BPharm, Faculty of Pharmacy — Ain Shams University. I build open-source computational tools at the intersection of cheminformatics, machine learning, and pharmaceutical formulation science, and publish peer-reviewed research on nanomedicine and drug delivery.
I'm a pharmacist and computational researcher working on tools that connect cheminformatics, machine learning, and pharmaceutical formulation engineering — with a focus on CNS drug delivery and nanomedicine. My long-term goal is to help build a coherent, reproducible, open-source ecosystem for computational pharmaceutics: engine that pharmaceutical researchers can actually trust, verify, and build on, not black-box tools with unverifiable claims. I care as much about honest reporting of what a model does and doesn't do as I do about the model itself.
An open-source pipeline that scores candidate drug-delivery-system formulations against an in-house, transparently-documented 62-criterion rubric, and includes a real deep-learning blood-brain- barrier permeability classifier (trained on the public BBBP benchmark, ~90% held-out accuracy, RDKit + TensorFlow) plus a genetic-algorithm formulation optimizer. Every computed value carries an explicit tier, method, and citation — including which parts are literature-grounded correlations versus in-house heuristics not yet independently validated.
Full, up-to-date list on ORCID (0000-0002-9171-437X).
Open to research collaborations, PhD/postdoc opportunities, and conversations about open-source computational pharmaceutics tooling.