Green manufacturing of amoxicillin trihydrate: a malic acid-assisted crystallization framework enhanced by Taguchi-ANN optimization


Ergin M. F., Yasa H., Onar H.

RSC ADVANCES, cilt.16, sa.16, ss.14793-14805, 2026 (SCI-Expanded, Scopus) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 16 Sayı: 16
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1039/d5ra09898j
  • Dergi Adı: RSC ADVANCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Chemical Abstracts Core, Compendex, Directory of Open Access Journals
  • Sayfa Sayıları: ss.14793-14805
  • İstanbul Üniversitesi-Cerrahpaşa Adresli: Hayır

Özet

Industrial production of amoxicillin trihydrate (AMCT) often suffers from low yield, impurity inclusion, and inconsistent crystal morphology. This study introduces a scalable green crystallization strategy using malic acid as a biodegradable habit modifier, developed as part of an improved eco-friendly AMCT manufacturing framework. A hybrid optimization approach integrating Taguchi design with Artificial Neural Network (ANN) modeling was employed to capture both linear and nonlinear interactions among critical process variables. Multi-technique characterization (XRD, FTIR, DSC, BET, LC-MS) confirmed that malic acid preserves lattice integrity while substantially refining particle attributes, reducing crystallite size from 85.9 to 66.4 nm and increasing specific surface area from 5.27 to 11.07 m(2) g(-1). This significant increase in surface area is a key physical factor theoretically favoring improved dissolution kinetics. The ANN model exhibited excellent predictive performance (R-2 > 0.99) for both purity and yield. Under optimized conditions (2.5 M malic acid, pH 5.5, 60 min, 1500 rpm), AMCT crystals were obtained with 99.21% purity and 61.82% yield. These results demonstrate a robust, data-driven framework for sustainable AMCT production, providing a high-performance alternative to conventional mineral-acid-based crystallization methods.