Up and running
By: Kimberly Ray | March 08, 2017
How evidence-based decision making and working differently improves patient enrollment in clinical trials.
In the world of drug development, timing is everything. Every day that a drug can get to market sooner means that more lives can potentially be changed for the better. Yet the development process is plagued by delays at every step. From recruiting failures to protocol amendments that add months to the cycle time, we are losing precious time every day.
One area where these delays can be reduced is in rethinking site selection and start-up. At this year’s CROWN Congress, I'm giving a presentation on innovations happening in the site start-up space that promise to change the way we recruit for clinical trials. Here are some of the highlights:
Choosing the right sites is critical for the success of any clinical trial, but too often these decisions rely on limited data about a specific site’s access to the targeted patient pool. Part of the problem is that sites are not given enough time to conduct a proper feasibility assessment as everyone is trying to move as quickly as they can at the beginning of the study. This leads to high rates of failure in meeting recruiting targets. According to a Tufts Center for the Study of Drug Development (CSDD) report nearly half of sites in any given trial either fail to enroll a single patient or fail to meet their recruitment targets in the desired timeline. The rates of failure can be even higher in rare disease research and precision medicine trials that target highly specific patient populations.
But they don’t have to be. By harnessing analytics to figure out where patients are before sites are chosen, we can better support the sites in their feasibility efforts and eliminate some of the uncertainty in the site selection process. Through this approach, we evaluate de-identified patient data from multiple sources, including electronic medical records, insurance claims, and prescription information, to make evidence-based decisions about where patients are located. Once we have this information, we can create heat maps that show which trial sites are located closest to the largest patient populations, thus making the trial more accessible to patients in need.
This is especially useful in trials with inclusion/exclusion criteria that can eliminate a large percentage of a site’s patient population. In one example, we worked on an Irritable Bowel Disease study where an initial review of two sites showed both had about 350 patients diagnosed with Crohn’s Disease. However, when we reviewed which sites had patients that had never used a biologic treatment, which was a key inclusion criteria, the number of potential patients dropped eight-fold, leaving one site with more than 100 patients, and the other with just 16.
Being able to explore data to such a micro-level is going to enhance the way we recruit for trials, and can reduce the time and cost lost to working with sites that can’t enroll. Leveraging this data will benefit all the stakeholders in clinical research: the sites, the sponsors, and the patients.
Finding the right sites is only part of the efficiency solution. We also need to shorten the time to get these sites up and running. This is particularly important in precision oncology trials, where patients often can’t wait 240 days – the typical amount of time it takes to ramp up an oncology site (pre-study visit to site initiation) according to Tufts – before starting a treatment. A recent study from MD Anderson Cancer Center showed that even when oncology patients were eligible for a genomically-matched clinical trial, only one-in-ten went on to participate. One of the primary reasons for declining was timing of the trial.
If sponsors want to recruit and retain these hard to find patients, and move their trials forward faster, reducing the time to start-up is vital.
At QuintilesIMS, we are tackling this challenge by proactively preparing sites before trials even begin. As part of our Quintiles Precision Enrollment strategy, we’ve established a network of over 130 investigative sites across the U.S. that are committed to using this innovative process. In this model, a site is only opened after a patient is identified. Working this way eliminates the risk of investing in a site that can’t find these very specific patients and it opens access to more trials for the patients who need them.
However, to make this model work, we must be able to expedite the opening of a site once a patient is found. By using master contracts and rate cards, a central IRB and aligned processes, every oncology site in the Precision Enrollment network can be up-and-running within 21 days.
In a recent project, one of our network sites identified a renal carcinoma patient who fit the specific enrollment criteria for the study. The project team – site, sponsor and CRO – worked round the clock to get that site initiated in 12 business days to meet the needs of the patient.
We are tremendously proud of these kinds of accomplishments, and are excited about the possibilities that this innovative approach to recruiting brings to our clients, the sites, and the patients we serve together. We plan to expand it to other regions and disease areas over time. This model promises to be a game-changer for clinical research, and we believe that when companies have the tools and support to adopt this accelerated approach, it will cut months from the research process and help speed innovative new drugs to market.