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Artificial Intelligence: Unending Singularity in Clinical Research?
Biorasi Insights: Artificial Intelligence: Unending Singularity in Clinical Research?
By Neha Shinde and Sunny Kadam
Is Artificial Intelligence (AI) the new electricity? As the latest innovative spark in clinical trials, can AI justify the significant resources required to integrate it successfully?
Based on its ability to mirror and exceed human intelligence and perform automated tasks, AI looks set to transform every industry it touches, including clinical research. One crucial feature of this (re)evolution is the optimization of healthcare – enhancing the relationship between clinicians and patients. Technology continues to be an omnipresent engine of change in clinical research, across the development of safer and more effective pharmaceuticals and medical devices.
AI: Driving Analysis and Information in Clinical Trials
AI has the potential to become more than just a guide to follow during clinical studies, enabling the identification of optimal drug utilization across all study phases. For example:
- AI can alert project stakeholders if there is upcoming obstacle to the trial that will knock the timeline off course.
- AI can integrate information that has been compiled from diverse sources and platforms, inclusive of current and historical data.
- AI can predict trends to highlight the effectiveness of a drug and reduce the possibility of adverse events.
- AI can be used to meticulously review adherence to inclusion and exclusion criteria across the study.
- AI can be used to optimize patient retention and engagement.
Additionally, by integrating AI with other tech, solutions-driven strategies for treatment can be greatly enhanced. This is especially true for personalized medicine, allowing a predictive approach to patient outcomes, as well as accelerating critical studies that require rapid deployment, such as treatment for the recent COVID pandemic.
AI: Harnessing the Data
What about personalized medicine? As a medical model designed to empower individual treatment and optimize patient outcomes (including adverse reactions and safety), integrating personalized medicine with AI can only enhance this therapeutic solution. This proves especially true for study obstacles, such as time constraints, which require alternative solutions, quick decisions, and accuracy. By merging AI with diverse electronic systems, teams from different disciplines can collaborate seamlessly, uniting their efforts towards a common goal centred around solution-driven strategies for personalized medicine.
AI’s breakthrough in healthcare is based on data-driven training datasets. Validating this data has its potential challenges, including the speed of both analysis and results. Additionally, destratification of the source will be key to delivering conclusive data that is in line with ethical considerations. Regulation is also essential for overseeing the application of any technology. As the potential for AI’s widespread adoption grows, regulatory entities must acknowledge its significance and prepare policies to accommodate its extensive use. In clinical trials, data privacy and security have always been a priority as AI relies heavily on patient data. Robust data
protection protocols, anonymization techniques, and adherence to regulatory standards can mitigate these concerns.
Though AI is a transformative tool with diverse applications, it will still require team members with the skillset to maximize large-scale advantages. Further, considerable resources will be needed to accommodate the upgraded infrastructure and costs associated with AI. However, if these requirements are met, the boost to time and efficacy in clinical trials and healthcare could be revolutionary. The broad array of improvements would affect monitoring devices, telemedicine, chatbots, robotics, fraud detection, patient data security, risk management, and many more. Integrated with AI, these tools will promote patient convenience and reduce the burden on healthcare facilities/personnel.
AI: Making the Investment
Investing in AI, especially from the POV of startups and research organizations, will present benefits over time to help in streamlining clinical protocols, drug formulations, and optimization of clinical trials. AI is a dynamic tool, but the choice of its deployment is the key. Over the long-term, AI has the potential to have groundbreaking, lasting effects in the field of clinical research.
