by Dr Steven Anderson, Chief Scientific Officer, Covance
There are a number of factors that are driving changes in how clinical trials are currently designed and performed, and will have a continuing impact on future trials. Included in these factors are:
- An increased understanding of disease biology and biomarkers that support drug development.
- Flexible approaches for trial design.
- Data analytics and the impact of “big data” on trial design and execution.
- Patient-centric approaches for clinical trials.
- Partnering models for the key stakeholders involved in trial design and execution.
Basic and applied sciences are providing a better understanding of disease biology and the relevant biomarkers (diagnostic, prognostic, therapy response etc.) associated with specific diseases or subcategories of that disease. With that improved understanding, comes the increased incorporation of biomarkers in the design and execution of clinical trials. Biomarkers are incorporated in a variety of ways including exploratory endpoints, patient stratification and selection for study arms, all the way through the use as a companion diagnostic for an approved therapy. Biomarker driven trials are now common across all therapeutic areas and are important features of breakthrough therapy designations and the pathway for accelerated approval. Genomic and proteomic approaches to biomarker discovery and validation will support the continuing trend of the important use of biomarkers in the success of drug development.
Trial designs are also rapidly changing to provide flexibility and help adapt to regulatory approaches such as breakthrough therapy designations and accelerated approval considerations. This is particularly true in highly competitive areas such as oncology and immuno-oncology. The incorporation of biomarkers in basket and adaptive trials provides flexibility in study design and execution. The blurring of lines between phase I and II, and the rapid expansion of study cohorts based upon flexible study designs have significantly decreased timelines for drug development in areas like Oncology and the same or similar approaches should be relevant for other therapeutic areas.
The complexity of trials today results in increasing amounts of study data. Having appropriate analytical tools to help with study design, investigator performance and patient recruitment rates, as well as measures of safety and efficacy are increasingly important. There are, and will continue to be, an increasing number of data sources ranging from investigative sites, medical monitoring, lab data and mobile health information. The ability to assimilate, package and analyze those disparate data streams will be critical for trial success.
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Engagement of patients during the trial process will increase across therapeutic areas, expanding beyond the current patient-centric approaches in rare disease and orphan drug development. Finding ways to better meet patient needs, increase their understanding of clinical trials including specifics for their study, and the potential impact and burden for them and their families are important needs to address.
The complexity of trials also dictates additional considerations for interactions and relationships between all the key stakeholders - pharmaceutical/biotechnology companies, principle investigators and investigative sites, CROs and service providers, and the patients - for the trial execution and success. Flexibility, consultative interactions and new models for partnerships will help drive the way these relationships continue to evolve.
All of these features are not independent but rather interrelated. The relationships and interactions between these areas, and how they drive success today and in the future, will dictate how trials evolve and are positioned in the future.
