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CATEGORIES:Applied Mathematics Seminar Series
SUMMARY:Using mathematical modelling to predict optimal an
tibiotic treatment strategies. - Dr Pia Abel zur
Weisch\, University of TromsÃ¸
DTSTART:20160504T100000Z
DTEND:20160504T110000Z
UID:TALK2047AT
URL:/talk/index/2047
DESCRIPTION:Optimal dosing of antibiotics has proven challengi
ng - some antibiotics are most effective when they
are administered periodically at high doses\, whi
le others work best when minimizing concentration
fluctuations. Mechanistic explanations for why ant
ibiotics differ in their optimal dosing are lackin
g\, limiting our ability to predict optimal therap
y and leading to long and costly experiments.\n \n
We use mathematical models that describe both bact
erial growth and intracellular antibiotic-target b
inding to investigate the effects of fluctuating a
ntibiotic concentrations on individual bacterial c
ells and bacterial populations.\n \nWe show that p
hysicochemical parameters\, e.g. the rate of drug
transmembrane diffusion and the antibiotic-target
complex half-life are sufficient to explain which
treatment strategy is most effective. If the drug-
target complex dissociates rapidly\, the antibioti
c must be kept constantly at a concentration that
prevents bacterial replication. If antibiotics cro
ss bacterial cell envelopes slowly to reach their
target\, there is a delay in the onset of action t
hat may be reduced by increasing initial antibioti
c concentration. Finally\, slow drug-target dissoc
iation and slow diffusion out of cells act to prol
ong antibiotic effects\, thereby allowing for less
frequent dosing. Our model can be used as a tool
in the rational design of treatment for bacterial
infections. It is easily adaptable to other biolog
ical systems\, e.g. HIV\, malaria and cancer\, whe
re the effects of physiological fluctuations of dr
ug concentration are also poorly understood.
LOCATION:Lecture Room C\, Watson Building
CONTACT:David Smith
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