Clinical Trial Innovation: A Year in Review and What’s to Come in 2019


Applied Clinical Trials

2018 has been an exciting year in the clinical trials industry, as we have seen many changes in novel concepts, and the evolution of some concepts to the point where initiatives and pilots are crystalizing into common practice.

2018 has been an exciting year in the clinical trials industry, as we have seen many changes in novel concepts, and the evolution of some concepts to the point where initiatives and pilots are crystalizing into common practice.  The biopharmaceutical industry is enthusiastic about defining and solidifying the new concept of patient connectivity and information exchange, whereas digital health and AI concepts are implementedin many different forms. Alternatively, the well-established field of quality, risk management, and vendor oversight dabbles cautiously into analytics and innovation.

The Evolution of Patient Information Exchange and Connectivity

The concept of patient information exchange (also known as patient connectivity) emerged recently and had seen rapid evolution. At the beginning of 2018, while many biopharmaceutical executives have been talking about the theory, TransCelerate formally introduced the concept of patient information exchange, which is centered on enhancing communications between sponsors and patients. Notably, the initiative focuses on tending to patients’ need for information before, during, and after clinical trial participation. This information includes incorporating the patient in study design, raising awareness about clinical trials with patients in their communities, providing supplemental materials to patients during clinical trials, and giving data back to patients after clinical trial completion.

Additionally, information exchange envelops study site feedback to improve the patient experience in clinical trials. Near the end of 2018, Janssen and BMS implemented their versions of patient connectivity; concretely, Janssen identified that the clinical trial landscape is very competitive, as the need for patients in clinical trials is much higher thanpatients are available. Hence, collaborative approaches with patients during study design is thought to be one major factor that attracts and retains patients by creating studies around patients’ lives.

Moreover, Janssen is focusing on establishing relationships through patient community outreach, and supporting study sites with tools, information, and resources (driven by behavioral science) to assist patients through the clinical trial journey. Janssen is also embracing social media to attract patients to studies. On the other hand, BMS is taking a different approach by leveraging internet technology to maintain patient engagement with BMS studies; definitively, BMS’s Study Connect program screens, refers and educates patients about clinical trials, and if a patient disqualifies, continues to engage them. It is clear that the realm of patient connectivity is broad, and the biopharmaceutical industry is tackling critical pain points first (i.e., recruitment and engagement); it is likely that we will see initiatives that give data back to patients in the future.

Digital Health is Gaining Ground

The vast domain of digital health includes many factions ranging from wearable devices to digital biomarkers, to remote clinical trials. Experts have indicated that the industry has a way to go before clinical trials adopt more digital approaches, as few validated health measures exist, regulatory frameworks are not clear, and healthcare pilots are episodic and unproven. However, others argue that forces, such as study visit centralization, continuous data collection, and sponsor needs for improved data quality will drive digital transformation. Novartis created new digital biomarkers/Electronic Device Reported Outcomes (eDROs) for vision with the FocalView application. Additionally, Merck leveraged smart-trial methodology by piloting at-home finger prick devices that enable patients to provide PK samples without having to go to a lab, and the pilot demonstrated that PK data variability was similar to that of a lab procedure. While digital health has a long path before becoming an established practice in clinical trials, digital health in clinical trials is an area that will grow, as marked by the emergence of smaller enterprises, such as THREAD Research and Medable, which are enabling sponsors to collect data remotely via Bring Your OwnDevice (BYOD) platforms. Additionally, Oracle’s move to also invest in digital health by offering a data management workbench for mHealth studies marks significance. Despite these strides in digital health, some experts are skeptical, as wearable devices still have muchroom to establish validity and may not be relevant for clinical trial data collection requirements, as many wearables are collecting rudimentary data (i.e., vital signs).

Blockchain and AI

While blockchain is commonplace in technology, cryptocurrency, and the Estonian healthcare system, the concept is still in its early stages in the biopharmaceutical industry. However, some visionaries see massive potential for blockchain in the biopharmaceutical industry and clinical trials. Blockchain can be used for screening and recruitment, source documentation, drug supply chain, and clinical trial registration. Alternatively, AI is at the forefront of clinical trials, as several AI-based technologies, such as AICure (which is experiencing growth), are emerging in the space.

Risk Management and Vendor Oversight

Quality management analytics have penetrated many areas in industry-based clinical trials, and are now starting to impact regulatory agencies. FDA stated they are implementing risk-based inspections by identifying high-risk sites through innovative tools and approaches. The biopharmaceutical industry continues to advance quality measures by incorporating quality tolerance limits (QTLs) to expand adherence with the new ICH E6 R2 guideline. QTLs are now impacting protocol design, risk management, study and vendor oversight, and clinical study reports. Additionally, quality measures are now permeating contracting departments to establish governing principles with vendors, enforcing quality deliverables, creating frameworks for communications and escalation, and ensuring alignment and accountability. The biopharmaceutical industry is also becoming more vigilant with vendor oversight, as they are aligning their performance communications pathways with vendors through technological, analytical, and subjective measures.

RBM practices are starting to scale in the industry, as several large biopharmaceutical enterprises have completed RBM pilots, adjusted their functions and roles, and are starting to ramp RBM activities on many studies. BMS, for instance, started with a few RBM pilots in 2012, and are now implementing RBM in around 120 studies, and are executing commonly known key risk and performance indicators including quality indicators, efficiency indicators, and cycle time indicators. On the technology front, RBM service providers are offering targeted solutions, as Cyntegrity (an RBM technology provider) introduced therapeutically focused risk assessment categorization tools (RACTs) (i.e., OncoRACT and medical device RACT), and others are focusing on safety signal risk management technology.

What’s to Come in 2019?

On the patient information exchange and connectivity front, we expect to see more biopharmaceutical companies targeting main pain points (i.e., recruitment, enrollment, and retention). In the next year, it is not likely that we will see clinical trial data exchange with patients post-study completion; however, this initiative will eventually be tackled. On the digital health front, we expect to see much advancement with new measures and validations using eDROs. On the blockchain and AI front, it is unlikely that we’ll see any blockchain pilots. Though, we expect more AI-based technologies to emerge and grow. In the risk management and oversight topic, we anticipate seeing more novel quality management concepts emerge to demonstrate alignment with ICH E6 R2, and see technology growth, as the guidance hints that technology usage is required to properly demonstrate adequate quality and risk management.


Moe Alsumidaie, MBA, MSF is Chief Data Scientist at Annex Clinical, and Editorial Advisory Board member for and regular contributor to Applied Clinical Trials.

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