
Transforming research through patient-centric design and innovation
BackAuthors: Tom Mann & Samuel Salvaggio
Content published in Outsourcing Pharma.
1. What is driving the current evolution in clinical trial design?
There is an increasing focus on including patient perspectives in clinical trial design. Regulatory bodies are drafting new guidance that ultimately will drive pharmaceutical companies to truly integrate patient voices into trial design. This is crucial not only for ensuring real-world relevance, but it will also expedite the path to market. Some innovative companies are already embedding patient perspectives early in the process to deliver treatments that will align with patient needs and preferences. This shift in the clinical trial landscape will enhance both the therapeutic impact and the perceived value of new treatments.
Recent advancements in statistical methodologies and computing power are another key driver, enabling better utilization of the vast data collected during clinical trials. Recent regulatory initiatives, such as the FDA’s Project Optimus, are also shaping this evolution. Indeed, Project Optimus is trying to refocus oncology clinical trials to switch from the paradigm of maximum tolerated dose to introduce dose optimization, encouraging sponsors to ensure that treatments are effective but also better tolerated by patients.
As this trend continues, regulatory agencies are likely to expand their guidance to accommodate the new trend of assessing treatment effects through hierarchical composite endpoints that are multi-dimensional and ensure incorporating input from patients, advocacy groups, clinicians, and sponsors. By fostering clinical trials that assess treatment effect more holistically, the industry can improve treatment adoption and efficacy.
2. How does evaluating treatment effects from multiple assessments improve decision-making in clinical research?
Clinical trials generate vast amounts of data, yet regulatory approval relies on the assessment of the effect of a single primary outcome. While this can simplify analysis, it also underutilizes valuable information. Innovative and robust statistical methodologies allow for better use of all the additional data created during clinical trials and we can leverage this data to better estimate treatment effects. One of those methodologies leverages multiple outcomes hierarchically to estimate the Net Treatment Benefit (NTB) to reflect treatment effects.
With numerous papers published in peer-reviewed journals these past twenty years, Generalized Pairwise Comparisons, the methodology estimating the Net Treatment Benefit, established itself as a robust method to estimate treatment effects. Unlike traditional statistical assessments, it can integrate multiple clinically relevant outcomes- such as safety, efficacy and quality of life- hierarchically into a single statistical analysis. This approach provides a holistic view of a treatment’s value and resonates with diverse stakeholders, from statisticians to physicians.
In the end, the ultimate vision would be to allow patients directly to give input on how to build an endpoint that prioritizes clinical outcomes reflecting their preferences. Indeed, the stakeholders involved in clinical research might have different visions on what would be meaningful as an endpoint. For example, for some patients minimizing severe side effects may be as important as achieving clinical efficacy. Evaluating multiple outcomes acknowledges these varying perspectives, allowing for more nuanced and patient-relevant decision-making in clinical research.
3. How can we integrate patient perspectives into phase III clinical trials? What are the benefits and challenges of this approach?
Incorporating patient perspectives into clinical trials helps to ensure that these studies reflect the lived experiences of those they are designed to serve. This alignment not only enhances the perceived value of treatments but also fosters better patient engagement. By involving patients in selecting trial endpoints, researchers can produce data that is more relevant to real-world applications, ultimately leading to faster adoption and higher perceived value for the treatment.
Emerging technologies offer promising solutions. For instance, digital tools can capture patient preferences effectively and balance them against sponsor and clinician guidance to design endpoints based on patient real world needs.
However, achieving this integration is not without challenges as clinical research can be a conservative sector. Clinical and statistical innovation needs comprehensive evidence and case studies to be traditionally considered for trial design, making it slow to fully adopt these patient-centric approaches. Overcoming these hurdles requires a shift in perspective and the development of more effective strategies and tools to balance the needs of all stakeholders. One solution would be to discuss as soon as possible with regulators to propose these innovations and hear their feedback.
4. How does early strategic planning in trial design influence the efficiency and success of market access?
Strategic planning during early trial phases is pivotal for ensuring both efficient execution and successful market access. Engaging patients, payers, and clinicians upfront allows companies to identify key dimensions of treatment efficacy, safety, and tolerability. This collaborative approach ensures that trial data is collected with the aim to address the priorities of all stakeholders.
From a statistical perspective when using these innovative methods, leveraging more of the data collected during a trial will increase the statistical power and, thus reduces the number of patients needed for a trial. This in turn reduces time to market and costs, a win-win for patients and sponsors.
In terms of market access, the tendency for research and development departments to focus mainly on a treatment’s efficacy can be detrimental. Indeed, payers demand more comprehensive evidence, including real-world applicability and quantitative benefit-risk assessments. Estimators like the Net Treatment Benefit, which can integrate patient preferences and estimate multidimensional endpoints, enable a comprehensive benefit-risk assessment of a potential new treatment, making the data more compelling for market stakeholders.
Early planning is crucial to align trial outcomes with the complex needs of patients, clinicians, sponsors, regulators and payers. This will ensure smoother approvals and faster commercialization.
5. How have specific therapeutic areas benefited from the multidimensional assessment of treatment effects? Why are some areas particularly suitable for this approach?
Multidimensional assessment has proven particularly beneficial in therapeutic areas like cardiovascular disease and rare diseases. In cardiovascular research, numerous metrics, such as heart attack incidence and quality-of-life scores, are available, yet clinical events are often sparse. By prioritizing and hierarchizing these metrics, multidimensional assessments preserve their medical relevance while maximizing statistical power.
Rare diseases also stand to gain significantly. These conditions often involve small patient populations and complex disease profiles, making traditional trial designs challenging. Integrating multiple outcomes into a single evaluation framework can reduce the required sample size and provide a more comprehensive picture of treatment efficacy. This approach is invaluable in rare diseases, where patient recruitment is inherently limited.
6. Can you describe how this fits into the current regulatory landscape? What are the benefits and challenges?
Regulatory agencies, such as the FDA, are increasingly emphasizing holistic approaches to treatment evaluation. Recent guidance in rare diseases, for example, encourages the inclusion of patient perspectives and multidimensional assessments. While methodologies like Generalized Pairwise Comparisons and Net Treatment Benefit have gained traction in areas like cardiovascular research, other fields, such as oncology, are still awaiting their first trials employing Net Treatment Benefit as a primary endpoint.
Initiatives like Project Optimus demonstrate the alignment between regulatory goals and multidimensional methodologies. Dose optimization, a central tenet of the project, balances efficacy and safety—key elements in any benefit-risk assessment.
One of the challenges is promoting the adoption of these methodologies across therapeutic areas. While multidimensional approaches are conceptually straightforward, their statistical underpinnings can be complex, posing interpretability challenges.
Addressing these hurdles requires robust education and collaboration among biostatisticians, clinicians, and regulators to ensure broader acceptance and implementation.
Regulatory guidance will push the industry further, but the true transformation will come from companies that embed patient insights early in trial development. Tools that capture patient input in clinical research as early as before Phase II trials will stand out as game-changers. It will shape trials that resonate with patient needs, define new meaningful endpoints, and accelerate both approvals and time to market. This shift will establish patient-centricity as the gold standard for clinical research.