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Related Experiment Video

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Building Sub-Saharan African PBPK Populations Reveals Critical Data Gaps: A Case Study on Aflatoxin B1.

Orphélie Lootens1,2,3,4, Marthe De Boevre1,3,4, Sarah De Saeger1,3,4,5

  • 1Centre of Excellence in Mycotoxicology and Public Health, Department of Bioanalysis, Ghent University, 9000 Ghent, Belgium.

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|October 28, 2025
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Summary

Physiologically based pharmacokinetic models require distinct population data. Sub-Saharan Africa (SSA) shows significant CYP450 phenotype variations, necessitating regional PBPK modeling over a single entity approach.

Keywords:
CYP450-enzymesPBPKSub-Saharan Africadiversitygeneticspharmacokinetics

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Area of Science:

  • Pharmacokinetics and Drug Metabolism
  • Computational Biology and Modeling
  • Population Genetics and Epidemiology

Background:

  • Physiologically based pharmacokinetic (PBPK) models simulate compound behavior in diverse populations.
  • Categorizing individuals into distinct populations for PBPK modeling presents classification challenges.
  • Previous PBPK studies simulated aflatoxin B1 pharmacokinetics in South African populations.

Purpose of the Study:

  • To investigate the prevalence of clinical CYP450 phenotypes across Sub-Saharan Africa (SSA).
  • To assess the feasibility of defining SSA as a single population for PBPK modeling.
  • To identify regional variations in CYP450 enzyme activity relevant for PBPK simulations.

Main Methods:

  • Subdivided SSA into Central, East, South, and West African regions for analysis.
  • Collected and assigned available CYP450 phenotype data from literature to respective regions.
  • Constructed region-specific PBPK populations using SimCYP software and performed simulations with CYP probe substrates.

Main Results:

  • Significant differences in CYP450 phenotype frequencies (CYP2B6, CYP2C19, CYP2D6) were observed between African regions.
  • Critical data gaps were identified, with literature data covering less than 70% of most regions.
  • PBPK simulations revealed regional PK parameter variations, supporting the need for distinct regional models.

Conclusions:

  • Sub-Saharan Africa cannot be accurately represented as a single population for PBPK modeling due to significant regional CYP450 phenotype variations.
  • Limited in vivo data availability restricts comprehensive validation of PBPK models across SSA.
  • Future PBPK modeling in SSA requires extensive, region-specific data to enhance accuracy and predictive value, ideally at a regional level.