AI-driven innovations in pharmaceuticals: optimizing drug discovery and industry operations

Jaskaran Preet Singh Saini, Ankita Thakur and Deepak Yadav
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Abstract

The integration of artificial intelligence into the pharmaceutical industry has led to significant transformation in the process of drug discovery and development and management of the pharmaceutical sector. Artificial intelligence has accelerated the process of drug discovery by several folds owing to its ability to analyse large datasets and predict drug–target(receptor) interactions, which effectively reduces the time and expenditure. AI enables clinical trial design and patient recruitment through predictive analytics during the trial. It also allows for real-time tracking of patient outcomes and predicts the effectiveness of a trial. Artificial intelligence-driven automation also assists in manufacturing and supply chain processes, enabling inventory optimization and predictive maintenance and thereby improving the productivity as well as affordability of these processes. The current review discusses various key applications, prospects, and challenges of AI in the pharmaceutical industry, focussing on its transformative potential while addressing the need for ethical and regulatory frameworks to ensure equitable and safe AI adoption.

人工智能驱动的制药创新:优化药物发现和行业运营
人工智能与制药行业的融合,使制药行业的药物发现开发和管理过程发生了重大转变。由于人工智能能够分析大型数据集并预测药物-靶标(受体)相互作用,从而有效地减少了时间和支出,因此将药物发现的过程加快了几倍。人工智能通过试验期间的预测分析实现临床试验设计和患者招募。它还允许实时跟踪患者的结果,并预测试验的有效性。人工智能驱动的自动化还有助于制造和供应链流程,实现库存优化和预测性维护,从而提高这些流程的生产率和可负担性。当前的审查讨论了人工智能在制药行业的各种关键应用、前景和挑战,重点关注其变革潜力,同时解决道德和监管框架的需求,以确保公平和安全地采用人工智能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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