Abstract
Physiologically based pharmacokinetic (PBPK) models allow to simulate the behaviour
of compounds in diverse physiological populations. However, the categorization of individuals
into distinct populations raises questions regarding the classification criteria.
In previous research, simulations of the pharmacokinetics of the mycotoxin aflatoxin B1
(AFB1), were performed in the black South African population, using PBPK modeling.
This study investigates the prevalence of clinical CYP450 phenotypes (CYP2B6, CYP2C9,
CYP2C19, CYP2D6, CYP3A4/5) across Sub-Saharan Africa (SSA), to determine the feasibility
of defining SSA as a single population. SSA was subdivided into Central, East, South
and West Africa. The phenotype data were assigned to the different regions and a fifth SSA
group was composed of all regions’ weighted means. Available data from literature only
covered 7.30% of Central, 56.9% of East, 38.9% of South and 62.9% ofWest Africa, clearly
indicating critical data gaps. A pairwise proportion test was performed between the regions
on enzyme phenotype data. When achieving statistical significance (p < 0.05), a Cohen’s dtest
was performed to determine the degree of the difference. Next, per region populations
were built using SimCYP starting from the available SSA based SouthAfrican_Population
FW_Custom population, supplemented with the phenotype data from literature. Simulations
were performed using CYP probe substrates in all populations, and derived PK
parameters (Cmax, Tmax, AUCss and CL) were plotted in bar charts. Significant differences
between the African regions regarding CYP450 phenotype frequencies were shown for
CYP2B6, CYP2C19 and CYP2D6. Limited regional data challenge the representation of
SSA populations in these models. The scarce availability of in vivo data for SSA regions
restricted the ability to fully validate the developed PBPK populations. However, observed
literature data from specific SSA regions provided partial validation, indicating that SSA
populations should ideally be modelled at a regional level rather than as a single entity.
The findings, emerging from the initial AFB1-focused PBPK work, underscore the need for
more extensive and region-specific data to enhance model accuracy and predictive value
across SSA.
Toxins