Evolving novel and effective treatment plans in the context of infection dynamics models: Illustrated with HIV and HAART therapy

Rebecca Haines, David Corne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Several diseases involve complex interplay between an infection and the body's defences. Concerning AIDS, for example, this corresponds to developments in the immune system's responses and the HIV virus' counter-responses. Treatment for such diseases involves, at specific times, delivery of an agent that inhibits the infection. We hypothesise that: given a credible model of the combined dynamics of infection and response, the timing and quantities involved in treatment can be valuably investigated using that model. In particular, we investigate searching for optimised treatment plans with an evolutionary algorithm (EA). Our test case is a cellular automaton (CA) model of HTV dynamics, extended to incorporate HAART therapy (a favoured HTV treatment).An EA is wrapped around this model, and searches for treatments that maximally delay onset of AIDS, given certain constraints. We find that significant improvements over default HAART strategy are readily discovered in this way. © Springer-Verlag Berlin Heidelberg 2006.

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature, PPSN IX - 9th International Conference, Procedings
Pages413-422
Number of pages10
Volume4193 LNCS
Publication statusPublished - 2006
Event9th International Conference on Parallel Problem Solving from Nature - Reykjavik, Iceland
Duration: 9 Sep 200613 Sep 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4193 LNCS
ISSN (Print)0302-9743

Conference

Conference9th International Conference on Parallel Problem Solving from Nature
Abbreviated titlePPSN IX
CountryIceland
CityReykjavik
Period9/09/0613/09/06

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