Population pharmacokinetics of doripenem based on data from phase 1 studies with healthy volunteers and phase 2 and 3 studies with critically ill patients.
A population pharmacokinetic model of doripenem was constructed using data pooled from phase 1, 2, and 3 studies utilizing nonlinear mixed effects modeling. A 2-compartment model with zero-order input and first-order elimination best described the log-transformed concentration-versus-time profile of doripenem. The model was parameterized in terms of total clearance (CL), central volume of distribution (V(c)), peripheral volume of distribution (V(p)), and distribution clearance between the central and peripheral compartments (Q). The final model was described by the following equations (for jth subject): CL(j) (liters/h) = 13.6.(CL(CR)(j)/98 ml/min)(0.659).(1 + CL(race)(j) [0 for Caucasian]); V(c)(j) (liters) = 11.6.(weight(j)/73 kg)(0.596); Q(j) (liters/h) = 4.74.(weight(j)/73)(1.06); and V(p)(j) (liters) = 6.04.(CL(CR)(j)/98 ml/min)(0.417).(weight(j)/73 kg)(0.840).(age(j)/40 years)(0.307). According to the final model, population mean parameter estimates and interindividual variability (percent coefficient of variation [% CV]) for CL (liters/h), V(c) (liters), V(p) (liters), and Q (liters/h) were 13.6 (19%), 11.6 (19%), 6.0 (25%), and 4.7 (42%), respectively. Residual variability, estimated using three separate additive residual error models, was 0.17 standard deviation (SD), 0.55 SD, and 0.92 SD for phase 1, 2, and 3 data, respectively. Creatinine clearance was the most significant predictor of doripenem clearance. Mean Bayesian clearance was approximately 33%, 55%, and 76% lower for individuals with mild, moderate, or severe renal impairment, respectively, than for those with normal renal function. The population pharmacokinetic model based on healthy volunteer data and patient data informs us of doripenem disposition in a more general population as well as of the important measurable intrinsic and extrinsic factors that significantly influence interindividual pharmacokinetic differences.
Nandy
Partha
P
Clinical Pharmacology, Advanced PK/PD Modeling and Simulation, Johnson & Johnson Pharmaceutical Research & Development, LLC, Titusville, NJ 08560, USA. PNandy@its.jnj.com
Samtani
Mahesh N
MN
Lin
Rachel
R
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000900:Anti-Bacterial Agents / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D001424:Bacterial Infections / Q000188:drug therapy / Q000378:metabolism; D001499:Bayes Theorem; D015780:Carbapenems / Q000008:administration & dosage / Q000097:blood / Q000493:pharmacokinetics*; D003404:Creatinine / Q000378:metabolism; D016638:Critical Illness; D003428:Cross Infection / Q000188:drug therapy / Q000378:metabolism; D000077726:Doripenem; D005260:Female; D006801:Humans; D007668:Kidney / Q000378:metabolism; D008297:Male; D008657:Metabolic Clearance Rate; D008875:Middle Aged; D008954:Models, Biological; D017711:Nonlinear Dynamics; D018410:Pneumonia, Bacterial / Q000188:drug therapy / Q000378:metabolism; D011704:Pyelonephritis / Q000188:drug therapy / Q000378:metabolism; D051437:Renal Insufficiency / Q000378:metabolism; D014552:Urinary Tract Infections / Q000188:drug therapy / Q000378:metabolism; D055815:Young Adult
D000900:Anti-Bacterial Agents; D015780:Carbapenems; D003404:Creatinine; D000077726:Doripenem
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