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在产品生命周期管理中对人工智能和机器学习的审查

Maria Ana Martins da Cruz Borges Batalha¹, Daniel Alexandre Marques Pais², Rui Alexandre Estrela de Almeida²

¹Valgenesis Portugal, Lda maria.batalha@valgenesis.com.

PDA journal of pharmaceutical science and technology

|August 20, 2024

概括

人工智能 (AI) 和机器学习 (ML) 使制药制造商能够将未开发的数据转化为可操作的知识,以优化流程. 拥抱人工智能是未来竞争力和不断发展的行业中监管合规性的关键.

科学领域:

制药制造业制药制造业制药制造业
数据科学数据科学数据科学
过程优化过程优化

背景情况:

由于各种格式和系统,制药行业在利用大量制造数据方面面临着挑战.
过渡到Pharma 4.0需要增强数据捕获,存储和可访问性,以实现有效的过程操作.

研究的目的:

突出人工智能 (AI) 在将过程数据转化为可操作知识方面的关键作用.
强调人工智能在整个产品生命周期中支持关键功能的重要性.
为了强调AI驱动的制药制造业中数据完整性合规的必要性.

主要方法:

利用机器学习 (ML),人工智能的子集,使自主学习从制造数据.
分析各种专有数据格式和并行数据生成系统.
专注于人工智能应用程序的过程设计和优化.

主要成果:

人工智能有助于将原始过程数据转化为有价值的决策见解.
人工智能实施支持整个制药产品生命周期的关键功能.
人工智能的采用有助于驾Pharma 4.0的复杂性.

结论:

人工智能对于释放制造数据的潜力,以改善制药过程至关重要.
遵守数据完整性准则对于在受监管环境中实施人工智能至关重要.
人工智能驱动的转型对于制药行业的未来竞争力和性至关重要.

关键词:

人工智能的人工智能是人工智能.数字化的数字化生命周期管理生命周期管理机器学习是机器学习.药学4.0 制药公司制药和生物制药领域的产品.

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