Drug Release Analysis Framework
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Updated
Sep 8, 2026 - Python
Drug Release Analysis Framework
Stanford Appel Lab - Study Pharmacokinetics Project: Pharmacokinetic Data Modeling and Visualization Tool. Primary usage for drug delivery studies. Web app written in HTML/CSS/JS using libraries from CDNs so it can be deployed on static pages.
Stanford Appel Lab - Study Pharmacokinetics Project: Pharmacokinetic data modeling and visualization tool. Primary usage for drug delivery studies. Python supporting files and an example Jupyter Notebook for configuring custom PK analysis
With a focus on BBB modulation, safety, and translational relevance, this academic research project investigates targeted ultrasound and microbubble-mediated approaches for improved CNS and brain tumor drug delivery.
This model makes predictions on LNP Encapsulation Efficiency % based on training data acquired from the LNP Atlas project
CPP classification (F1 0.80) and cellular uptake regression (R² 0.79) on the POSEIDON database · DataCon 3.0 · Python · RDKit · CatBoost
MATLAB code for Ouyang et al. (2020) - A dose threshold to enhance nanoparticle tumour delivery. Quantification of nanoparticle concentration as a function of distance from blood vessels from 3D light-sheet microscopy images.
Official repository of "A Machine Learning Framework for Predicting Entrapment Efficiency in Niosomal Particles".
In silico approaches for designing and predicting highly effective cell penetrating peptides
Construct-validity audit of the standard blood–brain barrier (BBB) peptide benchmark: an identity-controlled re-evaluation + shared-source provenance/overlap map, with an open, CPU-reproducible evaluation harness. Do these predictors measure penetration, or their benchmarks?
Computational simulation of PLGA nanoparticle transport, drug release, and tumor response using finite difference methods in Python.
Personal academic site for Molham Sakkal - Cancer Cell Biology and Drug Delivery research at Al Ain University HBRC. Auto-synced from Google Scholar weekly.
CHIMERA v2: Computational design engine for PSC NRPS engineering. Stage 1 of the Pharmacosynthetic Constructor pipeline. This architecture is heavily in its WIP stage and currently a prototype expect bugs and unfinished code repairs and debugging is currently in progress
R package and Shiny application for reproducible empirical drug-release kinetic modelling
A transformer model to predict Lipid Nanoparticle (LNP) efficacy on different cell types
Review Article on Nanomaterial-Based Sensors for Biomedical and Pharmaceutical Applications
Method components (convection-diffusion residual, release-schedule optimizer) for PINN-based pulsatile flow and targeted drug delivery (J. Pharmacy and Bioallied Sciences, Dec 2025). Not a runnable pipeline — see Status.
Interactive BBB nanocarrier adhesion triage tool + literature gap map. DLVO/PMF physics via Pyodide, runs entirely in-browser. Liposomes only for now — not a validated efficacy predictor.
Liquidia — independent third-party profile of a public API surface, by API Evangelist. Liquidia Corporation (NASDAQ: LQDA) is a biopharmaceutical company focused on the development and commercialization of inhaled therapies for cardiopulmonary disease, specifically pulmonary arterial hypertension (PAH) and pulmonary hypertension associated with int
Rani Therapeutics — independent third-party profile of a public API surface, by API Evangelist. Rani Therapeutics is a clinical-stage biotechnology company developing the RaniPill, an ingestible robotic capsule engineered to deliver biologic drugs orally in place of subcutaneous or intravenous injections.
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