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>).

Ingredient specific diagnostics for drug exposure records in the Observational Medical Outcomes Partnership (OMOP) common data model.

Prepare prescription data (such as from the Clinical Practice Research Datalink) into an analysis-ready format, with start and stop dates for each patient's prescriptions. Based on Pye et al (2018) <doi:10.1002/pds.4440>.

A systematic biology tool was developed to repurpose drugs via a drug-drug functional similarity network. 'DrugSim2DR' first predict drug-drug functional similarity  in the context of specific disease, and then using the similarity constructed a weighted drug similarity network. Finally, it used a network propagation algorithm on the network to identify drugs with significant target abnormalities as candidate drugs.

Summarise patient-level drug utilisation cohorts using data mapped 
    to the Observational Medical Outcomes Partnership (OMOP) common data model. 
    New users and prevalent users cohorts can be generated and their 
    characteristics, indication and drug use summarised.

Includes various functions for playing drum sounds. beat() plays a drum sound
  from one of the six included drum kits. tempo() sets spacing between calls to beat()
  in bpm. Together the two functions can be used to create many different drum patterns.