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Related Concept Videos

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.
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...
Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance01:07

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Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
A recent model describes pravastatin's hepatobiliary excretion, mediated...
Pharmacokinetic Models: Overview01:20

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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.
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Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
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PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).

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Physiologically based pharmacokinetic (PBPK) modeling and simulation: applications in lead optimization.

Sheila Annie Peters1, Anna-Lena Ungell, Hugues Dolgos

  • 1Discovery DMPK, Astrazeneca R&D, Mölndal, Sweden. Sheila.Peters@astrazeneca.com

Current Opinion in Drug Discovery & Development
|June 30, 2009
PubMed
Summary

Physiologically based pharmacokinetic (PBPK) models are becoming more common in drug lead optimization. This review covers recent publications on PBPK applications in this field, highlighting its expanding scope.

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Area of Science:

  • Pharmacokinetics
  • Drug Discovery
  • Computational Modeling

Background:

  • Physiologically based pharmacokinetic (PBPK) models are gaining traction in drug development.
  • The application of PBPK in lead optimization (LO) is a growing area of research.
  • Despite limited current literature, PBPK's role in LO is expanding.

Purpose of the Study:

  • To review recent publications on PBPK modeling in lead optimization.
  • To highlight key areas where PBPK is applied during LO.
  • To provide an overview of the expanding scope of PBPK in drug discovery.

Main Methods:

  • Literature review of recent publications.
  • Analysis of PBPK model applications in lead optimization.
  • Categorization of PBPK applications into four key areas.

Main Results:

  • Identified a steady increase in publications on PBPK for LO.
  • Highlighted four important areas of PBPK application in the LO process.
  • Demonstrated the expanding scope and utility of PBPK modeling.

Conclusions:

  • PBPK modeling is an increasingly valuable tool in lead optimization.
  • Further research and application of PBPK in drug discovery are expected.
  • The reviewed areas represent critical applications of PBPK in accelerating drug development.