Clinical trials are the quintessential project, being both complex and requiring project management skills and techniques to bring them to a successful close. The measure of a project success — delivering on time and with quality inside the proposed budget — are key requirements in the highly competitive environment in which pharmaceutical and CRO organizations operate, yet this benchmark is seldom achieved.

Recent and upcoming guidelines from the International Council on Harmonization (ICH) have encouraged the modernization of clinical trials, specifically the implementation of risk management practices, technology, quality-by-design and critical thinking to increase efficiencies in clinical trials.

Yet today, the traditional drug development and study design process remains very sequential and siloed. Rigid research traditions, with clear separation of responsibilities, has resulted in a clinical development one-size-fits-all process with fixed timelines that have continued to increase with the scale, complexity and cost of clinical trials.

Breaking through these entrenched barriers holds the key to reducing runaway timelines and costs. Is this achievable? In short, the answer is yes. Pfizer, using these principles, successfully brought a highly effective and safe COVID-19 vaccine to market in under a year by treating the whole clinical development process (phase 1 to 3, and to some extent 4) as one protocol, managed by one team.

Studies show that at any given time about one-third of all clinical trials are behind schedule. Perhaps the most disturbing fact is that cycle times associated with starting clinical trials have not changed in more than two decades (CenterWatch Weekly, March 12, 2018). In fact they are getting slower, and the subsequent need for study rescue may increase the cost of trials by 20 percent or more. Clinical trials that get off to a good start are more likely to execute well and finish on-time and on-budget — study startup is the Achilles heel of clinical trials.

With unrelenting pressures to rein in budgets and cycle times, the application of project management techniques to study startup holds the key to optimizing operational efficiencies and compressing timelines.

According to the Project Management Institute, in the fast-tracking compression technique, also known as parallelization, activities normally performed in sequence are done in parallel for at least a portion of their duration. All of the vital activities on the critical path are reviewed and analyzed to determine which ones can be performed partially or fully in parallel with other activities. Activities not on the critical path don’t impact the overall schedule duration and are therefore not analyzed as part of this process.

In fairness, it is not the lack of knowledge of this technique by clinical project managers that is the problem, it’s the inability to spot white space (i.e., the opportunity to see where optimizations in the process can be made), and when to apply these techniques (i.e., optimal timing for intervention).

Today, no visualization of the sequence of activities in global clinical operations for study activation exists, and this is essential for defining not only what metrics to capture but which activities might be candidates for schedule compression. While country-specific activities may be defined, these are not generally applicable to other countries. Recently released ICH guidelines are renewing the focus on the need to define these activities in order to drive efficiencies in the initiation of clinical trials, and the Metrics Champion Consortium is working with industry stakeholders to define and release an associated industry standard. Additionally, activities long considered critical path mainstays (e.g., site contracting) may in fact present white space opportunities.

Moreover, the extensive use of Excel for tracking the progression of clinical trials persists, despite it lacking project management capabilities. This woefully inadequate tracking of operational performance data prevents clinical operation teams from identifying risk factors and bottlenecks that can disrupt cycle times and budgets. Frequently, problems are not identified until milestones are missed and project managers are forced to retroactively apply the crashing technique in order to get the study back on track. Ultimately, crashing should be used sparingly as there are significant cost implications and its overuse may indicate a more systemic problem — suboptimal planning. In the end, it is the parallelization that represents the greatest opportunity to realize efficiency gains that are reproducible across all studies, and not just on an as-needed basis.

For example, after a site has been identified as an ideal candidate for a clinical trial and the confidential disclosure agreement (CDA) signed, the feasibility survey and other activities must be completed before the site can be formally selected for the study, assuming no red flags are raised. This process takes on average 7.9 weeks, according to research by the Tufts Center for the Study of Drug Development.

Parallelization allows for this step in the selection process to be overlapped with the activation process if it is assessed that the likelihood of the site being rejected is low. In this scenario, the study package can be sent to the site as soon as the CDA is signed, resulting in an overall compression of the schedule from 36.4 weeks to 30.4 weeks.

This simple example underscores the opportunities conveyed by real-time operational insights and powerful predictive capabilities that can proactively guide clinical operation teams in the setup and execution of clinical studies. Moreover, these capabilities provide the foundation for the identification of white space and process optimizations that can be applied across the clinical trial continuum, transforming a process that has historically been sequential to one in which parallelization becomes the norm.

Morgan (craig.d.morgan@oracle.com) is responsible for directing the global marketing strategy and team for the Oracle Health Sciences suite of study startup applications. He is a technology and life sciences management professional with more than 15 years’ experience in the application of informatics and bioinformatics to drug discovery, and eClinical technology associated with starting clinical trials.