Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jul;87(7):2847-2854.
doi: 10.1111/bcp.14694. Epub 2021 Jan 11.

Constructing a representative in-silico population for paediatric simulations: Application to HIV-positive African children

Roeland E Wasmann  1 , Elin M Svensson  2   3 , A Sarah Walker  4 , Michelle N Clements  4 , Paolo Denti  1
Affiliations

Constructing a representative in-silico population for paediatric simulations: Application to HIV-positive African children

Roeland E Wasmann et al. Br J Clin Pharmacol. 2021 Jul.

Abstract

Aims: Simulations are an essential tool for investigating scenarios in pharmacokinetics-pharmacodynamics. The models used during simulation often include the effect of highly correlated covariates such as weight, height and sex, and for children also age, which complicates the construction of an in silico population. For this reason, a suitable and representative patient population is crucial for the simulations to produce meaningful results. For simulation in paediatric patients, international growth charts from the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) provide a reference, but these may not always be representative for specific populations, such as malnourished children with HIV or acutely unwell children.

Methods: We present a workflow to construct a virtual paediatric patient population using WHO and CDC growth charts, suggest piecewise linear functions to adjust the median of the growth charts by sex and age, and suggest visual diagnostics to compare with the target population. We applied this workflow in a population of 1206 HIV-positive African children, consisting of 19 742 observations with weight ranging from 3.8 to 79.7 kg, height from 55.5 to 180 cm, and an age between 0.40 and 18 years.

Results: Before adjustment, the WHO and CDC charts produced weights and heights higher compared to the observed data. After applying our methodology, we could simulate weight, height, sex and age combinations in good agreement with the observed data.

Conclusion: The methodology presented here is flexible and may be applied to other scenarios where WHO and CDC growth standards might not be appropriate. In addition we provide R scripts and a large ready-to-use paediatric population.

Keywords: modelling; paediatric population; pharmacokinetics-pharmacodynamics; simulation; underweight; weight-for-age.

PubMed Disclaimer

Conflict of interest statement

R.W. and P.D. are supported by PediCAP, which is part of the EDCTP programme supported by the European Union (grant number RIA2017MC‐2023). E.M.S. is supported by PanACEA, which is part of the EDCTP programme supported by the European Union (grant number TRIA2015‐1102‐PanACEA). A.S.W. and M.C. are supported by core support from the Medical Research Council UK to the MRC Clinical Trials Unit (MC_UU_12023/22) through a concordat with the Department for International Development. A.S.W. is also an National Institute for Health Research (NIHR) Senior Investigator. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health or Public Health England (PHE). P.D. receives support from the National Research Foundation (NRF) of South Africa (NRF grant 109 056).

Figures

FIGURE 1
FIGURE 1
The correlation between height‐ and weight‐for‐age z‐score in the ARROW dataset was 0.70
FIGURE 2
FIGURE 2
Agreement between the observed (blue dots) and simulated (black dots) distribution of weight (top row), height (middle row) and fat‐free mass (bottom row) before (left column) and after (right column) adjusting the simulated data using the sex‐ and age‐dependent adjustment factor. The lines represent the median, 5th and 95th percentile of the observed (blue) and simulated (black) data
FIGURE 3
FIGURE 3
Adjustment factors for patient weight (top) and height (bottom). The lines represent the piecewise linear functions describing the relation between age and the adjustment factor for females (red) and males (blue). The functions are given in Supporting Information Tables S1 and S2. The dashed red line represents the situation where a population is already in line with WHO and CDC growth charts
FIGURE 4
FIGURE 4
Agreement between the observed data from the CHAPAS‐3 trial (red dots) and simulated (black dots) distribution of weight (top row), height (middle row) and fat‐free mass (bottom row) before (left column) and after (right column) adjusting the simulated data using the sex‐ and age‐dependent adjustment factor. The lines represent the median of the observed (red) and simulated (black) data
See this image and copyright information in PMC

References

    1. Teutonico D, Musuamba F, Maas HJ, et al. Generating virtual patients by multivariate and discrete re‐sampling techniques. Pharm Res. 2015;32(10):3228‐3237. 10.1007/s11095-015-1699-x - DOI - PMC - PubMed
    1. Janmahasatian S, Duffull SB, Ash S, Ward LC, Byrne NM, Green B. Quantification of lean bodyweight. Clin Pharmacokinet. 2005;44(10):1051‐1065. 10.2165/00003088-200544100-00004 - DOI - PubMed
    1. Al‐Sallami HS, Goulding A, Grant A, Taylor R, Holford NHG, Duffull SB. Prediction of fat‐free mass in children. Clin Pharmacokinet. 2015;54(11):1169‐1178. 10.1007/s40262-015-0277-z - DOI - PubMed
    1. Anderson BJ, Holford NHG. Mechanism‐based concepts of size and maturity in pharmacokinetics. Annu Rev Pharmacol Toxicol. 2008;48(1):303‐332. 10.1146/annurev.pharmtox.48.113006.094708 - DOI - PubMed
    1. World Health Organization . WHO Child Growth Standards Length/Height‐for‐Age, Weight‐for‐Age, Weight‐for‐Length, Weight‐for‐Height and Body Mass Index‐for‐Age: Methods and Development. France: World Health Organization; 2006;369:1‐312. https://www.who.int/publications/i/item/924154693X

Publication types