Statistics suggest that Phase I clinical trials, while by no means free of challenges, are more manageable than later phases. They tend to take less time and cost less money; the drugs they test have a comfortable 70% chance of moving on to the next phase.1 These figures are a reprieve from some of the realities that make Phase I trials, in some respects, uniquely stressful. The absence of a safety profile for the drug being tested can make subject recruitment particularly challenging. And any errors or delays in Phase I can set the tone for the rest of the drug development process.
But what if the statistics that ease these pressures – the shorter timelines, lower price tags, and high success rates – are changing? A blogger at Bracken Data, a company providing analysis of clinical trial data, recently noted that the size of the average Phase I clinical trial seems to be increasing. Based on searches on ClinicalTrials.gov, the average Phase I enrollment increased 14% between 2013 and 2015, from 50 to 57. More patients could mean more sites, more forms, and more data, adding time and, consequently, expenses to these trials. This could be exacerbated by other trends adding complexity to Phase I, such as higher rates of outsourcing to CROs and study designs that integrate single ascending dose (SAD) and multiple ascending dose (MAD) approaches.2
If the years ahead bring larger, more complex Phase I clinical trials, what can researchers do to stunt the spikes in timeline and expense that may come as a result?
Simple tools for complex data management
As drug development becomes more complex and expensive in Phase I and beyond, EDC has become almost synonymous with quick study build and data management. And as demand for EDC increases, the industry has been a venue of intense competition, with vendors racing to develop the next big thing.
But when it comes to creating efficiencies that keep timelines and costs down, truly elite eClinical software depends on more than the sleekest and savviest new product or feature; just as important is whether the software is actually user-friendly. When evaluating EDC vendors, researchers should analyze not only the capabilities of a given software, but the quality of its interface. How easy is it to move between forms and visits? Are users able to access forms for each subject in one convenient location with as few intermediary steps as possible? Is there a distinction between soft and hard edit checks, allowing users to bypass queries that aren’t as critical to address, or does the software slow users’ progress by requiring a data edit for every query? Can the software intuit which fields are relevant based on previously entered data, and accordingly remove irrelevant fields that could otherwise obstruct users’ progress through their forms? How feasible it is to minimize timelines in increasingly large and complex Phase I studies depends in large part on the answers to these questions.
This is a reality that companies like Medrio have kept in mind while developing their software. While Medrio regularly releases products, features, and upgrades that create new successes for users, one of the most popular qualities of the software is its basic user-friendliness. Its ease of navigation and intuitive interface have earned Medrio a reputation as an ideal software for efficient study build and data management. This, in fact, sets Medrio apart from some of the biggest names in EDC, who may have all the bells and whistles a researcher could ask for but still generate complaints about inefficient or overly complicated navigation. They may require users to scroll from one visit page to the next in order to access an eCRF instead of displaying all eCRFs in one easily accessible location; they may continue to display variables and forms that previously entered data has rendered irrelevant. Cases like these show that no matter how far-reaching the capabilities of an EDC software may be, users will still struggle if the software lacks efficient, sensible design.
Phase I clinical trials are already notoriously time-sensitive. If the analysis from Bracken Data and the current interest in integrating SAD and MAD approaches do indeed foreshadow a trend toward larger Phase I trials with more complex protocols, they will become even more so. Without the efficiencies made possible by an intuitive and user-friendly eClinical software, such a shift could cause timelines and budgets to spiral out of control.
1 FDAReview.org; The Drug Development and Approval Process; 2016
2 European Medicines Agency; Revising the guideline on first-in-human clinical trials [press release]; November 2016