Prediction of Pharmacokinetics Prior to In Vivo Studies. 1. Mechanism‐Based Prediction of Volume of Distribution

Poulin, Patrick; Theil, Frank‐Peter

doi:10.1002/jps.10005

Cited by 509 publications

(497 citation statements)

References 163 publications

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“…In this study, the relevant vancomycin‐specific parameters were collected from the literature. The collected data are summarized in Table 1 13, 14, 15, 17. The vancomycin compound model was evaluated in the healthy volunteers and the general Japanese population models, before being used in renally impaired, hepatic disease (liver cirrhosis), and pediatric population models ( Figure 1).…”

Section: Methodsmentioning

confidence: 99%

Using a Vancomycin PBPK Model in Special Populations to Elucidate Case‐Based Clinical PK Observations

Emoto

Johnson

McPhail

et al. 2018

CPT Pharmacom & Syst Pharma

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Simultaneous changes in several physiological factors may contribute to the large pharmacokinetic (PK) variability of vancomycin. This study was designed to systematically characterize the effects of multiple physiological factors to the altered PK of vancomycin observed in special populations. A vancomycin physiologically based pharmacokinetic (PBPK) model was developed as a PK simulation platform to quantitatively assess the effects of changes in physiologies to the PK profiles. The developed model predicted the concentration‐time profiles in healthy adults and diseased patients. The implementation of developmental changes in both renal and non‐renal elimination pathways to the pediatric model improved the predictability of vancomycin clearance. Simulated PK profiles with a 50% decrease in cardiac output (peak plasma concentration (Cmax), 59.9 ng/mL) were similar to those observed in patients before bypass surgery (Cmax, 55.1 ng/mL). The PBPK modeling of vancomycin demonstrated its potential to provide mechanistic insights into the altered disposition observed in patients who have changes in multiple physiological factors.

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Section: Methodsmentioning

confidence: 99%

Using a Vancomycin PBPK Model in Special Populations to Elucidate Case‐Based Clinical PK Observations

Emoto

Johnson

McPhail

et al. 2018

CPT Pharmacom & Syst Pharma

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“…Physicochemical properties from efavirenz data (including log P, molecular weight, and pK a ) and in vitro data (permeation across Caco-2 cells and protein binding) were gathered from the literature and incorporated into the full-body model (22). The volume of distribution was simulated using the Poulin and Theil equation (35). This method describes the tissue-to-plasma ratio based on the individual organ volumes generated from the physB equations.…”

Section: Methodsmentioning

confidence: 99%

Efavirenz Is Predicted To Accumulate in Brain Tissue: an In Silico , In Vitro , and In Vivo Investigation

Curley

Rajoli

Moss

et al. 2017

Antimicrob Agents Chemother

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Adequate concentrations of efavirenz in the central nervous system (CNS) are necessary to suppress viral replication, but high concentrations may increase the likelihood of CNS adverse drug reactions. The aim of this investigation was to evaluate the efavirenz distribution in the cerebrospinal fluid (CSF) and the brain by using a physiologically based pharmacokinetic (PBPK) simulation for comparison with rodent and human data. The efavirenz CNS distribution was calculated using a permeability-limited model on a virtual cohort of 100 patients receiving efavirenz (600 mg once daily). Simulation data were then compared with human data from the literature and with rodent data. Wistar rats were administered efavirenz (10 mg kg of body weight Ϫ1 ) once daily over 5 weeks. Plasma and brain tissue were collected for analysis via liquid chromatography-tandem mass spectrometry (LC-MS/ MS). The median maximum concentrations of drug (C max ) were predicted to be 3,184 ng ml Ϫ1 (interquartile range [IQR], 2,219 to 4,851 ng ml Ϫ1 ), 49.9 ng ml Ϫ1 (IQR, 36.6 to 69.7 ng ml Ϫ1 ), and 50,343 ng ml Ϫ1 (IQR, 38,351 to 65,799 ng ml Ϫ1 ) in plasma, CSF, and brain tissue, respectively, giving a tissue-to-plasma ratio of 15.8. Following 5 weeks of oral dosing of efavirenz (10 mg kg Ϫ1 ), the median plasma and brain tissue concentrations in rats were 69.7 ng ml Ϫ1 (IQR, 44.9 to 130.6 ng ml Ϫ1 ) and 702.9 ng ml Ϫ1 (IQR, 475.5 to 1,018.0 ng ml Ϫ1 ), respectively, and the median tissue-to-plasma ratio was 9.5 (IQR, 7.0 to 10.9). Although it is useful, measurement of CSF concentrations may give an underestimation of the penetration of antiretrovirals into the brain. The limitations associated with obtaining tissue biopsy specimens and paired plasma and CSF samples from patients make PBPK modeling an attractive tool for probing drug distribution.

