The Coming AI Revolution in Health Care
Artificial intelligence (AI) has the potential to transform health care by improving the drug discovery process.
Key Takeaways
AI is increasingly impacting the health care sector, offering promising avenues for cost savings and enhanced patient outcomes.
One key application for AI in health care is in the drug discovery process. The technology can help identify drug targets and treatments, as well as increase the likelihood of success of clinical trials.
AI adoption could trim as much as 10% off the $4.7 trillion per year currently spent on health care in the U.S., according to National Bureau of Economic Research and Peter G. Peterson Foundation research.
Market Minute: The Coming AI Revolution in Health Care
How Can AI Improve Health Care?
By improving the drug discovery process
By transforming clinical trials
AI for Every Step of the Drug Discovery Process
Disease Understanding
Researchers study the disease's biology and pathology to identify its underlying mechanisms and impacts.
How AI Can Help: Trend Recognition
AI can analyze large datasets to identify patterns and correlations in disease progression, patient demographics and response to treatments.
Target Identification
Scientists pinpoint specific molecules or genes involved in the disease that new drugs can target.
How AI Can Help: Predictive Modeling
AI can analyze biological data and predict which molecules or genes are most likely to be effective targets for new drug development.
Target Validation
The identified targets are rigorously tested to confirm their role in the disease and their potential for therapeutic intervention.
How AI Can Help: Biological Simulation
AI can create models that mimic biological processes, allowing researchers to test and validate the effects of targeting specific molecules or genes.
Druggability Determination
Researchers assess whether the validated targets can be effectively modulated by small molecules or biologics.
How AI Can Help: Inputs Screening
AI can evaluate a vast array of chemical compounds to identify those most likely to interact effectively with validated targets.
Clinical Trial Confirmation
Potential drugs are tested in human trials to confirm their safety, efficacy and therapeutic benefit in treating the disease.
How AI Can Help: Patient Categorization
AI can analyze patient data and group individuals based on specific characteristics, ensuring more accurate and efficient clinical trial design and outcomes.
AI in Clinical Trials: Overcoming Challenges & Optimizing Patient Selection
Problem
• An estimated 90% of drugs fail during clinical trials.¹
• Choosing a dosage that strikes the right balance between efficacy and toxicity is currently a formidable hurdle. AI can help define and model the optimal balance.
How AI Can Help
• Research databases containing vast troves of data, a prerequisite for applied AI, hold the potential for more advanced patient profiling and modeling.
• AI could also help select the clinical trial participants most likely to benefit from a particular treatment.
Breaking the Cycle: How AI Can End the Drug Discovery “Doom Loop”
For half a century, increasing amounts of time, money and technology have led to fewer drugs approved per dollar spent on research.
Rather than improving exponentially like computing power, drug discovery per dollar has halved every nine years since 1950, according to data cited by BofA Global Research.
AI could break that “doom loop” cycle.
AI has the potential to transform health care, delivering better patient outcomes and positive financial results for the companies harnessing its benefits.
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Duxin Sun, Wei Gao, Hongxiang Hu, and Simon Zhou, “Why 90% of Clinical Drug Development Fails and How to Improve It?” Acta Pharmaceutica Sinica B 12, No 7 (July 2022): 3049-3062.
Clinical trials: In the health care industry, a clinical trial is a research study conducted with human participants to evaluate the safety, efficacy and side effects of medical interventions such as drugs, devices, treatments or procedures. These trials are crucial for determining whether new therapies or methods are effective and safe for widespread use. Clinical trials follow a structured protocol that outlines the study's objectives, methodology, participant criteria and data collection procedures.
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