title: Mixed-effect modeling for detection and evaluation of drug interactions: digoxin-quinidine and digoxin-verapamil combinations.
abstract: Mixed-effect modeling has been suggested as a possible tool to detect and describe drug interactions in patient populations receiving drug combinations for the treatment of disease states. The mixed-effect modeling program, NONMEM, was used to measure the effects of the well-known digoxin-quinidine and digoxin-verapamil drug interactions in 294 patients receiving oral digoxin as hospital inpatients. Fourteen percent of the population took either quinidine or verapamil concurrently with digoxin (mean quinidine dose = 857 +/- 397 mg/day, verapamil = 261 +/- 110 mg/day). Two regression models for digoxin oral clearance were used. Model 1 used the knowledge that digoxin is eliminated by both renal and nonrenal routes (TVCL = ClNR+m.CrCl, where TVCL is the population digoxin oral clearance, ClNR is the nonrenal clearance, and m is the slope of the line that relates creatinine clearance (CrCl) to digoxin clearance); model 2 used a more conventional regression approach with a simple series of multipliers. For both models, quinidine administration decreased population digoxin oral clearance by approximately 45% and verapamil therapy decreased population digoxin oral clearance by approximately 30%. These values are similar to those found by traditional drug interaction studies conducted in small patient or normal subject populations. Mixed-effect modeling can detect clinically relevant drug interactions and produce information similar to that found in traditional pharmacokinetic crossover study designs.
authors.affiliation: Department of Pharmacy, University of Washington, Seattle 98195, USA.
authors.forename: L A
authors.initials: LA
authors.lastname: Bauer
authors.forename: J R
authors.initials: JR
authors.lastname: Horn
authors.forename: H
authors.initials: H
authors.lastname: Pettit
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000378:metabolism; D000889:Anti-Arrhythmia Agents / Q000493:pharmacokinetics*; D001835:Body Weight / Q000502:physiology; D002121:Calcium Channel Blockers / Q000493:pharmacokinetics*; D003198:Computer Simulation; D003404:Creatinine / Q000097:blood; D004077:Digoxin / Q000493:pharmacokinetics*; D004338:Drug Combinations; D004347:Drug Interactions; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011802:Quinidine / Q000493:pharmacokinetics*; D012044:Regression Analysis; D014700:Verapamil / Q000493:pharmacokinetics*
chemical_list: D000889:Anti-Arrhythmia Agents; D002121:Calcium Channel Blockers; D004338:Drug Combinations; D004077:Digoxin; D003404:Creatinine; D014700:Verapamil; D011802:Quinidine