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A bioavailability score.

Yvonne C Martin1

  • 1Advanced Technology Division, Global Pharmaceutical Research and Development, Abbott Laboratories, Abbott Park, IL 60064-6100, USA. yvonne.c.martin@ abbott.com

Journal of Medicinal Chemistry
|April 29, 2005
PubMed
Summary

Scientists can now predict compound bioavailability (F) in rats using a new scoring method. This approach considers compound charge and polar surface area, outperforming traditional metrics for better drug development forecasting.

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Area of Science:

  • Medicinal Chemistry
  • Pharmacokinetics
  • Drug Discovery

Background:

  • Accurate prediction of compound bioavailability (F) is crucial for efficient drug discovery.
  • Existing methods like the rule-of-five and log P/log D have limitations in forecasting F.
  • Novel approaches are needed to assess permeability and bioavailability before costly testing.

Purpose of the Study:

  • To develop a predictive score for compound bioavailability (F > 10%) in rats.
  • To identify key physicochemical properties governing bioavailability based on compound charge.
  • To establish a reliable method for forecasting compound permeability and bioavailability.

Main Methods:

  • Development of a predictive score based on compound charge and polar surface area (PSA).
  • Evaluation of traditional metrics (rule-of-five, log P, log D, rotatable bonds) for compound categorization.
  • Validation of the predictive score using rat, Caco-2 cell, and human bioavailability data.

Main Results:

  • Compound charge significantly influences bioavailability prediction.
  • For anions, bioavailability (F > 10%) decreases with increasing polar surface area (PSA): 85% (PSA ≤ 75 Ų), 56% (75 < PSA < 150 Ų), 11% (PSA ≥ 150 Ų).
  • For neutral, zwitterionic, or cationic compounds, those passing the rule-of-five show higher bioavailability (55%) than those failing (17%).
  • The developed categorization also distinguishes Caco-2 cell permeability.

Conclusions:

  • A novel scoring system, considering compound charge and PSA, accurately predicts rat bioavailability.
  • This method offers a superior alternative to traditional metrics for forecasting compound permeability and bioavailability.
  • The findings aid in early-stage compound selection, reducing development costs and time.

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