Advancing algorithmic drug product development: Recommendations for machine learning approaches in drug formulation-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Advancing algorithmic drug product development: Recommendations for machine learning approaches in drug formulation

Published:2023-12 Issue: Volume:191 Page:106562
ISSN:0928-0987
Container-title:European Journal of Pharmaceutical Sciences
language:en
Short-container-title:European Journal of Pharmaceutical Sciences

Author:

Murray Jack D.,Lange Justus J.,Bennett-Lenane Harriet,Holm René,Kuentz Martin,O'Dwyer Patrick J.,Griffin Brendan T.

Funder

H2020 Marie Skłodowska-Curie Actions

Irish Research Council

Publisher

Elsevier BV

Subject

Pharmaceutical Science

Reference135 articles.

1. Trends in small molecule drug properties: a developability molecule assessment perspective;Agarwal;Drug Discov. Today,2022

2. Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research;Agatonovic-Kustrin;J. Pharm. Biomed. Anal.,2000

3. Algorithms for finding patterns in strings;Aho,1990

4. Two decades of blackbox optimization applications;Alarie;EURO J. Comput. Optim.,2021

5. The curse(s) of dimensionality;Altman;Nat. Methods,2018

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predictions of biorelevant solubility change during dispersion and digestion of lipid-based formulations;European Journal of Pharmaceutical Sciences;2024-09

2. Exploring the Role of Artificial Intelligence and Machine Learning in Pharmaceutical Formulation Design;International Journal of Newgen Research in Pharmacy & Healthcare;2024-06-30

3. Comparative Analysis of Chemical Descriptors by Machine Learning Reveals Atomistic Insights into Solute–Lipid Interactions;Molecular Pharmaceutics;2024-05-23

4. Utilizing Publicly Accessible Machine Learning for Training Student Formulators in Personal Care Product Formulation: Specification-Driven and Cost-Conscious Experiments;2024-01-18

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3