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As clinical studies increase in complexity in a myriad of ways, a key question often asked is, “Is our ability to create complexity increasing faster than our ability to understand complexity?” This is an exciting time to be involved in the reporting of data and metrics on the performance of a clinical study. However, it is important to understand the principles of visual presentation of data to ensure that the information is accessible, actionable, not misleading and ultimately valuable for the end consumer of information
A multitude of roles are involved in a clinical trial such as Clinical Study Leader, Clinical Supply Managers, Statisticians, Country Managers, CRAs/Monitors, and Site Personnel. In product management terms, these roles are considered User Personas. A clear understanding of these roles and the activities they are required to perform by asking the question ‘what problems are you trying to manage?’ provides the framework for identifying the information they need to perform their jobs.
Also important is understanding the lifecycle of a clinical study which, at its broadest, can be considered inception, design, start-up, subject recruitment, study conduct, close out, and submission. These lifecycle steps should be used to influence when information is presented and how its prominence may change over time, depending on the study status. Delivering information that is relevant to the user in alignment with business processes will help ensure that metrics are actionable and used.
There are generally 4 types of metrics that one could measure in the clinical trial industry:
Anecdotally, it would appear that while there is much focus on metrics addressing both cycle time and timeliness, there are fewer that monitor quality and cost within the clinical trial industry. These four elements need to be in balance to ensure that doing something on time does not result in a lot of rework along the way. One of the metrics that is often discussed in Electronic Data Capture (EDC) solutions is the close out rate of queries (i.e., the time taken from when a query is raised until it is resolved). This is a cycle time metric. Although important in a trial, this is measuring rework (i.e., a lack of quality). This is an example of an ineffective resource investment as it does not materially contribute to the outcome of the trial. Conversely, focusing effort on reducing the number of queries raised has twice the impact as it improves quality AND reduces the amount of resources required to do the rework. Focusing in this area is an effective use of resource as it materially contributes to the outcome of the study.
It is essential that these key points remain at the forefront:
Having the right information readily accessible especially for data-intensive clinical trials at the right time and in a format that is easy to understand helps focus on what is important. Without focus it is easy to become distracted and dwell on issues that do not have a positive impact on objectives. Keeping these basic principles in mind when defining metrics and designing how to display them is essential in delivering metrics that are valued by the user.
MaxisIT with its cloud based integrated solution brings an opportunity to sponsor to improve oversight of clinical investigations by enabling standardization and storage of data, allowing integration with different EDC,CTMS, Safety, PV, Health Care, and document management systems.
Predictive analytics with dashboard for metrics, key performance indicators, key risk indicators, configurable thresholds, triggers, alerts, escalations and workflows to drive proactive risk mitigation and actionable outcomes are the major features associated with our solution, enabling sponsors to take timely decisions and reassess the monitoring strategy throughout the monitoring cycle.
Increasing clinical development costs for drugs has been a concern for industry over the years and multidirectional efforts have been made to lower these costs through more efficient study management. Since monitoring accounts for a substantial proportion of the total study costs, major focus is towards lowering the monitoring costs through the analysis of risks involved during a clinical drug development lifecycle.
Significant savings have been claimed through the use of modified site management; centralized and planned source document verification with only essential onsite source data verification emerging out of inconsistencies assessed through centralized risk based monitoring.
Monitoring is an essential element of clinical trials, ensuring quality and integrity of a clinical investigation. Monitoring uncovers potential problems such as data entry errors or missing data, assures that study documentation exists, assesses the familiarity of the site’s staff with the protocol and required procedures, and provides a sense of the overall quality of a site.
Post FDA’s final guidance and EMA reflections on Risk Based Monitoring, Industry is transitioning from routine visits to clinical sites and 100% Source Data Verification to risk-based approaches to monitoring. This helps sponsors to focus on critical data elements by practicing Centralized Monitoring and relying more on technological advancements thus reducing trial cost and time significantly.
Factors like central data collection systems, and real time data standardization and analytics are important to get a sense of the big picture in order to effectively perform risk-based monitoring. EDC and CTMS have made central data collection possible with higher level of data accuracy than that with traditional data collection methods.
