Performance Improvement of a Natural Language Processing Tool for Extracting Patient Narratives Related to Medical States From Japanese Pharmaceutical Care Records by Increasing the Amount of Training Data: Natural Language Processing Analysis and Validation Study.

Background: Patients' oral expressions serve as valuable sources of clinical information to improve pharmacotherapy. Natural language processing (NLP) is a useful approach for analyzing unstructured text data, such as patient narratives. However, few studies have focused on using NLP for narratives in the Japanese language.

Using the Natural Language Processing System Medical Named Entity Recognition-Japanese to Analyze Pharmaceutical Care Records: Natural Language Processing Analysis.

Background: Large language models have propelled recent advances in artificial intelligence technology, facilitating the extraction of medical information from unstructured data such as medical records. Although named entity recognition (NER) is used to extract data from physicians' records, it has yet to be widely applied to pharmaceutical care records.

Objective: In this study, we aimed to investigate the feasibility of automatic extraction of the information regarding patients' diseases and symptoms from pharmaceutical care records.

Prediction of theophylline clearance in CCl4-treated rats using in vivo CYP1A2 and CYP3A2 contents assessed with the PKCYP test.

We previously established a method to predict the drug metabolism capacity of injured liver based on pharmacokinetic estimation of the amount of cytochrome P450 (CYP) in vivo (PKCYP test), by introducing the apparent liver-to-blood free concentration gradient in vivo (qg) as a parameter. Here we show that the amount of CYP3A2 in CCl(4)-treated rats can be estimated appropriately by applying the PKCYP test using midazolam (MDZ) as a probe, assuming that the qg value in control rats does not change. We applied the results to predict the clearance of theophylline as a model drug with a physiologically based pharmacokinetic model.

Application of the PKCYP test to predict caffeine clearance mediated by CYP1A2 in a rat acute liver injury model.

We previously established a method for assessing in vivo drug-metabolizing capacity by pharmacokinetic estimation of the quantity of cytochrome P450 (CYP) in vivo (PKCYP test), in which an apparent liver-to-blood free concentration gradient in vivo (qg) is introduced (Matsunaga et al., Jpn. J.