AI Medical Compendium Journal:
CPT: pharmacometrics & systems pharmacology

Showing 1 to 10 of 38 articles

Push Forward Clinical Management of Hematological Toxicity due to Lenalidomide Overexposure: Model-Informed Precision Dosing for Chinese Population With Renal Insufficiency.

CPT: pharmacometrics & systems pharmacology
Dose-dependent hematological toxicity of lenalidomide has been reported previously, and thus, there is a clinical need for dose individualization to manage toxicities. The objectives of this study were to explore optimal individualized dosing regimen...

Synthetic Data in Healthcare and Drug Development: Definitions, Regulatory Frameworks, Issues.

CPT: pharmacometrics & systems pharmacology
With the recent and evolving regulatory frameworks regarding the usage of Artificial Intelligence (AI) in both drug and medical device development, the differentiation between data derived from observed ('true' or 'real') sources and artificial data ...

Item Response Modeling and Artificial Neural Network for Differentiation of Parkinson's Patients and Subjects Without Evidence of Dopaminergic Deficit.

CPT: pharmacometrics & systems pharmacology
Approximately 15% of patients suspected of having Parkinson's disease (PD) present dopamine active transporter (DaT) scans without evidence of dopaminergic deficits (SWEDD), most of which will never develop PD. Leveraging Movement Disorders Society U...

Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations.

CPT: pharmacometrics & systems pharmacology
A variety of classical machine learning (ML) approaches has been developed over the past decade aiming to individualize drug dosages based on measured plasma concentrations. However, the interpretability of these models is challenging as they do not ...

Covariate Model Selection Approaches for Population Pharmacokinetics: A Systematic Review of Existing Methods, From SCM to AI.

CPT: pharmacometrics & systems pharmacology
A growing number of covariate modeling methods have been proposed in the field of popPK modeling, but limited information exists on how they all compare. The objective of this study was to perform a systematic review of all popPK covariate modeling m...

Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma.

CPT: pharmacometrics & systems pharmacology
We employed a mechanistic learning approach, integrating on-treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post-progression survival (PPS)-the duration from the time of document...

Accelerating virtual patient generation with a Bayesian optimization and machine learning surrogate model.

CPT: pharmacometrics & systems pharmacology
The pharmaceutical industry has increasingly adopted model-informed drug discovery and development (MID3) to enhance productivity in drug discovery and development. Quantitative systems pharmacology (QSP), which integrates drug action mechanisms and ...

Low-dimensional neural ordinary differential equations accounting for inter-individual variability implemented in Monolix and NONMEM.

CPT: pharmacometrics & systems pharmacology
Neural ordinary differential equations (NODEs) are an emerging machine learning (ML) method to model pharmacometric (PMX) data. Combining mechanism-based components to describe "known parts" and neural networks to learn "unknown parts" is a promising...

Artificial intelligence modeling of biomarker-based physiological age: Impact on phase 1 drug-metabolizing enzyme phenotypes.

CPT: pharmacometrics & systems pharmacology
Age and aging are important predictors of health status, disease progression, drug kinetics, and effects. The purpose was to develop ensemble learning-based physiological age (PA) models for evaluating drug metabolism. National Health and Nutrition E...

A stacking ensemble machine learning model for evaluating cardiac toxicity of drugs based on in silico biomarkers.

CPT: pharmacometrics & systems pharmacology
This study addresses the critical issue of drug-induced torsades de pointes (TdP) risk assessment, a vital aspect of new drug development due to its association with arrhythmia and sudden cardiac death. Existing methodologies, particularly those reli...