Application of Pharmacokinetic Prediction Platforms in the Design of Optimized Anti-Cancer Drugs

Application of Pharmacokinetic Prediction Platforms in the Design of Optimized Anti-Cancer Drugs

Cancer is the second most common cause of death in the United States, accounting for 602,350 deaths in 2020. Cancer-related death rates have declined by 27% over the past two decades, partially due to the identification of novel anti-cancer drugs. Despite improvements in cancer treatment, newly appr...

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Bibliographic Details
Main Authors: Tyler C. Beck, Kendra Springs, Jordan E. Morningstar, Catherine Mills, Andrew Stoddard, Lilong Guo, Kelsey Moore, Cortney Gensemer, Rachel Biggs, Taylor Petrucci, Jennie Kwon, Kristina Stayer, Natalie Koren, Jaclyn Dunne, Diana Fulmer, Ayesha Vohra, Le Mai, Sarah Dooley, Julianna Weninger, Yuri Peterson, Patrick Woster, Thomas A. Dix, Russell A. Norris
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Molecules
Subjects:
MEK1
machine learning
toxicity
cancer
drug discovery
drug development
Online Access:https://www.mdpi.com/1420-3049/27/12/3678

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https://www.mdpi.com/1420-3049/27/12/3678

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