人工智能和ATMP:患者优先.
Toni Manzano1, William Whitford1
1Summer 2025.
PDA journal of pharmaceutical science and technology
|November 24, 2025
概括
人工智能 (AI) 为分析复杂的高级治疗药物 (ATMP) 提供解决方案,解决化学,制造和控制 (CMC) 的挑战. 人工智能增强功效测试,过程监测和稳定性评估,同时确保数据保护和监管合规性.
科学领域:
- 生物技术是生物技术.
- 制药科学 制药科学
- 数据科学数据科学数据科学
背景情况:
- 先进治疗药物 (ATMP) 由于其固有的复杂性和可变性,存在独特的分析挑战.
- 目前用于功效测试,过程监测和稳定性评估的方法经常难以跟上ATMP的发展步伐.
- 全球不断变化的监管环境,包括数据保护法律,为ATMP分析增加了另一层复杂性.
研究的目的:
- 审查人工智能 (AI) 在高级治疗药物 (ATMP) 分析中的应用.
- 确定AI如何解决ATMPs化学,制造和控制 (CMC) 的挑战.
- 探索AI的整合,同时考虑数据保护和监管合规性.
主要方法:
- 对AI在制药分析中的应用进行文献综述,重点关注ATMPs.
- 分析用于实力测试,实时过程监测和稳定性评估的AI技术.
- 讨论监管方面的考虑,包括数据保护 (例如,GDPR,HIPAA) 和AI可解释性 (例如,SHAP值,物理信息的神经网络).
主要成果:
- 人工智能工具在提高ATMP分析的准确性和效率方面显示出巨大的潜力.
- 人工智能可以促进实时过程监测,并增强复杂生物学的稳定性评估.
- 解决数据隐私问题和确保人工智能模型透明度对于监管接受至关重要.
结论:
- 人工智能集成对于克服ATMP开发和制造中的分析障碍至关重要.
- 成功实施人工智能需要强大的数据治理和遵守全球隐私法规.
- 可解释的AI方法对于建立信任和确保AI驱动的ATMP分析的合规性至关重要.
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