thinking and designing differently Risk-based monitoring is typically a model for execution. But to optimally mitigate risk, the ideal first step is the upfront design and planning or risk-based thinking. It s about putting in place the right people, processes and technology to make Data-driven Trial Execution a reality. To inform our actions during trial execution, we implement a Quality by Design approach to identify both scientific and operational risks upfront and continuously throughout the trial. In many cases, this process starts at the time of protocol design so risk mitigation is built into the protocol and monitoring plan. In line with the recommendations of the EMA s reflection paper on RBM, this risk-based quality management approach drives how we think about, manage and report on the clinical trial. We start the design phase by bringing together our clinical project managers, safety and therapeutic medics, biostatisticians, and data management and operations experts. Together, they review and assess the design of your scientific and operational protocols. From endpoints to dosing to potential adverse events, this integrated team of experts identifies efficacy and safety risks to make sure the protocol can answer the scientific objectives of the study. They also look at the statistical analysis plan to determine statistical risks early on that may inform data collection and visualization. Then, they conduct an operational risk assessment, making sure the procedures and tools are in place to ensure that high-quality evidence is generated via the most appropriate sites based on their performance records. In the planning phase, we review the protocols to create alerts and triggers that monitor the identified risks throughout execution. Key risk indicators may include lab parameters, safety signals, accrual of endpoints, and stratification of patients whatever can help protect patients and achieve more efficient operations. Risk-based thinking can also be applied at the program level. In fact, considering critical program questions can help you design and plan a more effective protocol. How will a specific protocol fit with all other protocols in the program? What happens with unexpected findings, particularly around patient safety? What happens if the protocol doesn t deliver on time or the standard of care changes mid-trial? Will your design generate evidence to satisfy not only regulatory agencies but also payers and providers? Integrate data with advanced technology The power of Datadriven Trial Execution is enhanced by the technology behind it. Infosario Clinical, a robust technology suite, allows us to review trial, site and subject-level data in near real time so we can identify and respond to potential issues before they become problems. Infosario Clinical integrates an extensive range of data sources, including CTMS, resource management, labs, third-party data and EDC, all in one place. Numerous role-based data visualizations track and display key indicators such as adverse events or recruitment rates. As a result, we can achieve greater transparency into potential risks and more proactive, efficient trial management. For protocols and entire programs, design and planning lays the foundation of an effective risk-based monitoring strategy. It s a simple but powerful principle that guides how we approach and optimize execution of your trial. Figure 1: A quality by design approach Design Plan Execute Create/review scientific protocol, statistics plan, operational plan Develop alerts and triggers; conduct subject-level data review based on identified risks Implement trial and monitor against risk alerts; take action as needed Identify and reduce risk Quintiles Data-driven Trial Execution brings together risk-based thinking with insightful data analytics to power more actionable insights throughout the execution of your trial. In fact, what separates our delivery model from traditional on-site monitoring or even RBM approaches that combine on-site and centralized monitoring is the use of integrated, holistic data to lead decision making. Infosario Clinical integrates and delivers comprehensive, real-time data in interactive visualizations, 3

4 which allow us to zero in on signals and trends that could affect patient safety and operational performance and make smarter decisions about how to deploy monitoring resources. Risk assessment involves many of the activities from the design and planning phases to guide execution. After evaluating scientific and operational risks and setting up the appropriate triggers and alerts, we identify the critical data to be analyzed so we can develop the right monitoring strategy. We then use our knowledge of site performance around factors such as enrollment, protocol deviation rates or history of non-compliance to determine the monitoring plan to be used for each site. As we enroll patients and review triggers, we evaluate whether the site is performing as predicted; if not, we can course correct leading to more targeted and efficient monitoring. Risk assessment also includes several tactical activities, primarily handled by the project manager. Acting as a fulcrum between the operational plan and the operational team, the project manager plays a crucial role in overseeing the day-to-day plan and integrity of the trial, while coordinating action among the study team to mitigate risks. Figure 2: Technology enabling change Risk assessment Data surveillance Dynamic monitoring Our approach integrates three key components: Risk assessment Data surveillance Dynamic monitoring Tracking site data to enhance performance Just as execution depends on the inputs of design and planning, site performance depends on the specific sites you use for your trials. That s why we incorporate site selection and feasibility studies in our Data-driven Trial