PRA Health Sciences
Clinical Trials Managed on a Global Scale

Big Data has evolved to become a useful source to gain insights for many healthcare firms today. With the vast amounts of data applicable to managing clinical trials, pharmaceutical firms have to devise and employ new strategies to derive meaningful insights from rapidly growing data sources. Optimizing clinical trials, PRA Health Sciences, a Raleigh-based clinical research organization, employs Business Intelligence (BI) technology to provide scalable solutions that create value-inducing insight throughout the clinical trial process. “Without advanced decision support tools, predictive analytics, and process automation, it's difficult to translate large amounts of data into efficiently run, predictable, and quality clinical trials,” says Charles Piccirillo, SVP, IT and Development, PRA.

The company's ongoing technological integration in the clinical development process is unique in the industry. “At PRA, our extensive clinical trial expertise, combined with our experienced data scientists, advanced analytics and statistical analysis techniques, enable us to provide meaningful decision support solutions for our employees and customers” says Piccirillo.

The firm’s proprietary Predictivv platform is a fully integrated platform capable of designing, planning, and optimizing the management of clinical trials on a global scale. Predictivv harmonizes the data, processes, and personnel across the entire clinical study to provide adaptive intelligence and decision support in the clinical development process. Taking a strategic approach in how data is leveraged will enable PRA to manage clinical trials more predictably and efficiently.

The platform allows PRA to minimize unnecessary integration of data between disparate systems in many cases, reducing the need for integration. “We assemble a unique team of clinical experts that work closely with our clients to develop flexible, real-world solutions that comply with global standards and provide meaningful, data driven intelligence,” says Piccirillo.

PRA’s services have been leveraged by companies in pharmaceutical and biotechnology sectors around the world to overcome many data-related challenges.

Our extensive clinical trial expertise, combined with our experienced data scientists, advanced analytics and statistical analysis techniques, enable us to provide meaningful decision support solutions

In one instance, when a client advanced their timelines for database lock by nine months, PRA created a detailed closure plan that listed all tasks and activities and associated deadlines for each item that needed completion within a given timeline. PRA also calculated data flows and trained additional staff members for the client to ensure the trial was completed on time. The firm updated the client’s closure plan and data flow, when needed, and utilized PRA’s internal information intelligence to monitor the entire operation. Following the plan, the client was able to complete the trial in an efficient and cost-effective manner within the stipulated database lock. “Our model combines the power of clinical expertise and unique tools which enable our employees and teams to keep complex projects on track,” says Piccirillo.

Leveraging technologies like cloud, IaaS, PaaS, and more, the firm’s strategy focuses on high value enterprise solutions to deliver clinical studies with transparency at a faster pace than their competition. “To satisfy our clients and stay ahead in the market, we identify and implement new and unique ways to combine process, people, and technology while preparing ourselves for a continuously changing industry,” says Piccirillo. Using extensive amount of data, advanced analytics technologies, and deep therapeutic expertise as a guide, PRA selects optimal sites that yield targeted patients to support and simplify the management of the clinical trial.

For the future, PRA aims to build and implement solutions that further promote transparency, responsiveness, and predictability. “Our solutions are developed to leverage data for improved collaboration and decision-making throughout the drug development process,” concludes Piccirillo.