Modern analytics tools and technologies are driving the emergence of centralized monitoring because they provide powerful insights into data. Considering the large scales of current clinical trials, accuracy and effectiveness is problematic with on-site monitoring. Large problems go unnoticed when data results are only skimmed through on-site monitoring practices
What do the authorities have to say?
The EMA emphasizes on the identification of potential risks and prioritization should commence at a very early stage in the preparation of a trial, as part of the basic design process. The concerns with trial and protocol design, design of data collection tools/instruments, the design of the monitoring and data management strategies and plans, including the relative role of centralized versus on-site activities and the data quality tolerances, and the design of record keeping for the study should be addressed within the framework of these dimensions, implementing a quality by design approach. Risk assessment and mitigation plans should be appropriately disseminated within the organization, regularly reviewed and updated when new information becomes available.
FDA recommends that each sponsor design a monitoring plan that is tailored to the specific human subject protection and data integrity risks of the trial. The monitoring plan should identify the various methods intended to be used and the rationale for their use. Monitoring activities should focus on preventing or mitigating important and likely sources of error in the conduct, collection, and reporting of critical data and processes necessary for human subject protection and trial integrity.
Sponsors should prospectively identify critical data and processes, perform a risk assessment to identify and understand the risks that could affect the collection of critical data or the performance of critical processes, and then develop a monitoring plan that focuses on the important and likely risks to critical data and processes. The guidance highlights the importance of documenting the monitoring plan after assessing the project risks and needs. It also recommends that sponsors analyze ongoing data to continuously assess and adjust the monitoring strategy.
This encourage sponsors to adopt strategies that reflect a risk-based monitoring approach using a combination of monitoring strategies and activities. The approach should emphasize focus on centralized monitoring by identifying critical elements and a plan to address data integrity risks. Several initiatives are underway to promote RBM paradigms and different methodologies are being suggested to achieve maximum out of the RBM approach.
MaxisIT has been constantly in pursuit of providing best innovative solutions to divergent requirements of pharmaceutical industry. With unique integrated clinical development platform and analytical capabilities, our solutions have provided sponsors great ease of work enabling them analyze disparate data sources and derive critical decision scenario on the fly. MaxisIT ’s Holistic and Flexible solution architecture offers complete solution for RBM approach in a real sense.
At MaxisIT, we clearly understand strategic priorities within clinical R&D, and we can resonate that well with our similar experiences of implementing solutions for improving Clinical Development Portfolio via an integrated platform-based approach; which delivers timely access to study specific as well as standardized and aggregated clinical trial operations as well as patient data, allows efficient trial oversight via remote monitoring, statistically assessed controls, data quality management, clinical reviews, and statistical computing. Moreover, it provides capabilities for planned vs. actual trending, optimization, as well as for fraud detection and risk-based monitoring. MaxisIT’s Integrated Technology Platform is a purpose-built solution, which helps Pharmaceutical & Life sciences industry by “Empowering Business Stakeholders with Integrated Computing, and Self-service Dashboards in the strategically externalized enterprise environment with major focus on the core clinical operations data as well as clinical information assets; which allows improved control over externalized, CROs and partners driven, clinical ecosystem; and enable in-time decision support, continuous monitoring over regulatory compliance, and greater operational efficiency at a measurable rate”.
Post FDA’s final guidance on Risk Based Monitoring, Industry is transitioning from routine visits to clinical sites and 100% Source Data Verification to risk-based approaches to monitoring, focusing more on critical data elements by practicing Centralized Monitoring; relying more on technological advancements thus reducing trial cost and time significantly. The industry needs an out-of-the-box end to end solution that will cover all the bases for efficient risk based monitoring allowing business to stay agile and lean while making better and informed business decisions that will allow them to achieve faster and quality clinical drug development compliant to regulatory and assured cost savings
As technology is playing vital role in data collection during clinical trial conduction, multiple data sources like EDC, CTMS, PV, IVRS needs to be handled by sponsor. Before applying analytics on the data it is of utmost importance to place all data at single place. MaxisIT ’s unique data integration capability enables tool to communicate with disparate data sources. As integration is metadata driven it is highly configurable to sponsor specific metadata as well as standard metadata.
