Artificial intelligence and machine learning-assisted digital applications for biopharmaceutical manufacturing

人工智能和机器学习辅助的生物制药生产数字化应用

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Abstract

Artificial intelligence and automation are no longer just buzzwords in the biopharmaceutical industry. The manufacturing of a class of biologics, comprising monoclonal antibodies, cell therapies, and gene therapies, is far more complex than that of traditional small molecule drugs. Therefore, applications based on artificial intelligence are essential for successfully manufacturing this new class of biologics more quickly and more economically. Some biologics manufacturers, academic researchers, and young entrepreneurs have already begun implementing artificial intelligence-based applications to increase operational efficiency, enhance process understanding, improve process monitoring, and achieve better regulatory compliance. Regulatory guidance from health agencies on the use of artificial intelligence and machine learning is acting as a catalyst in the adoption process of these new technologies by the biopharmaceutical industry. Research in artificial intelligence and machine learning has also advanced significantly in the last decade. At the same time, new cloud technologies have made the development and deployment of machine learning applications much easier. Several examples of artificial intelligence and machine learning applications in monoclonal antibodies manufacturing already exist. Cell and gene therapy, which present the future of medicine, will also benefit from this new technology. Overall, advancements in this domain will essentially help better serve patients' needs.

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