Prediction of Human Volume of Distribution Values for Neutral and Basic Drugs. 2. Extended Data Set and Leave-Class-Out Statistics

2004 ◽  
Vol 47 (5) ◽  
pp. 1242-1250 ◽  
Author(s):  
Franco Lombardo ◽  
R. Scott Obach ◽  
Marina Y. Shalaeva ◽  
Feng Gao
Keyword(s):  
Volume Of Distribution ◽  
Basic Drugs ◽  
Data Set ◽  
Neutral And Basic Drugs

scholarly journals Quantitative Structure – Pharmacokinetics Relationships Analysis of Basic Drugs: Volume of Distribution

2015 ◽  
Vol 18 (3) ◽  
pp. 515 ◽  
Author(s):  
Zvetanka Dobreva Zhivkova ◽  
Tsvetelina Mandova ◽  
Irini Doytchinova
Keyword(s):  
External Validation ◽  
Model Development ◽  
Predictive Ability ◽  
Structural Features ◽  
Volume Of Distribution ◽  
Pharmacokinetic Parameters ◽  
Basic Drugs ◽  
Quantitative Structure ◽  
Data Set ◽  
Rapid Discrimination

Purpose. The early prediction of pharmacokinetic behavior is of paramount importance for saving time and resources and for increasing the success of new drug candidates. The steady-state volume of distribution (VDss) is one of the key pharmacokinetic parameters required for the design of a suitable dosage regimen. The aim of the study is to propose a quantitative structure – pharmacokinetics relationships (QSPkR) for VDss of basic drugs. Methods: The data set consists of 216 basic drugs, divided to a modeling (n = 180) and external validation set (n = 36). 179 structural and physicochemical descriptors are calculated using validated commercial software. Genetic algorithm, stepwise regression and multiple linear regression are applied for variable selection and model development. The models are validated by internal and external test sets. Results: A number of significant QSPkRs are developed. The most frequently emerged descriptors are used to derive the final consensus model for VDss with good explanatory (r2 0.663) and predictive ability (q2LOO-CV 0.606 and r2pred 0.593). The model reveals clear structural features determining VDss of basic drugs which are summarized in a short list of criteria for rapid discrimination between drugs with a large and small VDss. Conclusions: Descriptors like lipophilicity, fraction ionized as a base at pH 7.4, number of cycles and fused aromatic rings, presence of Cl and F atoms contribute positively to VDss, while polarity and presence of strong electrophiles have a negative effect. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.

scholarly journals Population Pharmacokinetics of Fluconazole in Young Infants

2008 ◽  
Vol 52 (11) ◽  
pp. 4043-4049 ◽  
Author(s):  
K. C. Wade ◽  
D. Wu ◽  
D. A. Kaufman ◽  
R. M. Ward ◽  
D. K. Benjamin ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Compartment Model ◽  
Volume Of Distribution ◽  
Relative Standard Error ◽  
Data Set ◽  
Mixed Effect ◽  
Young Infants ◽  
Relative Standard ◽  
Population Pk ◽  
The Impact

ABSTRACT Fluconazole is being increasingly used to prevent and treat invasive candidiasis in neonates, yet dosing is largely empirical due to the lack of adequate pharmacokinetic (PK) data. We performed a multicenter population PK study of fluconazole in 23- to 40-week-gestation infants less than 120 days of age. We developed a population PK model using nonlinear mixed effect modeling (NONMEM) with the NONMEM algorithm. Covariate effects were predefined and evaluated based on estimation precision and clinical significance. We studied fluconazole PK in 55 infants who at enrollment had a median (range) weight of 1.02 (0.440 to 7.125) kg, a gestational age at birth (BGA) of 26 (23 to 40) weeks, and a postnatal age (PNA) of 2.3 (0.14 to 12.6) weeks. The final data set contained 357 samples; 217/357 (61%) were collected prospectively at prespecified time intervals, and 140/357 (39%) were scavenged from discarded clinical specimens. Fluconazole population PK was best described by a one-compartment model with covariates normalized to median values. The population mean clearance (CL) can be derived for this population by the equation CL (liter/h) equals 0.015 · (weight/1)0.75 · (BGA/26)1.739 · (PNA/2)0.237 · serum creatinine (SCRT)−4.896 (when SCRT is >1.0 mg/dl), and using a volume of distribution (V) (liter) of 1.024 · (weight/1). The relative standard error around the fixed effects point estimates ranged from 3 to 24%. CL doubles between birth and 28 days of age from 0.008 to 0.016 and from 0.010 to 0.022 liter/kg/h for typical 24- and 32-week-gestation infants, respectively. This population PK model of fluconazole discriminated the impact of BGA, PNA, and creatinine on drug CL. Our data suggest that dosing in young infants will require adjustment for BGA and PNA to achieve targeted systemic drug exposures.

scholarly journals Amikacin Pharmacokinetics To Optimize Dosing in Neonates with Perinatal Asphyxia Treated with Hypothermia

