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Drug Distribution: Plasma Protein Binding01:29

Drug Distribution: Plasma Protein Binding

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Drugs predominantly attach to plasma proteins, with only a small percentage remaining unbound. The unbound portion can be calculated as one minus the bound fraction. Acidic drugs form large, inactive complexes by reversibly binding to plasma albumin, which prevents them from diffusing across biological barriers. These drug-protein complexes act as reservoirs for the drugs. As the concentration of unbound drugs decreases, these complexes quickly dissociate to release the free drug, maintaining...
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Protein-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

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Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
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Nonlinear Pharmacokinetics: Bioavailability and Protein-Drug Binding01:22

Nonlinear Pharmacokinetics: Bioavailability and Protein-Drug Binding

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When a drug follows nonlinear pharmacokinetics, its bioavailability, the amount of the drug that reaches the systemic circulation, can change with different doses. This is due to the presence of a saturable pathway. The pathway becomes saturated as the drug concentration increases, decreasing the absorption rate. Consequently, the drug's bioavailability may be lower than expected at higher doses.
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Physiological Pharmacokinetic Models: Assumption with Protein Binding01:13

Physiological Pharmacokinetic Models: Assumption with Protein Binding

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Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
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One-Compartment Open Model for IV Bolus Administration: Estimation of Elimination Rate Constant, Half-Life and Volume of Distribution01:09

One-Compartment Open Model for IV Bolus Administration: Estimation of Elimination Rate Constant, Half-Life and Volume of Distribution

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The one-compartment open model is a simplified approach used in pharmacokinetics to understand the distribution and elimination of a drug administered through an intravenous bolus. This model assumes rapid drug dispersal throughout the body and elimination using a first-order process. Key pharmacokinetic parameters, such as the elimination rate constant (k), half-life (t1/2), and the apparent volume of distribution (Vd), can be estimated from this model. The elimination rate is calculated...
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Drug Concentrations: Measurements01:23

Drug Concentrations: Measurements

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Drug concentration is the quantity of a drug present in a biological sample. Measuring drug amounts in biological samples allows the clinician to understand how a drug is absorbed, distributed, metabolized, and excreted. Samples can be obtained through invasive or non-invasive methods. Invasive techniques involve surgical or parenteral interventions to gather blood, cerebrospinal fluid, or tissue biopsy. Conversely, non-invasive approaches provide samples like urine, feces, and saliva.
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Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
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A novel method for predicting the unbound valproic acid concentration.

Masayuki Ishikawa1, Masashi Uchida1, Takahiro Asakawa2

  • 1Division of Pharmacy, Chiba University Hospital, Chiba, Japan; Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan.

Drug Metabolism and Pharmacokinetics
|April 20, 2023
PubMed
Summary

A new formula accurately predicts unbound valproic acid (VPA) levels using total VPA and serum albumin. This improved prediction tool is widely applicable for patients without severe kidney issues.

Keywords:
Bipolar disorderEpilepsyProtein bindingTherapeutic drug monitoringValproic acid

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Area of Science:

  • Pharmacokinetics
  • Clinical Chemistry
  • Drug Monitoring

Background:

  • Accurate prediction of unbound valproic acid (VPA) concentration is crucial for therapeutic drug monitoring.
  • Existing prediction formulas exhibit limitations in accuracy and applicability.

Purpose of the Study:

  • To develop a more accurate and widely applicable prediction formula for unbound VPA concentration.
  • To evaluate the performance of the new formula against existing methods.

Main Methods:

  • Retrospective analysis of 136 datasets from 75 patients.
  • Development of a prediction formula based on a combined parameter: (total VPA concentration [μM] - 2 × serum albumin [μM]).
  • Validation using external datasets from patients without severe renal failure.

Main Results:

  • A significant correlation (r=0.76, p<0.001) was found between the combined parameter and the free fraction of VPA.
  • The developed formula demonstrated lower prediction errors compared to previous formulas in external validation.
  • The new formula showed weak trends with total VPA or serum albumin, indicating robustness.

Conclusions:

  • The novel prediction formula based on (total VPA [μM] - 2 × serum albumin [μM]) offers high accuracy and broad applicability.
  • This formula is particularly effective for predicting unbound VPA in patients without severe renal impairment.
  • The study provides a valuable tool for optimizing VPA therapy and patient management.