Execution offering. Tracking site behavior over time and across multiple studies gives you a higher level of confidence about which sites can help enroll the right patients and mitigate risk for your own trial. The more you know, the more you can integrate quality at every point of development, the more likely your trials will conclude successfully. Data surveillance allows us to look for and respond to the alerts and triggers called for in the operational plan. In this step, data are cleaned remotely, which produces more thoroughly cleaned data than even an on-site CRA visit. Then, we integrate data from various sources into dashboards that facilitate insights throughout execution rather than at preset intervals. For example, if patient recruitment rates are chosen as a key indicator, a high-recruiting site indicates a need to focus additional resources there to make sure the right patients are being selected. Data surveillance allows us to test upfront assumptions throughout a trial so we can recalibrate triggers. Our model includes the use of integrated patient, site and study data, where medically trained personnel monitor subject-level data in near real-time to connect insights faster than previously possible. We developed this industry-leading model, combining our expertise with technology and streamlined, automated processes to improve patient safety. Data surveillance includes: Data management review. Data are initially cleaned using many familiar techniques, including data entry, edit specifications and query writing. We design a data-cleaning strategy to incorporate key risks so when queries are run later, we can make sure we re supporting our upfront risk assessment goals. Subject-level review. Our comprehensive subject-level reviews evaluate the medical congruency of data. Also called holistic patient review, this process allows medically trained monitors to look at subject data centrally and sequentially. By comparing cleaned data across multiple visits, these subject-level data reviewers can efficiently detect trends that could have been missed if data were not integrated across time. 4

5 Figure 3: Proven operating model Quintiles project team Improvement in action: dealing with too much data Data Sites Risk assessment Subject Site Data surveillance Study Data cleaning Dynamic monitoring Triggers & alerts CRAs Recognizing that setting triggers for monitoring trial data via on-site or remote site visits is key to targeting risk, we developed a wide array of generic triggers to be used across all of one sponsor s studies. However, we quickly decided that we needed to concentrate on a key number of core triggers, so we deployed only the most crucial triggers to identify potential operational and quality drivers that enabled us to take action. Queries Integrated trial data Action Infosario Clinical This subject-level review component allows us to: Monitor issues/actions from data cleaning and medical reviews Monitor query rates and metrics Monitor relationship between data issues and reduced SDV Monitor site performance metrics data flow, SDV backlogs, outstanding queries Present data reports to site monitors to facilitate dynamic, informed decision making around sitemonitoring strategy Critically review the process regularly Data analytics review. This is an ongoing review and trend analysis of data issues, operational metrics and triggers that supports a dynamic, flexible and targeted site-monitoring strategy as well as driving high quality study execution. Comparing day-to-day operational data across sites and countries helps identify under performing sites or unaddressed operational risk. And by examining meta-data from recent studies in the same therapeutic area, with the same geographical spread or inclusion/exclusion criteria, we can forecast enrollment, screening and randomization rates so you aren t surprised by unforeseen trial costs or delays. Centralized data and operational surveillance delivers optimal data cleaning methods, while leveraging our therapeutic knowledge and using innovative technology to support overall trial cost reductions while improving quality and site compliance through world-class analytics. 5

6 This new model provides: The ability to impact clinical monitoring costs Decreases time to analysis-ready data for medical subject-level reviews Increased quality with reduced risks using holistic patient, site and study reviews Dynamic monitoring is a way to balance on-site monitoring with remote monitoring, so the right resources can be allocated for each trial s unique needs based on site performance data throughout the trial. Dynamic refers not only to assigning the right combination of resources but also to continuously adjusting monitoring strategies according to ongoing input from project managers and our data surveillance group. For example, based on our risk assessment, a site may initially require few on-site visits. But if we start to identify outliers or inconsistencies in that site s data, we may include additional on-site monitoring, or shift our monitoring schedule from every six weeks to every two weeks. The key is letting the data determine our monitoring strategy rather than letting the initial strategy dictate ongoing operations. Dynamic monitoring changes the role of clinical research associates (CRAs) and the overall communication process with sites. We ve improved communication with sites with increased focus placed on potentially higher risk sites, driving more focus on critical items. CRAs are focused on critical data versus verifying all data, so resource allocation and efficiency is higher for CRAs and sites. With a more centralized approach to monitoring, CRAs must be prepared to interpret data signals and use their knowledge of the protocol and site requirements to drive action. They must also be prepared to manage