Source Data Validation (SDV)
Risk based monitoring emphasizes on selective source data validation in place of onsite 100% source data validation. Our solution offers seamless, real time data validation to extract discrepancies like missing data, duplicate records, data outliers, and inconsistent data. SDV engine also enables users to identify data fraudulence. This level of data validation increases data integrity and quality.
Data standardization is the first step to ensure that your data is able to be used for analysis and shared across the regulatory. This establishes trustworthy data for use by other applications. Ideally, such standardization should be performed during data entry. If it is not done a comprehensive back end process is necessary to eliminate any inconsistencies in the data. Our standardization capability provides most comprehensive data standardization and transformations across the standards. Being a Metadata driven process it is flexible and configurable across different data standards. Its drag and drop utility makes data standardization easiest ever.
Analytics and Reporting
Effective risk based monitoring can be achieved using different statistics on disparate data related to ongoing trials. Many analytical tools are focusing their efforts on developing RBM oriented analytical engines with user friendly dashboards. Statistics being a functional entity limited to specific user group, configuration of complex statistical reports is never been a welcome step for end user. Data aggregation is imperative while handling disparate data for analytics. Our solutions provide metadata driven data aggregation which enables complex data analytics easier for user. It enables user to have cross functional report generation and better visibility through different data having linkage or dependencies.
MaxisIT ’s innovative analytics tool offers most user friendly operability and role based dashboard allowing users to have multiple reports like data driven visualizations, statistical reports and scenario modeling. Our analytics dashboard provides unique functionality of cross-functional drilldowns. Drilldown functionality allows user to navigate from one report to multiple another reports to understand depth of data and analyze root cause of issue. Similarly our unique entity of scenario modeling leverages understanding of complex cross-functional correlations and enables user to understand complex issue origins.
Monitoring Issue and Risk Management
Management of risks and issues emerged during central and onsite monitoring needs to be handled efficiently for faster resolution. Knowing the risks during monitoring execution and assessing the issues derived from central and onsite monitoring is centralized in our solution to allow the user to have easier navigation through monitoring interfaces and better visibility of all issues, action, and status with multiple levels of filters. User is able to generate monitoring reports based on the study, site, or other attributes by applying filters in our monitoring report generation interfaces. It also allows input of monitoring activities for onsite monitoring which updates central issue log. Our risk and issue log allows users to have an overview of complete status report and audit trails for all issues occurred during the study. All the reports generated are exportable in different formats like xls, pdf, png, jpg, html depending upon the report types. Trial conduction also contains a large amount of content management in form of multiple documents and forms. Our content management platform gives users a simplified content development solution where content development is highly organized with author reviewer workflow and features like reusability, resulting in cost-effective and quality content development.
MaxisIT ’s solution is highly compliant to different global regulatory standards like 21 CFR part 11 or CSV guidelines by EMA etc. Central and highly secured data storage adds to the completeness of the solution where complete organizational usability of solution is through its single sign-on, role-based user access facilities making it a highly reliable, scalable and complete solution for RBM.
At MaxisIT, we clearly understand strategic priorities within clinical R&D, and we can resonate that well with our similar experiences of implementing solutions for improving Clinical Development Portfolio via an integrated platform-based approach; which delivers timely access to study specific as well as standardized and aggregated clinical trial operations as well as patient data, allows efficient trial oversight via remote monitoring, statistically assessed controls, data quality management, clinical reviews, and statistical computing. Moreover, it provides capabilities for planned vs. actual trending, optimization, as well as for fraud detection and risk-based monitoring.
MaxisIT’s Integrated Technology Platform is a purpose-built solution, which helps Pharmaceutical & Life sciences industry by “Empowering Business Stakeholders with Integrated Computing, and Self-service Dashboards in the strategically externalized enterprise environment with major focus on the core clinical operations data as well as clinical information assets; which allows improved control over externalized, CROs and partners driven, clinical ecosystem; and enable in-time decision support, continuous monitoring over regulatory compliance, and greater operational efficiency at a measurable rate”.