Biosimilars in the Era of Artificial Intelligence—International Regulations and the Use in Oncological Treatments

Pharmaceuticals Pub Date : 2024-07-10 DOI:10.3390/ph17070925
T. G. Bas, V. Duarte
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Abstract

This research is based on three fundamental aspects of successful biosimilar development in the challenging biopharmaceutical market. First, biosimilar regulations in eight selected countries: Japan, South Korea, the United States, Canada, Brazil, Argentina, Australia, and South Africa, represent the four continents. The regulatory aspects of the countries studied are analyzed, highlighting the challenges facing biosimilars, including their complex approval processes and the need for standardized regulatory guidelines. There is an inconsistency depending on whether the biosimilar is used in a developed or developing country. In the countries observed, biosimilars are considered excellent alternatives to patent-protected biological products for the treatment of chronic diseases. In the second aspect addressed, various analytical AI modeling methods (such as machine learning tools, reinforcement learning, supervised, unsupervised, and deep learning tools) were analyzed to observe patterns that lead to the prevalence of biosimilars used in cancer to model the behaviors of the most prominent active compounds with spectroscopy. Finally, an analysis of the use of active compounds of biosimilars used in cancer and approved by the FDA and EMA was proposed.
人工智能时代的生物仿制药--国际法规和在肿瘤治疗中的应用
这项研究基于在充满挑战的生物制药市场中成功开发生物仿制药的三个基本方面。首先,八个选定国家的生物仿制药法规:日本、韩国、美国、加拿大、巴西、阿根廷、澳大利亚和南非代表了四大洲。对所研究国家的监管方面进行了分析,强调了生物仿制药所面临的挑战,包括其复杂的审批程序和对标准化监管准则的需求。生物仿制药在发达国家还是发展中国家的使用情况并不一致。在观察到的国家中,生物仿制药被认为是治疗慢性病的受专利保护生物制品的最佳替代品。在第二个方面,分析了各种分析性人工智能建模方法(如机器学习工具、强化学习、有监督、无监督和深度学习工具),以观察导致生物仿制药在癌症中普遍使用的模式,从而利用光谱学对最突出的活性化合物的行为进行建模。最后,提出了对用于癌症并获得 FDA 和 EMA 批准的生物仿制药活性化合物使用情况的分析。
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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