Special Issue "Preclinical Pharmacokinetics and Bioanalysis"

A special issue of Pharmaceutics (ISSN 1999-4923).

Deadline for manuscript submissions: 31 May 2018

Special Issue Editors

Guest Editor
Dr. Lingzhi Wang

Cancer Science Institute of Singapore, National University of Singapore, Singapore
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Interests: pharmacokinetics; natural compounds; anticancer agents; drug–drug interactions; cancer biomarkers
Guest Editor
Dr. Xiaoqiang Xiang

Department of Clinical Pharmacy , School of Pharmacy, Fudan University , Shanghai, China
Website | E-Mail
Interests: physiologically-based pharmacokinetic modeling; drug–drug interactions; pharmacogenomics
Guest Editor
Dr. Paul Chi Lui Ho

Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore
Website | E-Mail
Interests: pharmacokinetics; biopharmaceutics; drug delivery systems; nanotechnology; CNS drugs

Special Issue Information

Dear Colleagues,

Today, the development of new drugs is still very time consuming, extremely costly, and suffers from high attrition rates, despite the modern technologies that are widely used in the drug research and development field. One of the biggest bottlenecks in the early phase of drug development is the lack of high-throughput approaches for preclinical pharmacokinetics (PK) screening. Nevertheless, this area has been greatly improved over the past decade because of the revolutionary changes in bioanalytical methods. In particular, with the LC-MS/MS platform, a PK assay for a new drug candidate can be developed in only a few hours, compared with several months as in the past using HPLC-UV/FL methods. Many new preclinical PK screening approaches, including cassette dosing PK, cassette analysis, snapshot PK and rapid PK have been proposed and tested. The progress of these PK technologies could significantly accelerate the process of drug discovery. In addition, they can be widely applied in different stages of drug development to eliminate weak candidates.

This Special Issue on “Preclinical Pharmacokinetics and Bioanalysis” aims to highlight the latest development technologies in this area and to inspire future research in this exciting area.

Dr. Lingzhi Wang
Dr. Xiaoqiang Xiang
Dr. Paul Chi Lui Ho
Guest Editors

Manuscript Submission Information

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Keywords

  • Cassette dosing pharmacokinetics
  • Cassette analysis
  • Snapshot pharmacokinetics
  • Rapid pharmacokinetics
  • Full pharmacokinetics
  • CNS drug pharmacokinetics
  • Ocular pharmacokinetics
  • Drug Analysis
  • Drug metabolism

Published Papers (5 papers)

