GAO-24-107634 Generative AI in Health Care
Science, Technology Assessment,
and Analytics
SCIENCE & TECH SPOTLIGHT:
GENERATIVE AI IN HEALTH
CARE
GAO-24-107634, September 2024
WHY THIS MATTERS
The health care sector faces many challenges, such as high
costs, long timelines for drug development, and provider
burnout. Generative artificial intelligence (AI) is an emerging
tool that may help address these and other challenges.
KEY TAKEAWAYS
» Several companies are developing generative AI tools to
speed up drug development and clinical trials, improve
medical imaging, and reduce administrative burdens.
» However, most tools remain largely untested in real-life
settings, and generative AI can create erroneous outputs.
» The technology raises questions for policymakers about
how to balance potential benefits with protections for
patients and their data.
THE TECHNOLOGY
What is it? Generative AI is a machine learning technology that
can create digital content such as text, images, audio, or video.
Unlike other forms of AI, it can generate novel content. For
example, using existing chemical and biological data, it can
create new molecular structures with desired characteristics for
use in drug development.
How does it work? Like other forms of machine learning,
generative AI uses algorithms that are “trained” on very large
datasets—ranging from millions to trillions of data points.
Training is the iterative process of feeding data through the
model until it can perform a specific task (see GAO-24-106946).
In the health care sector, generative AI models generally train
on a large volume of curated health care data, which could
include clinical notes, clinical trial data, and medical images.
Figure 1. Examples of Potential Uses of Generative AI in Health Care
OPPORTUNITIES
Generative AI has a wide range of emerging uses in health care,
which vary in maturity. Some examples include:
Developing drugs. Generative AI can design new drug
candidates, which could accelerate development timelines
by replacing the conventional manual design process. Like
conventionally designed drug candidates, generative AI-
designed drugs must be validated and interpreted by
researchers, and safety and efficacy must be
demonstrated in clinical trials. As of December 2023,
around 70 drugs developed with some assistance from
generative AI were in clinical trials with patients, though
none are on the market, according to recent studies.
