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Related Concept Videos

Clearance Models: Noncompartmental Models01:17

Clearance Models: Noncompartmental Models

Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
One-Compartment Open Model for IV Bolus Administration: Estimation of Clearance00:56

One-Compartment Open Model for IV Bolus Administration: Estimation of Clearance

Clearance is a key pharmacokinetic parameter that quantifies the volume of body fluid from which a drug is entirely removed within a specific time frame. It is crucial in assessing how a drug is eliminated from the body and has critical clinical applications.
In the one-compartment open model for intravenous (IV) bolus administration, clearance is estimated by dividing the elimination rate by the plasma drug concentration. This equation leverages the elimination rate constant and the apparent...
Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's proficiency in drug...
Clearance Models: Compartment Models01:25

Clearance Models: Compartment Models

Clearance measures drug elimination from the central compartment, including plasma and highly perfused organs like kidneys and liver. Its calculation varies depending on pharmacokinetic models and administration routes. The one-compartment model, for instance, portrays the pharmacokinetics of polar drugs such as aminoglycoside antibiotics administered intravenously and readily excreted in urine. In this case, clearance is influenced by the terminal rate constant (λz) and the total volume of...
Drug Product Performance: In Vitro–In Vivo Correlation01:20

Drug Product Performance: In Vitro–In Vivo Correlation

In pharmaceutical development, it's crucial to establish a predictive in vitro–in vivo correlation (IVIVC) for two or more formulations to gain a comprehensive understanding of release properties. IVIVC reduces the need for costly in vivo studies and facilitates the establishment of meaningful dissolution specifications with significant cost savings and decreased regulatory burden. Furthermore, a meaningful IVIVC should predict Cmax and AUC within 20%, aligning with FDA guidance while adhering...
Drug Elimination: The Concept of Clearance01:06

Drug Elimination: The Concept of Clearance

Drug elimination refers to removing drugs from the body, either through urine by the kidneys or through bile by the liver. Drug clearance is a pharmacokinetic parameter that measures the efficiency of drug removal from the bloodstream within a specific time frame. It is calculated as the rate at which a drug is eliminated from plasma divided by the plasma concentration of the drug.
Drug clearance is not limited to renal excretion but encompasses all organs involved in drug elimination,...

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Predicting clearance in humans from in vitro data.

R Scott Obach1

  • 1Pharmacokinetics, Dynamics, and Drug Metabolism, Pfizer Inc., Groton, CT 06340, USA. r.scott.obach@pfizer.com

Current Topics in Medicinal Chemistry
|February 16, 2011
PubMed
Summary
This summary is machine-generated.

Predicting drug clearance in humans using in vitro metabolism data is crucial for new drug development. This chapter details methods for scaling in vitro data, highlighting necessary assumptions for accurate in vivo predictions.

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Area of Science:

  • Pharmacokinetics and Drug Metabolism
  • Drug Discovery and Development
  • Biotechnology

Background:

  • In vitro metabolism studies are standard in drug development for predicting human clearance.
  • Human liver microsomes, containing cytochrome P450 enzymes, are vital for high-throughput screening.
  • Accurate in vitro data is essential for effective drug design.

Purpose of the Study:

  • To describe methods for scaling in vitro clearance data to predict in vivo human clearance.
  • To outline the critical assumptions inherent in scaling in vitro data for in vivo predictions.
  • To discuss emerging drug clearance processes and prediction methods.

Main Methods:

  • Utilizing in vitro metabolic stability assays in human liver microsomes.
  • Applying scaling factors to extrapolate in vitro clearance data to in vivo predictions.
  • Reviewing technical considerations for generating reliable in vitro data.

Main Results:

  • Established methodologies for scaling in vitro drug metabolism data.
  • Identified key assumptions in the scaling process, including technical and procedural aspects.
  • Highlighted the importance of understanding cytochrome P450 enzyme activity.

Conclusions:

  • In vitro metabolism data scaling is a valuable tool for predicting human drug clearance.
  • Careful consideration of assumptions is paramount for successful in vivo prediction.
  • Ongoing research is expanding prediction methods for other drug clearance pathways.