Novel Strategies Transform Clinical Trials Into Future Opportunities

For the rigorous evaluation of novel medicines, clinical trials are essential to ensure safety and efficacy. However, clinical trials are experiencing turbulent times due to challenges such as increased costs and advances in analytical methods. Bound by rigid requirements, traditional trial designs lack the flexibility to apply new approaches to studies and adjust to the pace of technological and scientific advancements. Data privacy concerns and the demand for broader representation and transparency have modern clinical trials navigating a host of scientific, ethical, and operational complexities. But their potential to assess a host of diseases and chronic conditions is greater now than ever before. Here to explain these challenges and the novel approaches used in today’s modern trials is Westat’s Adam Yates, PhD, a Principal Statistical Associate for Clinical Research.

Q. Clinical trials have long relied on established design features like control groups, randomization, and blinding. What are some of the key challenges that today’s clinical researchers face in applying these standards—particularly in studies involving rare diseases or hard-to-reach populations?

A. Clinical trials examining rare diseases can be challenging for both trial planning and implementation, mainly because of the difficulty and complexity of recruiting enough people with these diseases. Recruiting hard-to-reach populations presents similar challenges, requiring convoluted planning efforts. Trials involving these populations tend to be longer, resulting in increased costs and complicated data analysis. Also, protecting participants’ personal health information is a challenge because it’s at risk of disclosure due to the often small number of trial participants, the populations from which they come, and increasingly common publishing requirements that manuscript data be publicly accessible. Especially with artificial intelligence (AI) and machine learning (ML) tools increasingly accessible, we have to work harder to mask participants’ identities and safeguard their health information.

Q. Many modern health conditions—such as chronic illnesses, cancers, and genetic disorders—require long-term studies to evaluate treatment impact. How do these extended timeframes affect clinical trial design and participant engagement?

A. Trials for these conditions may demand participant involvement lasting over a decade. This means keeping participants engaged, meeting increased staffing costs, storing biological samples, and even ethical considerations of withholding potentially beneficial care from the comparator group. The speed of scientific discovery and advancement increasingly presents new challenges for trials with extended observation times as well. Classic clinical trial designs can be risky for lengthy longitudinal studies because they are less adaptive to new circumstances or information. They’re not designed to be changed very much once they begin, and this is where modern clinical trial designs can be really powerful.

Q. With the rise of advanced tools and techniques for analyzing complex data, what are the benefits and trade-offs of incorporating these into clinical trial design?

A. Certainly, AI and ML methods are powerful tools for investigating complex data. They are well-suited to identifying patterns and associations in large volumes of data and have even been shown to detect deviations in patterns, such as those in MRI scans for tumors or blood clots, earlier than humans can detect them. A trade-off, however, is that while AI, ML, and natural language processing (NLP) methods thrive when they can draw on large amounts of data, leveraging these techniques with smaller data sets can be more challenging. Applying these tools in clinical trial design is an area of exciting exploration with potential to greatly improve adaptive clinical trials. Westat has developed the WesLytics platform to leverage these tools in an integrated and dynamic ecosystem to maximize the application and utility of these methods. When working with our clients, we navigate these issues from a considered perspective, incorporating design, data science, and biostatistical viewpoints from our in-house experts.

Q. Ethical considerations have always been part of clinical research, but modern studies raise new concerns—from data privacy to questions about withholding care in control groups. How are today’s researchers navigating these evolving ethical landscapes?

A. I think one of the most promising and exciting ways modern clinical research can address some of the leading ethical concerns is through the development of “synthetic data” applications. Synthetic data are artificial data designed to mimic real-world data, generated through statistical methods. The data retain the underlying statistical properties of the original data on which they are based, enabling evaluation of risk and quality while increasing utility. Synthetic data can supplement or even replace real datasets in testing, training, and research settings. This presents opportunities to address some key ethical considerations, such as placebo/comparison groups being necessary but requiring denial of potentially beneficial care, or concerns over the disclosure of participants’ public health information.

For example, Westat is developing a synthetic data tool kit using AI, focused on privacy protection of real-world patient health data (made up of over 30 billion rows of data). While it is still an area of active statistical research, the use of synthetic control groups in clinical trials has many exciting potential benefits. Westat is actively exploring work in this area with various partners, including the generation and validation of synthetic control arms in clinical trials, and synthetic data use for “digital twin” development using real-world data.

Q. Innovative trial designs like pragmatic trials, umbrella trials, factorial design trials, and even AI-driven approaches are gaining traction. What opportunities do these novel methods offer, and what hurdles do researchers face in implementing them?

A. There are a number of opportunities offered by novel approaches to clinical trials. These include flexibility and adaptability, and the capacity to simultaneously look at multiple interventions. But flexibility comes with some risks, as you can create situations where trial adaptations undermine the clarity of the data, and the trial becomes useless. Thus, it takes expert forethought, meticulous planning, and anticipation of the scenarios where biases could be introduced. And it requires rigorous staff training, validation, and statistical control to ensure the approach is scientifically defensible. Westat is well-positioned in this regard, as we can leverage the breadth of cross-disciplinary expertise to both anticipate and address trial planning challenges, as well as a multitude of other client needs.

Q. For those who may not think about modern clinical research every day, how would you describe the impact this work has on the health and well-being of Americans—now and into the future?

A. Clinical trials are a critical component for medical science to improve healthcare and better inform the development of health policies. By advancing trial design and implementation, we can develop new ways of collecting, generating, and testing data that meet the needs of advancements in analytical methods. These trials can lead to new findings, accelerate the discovery and application of interventions, and advance medical knowledge that can benefit future patients.