ABSTRACT The prevalent formation of by‐products in conventional methamphetamine (MA) synthesis critically impairs final product purity, presenting a significant challenge that necessitates elaborate and costly downstream purification strategies. To overcome these limitations, this study introduces molecularly imprinted polymer (MIP)‐based nanopolymers as a highly selective, efficient, and cost‐effective alternative for the isolation of MA and its primary metabolite, amphetamine (AMP). Novel MA‐imp‐HEMAT and AMP‐imp‐HEMAT nanopolymers were synthesized via bulk polymerization and thoroughly characterized using FTIR, zeta potential, particle size analysis, and SEM. The polymers demonstrated high binding capacities of 1039 mg/g for MA and 967 mg/g for AMP with negligible cross‐reactivity (relative % Q : 1.27% for MA, 2.46% for AMP). Both nanopolymers exhibited excellent reusability, retaining desorption efficiencies above 95% across five consecutive cycles. To enhance data granularity while minimizing experimental resource demands, Gaussian noise–based sampling and interpolation‐driven data augmentation were applied. The fidelity of the augmented datasets was statistically confirmed through Kolmogorov–Smirnov (K‐S) tests with CatBoost achieving the lowest MAE. In the AMP‐non‐imp‐HEMAT system, SVR exhibited the best generalizability ( R 2 = 0.8946). This study presents a hybrid experimental–computational framework that integrates selective MIP nanopolymer design with data‐driven modeling for high‐fidelity prediction of analyte binding behavior. The proposed approach provides a scalable and resource‐efficient alternative to conventional chromatographic purification methods, with direct implications to produce pharmaceutical‐grade MA and AMP.
Dokuzparmak et al. (Fri,) studied this question.