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Related Concept Videos

Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal assumptions,...
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
Pharmacokinetic–Pharmacodynamic Relationship: Problems01:24

Pharmacokinetic–Pharmacodynamic Relationship: Problems

The empirical approach to drug therapy optimization relies on correlating pharmacological response with administered dosage. Such an approach can be costly, time-consuming, and often yields poor correlation due to variables like formulation factors and drug elimination characteristics. A more precise approach correlates response with plasma drug concentration or the amount of drug in the body, rather than dosage. This is achieved through pharmacokinetic-pharmacodynamic (PK/PD) modeling, which...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.

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A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
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Predicting pharmacokinetic profiles using in silico derived parameters.

Natalie A Hosea1, Hannah M Jones

  • 1Department of Pharmacokinetic, Dynamics and Metabolism, Pfizer, Inc., Cambridge, Massachusetts 02140, USA. natalie.hosea@pfizer.com

Molecular Pharmaceutics
|February 23, 2013
PubMed
Summary
This summary is machine-generated.

Accurate human pharmacokinetic (PK) predictions are crucial for drug development. Modeling and simulation using in silico or in vitro data can successfully predict PK profiles, aiding early discovery decisions.

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Area of Science:

  • Pharmacokinetics and Drug Metabolism
  • Computational Chemistry and Molecular Modeling
  • Pharmaceutical Sciences

Background:

  • Human pharmacokinetic (PK) predictions are vital for evaluating drug candidates.
  • Accurate estimation of clearance, volume of distribution, bioavailability, and plasma-concentration-time profiles are key endpoints.
  • Traditional methods often rely on in vivo data, but in vitro or in silico approaches offer alternatives.

Purpose of the Study:

  • To demonstrate the feasibility of predicting human PK profiles using modeling and simulation with limited data.
  • To showcase the utility of commercially available software like GastroPlus in early drug discovery.
  • To highlight the value of in silico and in vitro data for predicting absorption and disposition.

Main Methods:

  • Utilized GastroPlus software for modeling and simulation.
  • Employed in silico derived parameters for PK predictions.
  • Applied in vitro measured parameters for PK predictions.
  • Conducted case studies in early drug discovery settings.

Main Results:

  • Successfully predicted plasma-concentration-time profiles using both in silico and in vitro data.
  • Demonstrated the feasibility of predicting PK profiles with minimal data.
  • Case studies confirmed the accuracy of GastroPlus predictions.

Conclusions:

  • Modeling and simulation with in silico or in vitro data can adequately predict human PK profiles.
  • This approach provides valuable information for dose selection, compound optimization, and clinical protocol design.
  • The use of modeling and simulation is beneficial in early discovery and exploratory development for predicting absorption and disposition.