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所在平台: Udemy |
课程主页: https://www.udemy.com/course/gamp-5-consideration-and-validation-of-ai-ml-gxp-systems/
课程评论：没有评论
课程名称：GAMP 5 - AI和ML GxP系统的考虑与验证 课程概述： 本课程旨在深入理解GAMP 5对人工智能（AI）和机器学习（ML）系统的视角，以及AI/ML的支持流程。学员将学习良好的机器学习实践（GMLP），探索AI和ML系统的验证，了解基于ChatGPT的计算机化系统和基于云AI服务的计算机化系统。此外，还将分析与生产系统如制造执行系统（MES）相关的商业案例。 课程范围： - 理解AI的主要概念及GAMP 5在AI与ML中的应用，包括概念阶段、项目阶段和操作阶段 - GAMP 5的机器学习子系统支持流程 - 良好的机器学习实践（GMLP） - AI和ML系统的验证 - 基于ChatGPT的计算机化系统 - 基于云AI服务的计算机化系统 - 基于MES的AI商业案例 通过利用AI的能力，制造商能够降低成本，提高效率，并最终改善患者的治疗效果。随着数字技术的不断进步，制药制造业在未来的转型潜力巨大。AI的持续发展将促使其在制药领域的应用不断扩大，推动创新、简化流程，并为新治疗和疗法的发展做出贡献。这种变革力量将重塑整个行业格局，促进更精确、高效和以患者为中心的医疗服务新时代的到来。 AI的整合不仅优化了现有的制造流程，还为药物开发、生产和分销开辟了全新的途径。这种向AI驱动的制药制造转变标志着医疗产品制造和交付方式的范式变革，承诺在全球范围内革新医疗保健。
The goal of the courseUnderstand GAMP5's perspective on AI and ML systemsUnderstand the supporting processes of AI/MLUnderstand good machine learning practices (GMLP)Explore the validation of AI and ML systemsUnderstand computerized systems based on ChatGPTUnderstand computerized systems based on cloud AI servicesUnderstand the business case related to production systems like MESScope of the courseUnderstanding the main concepts of AIGAMP 5 - AI & ML - concept phase, project phase, operation phaseGAMP 5 ML sub-system supporting processesGood Machine Learning Practice GMLPValidation of AI and ML systemsComputerized systems based on ChatGPTComputerized systems based on AI cloud servicesAI business case based on MES systemHarnessing AI's capabilities enables manufacturers to reduce costs, enhance efficiency, and ultimately improve patient outcomes. With the ongoing evolution of digital technology, pharmaceutical manufacturing is poised for further transformation in the years ahead. As AI continues to advance, its application in pharmaceuticals will likely expand, driving innovation, streamlining processes, and contributing to the development of novel treatments and therapies. This transformative power has the potential to reshape the entire industry landscape, fostering a new era of healthcare delivery that is more precise, efficient, and patient-centric.The integration of AI not only optimizes existing manufacturing processes but also opens up avenues for entirely new approaches to drug development, production, and distribution. This shift towards AI-driven pharmaceutical manufacturing represents a paradigmatic change in how medicines are made and delivered, promising to revolutionize healthcare on a global scale.
