Can Digitizing Clinical Trials Help Reverse Eroom's Law?

By Ed Miseta, Chief Editor, Clinical Leader

Eroom’s Law models the decline in R&D efficiency of traditional pharmaceutical therapies.  Basically, it explains that even with the tremendous and continued advancements in technology—processing power, storage, and bandwidth capability (Eroom is Moore spelled backwards, as in Moore’s Law)—the R&D cost to bring a new drug to market is still increasing linearly.

Ryan Rossier, VP of platform solutions at healthcare consultancy Medullan, believes digitizing clinical trials is the way for pharma to reverse Eroom’s Law. “The R&D departments within companies need to take advantage of new and evolving technological advancements,” he says. “We see this happening in other areas, like biology, where the cost to sequence your entire genome will soon be less than a car payment.”

How exactly can digitizing clinical trials help to lower R&D costs? According to Rossier, approximately 30 percent of the time and effort devoted to clinical trials is spent recruiting and enrolling patients. Even with that amount of dedication, 48 percent of sites will under enroll or, worse yet, fail to enroll a single participant. He notes digitizing clinical trials will help lower R&D costs in two primary ways: Recruitment and enrolling patients faster. Digitization will also ensure participants stay for the duration of the trial.

In addition, digitization of clinical trials can:

• Enable remote and electronic data collection, removing the need for physical sites and reducing the need to collect and process data from case report forms
• Provide online education and learning materials
• Enable adaptive clinical trials to capture, clean, and interpret data in a near real-time fashion for higher quality, shorter, and less expensive clinical trials.

“With broader acceptance and adoption of online social platforms such as Twitter and Facebook, sponsors and others responsible for recruitment can reach a much wider demographic in a much more scalable way,” says Rossier. “One example from Australia shows the power of utilizing Facebook ads to recruit women aged 16 to 25 to participate in a health study.  The study resulted in an average cost in advertising fees per compliant participant of U.S. $20, making the effort highly cost effective.”

In conventional designs, research progresses in a waterfall type fashion. The trial is completed, results are analyzed, and the compound is (or isn’t) advanced to the next research phase. Decisions regarding dosage, randomization, and sample size are made in advance and fixed throughout the study. Using this probabilistic approach, studies have to be large to ensure statistical significance. Unfortunately, timelines can run in years and investment can run into the millions of dollars before there’s any demonstration of success or failure.

“In an adaptive trial, data are analyzed at designated interim points, allowing researchers to use results to focus the trial on the most promising doses, disease indications, or patient populations,” Rossier says. “The study design is not fixed, but rather defined based on the analysis and interpretation of data along the way. Using this approach, early findings can be used to redirect the trial toward the most positive outcome. One example would be halting the evaluation of a dose that interim analysis shows to be ineffective and reallocating those patients to one that has shown positive initial results. This continuous, data-informed process increases the likelihood of success, or just as importantly, reduces the investment into a product that is bound to fail.”

Make Adjustments With Real-Time Data

Real-time data is just one ingredient that enables trials to “adjust on the fly.” To take full advantage of real-time data capture, researchers must start with a flexible or adaptive study design. They must also have the process and technology capability to cleanse, analyze, and interpret the data being captured in near real-time to make adjustments to the trial at the interim milestones within the study.

For those concerned about FDA approval, Rossier notes the agency promotes the use of electronic data capture (EDC) due to its reliability, quality, integrity, and traceability of the clinical data. The FDA also has several guidelines related to security and compliance of EDC to ensure confidence in its reliability, quality, and integrity.

FDA provided draft regulation guidance on adaptive clinical trials in 2010 as an update to a 2006 Critical Path Opportunities Report calling for the development of new adaptive design methods to increase trial efficiencies. The 2006 report promotes the advances in research by applying early data to improve decision making.  

“Digitization of clinical trials has the potential to save significant time, and as a result, significant cost,” says Rossier. “Some reports suggest clinical trials cost $35,000 per day on average. When you include foregone revenue upwards of $600,000 to $8 million per day, you can see why this is such a hot topic.”

Challenges To Overcome

There are still challenges that must be overcome for any company wanting to digitize clinical trials. The first is rigid internal clinical development processes and a lack of willingness by individuals to experiment with study and clinical trial design. With the cost of trials being so high, adaptive trials can still be seen by any companies as a risky and unnecessary endeavor. Rossier notes in many companies there is also a lack of internal expertise on digital solutions and the enabling technology platforms. Finally, the regulatory requirements of data management and security may be something many companies have not considered or had to deal with before.

While none of these concerns are insurmountable, they can still make many executives wary. “For me, it’s all about addressing the inertia in what is typically a very conservative industry,” notes Rossier. “Although the experience level within companies is increasing, many drug developers remain cautious in their approach to digitizing clinical trials. Everyone seems to be taking a wait-and-see approach before investing heavily, seemingly not concerned with the downward trend of R&D efficiency. This creates a terrific opportunity to disrupt the status quo, show the value and benefit, and force others, including regulatory bodies, to be a part of the solution.”

Consultants and knowledgeable CROs will certainly help. Consultants are able to offer expertise that may not exist in-house. CROs offer expertise and experience in statistical methodology, regulatory affairs, and trial conduct. CROs that will be most helpful in the future will have an in-depth understanding of adaptive design and likely partner with digital health experts and those with the operational infrastructure necessary to support adaptive study execution.

The electronic technology platform necessary to support such studies will also be a key component moving forward.  To shape trials based on interim results, data must first be collected, monitored, cleaned, and analyzed quickly, accurately, and reliably.

“Currently, early adopters are taking on the burden of creating the patterns needed in digitally enabled clinical trials,” adds Rossier. “Within the next five years these emerging patterns will be tried and tested and will forge the path for adoption by all. Within 20 years, health care providers will be prescribing digital applications more often than they’re prescribing pills.”