%global debug_package %{nil}
%global packname dfped
%global packver 1.1
%global rlibdir /usr/local/lib/R/library
Name: R-CRAN-%{packname}
Version: 1.1
Release: 3%{?dist}
Summary: Extrapolation and Bridging of Adult Information in Early PhaseDose-Finding Paediatrics Studies
License: GPL (>= 3)
URL: https://cran.r-project.org/package=%{packname}
Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz
BuildRequires: R-devel >= 3.0.2
Requires: R-core >= 3.0.2
BuildArch: noarch
BuildRequires: R-CRAN-rstan >= 2.8.1
BuildRequires: R-CRAN-ggplot2 >= 2.0.0
BuildRequires: R-stats4
BuildRequires: R-methods
BuildRequires: R-stats
BuildRequires: R-graphics
BuildRequires: R-grDevices
Requires: R-CRAN-rstan >= 2.8.1
Requires: R-CRAN-ggplot2 >= 2.0.0
Requires: R-stats4
Requires: R-methods
Requires: R-stats
Requires: R-graphics
Requires: R-grDevices
%description
A unified method for designing and analysing dose-finding trials in
paediatrics, while bridging information from adults, is proposed in the
'dfped' package. The dose range can be calculated under three
extrapolation methods: linear, allometry and maturation adjustment, using
pharmacokinetic (PK) data. To do this, it is assumed that target exposures
are the same in both populations. The working model and prior distribution
parameters of the dose-toxicity and dose-efficacy relationships can be
obtained using early phase adult toxicity and efficacy data at several
dose levels through 'dfped' package. Priors are used into the dose finding
process through a Bayesian model selection or adaptive priors, to
facilitate adjusting the amount of prior information to differences
between adults and children. This calibrates the model to adjust for
misspecification if the adult and paediatric data are very different. User
can use his/her own Bayesian model written in Stan code through the
'dfped' package. A template of this model is proposed in the examples of
the corresponding R functions in the package. Finally, in this package you
can find a simulation function for one trial or for more than one trial.
These methods are proposed by Petit et al, (2016)
.
%prep
%setup -q -c -n %{packname}
find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \;
%build
%install
mkdir -p %{buildroot}%{rlibdir}
%{_bindir}/R CMD INSTALL -l %{buildroot}%{rlibdir} %{packname}
test -d %{packname}/src && (cd %{packname}/src; rm -f *.o *.so)
rm -f %{buildroot}%{rlibdir}/R.css
%files
%dir %{rlibdir}/%{packname}
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/help
%{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%{rlibdir}/%{packname}/INDEX