We present the
open-source AiZynthFinder software that can be readily used in retrosynthetic
planning. The algorithm is based on a Monte Carlo tree search that recursively
breaks down a molecule to purchasable precursors. The tree search is guided by
an artificial neural network policy that suggests possible precursors by
utilizing a library of known reaction templates. The software is fast and can typically find a
solution in less than 10 seconds and perform a complete search in less than 1
minute. Moreover, the writing of the code was guided by a range of software
engineering principles such as automatic testing, system design and continuous
integration leading to robust software. The object-oriented design makes the
software very flexible and can straightforwardly be extended to support a range
of new features. Finally, the software is clearly documented and should be easy
to get started with. The software is available at http://www.github.com/MolecularAI/aizynthfinder.
Development and Uncertainty Analysis of an Automatic Testing System for Diffusion Pump Performance