QUANTUM-DOT-ASSISTED ELECTRONIC SENSING AND MATHEMATICAL OPTIMIZATION OF pH-RESPONSIVE HYDROGEL DRUG DELIVERY: A COMPUTATIONAL FRAMEWORK

Source abstract

Background: pH-responsive hydrogels are promising materials for controlled drug delivery because changes in environmental pH can influence polymer ionization, network swelling, and molecular transport. However, predicting drug-release behaviour and interpreting associated measurements remain challenging because of the coupled effects of polymer chemistry, drug diffusion, and measurement uncertainty. Mathematical modelling, quantum-dot-based optical transduction, and electronic signal processing provide complementary approaches for investigating these processes. Objective: This study proposes an integrated computational framework combining pH-responsive hydrogel drugrelease modelling, quantum-dot-assisted optical sensing, electronic signal processing, and mathematical optimization. Methods: The framework is centred on a poly(2-hydroxyethyl methacrylate-co-methacrylic acid) (pHEMA-coMA) hydrogel containing phenylpropanolamine as a reference drug. The proposed model connects pH-dependent hydrogel swelling with drug transport and release. A virtual quantum-dot optical module is introduced to represent a calibrated concentration-dependent measurement response, while an electronic signal-processing module is designed to examine the effects of sampling, measurement noise, baseline variation, and digital filtering. Numerical verification, comparison with published reference data, sensitivity analysis, uncertainty quantification, and multi-objective optimization are specified as evaluation procedures. Results: The manuscript establishes the mathematical and computational structure required to investigate the coupled system. Quantitative performance, including drug-release prediction errors, numerical convergence, sensor-response characteristics, signal-processing metrics, and optimization outcomes, must be established through execution of the model and comparison with appropriate reference data. No unperformed simulations or experimental outcomes are presented as completed findings. Conclusion: The proposed framework provides a structured computational approach for connecting pHresponsive hydrogel drug-release modelling with optical measurement and electronic signal interpretation. Its predictive accuracy and practical applicability remain to be established through reproducible numerical implementation, comparison with published experimental data, and independent validation of the proposed sensing mechanism.