How Incorporating Artificial Intelligence in Drug Discovery and Clinical Trials Can Boost the Healthcare Industry?
One of the key technologies being deployed for medical research advancement is artificial intelligence (AI). AI is an umbrella term that encompasses various technologies such as machine learning (ML), deep-learning, supervised learning, and recursive learning. The usage of AI within medical research, specifically drug discovery and clinical trial, possesses the potential to improve the processes in various ways through better data collection and analysis, generation of virtual 3D models depicting drug and ligand binding interaction, designing of clinical studies, optimization of clinical trials, and real-world evidence analysis.
The global AI-enabled drug discovery and clinical trials market is in the nascent stage of development. Consequently, the macro healthcare industry factors such as rising emphasis on patient engagement and surging funding activities are expected to have a significant impact on the market during the forecast period. Additionally, various methods of AI integration employed by healthcare giants, such as Novartis AG, GlaxoSmithKline plc, and Eli Lilly and Company, are set to shape the market during the forecast period.
Incorporation of AI can benefit the healthcare stakeholders in various aspects such as improvement in medication adherence (during clinical trials), prediction of falling-out rate (participants not completing a clinical trial), analysis of potential drug compound (by generation of 3D models of drug-ligand binding interaction), and repurposing of existing drugs (discovering novel usage for an existing drug).
According to the market intelligence published by BIS Research, titled “Global AI-Enabled Drug Discovery and Clinical Trials Market — Analysis and Forecast, 2019–2030”, the market generated a revenue of $250 million in 2018 and is expected to grow at a CAGR of 24.88% during the forecast period from 2019 to 2030.
The growth of the market is driven by increasing drug development expenditure, facilitation of polypharmacology, and growing number of synergistic activities. In addition, there are several factors that are restraining the growth of the market, including lack of regulations and ethical issues.
The key strategies evident in global AI-enabled drug discovery and clinical trials market include collaborations and partnerships, fundings, product launch and upgradation, mergers and acquisitions, and others. Owing to the niche nature of the market, the majorly employed strategies for entering the market were partnerships and collaborations (48%) and funding (21%). These were followed by product launches (12%) and mergers and acquisitions (1%).
Other key players of the market such as Atomwise, Inc., Cyclica, Inc., and Standigm, Inc. also partnered with different pharmaceutical companies and universities. The partnerships accelerated AI adoption for large clinical datasets analysis and for virtual designing of the drugs.