June 19, 2015
By Riley McDermid, BioSpace.com Breaking News Sr. Editor
Clinical data is the foundation to medical product development and remains the cornerstone for the industry’s innovation, an executive with Medidata told BioSpace at DIA 2015 this week.
Frances E. Nolan, Vice President of Quality and Regulatory Affairs at Medidata, was part of a panel, “How Risk-Based Monitoring and eSource Methodologies are Impacting Clinical Sites, Patients, Regulators and Sponsors.”
BioSpace caught up with Nolan afterwards to talk about the topic of eClinical/eSource and the different mechanisms for capturing clinical data, as well as different operating models for how data is stored and maintained.
How is clinical data crucial to what the life sciences do every day, and what processes or technology is helping to ensure its quality?
Clinical data is the foundation of medical product development and is essential to healthcare innovation. High-quality data that is collected and verified in a safe, compliant and effective way allows pharma, biotech, and medical device companies to further research and hopefully get to a stage where they can get regulatory approval for their product.
Risk-based monitoring (RBM) is an example of how new approaches are helping the life sciences industry reimagine trial operations and processes to get new therapies to patients sooner.
A proven methodology for making better use of limited resources while providing a higher level of clinical data accuracy and quality, RBM is reflected by a reduced reliance on traditional on-site monitoring methods, along with a more focused utilization of off-site or remote monitoring activities and centralized services to identify emerging risks (leveraging real-time analytics around subject and site data).
Medidata offers innovative technology that allows customers to understand complex interrelated datasets and target resources where they are needed most, enhancing the quality of data reviews while increasing the effectiveness and efficiency of clinical trials. By utilizing proprietary algorithms, we can help identify sites and data needing closer attention, allowing for adjustments to risk indicators that can lead to early detection of anomalies and outliers in clinical data—including potential fraud and misconduct.
What needs to change in the way we collect and manage clinical data?
The traditional approach to monitoring clinical trials relies to a great extent on conducting 100 percent source data verification (SDV). Monitors cross-check data entered into case report forms (CRFs) with original source documents.
Medidata partnered with TransCelerate Biopharma to evaluate the efficiency of this model back in 2014 and the results were clear. Using data from 7,000 clinical trials, it was found that only ~1.1 percent of the electronic CRF (eCRF) corrections were attributed to SDV versus other data correction methods.
Moreover, 96.3 percent of data is never corrected after entry to database. So where is the value-add of conducting 100 percent SDV? Something needs to change.
Targeted, reduced SDV is just a component of RBM, which also incorporates off-site or remote monitoring, as well as centralized monitoring techniques. The premise behind RBM is to focus sponsor oversight on the most important aspects of study connect, thereby enhancing patient protection and improving the quality of clinical trial data.
What are the biggest challenges you see in risk-based monitoring?
Some of the biggest challenges to the industry’s adoption of risk-based monitoring relate to the operational, procedural and resource allocation changes that are required to successfully implement this methodology. Shifting from an on-site monitoring model to one that relies more on remote and centralized techniques means that the industry needs to change its formal monitoring procedures and introduce organizational changes, as well as hire or train personnel who have the ability to take a more holistic approach of assessing activities occurring at the site.
What’s the optimal operating model?
The optimal operating model for risk-based monitoring is one with centralized monitoring at the core that utilizes personnel with data-focused, analytical skills. The model leverages a “Quality by Design” approach, and begins with early and ongoing risk assessment of critical data. Targeted remote monitoring and on-site monitoring focus on patient safety and help ensure data quality. Regulators have been proponents of risk-based monitoring for years and want to see the industry adopt this approach.
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