Rapid development of pharmaceutical reagents is of the utmost interest for our collective health. Small molecule pharmaceuticals in particular are highly sought-after chemicals. Unfortunately the synthesis of these species can take months to discover and optimize because of a reliance on human-driven experimentation. Machine learning (ML) can be used to accelerate this process by building models to predict reaction conditions and yield and guide experimentation. Using a database of published chemical reactions, over 300 unique transformations involving samarium iodide from more than 200 separate publications are identified and used to build an accurate ML model. This approach could be used to automate chemical space exploration by allowing a computer to predict conditions for and then set up its own experiments, dramatically increasing the pace of discovery.
Projects & Publications
py2sambvca - Python interface to SambVca catalytic pocket calculator
Simple thin client to interface python scripts with SambVca catalytic pocket Fortran calculator. Available on Python Package index and featured on SambVca webserver. py2sambvca is available for download via GitHub and is citable via figshare.
AIMSim - Accessible and Extensible GUI for similarity visualization of chemical datasets
Artificial Intelligence Molecular Similarity (AIMSim), an accessible cheminformatics platform for performing similarity operations on collections of molecules (molecular datasets), provides a unified platform to perform similarity-based tasks on molecular datasets. AIMSim is currently in pre-print and can be found on chemrxiv.
CROW - High Throughput Experimentation Data Management Software
Crow is an open-source research tool written in Python for use in the retrieval, diagnosis, and presentation of multivariate High Throughput Experimentation data. Crow is available for download via GitHub and is citable via figshare.
MATLAB Start to Finish - Lecture Series and Practice Problems for MATLAB
Included in this repository is an (approximately) 10-week curriculum intended to cover all the essentials of MATLAB, ranging from "what is the command window?" up to evaluating partial differential equations symbolically, with a focus on the skills needed for an undergraduate chemical engineering student. View the materials on GitHub.