News Center
Blog
The Transformation of AI Pharmaceutical Applications and Regulatory Frameworks
Release time:
2024-12-05
In order to ensure the safety and ethics of AI applications, as well as the correctness of their use, governments around the world are working to build a more comprehensive legal framework.
To ensure the safety and ethics of AI applications, as well as the correctness of their use, governments around the world are working to build a more comprehensive legal framework. The first global regulation specifically targeting AI—the EU's Artificial Intelligence Act—will take effect on February 2, 2025, setting a precedent for international AI governance. In the field of drug development, AI applications involve clinical diagnosis, monitoring, decision support for treatment, or patient interaction. The aim is to ensure the safety, transparency, and fairness of AI technology through strict regulations, but it can be anticipated that this act will also bring new compliance pressures and operational costs for businesses. The United States is also working to establish a regulatory system for AI applications in pharmaceuticals as quickly as possible. On January 6, 2025, the FDA released a draft guidance titled "Considerations for the Use of Artificial Intelligence to Support Drug and Biological Product Regulatory Decision-Making," which provides a systematic framework for the industry and stakeholders to assess and ensure the credibility of AI models throughout the drug development lifecycle, while encouraging applicants and other stakeholders to communicate with the FDA early to discuss AI model risks. In addition to regulatory factors, driven by steady improvements in algorithm efficiency, hardware efficiency, and the availability of training data, the computational performance of AI is expected to at least double in the coming year, enhancing its ability to make biological or medical predictions. However, biological systems are extremely complex, and transitioning from molecular-level predictions to cellular or human-level predictions is very challenging. Therefore, it is expected that more molecules discovered by AI will enter clinical trials, but the application process of AI in generating clinical evidence will be relatively slow.
Address: Zhigu Workshop, 2239 Longcheng Avenue, Zhonglou District, Changzhou City, Jiangsu Province
E-mail: info@anikare.com
E-mail: sales@anikare.com