信息学和人工智能指导的监管和翻译研究格局的评估在美国的第一类瘤药物,2018-2022年
Jay G Ronquillo1,2, Brett South1,2, Prakash Naik2
1Worldwide Medical and Safety, Pfizer Inc, New York, NY.
JCO clinical cancer informatics
|September 30, 2024
概括
开发新型癌症药物需要广泛的研究,一流的癌症治疗平均需要33年的目标研究. 生物医学信息学和人工智能有助于在这个复杂的药物开发管道中进行导航.
科学领域:
- 生物医学信息学 生物医学信息学
- 人工智能的人工智能
- 药物开发 药物开发
- 瘤学研究研究
背景情况:
- 癌症药物开发是一个复杂而漫长的过程.
- 第一类药物代表了重要的治疗进步.
- 生物医学信息学和人工智能为分析药物开发提供了新的方法.
研究的目的:
- 评估成功的第一类癌症药物的监管和翻译研究格局.
- 分析FDA批准的新一代第一类药物的特征.
- 利用生物医学信息学和人工智能来评估癌症药物开发.
主要方法:
- 对FDA批准的新一代第一类药物 (2018-2022) 的回顾性观察性研究.
- 根据癌症对抗非癌症的指示对药物的分层.
- 使用生物医学信息学管道与ChatGPT进行公共数据库数据分析.
主要成果:
- 在107种第一类药物中,有30种 (28%) 用于癌症治疗.
- 瘤药物需要平均33年的目标研究,而非癌症药物需要43年的时间.
- 94.4%的第一类药物至少有25年的目标研究出版物.
结论:
- 第一类癌症治疗的特点是多样化的标和加速的调节途径.
- 翻译研究指标是复杂的癌症药物领域的关键指标.
- 生物医学信息学和人工智能为药物开发挑战提供了可扩展,数据驱动的解决方案.
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