AI, Predictive Analytics, Big Data: How Technology Is Impacting Clinical Research, Drug Trials In India
Clinincal Trials In India: Technological applications contribute to a systematic patient recruitment process, ensuring better patient retention and monitoring in trials and improved data capture.
Over the last decade, there have been numerous examples across sectors of how technology and innovation have changed the way we live our daily lives — metros and online cab services have revolutionized transportation, “at-home” financial services have reduced the need to visit banks and onlineedelivery services preclude the need to visit restaurants or grocery stores. All of these factors have combined to make everyday life easier.
The impact of technology in the healthcare space, however, has been modest. Online doctor consultations and online pharmacies received a big boost during COVID-19 but these have not been as transformational as depicted. The impact of these technological advances in the area of clinical research has been even less dramatic.
In the wake of this the clinical research industry continues to face multiple challenges: high development costs, high attrition of candidate molecules, long development timelines, etc. During the peak of COVID-19, there were other operational challenges that the industry faced, including slower patient recruitment, lack of patient diversity and disruptions in scheduled visits leading to gaps in data collection among others. This has prompted the clinical trial industry to look harder toward innovation and technology to help address some of these concerns.
New Age Technological Application In Clinical Research
With the rise of technological applications, the clinical research sector also witnessed new solutions to circumvent these challenges. Innovations expected to make a difference include wearables, telemedicine, synthetic biology, artificial intelligence, big data and predictive analytics. These solutions would contribute to a systematic patient recruitment process, ensuring better patient retention and monitoring in trials and improved data capture.
Patient Recruitment in Clinical Trials: Studies have shown that patients having the same disease could be connected as a community to support each other as this would help them to navigate their patient journey more effectively. For example, patients with Alzheimer's could be connected with the support of non-profit foundations and patients’ caregivers. This provides companies engaged in clinical research access to a larger pool of potential patients who might benefit from enrolling in new clinical trials.
With the explosion of social media, these community groups are not restricted to a physical region; in fact, one could quite literally join these communities across the world, greatly enhancing the diversity of patients participating in clinical trials.
Telemedicine in Clinical Research: The government approval to legalise telemedicine in India on 25 March 2020 provided strong support for regular HCP-Patient communication. It enabled evaluation through a “virtual” medium at specified time intervals providing a much-needed detailed standardisation of documentation and quicker adoption of such technological advances for better outcomes.
Having the telemedicine option helps in better conduct of clinical trials in a number of ways. If a patient has to travel to the site for every visit, then the burden on the patient can be quite high. If at least some of the visits can be virtual, many more patients can participate and compliance with study visit schedules and patient retention are improved.
Remote data capture systems: The ability to regularly monitor patients and collect relevant information without having the patients come into the clinic was especially difficult during the last two years. Smartphone-based applications, wearables and mobile devices have helped in improving data capture remotely with remote data capture systems being either episodic (like capturing consent, adverse events, etc.) and typically captured through an applicationor continuous (like a continuous glucose monitoring device) and captured through a wearable device. While the first type is used much more commonly today, there are still challenges (availability of clinical-grade wearable devices, robust methods to capture, store and analyse this high-velocity data) that need to be addressed before the continuous remote capture systems become widely used.
Special care is needed to ensure that the data collected is stored appropriately considering privacy laws and is structured and organised to be amenable to further analyses. Some of the ways that these concerns are being addressed are through centralised data hubs and data lakes, and advanced analytical methods that could provide meaningful insights.
Decentralised clinical trials: The rise of virtual trials with the support of telemedicine and point-of-care diagnostic devices, door-step sample collection and analysis has supported the continuity of clinical trials. It should also be noted that depending on the type of therapy, hybrid models can also be implemented that include select visits to the principal investigator at the study site.
Managing Clinical Trial Data In The New Normal
With real-world data and evidence becoming more crucial to clinical trials, technological advancements and process innovations are now focused on the incorporation of these data sources into clinical studies. Clinical data management has also evolved over the last couple of years to provide high-quality data with a low number of errors.
Traditional data management platforms like Oracle Clinical, Medidata Rave, Veeva etc. are providing newer ways of collecting data through different sources. New players like Openclinica, Redcap Cloud etc. are enabling data capture from real-world sources as well. In addition, Elluminate and Veeva CDB are making it possible to bring together data from multiple sources more easily, standardizing and providing easier access to the data. This allows early identification of data-related issues and the opportunity to course correct almost in real-time.
The Way Forward For Drug Development And Clinical Trials
Advancements in technology in the clinical research sector hold tremendous promise for the future of trials. Technological innovations in the overall drug development process is not limited to just clinical development and advances in data management.
Predictive analytics and Artificial Inteligence (AI) has come a long way in supporting rational drug design process. AI has the potential to validate hit and lead compounds faster and provide accurate results of the drug target and optimised drug structure. Similarly, AI helps in poly-pharmacology, drug repurposing and drug screening. Similarly, Machine Learning (ML) has contributed imensly in the area of Quantitative structure-activity relationship (QSAR)-based computational model that is capable of predicting large numbers of compounds for its physicochemical parameters.
Even in the field of pre-clinical testing, technological advancements in process and procedures associated with in vitro cell based assays have been able to provide better characterization of a drug candidate's activity and specificity. These models can also be replicated using human cell lines in high through output screening in the potency of the new chemical entity in managing or treating a disease.
There are a whole host of innovations in the research area of clinical trials including implementing algorithms to predict the occurrence of diseases, identifying patterns in medical images, analysing complex genomic data, etc. Therefore, the collective advancement in scalable technological innovations in the preclinical and clinical stages of drug development has been able to bring about operational efficiencies that could lead to an overall decrease in drug development timelines and costs.
With AI, the Internet of Medical Things, predictive analytics and big data already being implemented and constantly improved, the role of technology in advancing the future of clinical trials will continue to improve in 2022 and beyond.
(The author is the VP, GDO India Head & Innovation Head, Parexel India)
[Disclaimer: The opinions, beliefs, and views expressed by the various authors and forum participants on this website are personal.]
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