Jain Ashish, Salas Maribel, Aimer Omar, Adenwala Zahabia
Curis Inc., 128 Spring Street, Suite 500, Lexington, MA, 02421, USA.
Bayer Pharmaceuticals, Whippany, NJ, USA.
Drug Saf. 2025 Feb;48(2):119-127. doi: 10.1007/s40264-024-01483-9. Epub 2024 Sep 27.
Artificial intelligence is increasingly being used in pharmacovigilance. However, the use of artificial intelligence in pharmacovigilance raises ethical concerns related to fairness, non-discrimination, compliance, and responsibility as the central ethical principles in risk assessment and regulatory requirements. This paper explores these concerns and provides a roadmap to how to address these challenges by considering data collection, privacy protection, transparency and accountability, model training, and explainability in artificial intelligence decision making for drug safety surveillance. A number of responsible approaches have been identified including an ethics framework and best practices to enhance artificial intelligence use in healthcare. The document also recognizes some initiatives that have demonstrated the importance of ethics in artificial intelligence pharmacovigilance. Nevertheless, the major needs mentioned in this paper are transparency, accountability, data protection, and fairness, which stress the necessity of collaboration to construct a cognitive framework aimed at integrating ethical artificial intelligence into pharmacovigilance. In conclusion, innovation should be balanced with ethical responsibility to enhance public health outcomes as well as patient safety.
人工智能在药物警戒中的应用日益广泛。然而,人工智能在药物警戒中的使用引发了与公平、非歧视、合规性和责任相关的伦理问题,这些是风险评估和监管要求中的核心伦理原则。本文探讨了这些问题,并通过考虑人工智能在药物安全监测决策中的数据收集、隐私保护、透明度和问责制、模型训练以及可解释性,提供了应对这些挑战的路线图。已经确定了一些负责任的方法,包括一个伦理框架和增强人工智能在医疗保健中应用的最佳实践。该文件还认可了一些已证明伦理在人工智能药物警戒中重要性的举措。尽管如此,本文提到的主要需求是透明度、问责制、数据保护和公平性,这强调了合作构建一个旨在将符合伦理的人工智能融入药物警戒的认知框架的必要性。总之,创新应与伦理责任相平衡,以改善公共卫生成果和患者安全。