You can call me Ben.
I'm a Pharmacology graduate from the University of Reading and an incoming MSc student in Artificial Intelligence for Drug Discovery at Queen Mary University of London.
My interests lie at the intersection of pharmacology, computational chemistry and artificial intelligence. I'm currently building open source scientific software for computational drug discovery, cheminformatics and molecular modelling.
This GitHub documents my transition from pharmacology to computational drug discovery through open source scientific software projects, each inspired by real problems encountered during my studies.
- 🧬 Computational Drug Discovery
- 🤖 Artificial Intelligence for Drug Discovery
- 🧪 Molecular Docking
- ⚗️ Cheminformatics
- 🧫 Structure Based Drug Design
- 💻 Scientific Software Development
- 💊 Pharmacology
A ligand pre screening tool designed to support molecular docking workflows.
Compares molecular structures using RDKit Morgan fingerprints and Tanimoto similarity.
Evaluates compounds using molecular descriptors and Lipinski's Rule of Five.
A pharmacokinetic simulator modelling first order elimination and repeated dose accumulation.
- Python
- RDKit
- Artificial Intelligence for Drug Discovery
- Machine Learning
- Scientific Software Engineering
- Structure Based Drug Design
- Computational drug discovery
- Cheminformatics
- Molecular docking
- Scientific Python projects
- Scientific software architecture
- Python best practices
- Open source research software
Every project on my GitHub started with me asking, "There has to be a faster way to do this." DockAssist was the first, inspired by my undergraduate dissertation on molecular docking reproducibility, and it set the direction for everything that followed.
Incoming MSc in Artificial Intelligence for Drug Discovery
Queen Mary University of London
BSc Pharmacology
University of Reading
Building practical software for computational drug discovery, one project at a time.