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“…A quantitative determination of newly synthesized compounds in rat plasma is a prerequisite criterion before in vivo experiment [16,17]. Thus, in continuation to our previous study, we described herein the pharmacokinetic studies of all the three compounds in rat plasma with an oral administration of 10 mg/kg dose.…”

Section: Singh Et Almentioning

confidence: 83%

Determination of 5h-Benzo[2,3][1,4]oxazepino[5,6-B]indoles in Rat Plasma by Reversed-Phase High-Performance Liquid Chromatographic-Ultraviolet Method: Application to Pharmacokinetic Studies

Singh

Raj

Rai

et al. 2017

Asian J Pharm Clin Res

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Objective: Recently, we reported newly synthesized 5H-benzo [2,3] [1,4]oxazepino [5,6-b]indole) derivatives and proved their cytotoxicity against hepatocellular carcinoma specific Hep-G2 cell lines. We attempted herein to describe a reversed-phase high-performance liquid chromatographic method for the determination of three most active compounds 6a, 10a, and 15a in rat plasma to predict their pharmacokinetics parameters before in vivo study. Methods:A rapid and sensitive reversed-phase high-performance liquid chromatographic was employed for the determination of 6a, 10a, and 15a in rat plasma. Each compound was separated by a gradient elution of acetonitrile and water with 1 mL/min flow rate. The detector was set at 270, 285, and 275 nm for 6a, 10a, and 15a and the recorded elution times were 2.00, 2.87, and 1.88 min, respectively. Results:The calibration curve was linear with R 2 of 0.938, 0.875, and 0.923 over the concentration range of 0.1-50 µg/mL. The inter-and intraday variations of the assay were lower than 12.26%; the average recovery of 6a, 10a, and 15a was 97.31, 92.56, and 95.23 % with relative standard deviation of 2.12%, 3.25%, and 2.28%, respectively. The C max and T max were ~ 46.34, 18.56, and 25.65 µg/mL and 2.0, 4.0, and 4.0 h for 6a, 10a, and 15a, respectively, which indicate a robust method of detection in the present experiment. Conclusion:The study suggests that all of the three compounds have a lower rate of absorption, higher volume of distribution, and lower clearance rate, indicating good therapeutic response for in vivo activity.

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Prediction of Pharmacokinetics Prior to In Vivo Studies. 1. Mechanism‐Based Prediction of Volume of Distribution

Cited by 509 publications

References 163 publications

Using a Vancomycin PBPK Model in Special Populations to Elucidate Case‐Based Clinical PK Observations

Using a Vancomycin PBPK Model in Special Populations to Elucidate Case‐Based Clinical PK Observations

Efavirenz Is Predicted To Accumulate in Brain Tissue: an In Silico , In Vitro , and In Vivo Investigation

Determination of 5h-Benzo[2,3][1,4]oxazepino[5,6-B]indoles in Rat Plasma by Reversed-Phase High-Performance Liquid Chromatographic-Ultraviolet Method: Application to Pharmacokinetic Studies

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