and communicate with the site remotely, in addition to conducting site visits. We ve found that this deepens the relationship between sites and monitors, on- and off-site, which is fundamental to making dynamic monitoring work. Enhance performance at every stage While the three capabilities of Data-driven Trial Execution risk assessment, data surveillance and dynamic monitoring comprise distinct activities, they aren t siloed. Instead, each area constantly informs the others. Data surveillance may determine that risk thresholds created during the risk assessment phase need to be modified. Or data analytics scientists may identify sites that require you to recalibrate your dynamic monitoring strategy. Communication between the project manager and medical and clinical monitors is crucial both to ensure ongoing protocol compliance and to help each function remain focused on study risks as they emerge and evolve over the course of a trial. Through the joint access and use of Infosario Clinical, such efficient collaboration is now possible. Achieve a new level of transparency One of the most powerful data visualizations at your disposal is Site View. This dashboard allows monitors to track milestones and interpret performance across sites to quickly identify potential issues or trends. With this holistic view, available throughout the trial, we can take actions more quickly than previously possible keeping the trial on track every step of the way. Figure 4: Reach the optimal balance of on-site and remote monitoring resources based on study-specific risk. Centralized & remote monitoring On-site monitoring Informed consent & IP On-site relationship Source document Protocol Medical & data monitoring Virtual relationship Site progression mngt High Medium Low The FDA recognizes that an approach focused on the risks to the most critical data elements is more likely to ensure patient safety and study quality than routine site visits and 100% SDV. Responsive action based on level of site risk 6

7 Execute RBM confidently consistent with regulatory guidance As new technologies have enabled RBM, new regulatory guidance is empowering more pharmaceutical companies to consider this approach. The FDA s final industry guidance on RBM and the EMA s reflection paper on risk-based quality management recognize that a risk-based approach to monitoring can address the growing complexity of clinical trials while maintaining and even enhancing data quality. The FDA acknowledges that no single approach to clinical monitoring works for every trial including those involving 100% SDV. In fact, the FDA reports an approach focusing on the risks to the most critical data elements is more likely to ensure patient safety and study quality than routine site visits and 100% data verification. It s important to tailor monitoring strategies to a specific study. Sometimes this may include only onsite monitoring using 100% SDV. However, this option no longer needs to be the de facto approach. On-site monitoring can be combined with centralized, remote monitoring to offer just as much vigilance in clinical oversight. We ve used risk-based monitoring principles and processes in studies covering oncology, diabetes and many other therapeutic areas. The FDA points out that certain activities such as following up on missing or inconsistent data, analyzing performance metrics or completing administrative or regulatory tasks may actually be better suited to remote monitoring. A focus on quality should be included in every monitoring strategy. The integration of advanced technology, coupled with our expertise and the development of new processes and roles, allows us to deliver a new level of value to our customers. Martin Giblin, Quintiles RBM leader According to the FDA, quality begins with a well-designed protocol and monitoring plan that identifies critical data and processes. In other words, upfront design and planning are necessary to protect patients and study integrity. In addition, the FDA encourages using: A thorough risk assessment to ensure monitoring efforts can prevent likely sources of error Statistical analyses to identify trends that could go undetected by on-site monitoring A combination of centralized, remote and on-site monitoring Technology to assess quality metrics in real time While regulatory authorities don t specify which technologies can enhance study quality, we ve learned from building our own systems that any effective quality data solution includes some key elements: A master data management (MDM) solution that can pull critical values from a data warehousing structure Integrated data, with terms standardized across the organization A data quality governance plan that addresses data use across silos Optimized, secured access for a broad range of key users Together, these elements allow for greater data transparency. More importantly, they drive increased trust. With access to the same information and the same terms, everyone will have greater confidence in the data and will be more likely to act on it. Connect insights for superior delivery and better outcomes With trial complexities and costs increasing, it s time to take advantage of technology to connect insights faster in order to execute trials more efficiently, without sacrificing quality or wasting resources. Capitalizing on new technologies and workflows, Quintiles Data-driven Trial Execution integrates riskbased thinking, data analytics and many years of process refinement for superior delivery and more predictable trial outcomes at potentially lower costs. It combines study start-up, project management, clinical monitoring, data management and analytics to optimize trial conduct while meeting regulatory demands and quality requirements for Good Clinical Practice (GCP). This kind of innovation will ensure the future of drug development. 7