Clinical Trials Management: Spot Problems Earlier, Easier with Visual Analysis


The number of clinical trials has grown more than 35 times since the National Institutes of Health first made its site public in 2000. And the data incorporated in the 195,770 trials registered so far in 2015 has expanded to include not only traditional clinical measures, but also translational and outcomes data. 

With that much data, and the proliferation of technologies to support its creation, how can Clinical Project Managers (CPMs) and Clinical Research Associates (CRAs) improve visibility into their trials? How can they spot problems and address issues earlier in the clinical process? And lastly – how can they do these things without attending coding bootcamp or becoming a computer scientist?

Go for Visual Analytics

What’s needed for effective clinical trial management are unifying solutions that enable analytically driven decision-making. Faster, dynamic solutions enable the user to quickly analyze disparate data from multiple sources to create a complete picture of what’s occurring in clinical development – as it happens. 

It’s no longer a clinical best practice to wait six months for data to be locked, cleaned, and analyzed. Traditional reporting methods are too slow, cumbersome, and time consuming. Trial data is needed from ‘First Patient In’ -not at discrete time points, but rather in an ongoing manner. Visual data analytics based on electronic data capture make this possible. 

Incorporating visual analysis into clinical operations provides timely information and actionable insight to keep trials on track. Program, country, and study managers and monitors can make decisions based on live, interactive scorecards that track everything from planned vs. actual budgets, to study milestones including Investigator Review Board approvals and patient visits. 

Choosing the right visual analytics platform can help companies achieve clinical operational excellence. But analytics platforms are only as effective as the underlying expertise available to platform users. At PerkinElmer, for example, our clinical analytics platform - powered by TIBCO Spotfire® - is backed by our years of experience:

     • Building advanced analytics solutions to cover drug development workflow needs

     • Breaking rigid data silos to power real-time and predictive analytics

     • Offering value-added analytics consulting services to adapt the solutions to specific client needs.

Empowering Risk-Based Monitoring

FDA, EMA, and PMDA all recommend risk-based monitoring (RBM) of clinical investigations to enhance patient safety, improve data quality, and drive efficiencies. Visual analytics provide valuable insights for RBM, as it accelerates data aggregation through continuous collection and automated consolidation. 

To confidently identify and assess issues early enough to improve study safety and efficiency, technology platforms must enable continuous monitoring with near real-time intuitive visualizations, analytic dashboards, and applications.

Visual Leads to Virtual

Virtual biotechs – small companies with a few executives overseeing the outsourcing of biopharmaceutical R&D – have emerged in the last ten years in response to tightening capital markets. They rely on the leanest development teams and outsourcing to achieve clinical proof of concept for a drug candidate.

This new drug development model coincides with the emergence of faster, flexible visual analytics and business intelligence tools which assist small, nimble companies in their drug development efforts. Virtual biotechs use flexible platforms with real-time access to aggregated data and programs for trial management, monitoring, data analyses, and business operations. The right platform can take a virtual firm and its partners from initial study startup with applications for trial timelines and progression to Phase III project management. 

Spotting Outliers, Trends, and Problems

At its heart, effective clinical trial management means finding the things that are going wrong, or have the potential to go wrong, early. The right platforms for visual analytics – for both business and science intelligence – help the user more easily and rapidly spot the outliers, find the trends, and unearth the problems that are buried in the sea of clinical operations data. 

Making the change from traditional reporting and query tools to a visual analytics platform means less time preparing data, and far more time acting on the insights from it. 

Are you using the right visual analytics platform for clinical trial management and data analysis?