AI Medical Compendium Journal:
CPT: pharmacometrics & systems pharmacology

Showing 11 to 20 of 38 articles

Bridging pharmacology and neural networks: A deep dive into neural ordinary differential equations.

CPT: pharmacometrics & systems pharmacology
The advent of machine learning has led to innovative approaches in dealing with clinical data. Among these, Neural Ordinary Differential Equations (Neural ODEs), hybrid models merging mechanistic with deep learning models have shown promise in accura...

Simulating realistic patient profiles from pharmacokinetic models by a machine learning postprocessing correction of residual variability.

CPT: pharmacometrics & systems pharmacology
We address the problem of model misspecification in population pharmacokinetics (PopPK), by modeling residual unexplained variability (RUV) by machine learning (ML) methods in a postprocessing step after conventional model building. The practical pur...

Deep-NCA: A deep learning methodology for performing noncompartmental analysis of pharmacokinetic data.

CPT: pharmacometrics & systems pharmacology
Noncompartmental analysis (NCA) is a model-independent approach for assessing pharmacokinetics (PKs). Although the existing NCA algorithms are very well-established and widely utilized, they suffer from low accuracies in the setting of sparse PK samp...

Computational drug discovery on human immunodeficiency virus with a customized long short-term memory variational autoencoder deep-learning architecture.

CPT: pharmacometrics & systems pharmacology
Despite attempts to control the spread of human immunodeficiency virus (HIV) through the use of anti-HIV medications, the absence of an effective vaccine continues to present a significant obstacle. In addition, the development of drug resistance by ...

Integrating machine learning with pharmacokinetic models: Benefits of scientific machine learning in adding neural networks components to existing PK models.

CPT: pharmacometrics & systems pharmacology
Recently, the use of machine-learning (ML) models for pharmacokinetic (PK) modeling has grown significantly. Although most of the current approaches use ML techniques as black boxes, there are only a few that have proposed interpretable architectures...

Synthetic Model Combination: A new machine-learning method for pharmacometric model ensembling.

CPT: pharmacometrics & systems pharmacology
When aiming to make predictions over targets in the pharmacological setting, a data-focused approach aims to learn models based on a collection of labeled examples. Unfortunately, data sharing is not always possible, and this can result in many diffe...

A decision support system based on artificial intelligence and systems biology for the simulation of pancreatic cancer patient status.

CPT: pharmacometrics & systems pharmacology
Oncology treatments require continuous individual adjustment based on the measurement of multiple clinical parameters. Prediction tools exploiting the patterns present in the clinical data could be used to assist decision making and ease the burden a...

Computational design of clinical trials using a combination of simulation and the genetic algorithm.

CPT: pharmacometrics & systems pharmacology
Artificial intelligence (AI) has come to be used in various technological fields in recent years. However, there have been no reports of AI-designed clinical trials. In this study, we tried to develop study designs by a genetic algorithm (GA), which ...