Why are clinical trials so difficult and so much work?

Written by Cmed

Have you seen many paradigm shifts lately?

Clinical trials are becoming more complex. There have been recent advances in how clinical trials are conducted, but how can we fully harness the benefits?

Cmed CEO, David Connelly explains in a recent Applied Clinical Trials article how new developments in technology really can sweep away old paradigms, to bring a much brighter future for clinical trials.

Accepting that studies can be difficult and complex, have we, as an industry, nevertheless overcomplicated the problem? A clinical trial can be considered as basically a scientific experiment involving people. The clinical data generated from subjects is key to determining the effectiveness and safety of the treatment. If this is the core data, then all other data and information can be considered as ancillary. Undoubtedly, this other data is important for many reasons: ensuring the study is well planned, managed, ethical, compliant, that the clinical data can be trusted.

But have we structured organizations and used technologies that fail to appreciate that the clinical data is the core output of a clinical trial? Have boundaries been created in the wrong places and silos inadvertently created?

So what?

When we try to integrate disparate systems to manage clinical data, the result is a patchwork of systems with inadequate interoperability and data all over the place: as has been called a “Frankenstein” of siloed systems. Despite laudable efforts toward industry data standards, we still end up mapping and reformatting data and meta data.

There are many consequences for patients and their families, doctors, nurses, study coordinators at the investigator sites and for our industry. The “insane cost of developing new drugs” when considering the high and late failure rate is well known, so too the consequences, including potentially good or life-saving treatments remaining undeveloped. A third of all new marketed products are found to have serious safety issues not recognized before in the clinical trial data.

What can we do?

Have a real commitment to bring about change and allocate the resources, financial, and people.

Build for flexibility and adaptability in a fast-changing world. One type of system or process probably doesn’t fit all, not for all types of trials, all products, in all sites, in all geographies. It is like saying we only need one type of motor vehicle, or one type of car, to meet all our transport or recreational needs.

Be brutal with legacy technology, organizational structures, job roles, and processes. Ask whose investment you are protecting — yours or the vendors? Look at the vastly scalable modern technologies being used elsewhere, including in our daily lives, and accept no less.

Be practical. For example, few people will argue that being able to have all sites enter or load clinical trial data into an electronic medical record (EMR) and then extract data from these systems looks like a more logical, streamlined approach that could save site staff work and potentially reduce errors. In specific studies, in certain situations and locations, this could be a great approach. As a scalable, viable solution within the next decade, this may be quite another matter. So, what can we do now?

Treat clinical trial data as if it is as valuable as gold dust, not sand. Invest in the application of modern data science technologies and expertise, live analytics, and AI rather than downplay data management.

The full article, The Ghost of Clinical Trials Past, Present, and Future by David Connelly appears in the December issue of Applied Clinical Trials