Machine learning and artificial intelligence in toxicological sciences
Abstract Machine learning and artificial intelligence approaches have revolutionized
multiple disciplines, including toxicology. This review summarizes representative recent …
multiple disciplines, including toxicology. This review summarizes representative recent …
Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling
Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development
and risk assessment of environmental chemicals. PBPK model development requires the …
and risk assessment of environmental chemicals. PBPK model development requires the …
A systematic study of key elements underlying molecular property prediction
Artificial intelligence (AI) has been widely applied in drug discovery with a major task as
molecular property prediction. Despite booming techniques in molecular representation …
molecular property prediction. Despite booming techniques in molecular representation …
The coming of age of AI/ML in drug discovery, development, clinical testing, and manufacturing: The FDA Perspectives
SK Niazi - Drug Design, Development and Therapy, 2023 - Taylor & Francis
Artificial intelligence (AI) and machine learning (ML) represent significant advancements in
computing, building on technologies that humanity has developed over millions of years …
computing, building on technologies that humanity has developed over millions of years …
How can machine learning and multiscale modeling benefit ocular drug development?
The eyes possess sophisticated physiological structures, diverse disease targets, limited
drug delivery space, distinctive barriers, and complicated biomechanical processes …
drug delivery space, distinctive barriers, and complicated biomechanical processes …
Artificial intelligence for quantitative modeling in drug discovery and development: An innovation and quality consortium perspective on use cases and best practices
Recent breakthroughs in artificial intelligence (AI) and machine learning (ML) have ushered
in a new era of possibilities across various scientific domains. One area where these …
in a new era of possibilities across various scientific domains. One area where these …
Application of machine learning techniques to the analysis and prediction of drug pharmacokinetics
R Ota, F Yamashita - Journal of Controlled Release, 2022 - Elsevier
In this review, we describe the current status and challenges in applying machine-learning
techniques to the analysis and prediction of pharmacokinetic data. The theory of …
techniques to the analysis and prediction of pharmacokinetic data. The theory of …
Adoption of machine learning in pharmacometrics: an overview of recent implementations and their considerations
A Janssen, FC Bennis, RAA Mathôt - Pharmaceutics, 2022 - mdpi.com
Pharmacometrics is a multidisciplinary field utilizing mathematical models of physiology,
pharmacology, and disease to describe and quantify the interactions between medication …
pharmacology, and disease to describe and quantify the interactions between medication …
The role of “physiologically based pharmacokinetic model (PBPK)” new approach methodology (NAM) in pharmaceuticals and environmental chemical risk …
Physiologically Based Pharmacokinetic (PBPK) models are mechanistic tools generally
employed in the pharmaceutical industry and environmental health risk assessment. These …
employed in the pharmaceutical industry and environmental health risk assessment. These …
Landscape analysis of the application of artificial intelligence and machine learning in regulatory submissions for drug development from 2016 to 2021
Q Liu, R Huang, J Hsieh, H Zhu… - Clinical …, 2023 - pubmed.ncbi.nlm.nih.gov
Landscape Analysis of the Application of Artificial Intelligence and Machine Learning in
Regulatory Submissions for Drug Development From 2016 to 2021 Landscape Analysis of …
Regulatory Submissions for Drug Development From 2016 to 2021 Landscape Analysis of …