Solution and implementation of distributed lifespan models
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...
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Published in | Journal of pharmacokinetics and pharmacodynamics Vol. 40; no. 6; pp. 639 - 650 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Boston
Springer US
01.12.2013
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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ISSN: | 1567-567X 1573-8744 |
DOI: | 10.1007/s10928-013-9336-y |