The pharmaceutical industry is experiencing a seismic shift in the way clinical trials are ideated, designed, and executed. Influenced by the evolution of technology, shifting regulations, and a focus on the patient voice, the world of clinical research is changing at light speed. This article considers the main attributes that are informing clinical trials today: decentralized clinical trials (DCTs), digital health, adaptive designs, updated regulations, and real-world data.
Clinical trials have long been an integral part of the evidence-generation process in pharmaceuticals. All too often, studies were executed in a rigid, site-based model without enough flexibility. In the last decade, however, with an increased pace of change, especially because of the pandemic, we have begun to see some of the long-standing traditions challenge traditional parameters of trial conduct. Today, we are focused on speed, scale, diversity, and data integrity, which forces us to reconsider how we do trials.
The use of DCTs is one of the most significant paradigm shifts in the trial landscape, inspired by the fact that DCTs minimize site visits and allow for telemedicine, home health, mobile technology, and direct-to-patient medication delivery.
Benefits of DCTs include:
• Improved patient recruitment and retention
• Improved access to participants in rural or underserved populations
• More flexible options for patients at visit times
Pfizer, Novartis, and Sanofi have all responded to the pandemic-led changes and patients’ changing expectations and have adopted DCTs in some way in their trial protocols
By partially automating processes where they can, AI and machine learning are also used as supplemental tools in clinical research to improve efficiency in designing protocols, trial matching and patient enrollment, data monitoring, and even predicting adverse events in clinical innovations. Importantly, AI can also serve as a useful tool for adaptive designs by analyzing real-time information during trials to determine recommendations on whether trials should continue or be stopped, as well as dose modifications or cohort changes.
Some examples of digital health solutions used in trials are:
• Wearables to provide continuous biometric monitoring (e.g. Apple Watch, Fitbit)
• ePROs (Electronic Patient-Reported Outcomes)
• Remote eConsent
Digital solutions have the potential to enhance the richness of data and provide support to alleviate protocol deviations and site burden.
Adaptive trial designs introduce a flexible model of study design that allows for study modifications in response, for example, to the outcomes of interim analyses (e.g. sample size re-estimation, stopping ineffective treatment arms). Updated regulations, such as those endorsed by both the FDA and EMA to support adaptive trial designs, prescribe that it is possible to reorganize a study as a strategy to reduce time to market and ensure the most efficient use of medicines overall (e.g. invest in useful medicines). Adaptive designs have risen in relevance in therapeutic areas that have small patient populations or unmet needs, or in oncology and rare diseases where the demand for both speed and precision is high.
This model clearly offers some benefits in instances like oncology and rare diseases with limited patient sizes and significant unmet needs, requiring a flexible, nimble, and precise approach.
Regulatory agencies around the world are starting to change their rules to allow innovation without putting safety on the line. The FDA’s Project Optimus and Project Pragmatica and EMA’s Adaptive Pathways are tangible examples.
Moreover, the International Council for Harmonisation (ICH) is revising the GCP guidelines within E6 (R3) to be more approachable and relevant to contemporary trial conduct and techniques, including the use of digital tools, real-time interactions, and remote monitoring.
''Patient voices are no longer optional—they're the cornerstone of ethical innovation''
Patient-Centric Trial Designs
Patient engagement is no longer something to check off or a box to tick. Engagement brings projects to life. Increasingly, sponsors welcome patients into their protocol development, outcome selection, and even recruiting plans. The focus has moved towards including patients in more aspects of trial conduct. The participants, or a subset of them, are prized sources of strategic input, as they have the firsthand experience of participating in the study in question.
Some of the trends include:
• Designing trials around patient availability and circumstances (for example, home visits or flexible timeframes)
• Embedding diversity and inclusion frameworks
• Conducting and distributing trials with broader access
The use of Real-World Data (RWD) is becoming more widely accepted as an adjunct to, and sometimes even a substitute for, clinical trial data. It helps generate data more representative of routine clinical practice and broader populations.
Hybrid models combine both RCTs and RWE to maximize external validity and to understand and embrace other essential forms of scientific validation. As an example, pragmatic trials embedded in electronic health records (EHRs) will enable the generation of the best pivotal evidence of drug efficacy, suitable for review by regulators and payers to expedite approval.
“Today, trials aren't just about data—they're about access, diversity, and digital empowerment.”
The innovation is impressive but has introduced some uncertainty and challenges:
• Data collection, cybersecurity, and data privacy risks
• Interoperability issues with digital platforms or applications
• Diverse regulatory expectations
• The need to mitigate verifiable bias for validation of AI and algorithms
• Lack of talent or experience in clinical operations development and program management
The clinical trials landscape in the pharmaceutical industry is undergoing a revolution. Decentralized trials, the integration of AI, adaptive designs, and patient-centric practices are fundamentally changing paradigms. Although some barriers exist, it is evident that we are moving towards a more efficient, inclusive, and data-led future. As stakeholders continue to invest in research and as digital technologies spark a modern clinical research revolution, it will require the development of partnerships and collaboration between industries, regulators, and patients to fully adapt to the modern version of clinical research.
According to Deloitte, 75% of clinical trials are expected to adopt some DCT elements by 2027.
By Veena Reddappa
MSM/SE