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Research

Open AccessArticle Pharmacokinetics and Pharmacodynamics of (S)-Ketoprofen Co-Administered with Caffeine: A Preclinical Study in Arthritic Rats
Pharmaceutics 2018, 10(1), 20; https://doi.org/10.3390/pharmaceutics10010020
Received: 31 October 2017 / Revised: 16 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
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Abstract
The purpose of the present study was to determine whether caffeine modifies the pharmacokinetics and pharmacodynamics of (S)-ketoprofen following oral administration in a gout-type pain model. 3.2 mg/kg of (S)-ketoprofen alone and combined with 17.8 mg/kg of caffeine were
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The purpose of the present study was to determine whether caffeine modifies the pharmacokinetics and pharmacodynamics of (S)-ketoprofen following oral administration in a gout-type pain model. 3.2 mg/kg of (S)-ketoprofen alone and combined with 17.8 mg/kg of caffeine were administered to Wistar rats and plasma levels were determined between 0.5 and 24.0 h. Additionally, antinociception was evaluated based on the protocol of the PIFIR (pain-induced functional impairment in the rat) model before blood sampling between 0.5 and 4.0 h. Significant differences in Cmax, AUC0-24, and AUC0-∞ values were observed with caffeine administration (p < 0.05). Also, significant differences in Emax, Tmax, and AUC0-4 values were determined when comparing the treatments with and without caffeine (p < 0.05). By relating the pharmacokinetic and pharmacodynamic data, a counter-clockwise hysteresis loop was observed regardless of the administration of caffeine. When the relationship between AUCe and AUCp was fitted to the sigmoidal Emax model, a satisfactory correlation was found (R2 > 0.99) as well as significant differences in Emax and EC50 values (p < 0.05). With caffeine, Emax and EC50 values changed by 489.5% and 695.4%, respectively. The combination studied represents a convenient alternative for the treatment of pain when considering the advantages offered by using drugs with different mechanisms of action. Full article
(This article belongs to the Special Issue Preclinical Pharmacokinetics and Bioanalysis)
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Open AccessArticle Development of a Region-Specific Physiologically Based Pharmacokinetic Brain Model to Assess Hippocampus and Frontal Cortex Pharmacokinetics
Pharmaceutics 2018, 10(1), 14; https://doi.org/10.3390/pharmaceutics10010014
Received: 2 January 2018 / Revised: 8 January 2018 / Accepted: 12 January 2018 / Published: 17 January 2018
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Abstract
Central nervous system drug discovery and development is hindered by the impermeable nature of the blood–brain barrier. Pharmacokinetic modeling can provide a novel approach to estimate CNS drug exposure; however, existing models do not predict temporal drug concentrations in distinct brain regions. A
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Central nervous system drug discovery and development is hindered by the impermeable nature of the blood–brain barrier. Pharmacokinetic modeling can provide a novel approach to estimate CNS drug exposure; however, existing models do not predict temporal drug concentrations in distinct brain regions. A rat CNS physiologically based pharmacokinetic (PBPK) model was developed, incorporating brain compartments for the frontal cortex (FC), hippocampus (HC), “rest-of-brain” (ROB), and cerebrospinal fluid (CSF). Model predictions of FC and HC Cmax, tmax and AUC were within 2-fold of that reported for carbamazepine and phenytoin. The inclusion of a 30% coefficient of variation on regional brain tissue volumes, to assess the uncertainty of regional brain compartments volumes on predicted concentrations, resulted in a minimal level of sensitivity of model predictions. This model was subsequently extended to predict human brain morphine concentrations, and predicted a ROB Cmax of 21.7 ± 6.41 ng/mL when compared to “better” (10.1 ng/mL) or “worse” (29.8 ng/mL) brain tissue regions with a FC Cmax of 62.12 ± 17.32 ng/mL and a HC Cmax of 182.2 ± 51.2 ng/mL. These results indicate that this simplified regional brain PBPK model is useful for forward prediction approaches in humans for estimating regional brain drug concentrations. Full article
(This article belongs to the Special Issue Preclinical Pharmacokinetics and Bioanalysis)
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Open AccessArticle Determination of Tangeretin in Rat Plasma: Assessment of Its Clearance and Absolute Oral Bioavailability
Pharmaceutics 2018, 10(1), 3; https://doi.org/10.3390/pharmaceutics10010003
Received: 6 November 2017 / Revised: 9 December 2017 / Accepted: 24 December 2017 / Published: 29 December 2017
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Abstract
Tangeretin (TAN) is a dietary polymethoxylated flavone that possesses a broad scope of pharmacological activities. A simple high-performance liquid chromatography (HPLC) method was developed and validated in this study to quantify TAN in plasma of Sprague-Dawley rats. The lower limit of quantification (LLOQ)
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Tangeretin (TAN) is a dietary polymethoxylated flavone that possesses a broad scope of pharmacological activities. A simple high-performance liquid chromatography (HPLC) method was developed and validated in this study to quantify TAN in plasma of Sprague-Dawley rats. The lower limit of quantification (LLOQ) was 15 ng/mL; the intra- and inter-day assay variations expressed in the form of relative standard deviation (RSD) were all less than 10%; and the assay accuracy was within 100 ± 15%. Subsequently, pharmacokinetic profiles of TAN were explored and established. Upon single intravenous administration (10 mg/kg), TAN had rapid clearance (Cl = 94.1 ± 20.2 mL/min/kg) and moderate terminal elimination half-life (t1/2 λz = 166 ± 42 min). When TAN was given as a suspension (50 mg/kg), poor but erratic absolute oral bioavailability (mean value < 3.05%) was observed; however, when TAN was given in a solution prepared with randomly methylated-β-cyclodextrin (50 mg/kg), its plasma exposure was at least doubled (mean bioavailability: 6.02%). It was obvious that aqueous solubility hindered the oral absorption of TAN and acted as a barrier to its oral bioavailability. This study will facilitate further investigations on the medicinal potentials of TAN. Full article
