儿科药物配方开发:利用人类味觉板并将其数据纳入机器学习培训中
Okhee Yoo1, Britta S von Ungern-Sternberg2,3,4, Lee Yong Lim1
1Pharmacy, School of Allied Health, University of Western Australia, Perth, WA 6009, Australia.
Pharmaceutics
|August 26, 2023
概括
人类味觉面板和人工神经网络 (ANN) 可以改善儿科药物味觉掩饰. 年轻人可以替代儿童,ANN可以预测苦味,优化配方开发.
科学领域:
- 制药科学 制药科学
- 药物运输 药物运输 药物运输
- 感官科学 感官科学
背景情况:
- 味道掩饰对于儿科药物配方来说至关重要,以提高坚持性.
- 使用儿童进行口味评估存在道德和实际挑战.
- 年轻的成年人 (18-40岁) 具有与儿童相似的味觉敏感性,使他们成为合适的替代品.
研究的目的:
- 审查人类口味面板和人工神经网络 (ANN) 在口味掩护儿科药物配方中的实用性.
- 探索年轻成年人作为儿童品味评估中的替代品的潜力.
- 评估ANN在优化口味掩饰策略中的作用.
主要方法:
- 使用人类口味板,包括选苦味检测值和使用评分系统.
- 雇佣年轻成年人 (18-40岁) 作为品味小组成员.
- 利用人工神经网络 (ANN) 和机器学习分类器来优化口味掩饰和预测苦味.
主要成果:
- 年轻的成年人可以作为儿童味道敏感性的有效代理.
- 在模拟复杂的口味掩饰变量和预测苦味强度方面,ANN显示出潜力.
- 评分系统和验收值可以在开发过程中增强配方评估.
结论:
- 人类味道小组和ANN提供了补充的方法来解决儿科药物中口味掩饰的挑战.
- 需要进一步的研究来确定各种药物分子的特定口味掩饰技术.
- 将机器学习算法与人类可接受性数据的精细化可以显著推进儿科配方开发.
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