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drugdevelopR - Utility-Based Optimal Phase II/III Drug Development Planning

Plan optimal sample size allocation and go/no-go decision rules for phase II/III drug development programs with time-to-event, binary or normally distributed endpoints when assuming fixed treatment effects or a prior distribution for the treatment effect, using methods from Kirchner et al. (2016) <doi:10.1002/sim.6624> and Preussler (2020). Optimal is in the sense of maximal expected utility, where the utility is a function taking into account the expected cost and benefit of the program. It is possible to extend to more complex settings with bias correction (Preussler S et al. (2020) <doi:10.1186/s12874-020-01093-w>), multiple phase III trials (Preussler et al. (2019) <doi:10.1002/bimj.201700241>), multi-arm trials (Preussler et al. (2019) <doi:10.1080/19466315.2019.1702092>), and multiple endpoints (Kieser et al. (2018) <doi:10.1002/pst.1861>).

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5.69 score 3 stars 15 scripts 152 downloads

baskwrap - Wrapper Package for Several Basket Trial R Packages

A simple interface to switch between two methods for calculating basket trial characteristics, numerical integration ("exact") and Monte Carlo simulation ("simulated") for the basket trial design by Fujikawa et al. 2020 <doi:10.1002/bimj.201800404>. The exact implementation is from the 'baskexact' package, see Baumann (2024) <doi:10.1016/j.softx.2024.101793>. The simulated implementation is from the 'basksim' package, which was developed for Baumann et al. (2024) <doi:10.1080/19466315.2024.2402275>. The package's syntax is compatible with the 'basksim' syntax and easily extendable.

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basket-trialsbayesian-statisticsclinical-trialsjagscpp

4.08 score 1 stars 1 dependents 3 scripts 546 downloads

baskoptr - Utility-Based Optimization for Basket Trial Designs

A unified framework for optimizing basket trial designs. To this end, the package supplies several utility functions and also a function for executing optimization algorithms on basket trial designs. The considered utility functions are discussed in Sauer et al. (2025) <doi:10.1371/journal.pone.0323097>.

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basket-trialsclinical-trialsoptimizationutility-functionsjagscpp

3.81 score 3 scripts 146 downloads

optimizr - Further Numerical Optimization Algorithms

A collection of numerical optimization algorithms. One is a simple implementation of the primitive grid search algorithm, the other is an extension of the simulated annealing algorithm that can take custom boundaries into account. The methodology for this bounded simulated annealing algorithm is due to Haario and Saksman (1991), <doi:10.2307/1427681>.

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grid-searchoptimization-algorithmssimulated-annealing

3.18 score 3 scripts 484 downloads