title: Solution and implementation of distributed lifespan models.
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.
authors.affiliation: Department of Pharmaceutical Sciences, State University of New York at Buffalo, 403 Kapoor Hall, Buffalo, NY, 14214, USA, gilbertk@buffalo.edu.
authors.forename: Gilbert
authors.initials: G
authors.lastname: Koch
authors.forename: Johannes
authors.initials: J
authors.lastname: Schropp
mesh_terms: D000465:Algorithms; D002470:Cell Survival / Q000187:drug effects; D004912:Erythrocytes / Q000166:cytology / Q000187:drug effects / Q000378:metabolism; D004921:Erythropoietin / Q000008:administration & dosage / Q000493:pharmacokinetics* / Q000494:pharmacology* / Q000627:therapeutic use; D006454:Hemoglobins / Q000032:analysis*; D006801:Humans; D007674:Kidney Diseases / Q000097:blood / Q000188:drug therapy*; D008954:Models, Biological; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D012984:Software; D016008:Statistical Distributions
chemical_list: D006454:Hemoglobins; D004921:Erythropoietin