Clinical trial success is a key factor for pharma companies when designing and recruiting patients into trials. Performance data on principal investigators and clinical trial sites provides invaluable insights to pharma companies, helping them leverage successful sites and patient populations to maximize their clinical development feasibility and operations.
In a recent article in Clinical Leader, Randy Krauss, head and executive director of metrics, analytics, and performance, Merck & Co., Inc. stated after working in clinical operations for 20 years: “If you asked colleagues gathered in a conference room about their organization’s goals or what’s important to the organization, it’s possible they could not articulate an answer. If you asked them what they wanted to measure, there would be no shortage of ideas. There is a tendency to want to measure everything.”
When incorporating performance data into the clinical development, clinical trial feasibility and operations teams must strategically assess data such as patient populations, principal investigators, and trial sites to determine the potential for success.
Why Looking at the Past is Critical to Future Success
Analyzing performance data from previous trials gives us deeper insight into which patient populations may be more receptive to recruitment, which sites offer the most successful outcomes, and even which principal investigators have the best track record of operating a successful trial.
This data can also provide guidance in terms of diversifying clinical trials to include different types of population demographics such as age, gender, race, ethnicity, or geographic location. In addition, it can reveal areas where limited access or lack of resources have been an obstacle for successful recruitment outcomes.
What Worked and Did Not Work
Performance data from past clinical trials can give insight into the underlying reasons why successful outcomes were achieved, which is critical for clinical development teams to maximize overall trial success.
Performance data will provide information on factors such as patient recruitment strategies, selection criteria of trial sites, and patient population demographics. For example, data can show if a particular trial site had a high rate of successful recruitment or if different types of strategies were employed to achieve diversified enrollment.
Performance data can also lead to more efficient and cost-effective trial designs by allowing research teams to identify areas in which additional resources may be needed to support successful outcomes. By studying trends in previous clinical trials, they can better develop recruitment strategies that target specific patient populations or focus on particular geographic locations in order to improve the diversity of their trial design.
In summary, performance data provides valuable insights into how clinical trials are performing and what factors are influencing their success.
But understanding historical performance data is key to making informed decisions about how to set up a trial for optimal results—and importantly, diversifying study design and recruitment efforts.
Patient Population Insights
Performance data from past clinical trials can provide invaluable insight into how successful a trial might be. This data can give an indication of what types of patient populations are most likely to participate, which principal investigators are best suited for the trial, and which trial sites have been successful in the past. It also allows teams to assess the success or failure of previous studies and determine where changes could be made for better results. All of this information is critical when setting up a new clinical trial as it provides an indication of what strategies have worked in the past and what could be improved upon for future studies.
Digging into Diversity
In addition to understanding performance data, leveraging it to create diverse trial designs and recruitment efforts is essential for creating successful clinical trials. This is especially true for rare disease populations, where understanding the nuances between different patient cohorts is key to achieving positive outcomes. Performance data on past trials can help identify patient groups that tend to respond better to certain treatments, recommend specific principal investigators based on their track record in similar trials, and even suggest optimal trial sites based on historical performance. In doing so, organizations can ensure that their clinical trials are designed with diversity in mind—allowing them to tap into a greater range of patients and achieve more comprehensive results.
H1 – Better for the Future
H1 recently announced a partnership with the Michael J. Fox Foundation (MJFF) where H1’s platform represents more than 10 million healthcare providers globally and over 420,000 clinical trials, MJFF can support its mission of increasing knowledge about the lived experience of Parkinson’s disease, engaging patients in research and trials, and supporting the development of new treatments and a cure.
The Michael J. Fox Foundation will use Trial Landscape to streamline its search for physicians who are actively treating Parkinson’s disease and gather comprehensive information on their patient populations and treatment approaches. This data will be invaluable in identifying potential contacts for marketing efforts, allowing the Foundation to effectively reach out to physicians who are most likely to be interested in their initiatives. Additionally, Trial Landscape will help the Foundation gain insights into underrepresented patient populations to better understand the specific needs and challenges faced by these groups and develop targeted strategies to support them effectively.
It’s clear that performance data from historical clinical trials plays an important role in helping organizations create efficient and inclusive study designs and recruitment efforts for future studies. With the right data at hand, clinical development teams can make informed decisions about how best to design a study and recruit
participants—ultimately leading to greater success when it comes time for execution.
As such, pharma companies should take advantage of this valuable resource as they plan out their next round of clinical trials—ensuring diversity within study design as well as recruitment efforts so that they get the most out of their studies and achieve superior outcomes overall.