Understanding cytokine-related therapeutic protein-drug interactions (TP-DI) is crucial for effective medication management in conditions characterized by elevated inflammatory responses. Recent FDA and ICH guidelines highlight a systematic, risk-based approach for evaluating these interactions, emphasizing the need for a thorough mechanistic understanding of TP-DIs. This study integrates the physiologically based pharmacokinetic (PBPK) model for TP (specifically interleukin-6, IL-6) with small-molecule drug PBPK models to elucidate cytokine-related TP-DI mechanistically.
View Article and Find Full Text PDFCell-based test methods with a phenotypic readout are frequently used for toxicity screening. However, guidance on how to validate the hits and how to integrate this information with other data for purposes of risk assessment is missing. We present here such a procedure and exemplify it with a case study on neural crest cell (NCC)-based developmental toxicity of picoxystrobin.
View Article and Find Full Text PDFBackground: Predicting metabolic drug-drug interactions (DDIs) via cytochrome P450 enzymes (CYP) is essential in drug development, but controversy has reemerged recently about whether in vitro-in vivo extrapolation (IVIVE) using static models can replace dynamic models for some regulatory filings and label recommendations.
Objective: The aim of this study was to determine if static and dynamic models are equivalent for the quantitative prediction of metabolic DDIs arising from competitive CYP inhibition.
Methods: Drug parameter spaces were varied to simulate 30,000 DDIs between hypothetical substrates and inhibitors of CYP3A4.
Real-time PCR (qPCR) testing is an essential component of early detection surveillance systems for Piscirickettsia salmonis infection in Atlantic salmon farms in Chile. Currently, all 11 laboratories in the authorised diagnostic laboratory network use assays based on published protocols. Compared with other P.
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