As we celebrate another International Clinical Trials Day, it is vital to acknowledge the past, understand the present and improve the future of clinical trial practices and ergo, medicine. Clinical trials are the most fit for purpose way to test the efficacy and safety of new clinical interventions such as drugs, medical devices and/or medical equipment. In order to deliver these trials, it is important to develop fitting study designs that have evolved considerably over the past decade with innovative new approaches. As a result of this, modern day clinical trials generate scientific and clinical data more rapidly compared to its predecessors.

The history of Clinical Trials is an interesting one and dates back centuries with the first record shown in the “Book of Daniel” that showed, the King of Babylon, Nebuchadnezzar and his efforts to make his subjects healthy by asking that they follow a diet of meat and wine. Some of his subjects were vegetarian, thus, was not happy with this strict diet, but they managed to obtain permission to keep to their diet of water and vegetables. After the 10-day period, the King noted the vegetarians were healthier than those consuming meat and wine. This influenced the implementation of the first public health policy based on evidence.

Fast forward to the 18th century, intellectualism, precision and logic gave birth to empirical knowledge that brought about many scientific advancements and cemented the fundamentals of modern-day medicine. As a result, this gave rise to the Scurvy Clinical Trial James Lind performed in 1747 amongst sailors. Lind was a surgeon who understood dietary changes could assist with treating patients that showed symptoms of the disease. Hence, the British Navy at the time introduced Lemon juice to all those taking overseas journeys in a bid to treat and prevent the condition.

Around 100 years later, Nicola Tesla, one of the most understated innovative inventors of all time created the first AI tool which was a combined radio with an unmanned device which, in modern day, would be considered as a robotic drone. Whilst, Tesla did not perform a clinical trial, the patent application for his idea and design was submitted in 1897 with the robotic boat displayed at Madison Square Garden in 1898. Tesla referred to the boat’s circuitry as the “logic gate” which led to the birth of “teleautomation” or in other words, “robot”. This of course has influenced modern day devices such as Amazon’s Echo, Robotic Surgery and many other healthcare devices.

Robotic surgery and the use of AI based systems within medical equipment were the initial formative years of healthcare advancement that used Phase I and II design methodologies. With specialties such as Radiology, General Surgery and Oncology, relying more on AI for clinical practice and to conduct clinical trials, it has influenced many other specialties such as Psychiatry to include AI as well to better support patients.

To start with, psychiatry and mental health clinical research are using AI based tools more in clinical trials over the last few years as compared to other clinical areas. Furthermore, over the last decade or so, the use of real-world data (RWD) to better clinical trials and accelerate analytical tools to understand diseases across the board, have been a primary focus in the research community. Thus, it is not a surprise to use resulting clinical trial data or RWD to develop study setup and deliver using technologies that can utilise data effectively. RWD is commonly used as a predictive AI model or analytical tool to accelerate disease understanding, site selection, recruitment of participants and improve quality by design methodologies.

But to further improve clinical trials, researchers across healthcare, academia and industry are utilising concepts and tools of AI as well. This is further emphasised by the increase use of retrospective data residing within electronic health records, wearable medical devices and AI tools composed of machine-learning (ML) algorithms that supports acceleration of medical advances to expand experimental treatments. Furthermore, AI’s natural language processing (NLP) methods could allow better patient identification from clinical healthcare records whilst still maintaining good clinical and ethical practices.

AI has the ability to transform clinical trials and significantly improve efficiency as well as performance that could help accelerate drug and medical device development, reducing the current timescales taken to introduce these to clinical practice. Furthermore, AI also has the ability to act as a “digital intervention” itself promoting personalised medicine approaches to improve quality healthcare. Therefore, it is safe to say AI will continue to be the loyal ally and companion of clinical trials as move towards revolutionising medicine for our future populations of patients.

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Author Bio

Dr. Gayathri Delanerolle

Dr. Gayathri Delanerolle. Highly experienced clinical research professional with research interests in Medical Technologies, Operational interventions, AI, Women’s Health, Medical Devices, Translational Medicine and Personalised therapies. Clinical Trialist in a multitude of areas including Oncology, Surgery, Interventional Radiology, Pathology, Diagnostic Medicine, Neurology, Tropical Medicine and Cardiology. Currently attached to University of Oxford’s Brain Health Clinical Trials Unit.