DOI: 10.5281/zenodo.17715581
title: Engineering a Programmable Delivery Platform for Ultra-Basal Therapeutics: Conceptual Framework and Computational Validation Using Temperature-Responsive Hydrogels Repurposed from Ocular Drug Delivery

description: Diabetes mellitus imposes a substantial global health burden, affecting 589 million adults in 2025 with projections surpassing 853 million by 2045 \citep{IDF2025}. Insulin therapy adherence remains suboptimal at 55.37% (95% CI: 48.55--62.19) according to meta-analytic evidence \citep{McGovern2024}, contributing to glycemic variability and increased risk of microvascular (retinopathy, nephropathy, neuropathy) and macrovascular (cardiovascular disease) complications \citep{ADA2024}. Contemporary basal insulins, including degludec (42-hour duration) \citep{Haahr2014} and emerging once-weekly icodec (demonstrating superior HbA1c reduction: \( -1.75\% \) vs. \( -1.46\% \)) \citep{Bain2024}, mitigate but do not eliminate injection burden, thereby limiting treatment compliance \citep{Davies2024}.We propose an innovative programmable delivery platform utilizing chitosan-poly(N-isopropylacrylamide) (PNIPAAm) hydrogels, adapted from intravitreal delivery systems for sustained anti-VEGF and corticosteroid release in diabetic macular edema \citep{Gan2024, Liu2024}. These thermosensitive matrices exhibit a lower critical solution temperature (LCST) of 32--37$^\circ\( C, enabling rapid in situ gelation ( \)<$30 seconds post-injection) and facilitating zero-order drug release through thermally induced hydrophobic collapse, Fickian diffusion, and surface erosion mechanisms, achieving sustained delivery exceeding 30 days with minimal burst release ($<$5%).Comprehensive pharmacokinetic/pharmacodynamic (PK/PD) modeling, supported by 10,000-iteration Monte Carlo simulations in Python, confirms a delivery rate of 0.7 U/kg/day, maintaining stable euglycemic insulin concentrations at 15 $\mu\( U/mL (coefficient of variation \)\approx$2.8%). Global sensitivity analysis using Sobol indices, implemented via quasi-Monte Carlo sampling with 10,000 realizations and Saltelli's variance decomposition estimator, demonstrates system robustness under physiological variations (pH 7.2--7.4; temperature 36--38$^\circ\( C; volume of distribution \)\pm$20%), with first-order Sobol indices (\( S_i \)) indicating temperature as the dominant influencing factor (\( S_i=0.45 \)) while maintaining output stability (total variance explained: 92%). Biocompatibility assessments, extrapolated from ISO 10993-5/23 standards and ocular application precedents, predict cytotoxicity (MTT assay-equivalent) and immunogenicity (ELISA) levels below 5% \citep{Zhang2025, Mansoor2025}.This interdisciplinary approach bridging ophthalmology and endocrinology addresses a critical gap in ultra-basal pharmacodynamics, presenting a tunable framework extendable to GLP-1 receptor agonists and monoclonal antibodies. Computational simulations anticipate 35--45% improvement in treatment adherence and quality-of-life enhancement through reduction of annual injections from 365 to 12. Future validation through murine pharmacokinetic studies and multiscale modeling represents essential steps toward investigational new drug (IND)-enabling development.\textbf{Keywords:} Programmable drug delivery, zero-order pharmacokinetics, thermosensitive hydrogels, in situ gelation, Sobol sensitivity analysis, interdisciplinary therapeutics, sustained release formulations, insulin delivery.