## Solution and implementation of distributed lifespan models

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2013
Journal article
##### Published in
Journal of Pharmacokinetics and Pharmacodynamics ; 40 (2013), 6. - pp. 639-650. - ISSN 1567-567X. - eISSN 1573-8744
##### Abstract
We consider a population where every individual has a unique lifespan. After expiring of its lifespan the individual has to leave the population. A realistic approach to describe these lifespans is by a continuous distribution. Such distributed lifespan models (DLSMs) were introduced earlier in the indirect response context and consist of the mathematical convolution operator to describe the rate of change. Therefore, DLSMs could not directly be implemented in standard PKPD software. In this work we present the solution representation of DLSMs with and without a precursor population and an implementation strategy for DLSMs in ADAPT , NONMEM and MATLAB . We fit hemoglobin measurements from literature and investigate computational properties.
##### Subject (DDC)
500 Natural Sciences
##### Cite This
ISO 690KOCH, Gilbert, Johannes SCHROPP, 2013. Solution and implementation of distributed lifespan models. In: Journal of Pharmacokinetics and Pharmacodynamics. 40(6), pp. 639-650. ISSN 1567-567X. eISSN 1573-8744. Available under: doi: 10.1007/s10928-013-9336-y
BibTex
@article{Koch2013-12Solut-26822,
year={2013},
doi={10.1007/s10928-013-9336-y},
title={Solution and implementation of distributed lifespan models},
number={6},
volume={40},
issn={1567-567X},
journal={Journal of Pharmacokinetics and Pharmacodynamics},
pages={639--650},
author={Koch, Gilbert and Schropp, Johannes}
}

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<dcterms:abstract xml:lang="eng">We consider a population where every individual has a unique lifespan. After expiring of its lifespan the individual has to leave the population. A realistic approach to describe these lifespans is by a continuous distribution. Such distributed lifespan models (DLSMs) were introduced earlier in the indirect response context and consist of the mathematical convolution operator to describe the rate of change. Therefore, DLSMs could not directly be implemented in standard PKPD software. In this work we present the solution representation of DLSMs with and without a precursor population and an implementation strategy for DLSMs in ADAPT , NONMEM and MATLAB . We fit hemoglobin measurements from literature and investigate computational properties.</dcterms:abstract>
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