Skeletal muscle digoxin binding in patients with renal failure.

Jogestrand, Tomas; Ericsson, F

doi:10.1111/j.1365-2125.1983.tb02153.x

Cited by 5 publications

(1 citation statement)

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“…K p values for the tissue compartments were initially calculated using Poulin and Theil's TC equation because this TC equation yields better results for prediction of neutral compounds (23). K p values for muscle of digoxin was estimated to be 35.7, which was obtained from the reported tissue binding data in human skeletal muscle (50). PK simulations were performed for women during late pregnancy and PP after a single oral dose (0.25 mg).…”

Section: Case Example 2: Digoxin (Bddcs Class 3)mentioning

confidence: 99%

A Simplified PBPK Modeling Approach for Prediction of Pharmacokinetics of Four Primarily Renally Excreted and CYP3A Metabolized Compounds During Pregnancy

Xia

Heimbach

Gollen

et al. 2013

AAPS J

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During pregnancy, a drug's pharmacokinetics may be altered and hence anticipation of potential systemic exposure changes is highly desirable. Physiologically based pharmacokinetics (PBPK) models have recently been used to influence clinical trial design or to facilitate regulatory interactions. Ideally, whole-body PBPK models can be used to predict a drug's systemic exposure in pregnant women based on major physiological changes which can impact drug clearance (i.e., in the kidney and liver) and distribution (i.e., adipose and fetoplacental unit). We described a simple and readily implementable multitissue/organ whole-body PBPK model with key pregnancy-related physiological parameters to characterize the PK of reference drugs (metformin, digoxin, midazolam, and emtricitabine) in pregnant women compared with the PK in nonpregnant or postpartum (PP) women. Physiological data related to changes in maternal body weight, tissue volume, cardiac output, renal function, blood flows, and cytochrome P450 activity were collected from the literature and incorporated into the structural PBPK model that describes HV or PP women PK data. Subsequently, the changes in exposure (area under the curve (AUC) and maximum concentration (C max)) in pregnant women were simulated. Model-simulated PK profiles were overall in agreement with observed data. The prediction fold error for C max and AUC ratio (pregnant vs. nonpregnant) was less than 1.3-fold, indicating that the pregnant PBPK model is useful. The utilization of this simplified model in drug development may aid in designing clinical studies to identify potential exposure changes in pregnant women a priori for compounds which are mainly eliminated renally or metabolized by CYP3A4.

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Section: Case Example 2: Digoxin (Bddcs Class 3)mentioning

confidence: 99%