Clinical Data Trends, Issues and Developments
Article Feb 14, 2017 | By Jack Rudd, Senior Editor for Technology Networks
When we consider technology, we often imagine ourselves attempting to keep pace with the latest innovations. However, when it comes to clinical trials we need a way for our systems to keep up with the increasing complexity and volume of data. In order to identify trends in data, it must be analysed across many different source systems. A platform for data integration which can handle any data from any source ultimately frees up more time for data collection and analysis, and allows users to visualise trends and report findings in near real-time.
To discuss the key trends and future of this rapidly evolving market, I spoke to Sudeep Pattnaik, President & CEO of ThoughtSphere.
JR: What are the major challenges in clinical data management right now?
Traditional systems for managing clinical trials typically include a combination of software and paper-based processes. Clinical data used for drug, device and diagnostic regulatory approvals are usually collected from a broad range of clinical development systems. Some systems are software-as-a-service (SaaS), others are deployed on-site. Electronic data capture (EDC) systems, while preferable to paper-based systems, lack the full data integration capabilities necessary for effective R&D operations, particularly the conduct of clinical trials, including trial monitoring, financial management, and the achievement of milestones. To identify data trends, data must be analysed across these different source systems. But the data are typically in silos that cannot be cross-queried, so decisions are made with limited collaboration. Information is provided to users through disconnected status reports. Real-time, proactive, continuous analysis of data is often not possible, so that information showing that a drug should fail can be missed for extended periods, while costly testing continues. A macro-level trend that plays into this data integration challenge is that of business consolidation in the biopharmaceutical industry. As companies consistently merge, systems must be cross queried and data must be consolidated to perform use cases such as risk-based monitoring (RBM) and project and portfolio management for example.
JR: How does your ClinDAP solution help to overcome these hurdles?
ThoughtSphere is at the forefront of innovations in clinical R&D technology promising to improve trial efficiency, accuracy, and the bottom line. Sponsors and contract research organisations (CROs) are seeking a data aggregation solution with integrated analytics that provides near real-time access to fully integrated data to help solve complex data analysis use cases.
A novel approach is needed to address the current data integration challenge – one that is not relational database oriented, in which a schema must be defined upfront, but a flexible solution that can handle any data from any data source therefore, leveraging big data architecture to aggregate both structured and unstructured data with relative ease. ThoughtSphere provides near real-time multi-data access to any clinical or nonclinical development system that can be deployed in days or weeks through a SaaS-based offering. This differs greatly from data warehouse projects that can take years to deploy. With a flexible approach to data integration, effective integration with so many disparate data sources is possible to achieve.
JR: Why is it important that ClinDAP is integrated with JReview? What does this enable?
The integration affords users never-before-seen benefits by integrating structured and unstructured clinical and operational datasets to make managing, interpreting and analysing simpler and, in turn, enhancing clinical research processes and intelligence. JReview is one of the most-used clinical analytics tools on the market, specifically designed for clinical researchers, and used by the FDA. The integration will help users address time-consuming data standardisation and transformation challenges.
JR: What trends and requirements for new innovations can you see emerging in the field over the next couple of years?
As the biopharmaceutical industry evolves and organizations grow and change, data standardisation will continue and so will the need for the flexibility to accommodate data from a growing number of source systems with their own formats. Instead of focusing on preparing data for analysis, enabling end users to visualize outliers and trends and report and collaborate on those findings will be a core competency companies must have to succeed in the rapidly changing biopharmaceutical industry. Our Data Integration Platform is the solid foundation to make this happen.
Francis S. Collins, M.D., Ph.D. Director of the National Institutes of Health, has recently directly addressed the issue of underrepresented groups in science: "Too often, women and members of other groups underrepresented in science are conspicuously missing in the marquee speaking slots at scientific meetings and other high-level conferences.”READ MORE
At Argonne National Laboratory, the Aurora supercomputer will lead the charge as the US's first system exceeding an exaflop, or a billion-billion calculations per second. In this article, we explore how Aurora could enable revolutionary advances in heterogeneous catalysis chemistry research, with implications for fossil fuel processing and small molecule conversion.READ MORE