(This article belongs to the Special Issue Preclinical Pharmacokinetics and Bioanalysis)
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Open AccessFeature PaperArticle Prediction of Drug-Drug Interactions with Bupropion and Its Metabolites as CYP2D6 Inhibitors Using a Physiologically-Based Pharmacokinetic Model
Pharmaceutics 2018, 10(1), 1; https://doi.org/10.3390/pharmaceutics10010001
Received: 31 October 2017 / Revised: 5 December 2017 / Accepted: 19 December 2017 / Published: 21 December 2017
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Abstract
The potential of inhibitory metabolites of perpetrator drugs to contribute to drug-drug interactions (DDIs) is uncommon and underestimated. However, the occurrence of unexpected DDI suggests the potential contribution of metabolites to the observed DDI. The aim of this study was to develop a
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The potential of inhibitory metabolites of perpetrator drugs to contribute to drug-drug interactions (DDIs) is uncommon and underestimated. However, the occurrence of unexpected DDI suggests the potential contribution of metabolites to the observed DDI. The aim of this study was to develop a physiologically-based pharmacokinetic (PBPK) model for bupropion and its three primary metabolites—hydroxybupropion, threohydrobupropion and erythrohydrobupropion—based on a mixed “bottom-up” and “top-down” approach and to contribute to the understanding of the involvement and impact of inhibitory metabolites for DDIs observed in the clinic. PK profiles from clinical researches of different dosages were used to verify the bupropion model. Reasonable PK profiles of bupropion and its metabolites were captured in the PBPK model. Confidence in the DDI prediction involving bupropion and co-administered CYP2D6 substrates could be maximized. The predicted maximum concentration (Cmax) area under the concentration-time curve (AUC) values and Cmax and AUC ratios were consistent with clinically observed data. The addition of the inhibitory metabolites into the PBPK model resulted in a more accurate prediction of DDIs (AUC and Cmax ratio) than that which only considered parent drug (bupropion) P450 inhibition. The simulation suggests that bupropion and its metabolites contribute to the DDI between bupropion and CYP2D6 substrates. The inhibitory potency from strong to weak is hydroxybupropion, threohydrobupropion, erythrohydrobupropion, and bupropion, respectively. The present bupropion PBPK model can be useful for predicting inhibition from bupropion in other clinical studies. This study highlights the need for caution and dosage adjustment when combining bupropion with medications metabolized by CYP2D6. It also demonstrates the feasibility of applying the PBPK approach to predict the DDI potential of drugs undergoing complex metabolism, especially in the DDI involving inhibitory metabolites. Full article
(This article belongs to the Special Issue Preclinical Pharmacokinetics and Bioanalysis)
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Open AccessArticle Application of Pharmacokinetics Modelling to Predict Human Exposure of a Cationic Liposomal Subunit Antigen Vaccine System
Pharmaceutics 2017, 9(4), 57; https://doi.org/10.3390/pharmaceutics9040057
Received: 16 October 2017 / Revised: 18 November 2017 / Accepted: 4 December 2017 / Published: 7 December 2017
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Abstract
The pharmacokinetics of a liposomal subunit antigen vaccine system composed of the cationic lipid dimethyldioctadecylammonium bromide (DDA) and the immunostimulatory agent trehalose 6,6-dibehenate (TDB) (8:1 molar ratio) combined with the Ag85B-ESAT-6 (H1) antigen were modelled using mouse in-vivo data. Compartment modelling and physiologically
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The pharmacokinetics of a liposomal subunit antigen vaccine system composed of the cationic lipid dimethyldioctadecylammonium bromide (DDA) and the immunostimulatory agent trehalose 6,6-dibehenate (TDB) (8:1 molar ratio) combined with the Ag85B-ESAT-6 (H1) antigen were modelled using mouse in-vivo data. Compartment modelling and physiologically based pharmacokinetics (PBPK) were used to predict the administration site (muscle) and target site (lymph) temporal concentration profiles and factors governing these. Initial estimates using compartmental modelling established that quadriceps pharmacokinetics for the liposome demonstrated a long half-life (22.6 days) compared to the associated antigen (2.62 days). A mouse minimal-PBPK model was developed and successfully predicted quadriceps liposome and antigen pharmacokinetics. Predictions for the popliteal lymph node (PLN) aligned well at earlier time-points. A local sensitivity analysis highlighted that the predicted AUCmuscle was sensitive to the antigen degradation constant kdeg (resulting in a 3-log change) more so than the fraction escaping the quadriceps (fe) (resulting in a 10-fold change), and the predicted AUCPLN was highly sensitive to fe. A global sensitivity analysis of the antigen in the muscle demonstrated that model predictions were within the 50th percentile for predictions and showed acceptable fits. To further translate in-vitro data previously generated by our group, the mouse minimal-PBPK model was extrapolated to humans and predictions made for antigen pharmacokinetics in muscle and PLN. Global analysis demonstrated that both kdeg and fe had a minimal impact on the resulting simulations in the muscle but a greater impact in the PLN. In summary, this study has predicted the in-vivo fate of DDA:TDB:H1 in humans and demonstrated the roles that formulation degradation and fraction escaping the depot site can play upon the overall depot effect within the site of administration. Full article
(This article belongs to the Special Issue Preclinical Pharmacokinetics and Bioanalysis)
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