title: Analysis of low active-pharmaceutical-ingredient signal drugs based on thin layer chromatography and surface-enhanced Raman spectroscopy.
abstract: Active pharmaceutical ingredients (API) embedded in the excipients of the formula can usually be unravelled by normal Raman spectroscopy (NRS). However, more and more drugs with low API content and/or low Raman scattering coefficient were insensitive to NRS analysis, which was for the first time defined as Low API-Signal Drugs (LASIDs) in this paper. The NRS spectra of these LASIDs were similar to their dominant excipients' profiles, such as lactose, starch, microcrystalline cellulose (MCC), etc., and were classified into three types as such. 21 out of 100 kinds of drugs were screened as LASIDs and characterized further by Raman microscopic mapping. Accordingly, we proposed a tailored solution to the qualitation and quantitation problem of these LASIDs, using surface-enhanced Raman spectroscopic (SERS) detection on the thin layer chromatographic (TLC) plate both in situ and after-separation. Experimental conditions and parameters including TLC support matrix, SERS substrate, detection mode, similarity threshold, internal standard, etc., were optimized. All LASIDs were satisfactorily identified and the quantitation results agreed well with those of high performance liquid chromatography (HPLC). For some structural analogues of LASIDs, although they presented highly similar SERS spectra and were tough to distinguish even with Raman microscopic mapping, they could be successfully discriminated from each other by coupling SERS (with portable Raman spectrometer) with TLC. These results demonstrated that the proposed solution could be employed to detect the LASIDs with high accuracy and cost-effectiveness.
authors.affiliation: School of Pharmacy, Second Military Medical University, Shanghai 200433, People's Republic of China; College of Pharmacy, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, People's Republic of China.
authors.forename: Xiao
authors.initials: X
authors.lastname: Li
authors.affiliation: College of Pharmacy, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, People's Republic of China; Shanghai DiaCartra Biomedical LLC, Shanghai 200070, People's Republic of China.
authors.forename: Hui
authors.initials: H
authors.lastname: Chen
authors.affiliation: Department of Pharmacy, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai 201999, People's Republic of China.
authors.forename: Qingxia
authors.initials: Q
authors.lastname: Zhu
authors.affiliation: School of Pharmacy, Second Military Medical University, Shanghai 200433, People's Republic of China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: School of Pharmacy, Second Military Medical University, Shanghai 200433, People's Republic of China; College of Pharmacy, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, People's Republic of China. Electronic address: fenglufeng@hotmail.com.
authors.forename: Feng
authors.initials: F
authors.lastname: Lu
mesh_terms: D002855:Chromatography, Thin Layer / Q000379:methods; D004353:Drug Evaluation, Preclinical / Q000379:methods; D005079:Excipients / Q000032:analysis / Q000592:standards; D004364:Pharmaceutical Preparations / Q000032:analysis* / Q000592:standards; D013059:Spectrum Analysis, Raman / Q000379:methods*
chemical_list: D005079:Excipients; D004364:Pharmaceutical Preparations
keywords: Low active-pharmaceutical-ingredient signal drugs; Qualitation; Quantitation; Surface-enhanced Raman spectroscopy; Thin layer chromatography