Acknowledgements

PoPy could not have been developed without the efforts of many people for which we are very grateful.

David Cristinacce was PoPy’s mastermind, seeing an opportunity to reimagine nonlinear mixed effects modelling in a modern language (Python). He and Phil Tresadern were responsible for software development while Richard Dimelow and Andrew Cristinacce provided valuable user feedback that helped shape PoPy’s evolution. Overall direction and business management was provided by James Wright of Wright Dose Limited, PoPy’s financial sponsor.

Python was chosen as the modern language in which to reimplement NLME methods because of its rich ecosystem of libraries, and PoPy owes a debt to the creators and maintainers of the many libraries we used, including:

• NumPy: fast C-style arrays and numerical algorithms

• SciPy: ODE solving, numerical optimization, and statistics functions

• matplotlib: figure creation

• SymPy: symbolic manipulation of code that improves both speed and accuracy

• sphinx: documentation generation tools

• pylint: encourages good coding standards

• jenkins: continuous integration and delivery to keep PoPy “clean”