AI Medical Compendium Journal:
CPT: pharmacometrics & systems pharmacology

Showing 31 to 38 of 38 articles

Excipient knowledgebase: Development of a comprehensive tool for understanding the disposition and interaction potential of common excipients.

CPT: pharmacometrics & systems pharmacology
Although the use of excipients is widespread, a thorough understanding of the drug interaction potential of these compounds remains a frequent topic of current research. Not only can excipients alter the disposition of coformulated drugs, but it is l...

A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors.

CPT: pharmacometrics & systems pharmacology
Model-informed precision dosing (MIPD) approaches typically apply maximum a posteriori (MAP) Bayesian estimation to determine individual pharmacokinetic (PK) parameters with the goal of optimizing future dosing regimens. This process combines knowled...

An artificial neural network-pharmacokinetic model and its interpretation using Shapley additive explanations.

CPT: pharmacometrics & systems pharmacology
We developed a method to apply artificial neural networks (ANNs) for predicting time-series pharmacokinetics (PKs), and an interpretable the ANN-PK model, which can explain the evidence of prediction by applying Shapley additive explanations (SHAP). ...

Pharm-AutoML: An open-source, end-to-end automated machine learning package for clinical outcome prediction.

CPT: pharmacometrics & systems pharmacology
Although there is increased interest in utilizing machine learning (ML) to support drug development, technical hurdles associated with complex algorithms have limited widespread adoption. In response, we have developed Pharm-AutoML, an open-source Py...

Machine Learning in Drug Discovery and Development Part 1: A Primer.

CPT: pharmacometrics & systems pharmacology
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and develop...

Models and Machines: How Deep Learning Will Take Clinical Pharmacology to the Next Level.

CPT: pharmacometrics & systems pharmacology
Recent advances in machine learning (ML) have led to enthusiasm about its use throughout the biopharmaceutical industry. The ML methods can be applied to a wide range of problems and have the potential to revolutionize aspects of drug development. Th...

DrugMetab: An Integrated Machine Learning and Lexicon Mapping Named Entity Recognition Method for Drug Metabolite.

CPT: pharmacometrics & systems pharmacology
Drug metabolites (DMs) are critical in pharmacology research areas, such as drug metabolism pathways and drug-drug interactions. However, there is no terminology dictionary containing comprehensive drug metabolite names, and there is no named entity ...

CATTLE (CAncer treatment treasury with linked evidence): An integrated knowledge base for personalized oncology research and practice.

CPT: pharmacometrics & systems pharmacology
Despite the existence of various databases cataloging cancer drugs, there is an emerging need to support the development and application of personalized therapies, where an integrated understanding of the clinical factors and drug mechanism of action...