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@ARTICLE{HollandLetz:166369,
author = {T. Holland-Letz$^*$ and A. Kopp-Schneider$^*$},
title = {{A}n {R}-shiny application to calculate optimal designs for
single substance and interaction trials in dose response
experiments.},
journal = {Toxicology letters},
volume = {337},
issn = {0378-4274},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {DKFZ-2020-02858},
pages = {18 - 27},
year = {2021},
note = {#EA:C060#LA:C060#},
abstract = {Optimal experimental design theory proposes choosing
specific settings in experimental trials in order to
maximize the precision of the resulting parameter estimates.
In dose response experiments, this corresponds to choosing
the optimal dose levels for every available observation, and
can be applied both to singular dose-response relationships
and to interaction experiments where two substances are
given simultaneously at several different mixture ratios
('ray designs'). While the theory of experimental design for
this situation is well developed, the mathematical
complexity prevents widespread use in practical
applications. A simple to use application making the theory
accessible to practitioners is thus very desirable.Results
from established optimal experimental design theory are
applied to dose response applications, focusing on
log-logistic and Weibull class dose response functions.
Suitable optimal design algorithms to solve these problems
are implemented into an R-shiny based online application.The
application provides an interface to easily calculate
D-optimal designs not only for singular dose experiments,
but also for interaction trials with several combination
rays of substances. Furthermore, the app also allows
evaluating the efficiency of existing candidate designs, and
finally allows construction of designs which perform
robustly under different assumptions in regard to the true
parameters.},
keywords = {Combination index (Other) / D-optimal design (Other) /
Dose–response studies (Other) / Optimal experimental
design (Other) / R-shiny (Other) / Web application (Other)},
cin = {C060},
ddc = {610},
cid = {I:(DE-He78)C060-20160331},
pnm = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
pid = {G:(DE-HGF)POF4-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:33232777},
doi = {10.1016/j.toxlet.2020.11.018},
url = {https://inrepo02.dkfz.de/record/166369},
}