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Artificial intelligence (AI) and machine learning (ML) are no longer futuristic concepts; they are now part of how we live and work. The U.S. Food and Drug Administration uses the term AI to describe a branch of computer science, statistics, and engineering that uses algorithms or models to perform tasks and exhibit behaviors such as learning, making decisions, and making predictions. ML is a subset of AI that uses data and algorithms, without being explicitly programmed, to imitate how humans learn.
AI/ML’s growth in data volume and complexity, combined with cutting-edge computing power and methodological advancements, have the potential to transform how stakeholders develop, manufacture, use, and evaluate therapies. Ultimately, AI/ML can help bring safe, effective, and high-quality treatments to patients faster.
For example, AI/ML could be used to scan the medical literature for relevant findings and predict which individuals may respond better to treatments and which are more at risk for side effects. Conversational agents or chatbots, which are based on “generative” AI, have the potential to answer people’s questions about participating in clinical trials or reporting adverse events. Digital or computerized “twins” of patients can be used to model a medical intervention and provide biofeedback before patients receive the intervention.
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