Stability Indicating UHPLC and UPLC Methods for CNS Drugs: A Comprehensive Review of Recent Developments
Central nervous system (CNS) disorders represent a major global health burden necessitating precise and reliable quantification of CNS-active pharmaceutical ingredients (APIs). The analytical complexity associated with these drugs, due to narrow therapeutic indices, low systemic concentrations and complex biological matrices has accelerated the evolution of ultra-high-performance liquid chromatography (UHPLC) and ultra-performance liquid chromatography (UPLC) platforms. This review comprehensively explores the advancements in UHPLC/UPLC based stability indicating methods (SIMs) tailored for CNS drug analysis, focusing on their role in ensuring product integrity, efficacy and regulatory compliance. The shift from conventional HPLC to UHPLC/UPLC has significantly enhanced resolution, sensitivity and runtime efficiency, enabling precise detection of APIs, metabolites and degradation products in challenging matrices like plasma and cerebrospinal fluid. Regulatory frameworks such as ICH Q1A(R2) and Q2(R1) underscore the necessity for forced degradation studies and method validation parameters including specificity, precision, linearity and robustness. Emerging trends such as Green Analytical Chemistry (GAC), quality by design (QbD) and AI-driven optimization are redefining modern analytical workflows. Furthermore, the integration of hyphenated techniques (e.g., UHPLC–MS, LC-QTOF-MS, NMR) has enhanced impurity profiling and degradation product characterization. Automation and digital compliance frameworks are now essential for real time release testing and sustainable analytical operations. Despite these advancements challenges persist in matrix effects, pediatric validations and degradation toxicity assessment. This review concludes by proposing future directions aimed at harmonizing innovation, precision and sustainability in CNS drug analysis.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-02
- DOI
- https://doi.org/10.5281/zenodo.16724304
- Primary Topic
- Analytical Methods in Pharmaceuticals
- Type
- article
- Field-Weighted Citation Impact
- 0.00