In drug discovery, companies face a long timeline and steep costs to receive drug approvals. The likelihood of getting to market successfully is less than 10%, according to a 2022 study.
“Even small advancements in time-to-lead optimization and improvements in the likelihood of clinical success are important to addressing the thousands of diseases that today have no known treatment or cure,” writes Anthony Costa, NVIDIA director of digital biology, in a HealthTecharticle.
Artificial intelligence helps with process control during drug production and can speed up time to market. Drug discovery and drug manufacturing are both part of pharma AI.
“Pharma AI refers to the broad application of AI technologies across the pharmaceutical industry, from drug discovery through manufacturing and commercialization,” explains Dan Sheeran, general manager for healthcare and life sciences at Amazon Web Services.
In manufacturing, pharmaceutical companies use AI and machine learning (ML) algorithms to boost efficiency, quality and reliability, Sheeran says. That includes using predictive maintenance of equipment to prevent unexpected downtime, AI-enabled digital twins for real-time process monitoring and optimization, and AI agents to orchestrate simulations and manual tasks.
“Ultimately, AI in drug manufacturing can lead to faster production times, lower costs, higher-quality products, reduced waste and potentially accelerate the delivery of life-saving medications to patients,” Sheeran says.
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