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Drug Metabolism: Phase I Reactions

Drug Metabolism: Phase I Reactions

A phase I reaction is a biochemical process that introduces a functionally reactive polar group to a substance. This transformation predominantly occurs in the liver, facilitated by the cytochrome P450 system of hemoproteins situated in the lipophilic endoplasmic reticulum of cells. The metabolite generated through this process can have varying polarities. If it is sufficiently polar, it can be easily excreted in the urine due to its water compatibility. However, if the metabolite is nonpolar,...

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Updated: Sep 6, 2025

Mass Spectrometry and Luminogenic-based Approaches to Characterize Phase I Metabolic Competency of In Vitro Cell Cultures

Mass Spectrometry and Luminogenic-based Approaches to Characterize Phase I Metabolic Competency of In Vitro Cell Cultures

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An improved method for cytochrome p450 reaction phenotyping using a sequential qualitative-then-quantitative

Angela C Doran¹, Alyssa L Dantonio², Gabrielle M Gualtieri³

¹Medicine Design - ADME Sciences, Pfizer, United States.

Drug Metabolism and Disposition: the Biological Fate of Chemicals

|July 1, 2022

Summary

This study introduces a two-step method for drug metabolism phenotyping, improving accuracy in identifying key drug-metabolizing enzymes. This approach enhances predictions of drug interactions and genetic variability in drug clearance.

Keywords:

cytochrome P450 drug metabolism drug-drug interactions

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Last Updated: Sep 6, 2025

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Covalent Fragment Screening Using the Quantitative Irreversible Tethering Assay

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Published on: February 28, 2025

Area of Science:

Pharmacology
Drug Metabolism
Biochemistry

Background:

Cytochrome P450 (CYP) reaction phenotyping is crucial for drug evaluation, determining fractional metabolism (f_m) by individual enzymes.
Current methods face challenges due to poor selectivity of CYP inhibitors and unreliable scaling of recombinant CYP (rCYP) data.
Accurate f_m values are essential for predicting drug-drug interactions (DDIs) and understanding inter-individual variability in drug exposure.

Purpose of the Study:

To develop and validate a novel two-step "qualitative-then-quantitative" approach for P450 reaction phenotyping.
To improve the accuracy and reliability of determining f_m values for major drug-clearing enzymes.
To provide better input data for physiologically-based pharmacokinetic (PBPK) models.

Main Methods:

A two-step strategy: 1) Qualitative assessment of rCYP potential to generate metabolites for 48 drugs.
2) Quantitative assessment using selective inhibitors and full inhibition curves for identified CYPs.
Comparison of f_m values obtained with the new method against existing estimates and clinical data for five selected drugs.

Main Results:

The qualitative step successfully identified important drug-metabolizing enzymes without missing any.
The two-step approach yielded f_m values closely aligning with clinical data for escitalopram, fluvastatin, pioglitazone, propranolol, and risperidone.
Findings demonstrated improved accuracy compared to estimates from single inhibitor concentrations and rCYP data with intersystem-extrapolation-factor corrections.

Conclusions:

The qualitative-then-quantitative approach offers a more reliable method for P450 reaction phenotyping.
This improved phenotyping strategy can enhance the accuracy of PBPK models for predicting DDIs and genetic polymorphism impacts.
The proposed method is recommended as a replacement for current standard reaction phenotyping strategies.