The U.S. Food and Drug Administration (FDA) plans to introduce generative artificial intelligence (AI) across all centers by the end of June, following substantial workforce reductions that began last month. This means that tasks previously performed by humans will be entrusted to AI. Global pharmaceutical companies like Pfizer and Johnson & Johnson (J&J) are also deploying AI across various operational areas, from drug candidate discovery to pharmaceutical market analysis.
Martin Makary, FDA Director General, noted on the 9th (local time) that the pilot project implementing generative AI in scientific reviews has been successfully completed, stating, "We will gradually introduce AI to all FDA centers by June 30."
Last month, U.S. Health and Human Services Secretary Kennedy Jr. carried out a workforce reduction of 3,500 FDA employees as part of a broader federal workforce downsizing initiative. The restructuring encompasses not only support sectors such as technology, procurement, human resources, and communication but also includes senior scientists in key departments that oversee pharmaceuticals, medical devices, food, and tobacco.
The market has grown increasingly concerned that the FDA's workforce reduction may delay the approval of pharmaceuticals and medical devices. The FDA plans to fill that gap with AI. The agency announced plans to establish a fully operational generative AI system integrated with its internal data platform.
The FDA believes that by utilizing AI tools, it can enhance work efficiency and reduce review times. Director General Makary remarked, "I was surprised at the success of the pilot project conducted earlier," adding, "We need to reduce the inefficient repetitive tasks that have consumed so much time in the review process, and the introduction of AI technology can dramatically increase review speed."
The acceleration of AI adoption is not exclusive to the FDA. Standard Hee, Deputy Director of the AI New Drug Convergence Research Institute at the Korea Pharmaceutical and Bio Association, said, "Developing new drugs through traditional methods takes an average of 10 to 15 years and costs over 3 trillion won," noting that AI can drastically reduce these timelines, becoming an essential tool for pharmaceutical and bio corporations.
Particularly, last month, the FDA announced it would replace animal testing with organoid tests, which are mini-organs grown from cells. The FDA predicts that using AI will allow it to achieve the effects of animal testing through organoid tests. For corporations, it has become increasingly important to evaluate and validate new drugs using advanced AI.
According to the AI New Drug Convergence Research Institute at the Korea Pharmaceutical and Bio Association, the global AI drug development market is expected to grow at an annual average rate of over 30%, reaching approximately 10 trillion won by 2030. IT companies like Google, Amazon, and NVIDIA are developing AI drug development technologies and platforms, collaborating with various global pharmaceutical companies. Kang Jae-woo, a professor at Korea University, stated, "AI is no longer just a simple analytical tool, but is evolving into a 'scientist' that replicates the strategies of skilled human researchers and makes decisions."
Global major pharmaceutical corporations are actively utilizing generative AI not only for drug candidate discovery but also for various tasks such as pharmaceutical market analysis. Palantir Technologies, the largest defense technology company in the U.S., is targeting healthcare fields like precision medicine, healthcare resource optimization, and the acceleration of drug development as new markets. The company has established various analytical systems in collaboration with the U.S. Department of Health and Human Services and the Centers for Disease Control and Prevention (CDC).
However, there are voices of concern regarding the accelerated adoption of AI in the pharmaceutical and bio sectors. Critics point out that generative AI is not a universal solution. They note that when data bias occurs in AI, there is a lack of regulations or standards to control it, meaning human intervention remains necessary.
There is also the issue of jobs. The pharmaceutical and bio industries are sectors with significant job creation effects, yet there is a perspective that as advanced technologies like AI and robotics evolve, new job opportunities may decrease in the medium to long term.