ARTICLE

How to Shorten Your Clinical Trial

Introduction

How to shorten the typical clinical trial is one of the most urgent questions in modern drug research and development.

The motivation behind it is obvious: Sponsors are under immense pressure not only to reduce drug prices, but also to bring therapies to patients faster. These two goals are at direct odds with the average length and cost of most trials. It is common for trials to take 10 years to complete, en route to accounting for more than one-third of the total price of drug development.

More positively, there are several promising options for shortening clinical trials. They include the implementation of adaptive designs.

The Pros and Cons of Adaptive Designs

With adaptive designs in place, it is possible to alter the structure of a trial based on relevant data collected throughout its duration. Because a trial can be dynamically refined as new insights come in, it can be streamlined to the point that it ultimately costs less than a traditional randomized double-blind study.

However, adaptive designs present unique statistical and regulatory challenges. More specifically, any adjustments to the data must not impact the statistical significance of the results. Any un-blinding - that is, for purposes of evaluating the accumulating data - will increase regulatory scrutiny.

Due to such hurdles with adaptive designs, they have not yet come close to overtaking randomized trials, which still account for the bulk of all clinical research. So, what can be done to accelerate drug development, short of modifying a trial’s fundamental design?

Exploring Other Options for Faster Clinical Trials

First, it’s important to note that many dimensions of a trial cannot be rushed without compromising its basic integrity:

  • Subjects have to be recruited and thoroughly screened.
  • Drug shipments must be coordinated and sent to the right sites.
  • On-site visits need to be conducted in accordance with established protocols.
  • Trial-related data has to be carefully entered, reviewed, and analyzed.

At the same time, there are some particular components of the clinical development process that can be sped up without sacrificing quality or accuracy. Let’s look at three of them in more detail, beginning, appropriately, with study startup.

Study Startup

This process alone can take more than eight months to complete, with delays that can rapidly cascade and greatly set back the trial’s progress. Its key tasks include selecting a site, compiling documents, and training clinical personnel.

Accelerating these activities and others is possible with the proper technologies. Clinical trial management systems (CTMS), electronic data capture (EDC) platforms, and electronic trial master files (eTMFs) have all been adopted to improve trial management. They have additional utility as ways to speed up study startup:

  • For example, the use of site-scoring algorithms can help in selecting the right sites.
  • Likewise, eTMFs can accelerate the compilation of essential documentation.
  • EDC and CTMS solutions can provide unified platforms for tracking site initiation, activation, and trainings.

Such technologies have greatly improved clinical development efficiency over the past 20 years, and they still have much untapped power for making clinical trials faster.

Market approval

What are the opportunities for faster market approval?

In the U.S., the Food and Drug Administration (FDA) has come under pressure to shorten the New Drug Application (NDA) review and approval process, so that therapies can reach patients faster. Legislation such as the 21st Century Cures Act exemplifies this ongoing push.

That progress aside, many in the pharmaceutical world continue to believe that the approval process cannot be shortened further without jeopardizing the quality of the review. In fact, the FDA already offers four pathways for expedited review: Priority Review, Breakthrough Therapy, Accelerated Approval, and Fast Track.

These routes can allow for approval in less than one year, compared to the decade-long process for standard end-to-end drug development.

Time to Submission

Shortening time to submission is perhaps the best single option for decreasing overall trial length. If successful, it streamlines a large range of activities. Indeed, the entire core of the drug development process - including the entry, preparation, and analysis of clinical data - sits between study startup and market approval, and can be improved by trimming time to submission.

How can you speed up the preparation and review of all of this data for the NDA? Once more, technologies like EDCs can yield substantial improvements here when properly applied. Shifting toward electronic management of the data entry and query closure processes will improve quality while reducing the risk of inconsistent or incomplete entries.

However, even with the integration of EDC systems, poor visibility and long review cycles can still be issues. That’s because in-stream data comes from numerous EDC platforms and in a variety of non-standardized formats. Accordingly, teams have to review and reconcile it alongside lab data.

This forced standardization is time-consuming and can complicate the identification of data quality issues and safety signals along the way. Working through so many disparate data domains and hierarchies means that trends and outliers are hard to spot, even after setting up a study data tabulation model.

In this context, heightening the visibility into in-stream clinical data is by far the most impactful action you can take to shorten time to submission. Doing so helps overcome the limitations of many EDC systems, which struggle to ensure data quality and support safety review without raising the risks of missing a critical signal. When clinical development teams have intuitive and user-centric clinical data analytics tools, they can better identify, investigate, and resolve issues with in-stream clinical data.

Review the webinar on combining medical review workflow with advanced analytics to drive faster submissions.