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The digitisation of clinical drug development

In an ecosystem that is as large and complex as drug development, there continues to be an ever-lasting desire for innovation and integration of novel technology and applications. This indomitable spirit amongst the drug developers has successfully led to many novel drugs while introducing and opening new frontiers for all involved in clinical drug development.

With a lot of advancements in digital applications and technology, as drug developers we now have a plethora of options that were lacking nearly 20 years ago, when I started pursuing drug development. This is very encouraging and has opened up avenues of exploration and acceleration in terms of new drug discovery, research and development. More so, some of the innovative approaches that have been attempted within the last decade have fundamentally changed the way we approach the clinical drug development landscape both from a design and execution perspective.

High rate of failure

According to the Fact book 2014, released by the Center for Medicine Research International (CMR), the average success rate from first toxicity dose to market approval is only 4.9 % {1}. Although there are several reasons, that we can attribute to this high rate of failure, one that usually gets the most attention is the increasing number of so-called ‘late-stage failures’ due to their economy and scale. These are mostly Phase 3 studies in which primary efficacy endpoints were not met or safety signals emerged. For example, between the years of 1998 and 2015 there were 640 novel therapeutics in development, 57% failed because of inadequate efficacy and unable to meet the studied endpoints {2}. A publication from MIT, using two large data sets, showed a success rate of only 40% for Phase 3 studies {3}. This has led to several attempts to exploit the utility of digital data in clinical drug development over the years.

Digital endpoints

As we explore ways and means to expand our armamentarium for clinical drug development, there have been some promising exploratory activities in the recent past that have gained industry wide traction in different disease areas. This applies to the use of digital data, both quantitative and qualitative.

One area of interest is the use of technology to gain new endpoints to quantify disease improvement by measuring physical parameters in a quality that is acceptable from a regulatory point of view. Recently, with the passage of the Prescription Drug User Fee Act (PDUFA VI), FDA now considers the ‘patient’s experience’ to be an integral part of the benefit versus risk of new drugs to facilitate successful product development. 

To measure these patient benefits, new methods, including wearable devices, medical applications (apps), and even machine-learning programs, will be needed. Furthermore, tools for capturing the patient’s experience both quantitatively or qualitatively, can transform many aspects of drug development simultaneously enhancing the quality, reducing the timelines and the overall cost of drug development.

Continuum of real world data

Although, incorporation of digital data and endpoints can be undertaken in a number of therapeutic indications, there are areas of clinical setting where its impact can be immediate. These digital endpoints can be part of the “Real World Data” (RWD) making them an integral part of clinical trial design providing more valuable insights into patients qualitative and quantitative experience.

Since self-reported outcomes in particular are biased, I believe digital technology and applications can help us reduce the noise, refine the data while making it more robust and approvable. For example, the 6-min walking test that is widely used in respiratory drug trials is a surrogate mobility test that is a widely used measure and regulatory endpoint.

Another clinical example where we can apply digital data is Gait, which is a characteristic of the functional status in older patients have been shown to be associated with survival in community-dwelling older patients. However, studies that currently assess activity and mobility as primary endpoints are often based on patient’s self-reported outcome or performance testing (e.g., 6-min walking distance), both of which have significant shortcomings and vary among different classes of disease and clinical setting. Therefore, with the advent of emerging digital technologies, we can now measure many aspects of mobility in the ‘real world’ on a continuous and long-term basis that can be used as effective outcome measures in a variety of therapeutic indications and clinical settings.

Data from a recent COPD study using 3 devices (a Samsung smartphone, a physical activity monitor and a smart inhaler sensor attached to the metered dose inhaler) is illustrative of the power of such data and more importantly the feasibility of incorporating them into a clinical trial design {4}. Results from the first ever randomized clinical trial studying the effect of digital intervention in children with autism spectrum disorder {5}, demonstrated the efficacy of a wearable digital intervention to improve social behaviour of children with Autism Spectrum Disorder (ASD). Data collected from these and other such studies provides us the conclusive evidence that the integration of digital health in drug development is not only feasible but also yields valuable insights towards a better understanding of the disease pathology in a real world environment.

Future of the digital landscape in clinical drug development

It is evident that this new frontier will need a lot more engagement from all the stakeholders involved. There are several initiatives that have been launched with the aim of promoting and streamlining the adoption of digital health data in clinical drug development both by private enterprises and government. As demonstrated by this collaboration {6}, Sponsors are keen to embrace the application of digital data in their clinical trial design. However, we need to develop both operational and regulatory framework so this approach becomes more mainstream as supposed to being as an after-thought.

One of the most forward looking initiatives is the one driven by the FDA to address the challenges and working towards standardization. FDA’s pilot program, called the “Software Pre-certification Program” for software as a medical device (SaMD), launched earlier this year in January 2019, is an attempt to establish the much needed regulatory framework for all of us in the industry. This is a step in the right direction which I believe will lead to furthering the path of integration of digital data in drug development, so my industry colleagues and I have an enhanced armamentarium at our disposal.

About the author

Uma Arumugam, MD joined ICON in 2011 and has been involved in clinical drug and device development for over 20 years, encompassing all the phases of a clinical trial, covering a wide range of therapeutic indications that include few NDAs. His expertise and the breadth of knowledge he gained over the years enables him to offer strategic counsel, from study design through to filing registration dossiers.

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