AI Medical Compendium Journal:
Clinical pharmacology and therapeutics

Showing 1 to 10 of 59 articles

Chat GPT vs. Clinical Decision Support Systems in the Analysis of Drug-Drug Interactions.

Clinical pharmacology and therapeutics
The current standard method for the analysis of potential drug-drug interactions (pDDIs) is time-consuming and includes the use of multiple clinical decision support systems (CDSSs) and the interpretation by healthcare professionals. With the emergen...

Machine Learning for Prediction of Drug Concentrations: Application and Challenges.

Clinical pharmacology and therapeutics
With the advancements in algorithms and increased accessibility of multi-source data, machine learning in pharmacokinetics is gaining interest. This review summarizes studies on machine learning-based pharmacokinetics analysis up to September 2024, i...

Progress, Pitfalls, and Impact of AI-Driven Clinical Trials.

Clinical pharmacology and therapeutics
Since the deep learning revolution of the early 2010s, significant efforts and billions of dollars have been invested in applying artificial intelligence (AI) to drug discovery and development (AIDD). However, despite high expectations, few AI-discov...

Predicting Survival in Patients with Advanced NSCLC Treated with Atezolizumab Using Pre- and on-Treatment Prognostic Biomarkers.

Clinical pharmacology and therapeutics
Existing survival prediction models rely only on baseline or tumor kinetics data and lack machine learning integration. We introduce a novel kinetics-machine learning (kML) model that integrates baseline markers, tumor kinetics, and four on-treatment...

Model-Informed Precision Dosing Using Machine Learning for Levothyroxine in General Practice: Development, Validation and Clinical Simulation Trial.

Clinical pharmacology and therapeutics
Levothyroxine is one of the most prescribed drugs in the western world. Dosing is challenging due to high-interindividual differences in effective dosage and the narrow therapeutic window. Model-informed precision dosing (MIPD) using machine learning...

Algorithmic Identification of Treatment-Emergent Adverse Events From Clinical Notes Using Large Language Models: A Pilot Study in Inflammatory Bowel Disease.

Clinical pharmacology and therapeutics
Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmacovigilance due to methodological limitations in text mining. Large language models (LLMs) like Bidir...

All that Glitters Is not Gold: Type-I Error Controlled Variable Selection from Clinical Trial Data.

Clinical pharmacology and therapeutics
Clinical trials are primarily conducted to estimate causal effects, but the data collected can also be invaluable for additional research, such as identifying prognostic measures of disease or biomarkers that predict treatment efficacy. However, thes...