模型模拟在药理学领域的应用以及理论可靠性的问题
Yoshiaki Kariya1, Masashi Honma2
1Education Center for Medical Pharmaceutics, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan; Laboratory of Pharmaceutical Regulatory Sciences, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan; Department of Pharmacy, The University of Tokyo Hospital, Faculty of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
数学模型在药物开发中至关重要. 通过先进的搜索算法和机器学习来提高参数值的可靠性,可以提高生物系统的模型准确性.
科学领域:
- 药理学 药理学是指药理学的学科.
- 计算生物学 计算生物学
- 系统生物学 系统生物学
背景情况:
- 数学模型在药物开发中越来越多地用于临床试验设计,疗效和毒性评估.
- 可靠的参数值对于准确的模型行为至关重要,但固定的或适合不良的参数可能会导致生物学上不准确的结果.
研究的目的:
- 要突出药理模型中的参数值可靠性的重要性.
- 引入先进的方法来改进药理动力学/药理动力学 (PK/PD) 和系统药理学模型中的参数确定.
主要方法:
- 建议使用综合搜索算法同时搜索所有参数值.
- 将这些搜索方法与机器学习技术相结合.
主要成果:
- 这些方法可以解决参数确定方面的挑战,从而导致更准确的模型输出.
- 在药理学研究中提高参数值和模型预测的可靠性.
结论:
- 对先前报告的参数值进行批判性评估是必不可少的.
- 先进的计算方法,包括机器学习,可以显著提高药理模型的稳定性和预测能力.
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