Predicting pharmacodynamic effects through early drug discovery with artificial intelligence-physiologically based pharmacokinetic (AI-PBPK) modelling

Pharmacodynamics Drug Development
DOI: 10.3389/fphar.2024.1330855 Publication Date: 2024-02-16T18:13:46Z
ABSTRACT
Graphical Abstract Main steps used to predict PK and PD outcomes of the compounds. (Step 1) Use different AI related simulations compound’s ADME physiochemical properties. 2) Predict using PBPK model. 3) models are how changes in drug concentrations affect gastric acid secretion pH. E/E0 is relative activity H + /K ATPase by drug; k sec rate constants for intra-gastric concentration; out elimination constant obs observed concentration ; I (Inhibition) current antisecretory effect (or pH level) max maximum possible can achieve; The term (I -I) represents far from its potential.
SUPPLEMENTAL MATERIAL
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