As the cost of drug development continues to rise and clinical research becomes lengthier and more complex, biopharmaceutical companies must find efficient ways to deliver trials with greater speed and quality at scale. One approach is through the use of a functional service provider (FSP) model, which gives sponsors access to experienced clinical research personnel without the cost and risk of employing qualified full-time staff.
Traditional clinical FSP models provide the flexibility to rapidly ramp-up global clinical teams across the globe, and easily adjust headcount in response to changes across studies or a portfolio of studies — whether that requires shutting down a program or building additional capacity due to incoming assets or an acquisition. Because functional service providers handle all the hiring, training and personnel administration, sponsors can focus their time on the most business-critical functions for them.
While shifting to a functional service partnership model is a first step in resourcing clinical programs at scale, there is growing need to deliver value beyond flexible staffing. With the advent of purpose-built clinical trial technology, data and analytics to support clinical trial planning, delivery and execution, an evolution of FSP models to leverage adjacent services, is poised to deliver transformative value compared with a traditional flexible staffing approach.
By strategically selecting services, technologies, and tools that empower clinical staff and harmonize historically fragmented elements across the clinical trial lifecycle, sponsors can create tailored, scalable solutions that significantly improve efficiencies.
While traditional FSP approaches are built around providing human capital to deliver clinical staffing services, greater efficiencies can be gained downstream through strategic partnering up front. For example, providing benchmark-based protocol reviews to inform protocol assessments and data-informed guidance on the best countries and sites for a trial mean fewer protocol amendments and time spent with low-performing sites down the road. These insights allow sponsors to streamline their research and avoid unnecessary delays and costs.
Throughout the trial, we can better support study teams by incorporating risk-based and centralized monitoring solutions to provide more focused process in which site visits are strategically targeted based on data-informed need. Risk-based monitoring (RBM) has been proven to deliver a more productive and proactive monitoring process where risks are continually assessed and issues are addressed faster with fewer staff, and data quality is significantly improved. In one 2019 study from the Association of Clinical Research Organizations (ACRO) members using RBM saw a 16 percent reduction in major findings in audits compared to those following a 100 percent source data verification (SDV) approach. They also experienced a 15 percent reduction in costs.
Along with RBM, here at IQVIA, we are advancing the FSP business model by offering additional tools to streamline and automate tasks in a way that better supports clinical staff throughout the clinical trials lifecycle. These can include:
As with all FSP solutions, sponsor teams need to be ready to embrace new team members, technologies and business processes to ensure success. The biggest risk to the success of any FSP model — whether you are adding a handful of staff or adopting a global solution — is managing change.
Taking the time up-front to educate study teams – ensuring an understanding of shared accountabilities and objectives — can help maximize the value these functional services partnerships bring to your business.
A clinical FSP solution is no longer limited to filling short-term talent gaps. With investments in technology and data, we now have the opportunity to offer strategically tailored clinically-focused solutions that eliminate wasted time and effort, avoid delays, and ensure the safety of clinical trial participants, all while delivering the highest quality data to meet regulators’ expectations.
It’s time to embrace all that technology and data analytics can do to improve the clinical trials process at each stage and a every scale.
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