CSLS-MC-Release-Kinetics: Dataset and simulation code for Probabilistic Prediction of Encapsulated Compound Release Mechanisms Across Polymer Categories: A Literature-Scale Monte Carlo Framework

Dataset and Python 3.11 simulation code for: Probabilistic Prediction of Encapsulated Compound Release Mechanisms Across Polymer Categories: A Literature-Scale Monte Carlo Framework. Submitted to Journal of Controlled Release. Contains: a systematically compiled kinetic parameter database (1,126 QC-passed records, 76 publications, 8 kinetic models, 6 molecular structure categories); derived data tables (Korsmeyer–Peppas simulation pool, Monte Carlo summary statistics, pairwise Mann–Whitney effect sizes, Dunn post-hoc comparisons, and Monte Carlo release profiles); a bootstrap Monte Carlo simulation script (N = 10,000 iterations; seeds 42/123/999); an R statistical validation script; and a Python requirements file. The deposited code performs the bootstrap Monte Carlo simulation, the statistical tests, and the parametric distribution fitting (with R fitdistrplus cross-validation).