2017 ◽  
Vol 61 (12) ◽  
Author(s):  
Sinziana Cristea ◽  
Anne Smits ◽  
Aida Kulo ◽  
Catherijne A. J. Knibbe ◽  
Mirjam van Weissenbruch ◽  
...  
Keyword(s):  
Perinatal Asphyxia ◽  
Volume Of Distribution ◽  
Stochastic Simulations ◽  
Therapeutic Drug ◽  
Published Data ◽  
Data Set ◽  
Dosing Interval ◽  
Proposed Model ◽  
Dosing Regimens ◽  
The Impact

ABSTRACT Aminoglycoside pharmacokinetics (PK) is expected to change in neonates with perinatal asphyxia treated with therapeutic hypothermia (PATH). Several amikacin dosing guidelines have been proposed for treating neonates with (suspected) septicemia; however, none provide adjustments for cases of PATH. Therefore, we aimed to quantify the differences in amikacin PK between neonates with and without PATH to propose suitable dosing recommendations. Based on amikacin therapeutic drug monitoring data collected retrospectively from neonates with PATH, combined with a published data set, we assessed the impact of PATH on amikacin PK by using population modeling. Monte Carlo and stochastic simulations were performed to establish amikacin exposures in neonates with PATH after dosing according to the current guidelines and according to proposed model-derived dosing guidelines. Amikacin clearance was decreased 40.6% in neonates with PATH, with no changes in volume of distribution. Simulations showed that increasing the dosing interval by 12 h results in a decrease in the percentage of neonates reaching toxic trough levels (>5 mg/liter), from 40 to 76% to 14 to 25%, while still reaching efficacy targets compared to the results of current dosing regimens. Based on this study, a 12-h increase in the amikacin dosing interval in neonates with PATH is proposed to correct for the reduced clearance, yielding safe and effective exposures. As amikacin is renally excreted, further studies into other renally excreted drugs may be required, as their clearance may also be impaired.

Prediction of pKa for Neutral and Basic Drugs Based on Radial Basis Function Neural Networks and the Heuristic Method

2005 ◽  
Vol 22 (9) ◽  
pp. 1454-1460 ◽  
Author(s):  
Feng Luan ◽  
Weiping Ma ◽  
Haixia Zhang ◽  
Xiaoyun Zhang ◽  
Mancang Liu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Radial Basis Function ◽  
Basis Function ◽  
Heuristic Method ◽  
Basic Drugs ◽  
Radial Basis ◽  
Neutral And Basic Drugs

scholarly journals Population Pharmacokinetics of Finafloxacin in Healthy Volunteers and Patients with Complicated Urinary Tract Infections

2018 ◽  
Vol 62 (4) ◽  
Author(s):  
Max Taubert ◽  
Mark Lückermann ◽  
Andreas Vente ◽  
Axel Dalhoff ◽  
Uwe Fuhr
Keyword(s):  
Urinary Tract ◽  
Healthy Volunteers ◽  
Urinary Tract Infections ◽  
Pharmacokinetic Model ◽  
Oral Absorption ◽  
Compartment Model ◽  
Volume Of Distribution ◽  
Population Pharmacokinetic ◽  
Data Set ◽  
Tract Infections

ABSTRACTFinafloxacin is a novel fluoroquinolone with increased antibacterial activity at acidic pH and reduced susceptibility to several resistance mechanisms. A phase II study revealed a good efficacy/safety profile in patients with complicated urinary tract infections (cUTIs), while the pharmacokinetics was characterized by highly variable concentration-versus-time profiles, suggesting the need for an elaborated pharmacokinetic model. Data from three clinical trials were evaluated: 127 healthy volunteers were dosed orally (n= 77) or intravenously (n= 50), and 139 patients with cUTI received finafloxacin intravenously. Plasma (2,824 samples from volunteers and 414 samples from patients) and urine (496 samples from volunteers and 135 samples patients) concentrations were quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). NONMEM was used to build a population pharmacokinetic model, and pharmacokinetic/pharmacodynamic relationships were investigated via simulations and logistic regression. A two-compartment model with first-order elimination described the data best (central volume of distribution [Vc] and peripheral volume of distribution [Vp] of 47 liters [20%] and 43 liters [67%], respectively, and elimination clearance and intercompartmental clearance of 21 liters/h [54%] and 2.8 liters/h [57%], respectively [median bootstrap estimates {coefficients of variation}]).Vcincreased with body surface area, and clearance was reduced in patients (−29%). Oral absorption was described best by parallel first- and zero-order processes (bioavailability of 75%). No pharmacodynamic surrogate parameter of clinical/microbiological outcome could be identified, which depended exclusively on the MIC of the causative pathogens. Despite the interindividual variability, the present data set does not support covariate-based dose adjustments. Based on the favorable safety and efficacy data, the clinical relevance of the observed variability appears to be limited. (This study has been registered at ClinicalTrials.gov under identifier NCT01928433.)

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