As we look ahead to International Clinical Trials Day next week, it’s worth pausing for the few minutes it will take to read this blog, to reflect on the astounding changes that have taken place in the world of clinical trials over the last half-decade. Five major trends shape the patient data environment we work in and are likely to continue to shape what we do and how we work well into the future:

Clinical trials as evidence. For well over a quarter of a century, the duration of my professional career in Pharma, the randomized controlled trial (RCT) has been the sine qua non of clinical trials. Efficacy and safety data collected in this setting was the evidentiary standard that determined the fate of a new medical entity (NME) being developed for the marketing authorization. Today, while the RCT still reigns supreme in regulatory circles, these types of trials are no longer sufficient to guarantee success of a product launch. Multiple stakeholders – payers, providers and, refreshingly, patients themselves, demand other types of evidence to support the value of a new drug.  Increasingly, the RCT is now just a component, albeit a major one, of an increasingly integrated and diverse evidence package or value dossier. Thus the RCT no longer is a stand-alone entity; context and contribution to a bigger evidence picture now factor into the very fabric of trial design.

Diversity of evidence. Correspondingly, the world of clinical evidence collection has become increasingly diverse. “Real-world” evidence, in the form of properly structured epidemiologic studies, both retrospective and prospective, provide robust contributions to evidence packages. Health economics and outcomes data contribute directly to value dossiers. Patient reported outcomes, patient experience data, and broader patient meta-data such as adherence and compliance information, help establish direct patient impact of a particular medication. They also provide data to predict the health and cost implications of new therapies on the population in a health system. Finally, more recently, the impact of digitized “direct from patient” health information, is beginning to enter the trial scene. All of these different data types and sources, broadens opportunities for the clinical trialist and also begins to shift the focus of the data collection from the patient as necessary “bystander” to the trial process, to the patient as a direct contributor to the trial process. Which leads to the third trend.

Patient-centricity. Getting the “right medicine, to the right patient, at the right dose to get the right outcomes,” has been the espoused mantra of the clinical trialist seeking to bring new therapies to patients who need and will benefit from them (while minimizing adverse outcomes). Note, however, that in this aspiration, the voice of the patient is nowhere to be heard; a paternalistic “we know what is best for you” culture operates subliminally in most trial designs and execution plans. Increasingly, this is not acceptable to patients, who give not only their bodies, but their time, and energy, scheduling their lives and those of family, friends and care-givers around the needs the trial. Patients are now demanding more say in the shaping of a conduct the trial (visits, procedures, etc.), the impact of the trial on their lives, and the risk/benefit profiles that they will find acceptable. They want transparency and information (to the extent that can be shared without jeopardizing the outcome of the trial) and they form social networks to share this information among themselves. This can pose daunting challenges for a controlling trialist, but also offers great opportunities for recruitment, retention and engagement in ways that can truly benefit trials as well.

It’s not just the drug. Increasingly trials are no longer just about looking at the outcomes of a single NME. Many diseases require combination therapy and NMEs are often add-ons to existing treatment paradigms, or used in what are called “novel-novel” combinations. They are paired with “companion diagnostics” to help segment patients into populations most likely to benefit, avoid risks and determine the right dose. This population segmentation, called precision medicine, is turning once common diseases (think breast cancer or lung cancer) into rare diseases as more and more targeted therapies for specific disease (e.g., tumor) types, reach the trial environment. Furthermore, drugs are increasingly paired with devices, not only as delivery systems, but in integrated ways that monitor response and adjust dose. All this leads to complexity of trial design and execution, but again affords great opportunity towards better outcomes.

Phase I, Phase II, Phase III is “old school”. As the rare disease paradigm takes increasing hold in certain segments of drug development, orphan drug, break-through therapy, and adaptive pathway regulatory designations lead to trial development paradigms in which early development trials (previously Phase I and Phase II) actually can become registration trials. Adaptive designs also blur the phase transition boundaries, even if the “learn/confirm” standard remains the regulatory norm. This too leads to trial complexity, demanding much more meticulous upfront planning; it also affords the opportunity to get medicines to patients who need them in a much more accelerated way.

While these trends now shake the previously monolithic structure of what we do and how we work in clinical trials, they also lead to increased challenges, complexity and cost.  This is likely to continue well into the future, even as we strive for more standardization and harmonization of both data collection and trial execution processes. They are, however, what makes our work as clinical trialists among the most stimulating, diverse, fun and rewarding of all health care professions. And that indeed is cause for celebration!