Mixed-Effect Modeling for Detection and Evaluation of Drug Interactions: Digoxin-Quinidine and Digoxin-Verapamil Combinations
作者:
Bauer Larry,
Horn John,
Pettit Herbert,
期刊:
Therapeutic Drug Monitoring
(OVID Available online 1996)
卷期:
Volume 18,
issue 1
页码: 46-52
ISSN:0163-4356
年代: 1996
出版商: OVID
关键词: Drug interactions;Mixed-effect modeling;NONMEM;Digoxin;Quinidine;Verapamil
数据来源: OVID
摘要:
SummaryMixed-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, ClNRis the nonrenal clearance, andmis 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 ≈45% and verapamil therapy decreased population digoxin oral clearance by ≈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.
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