In vitro-in vivo extrapolation, DDI risk, enzyme kinetics, and clearance prediction
In vitro to in vivo extrapolation of hepatic clearance using well-stirred model
Predict in vivo clearance from microsomal stability half-life data
FDA static model R1/R2/R3 for CYP inhibition and induction risk classification
Calculate fraction unbound in microsomes for IVIVE correction
Calculate Km, Vmax, and CLint from Michaelis-Menten kinetics data
Evaluate P-glycoprotein efflux ratio from Caco-2 or MDCK transport data
Predict renal clearance from GFR, tubular secretion, and reabsorption
Determine Biopharmaceutics Classification System class from solubility and permeability
Predict in vivo clearance from hepatocyte stability data using HPGL scaling and well-stirred model
Calculate CYP enzyme contributions (fm) from selective inhibitor data for DDI vulnerability assessment
Check drug-drug interactions from FDA-approved label text via DailyMed and openFDA
Explore drug-target relationships, mechanisms of action, and disease associations via Open Targets Platform
Scale PK parameters across species using allometric exponents to predict human CL and Vd from preclinical data
Detect flip-flop kinetics by comparing oral vs IV half-lives or ka vs ke
Fit power model (Y = a × X^b) for dose proportionality assessment or allometric scaling