Population characteristics

The population characteristics used in the model are obtained from NHANES datasets from various years ranging from 1999 - 2018.¹ The age, weight and height of the individual are generated randomly from a normal distribution. Based on the given age, appropriate mean and standard deviation for weight and height are chosen. BMI and BSA are computed based on the generated weights and heights. If the BMI is not in the acceptable range (i.e. <65 kg/m² for males, and <80 kg/m² for females, according to the NHAHES dataset), a new individual is generated until this condition is satisfied.

The organ weights were computed using various anthropometric equations obtained from the literature.² The organ weights depend on the population characteristics - age, weight, height, bmi and bsa of the individual. The organ volumes were computed using the organ weights and organ densities.

The cardiac output (Q_co) was computed from the weight of the individual³ as represented by the following equation:

The blood flow rate to the individual organs was computed as a percentage of the cardiac output.³

Currently, there are three species that can be selected on Teoreler, namely, human, rat and mouse.

When the species is human, the age group options are shown with Adult (18-60 years) and Child (2-18 years). Additional options including the year of study, minimum and maximum ages are shown.

The average population tends to vary every few years. Therefore, the model has an option to select the appropriate year during which the clinical study was performed. This way, the available population nearest to the study year is used for simulation. By default, the latest year is considered.

The user can define the age range for the population using the minimum age and maximum age input fields. The age range for the children and adult models are 2-18 years and 18-60 years, respectively. Random age values from a normal distribution, customized to the user-provided population range, will be generated.

Users can select specific animal strains to account for weight variations, aiding in the tailored simulation of pharmacokinetics. Each strain is accompanied by an associated age range, delineating the lower and upper limits for age-related weight computations. If a value falls outside this range, the computation considers the respective lowest or highest age to determine the weights accurately. This feature facilitates precise customization of pharmacokinetic simulations based on the chosen animal strain and its corresponding age parameters.

The animal's age influences the weight applied in the model. Next to each strain, the initial age of the animal should be specified to calculate the weights appropriately. If the age falls outside the given range for a particular strain, the weights will be computed using the lowest or highest age from the provided range.

Please note: Age of the animal should be provided in weeks.

An option to select the sex of the simulated individual is provided. If the option 'Both' is selected, and population is 1, an average male is simulated.

This value dictates the size of the simulated population, with a maximum of 100 individuals. A cap has been implemented to restrict the load on the server.

Please note: It's important to highlight that when the population is greater than one, the plasma plot displays a shared region representing the 90% confidence range, capturing any observed variations among the simulated individuals.

This value can be used to determine the percentage of female population in the total simulated population.

An option to regenerate the same population with identical characteristics, anatomy and physiology every simulation with same parameters is provided to reproduce the results.

1. Fryar CD, Carroll MD, Gu Q, Afful J, Ogden CL. Anthropometric Reference Data for Children and Adults: United States, 2015-2018. Vital Health Stat 3. 2021 Jan(36): 1-44. https://pubmed.ncbi.nlm.nih.gov/33541517
2. Bosgra S, Eijkeren Jv, Bos P, Zeilmaker M, Slob W. An improved model to predict physiologically based model parameters and their inter-individual variability from anthropometry. Crit Rev Toxicol. 2012 Oct;42(9):751-67. https://doi.org/10.3109/10408444.2012.709225
3. NSCEP. Physiological Parameter Values for PBPK Models. 1994. https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=9100K030.txt