Identification of high‐dimensional omics‐derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling

Identification of high‐dimensional omics‐derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling

Abstract Pharmacometric modeling can capture tumor growth inhibition (TGI) dynamics and variability. These approaches do not usually consider covariates in high‐dimensional settings, whereas high‐dimensional molecular profiling technologies (“omics”) are being increasingly considered for prediction...

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Bibliographic Details
Main Authors: Laura B. Zwep, Kevin L. W. Duisters, Martijn Jansen, Tingjie Guo, Jacqueline J. Meulman, Parth J. Upadhyay, J. G. Coen vanHasselt
Format: Article
Language:English
Published: Wiley 2021-04-01
Series:CPT: Pharmacometrics & Systems Pharmacology
Online Access:https://doi.org/10.1002/psp4.12603

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