title: A retention-time-shift-tolerant background subtraction and noise reduction algorithm (BgS-NoRA) for extraction of drug metabolites in liquid chromatography/mass spectrometry data from biological matrices.
abstract: A retention-time-shift-tolerant background subtraction and noise reduction algorithm (BgS-NoRA) is implemented using the statistical programming language R to remove non-drug-related ion signals from accurate mass liquid chromatography/mass spectrometry (LC/MS) data. The background-subtraction part of the algorithm is similar to a previously published procedure (Zhang H and Yang Y. J. Mass Spectrom. 2008, 43: 1181-1190). The noise reduction algorithm (NoRA) is an add-on feature to help further clean up the residual matrix ion noises after background subtraction. It functions by removing ion signals that are not consistent across many adjacent scans. The effectiveness of BgS-NoRA was examined in biological matrices by spiking blank plasma extract, bile and urine with diclofenac and ibuprofen that have been pre-metabolized by microsomal incubation. Efficient removal of background ions permitted the detection of drug-related ions in in vivo samples (plasma, bile, urine and feces) obtained from rats orally dosed with (14)C-loratadine with minimal interference. Results from these experiments demonstrate that BgS-NoRA is more effective in removing analyte-unrelated ions than background subtraction alone. NoRA is shown to be particularly effective in the early retention region for urine samples and middle retention region for bile samples, where the matrix ion signals still dominate the total ion chromatograms (TICs) after background subtraction. In most cases, the TICs after BgS-NoRA are in excellent qualitative correlation to the radiochromatograms. BgS-NoRA will be a very useful tool in metabolite detection and identification work, especially in first-in-human (FIH) studies and multiple dose toxicology studies where non-radio-labeled drugs are administered. Data from these types of studies are critical to meet the latest FDA guidance on Metabolite in Safety Testing (MIST).
authors.affiliation: Drug Disposition, Pharmaceutical Sciences, Schering Plough Research Institute, 2015 Galloping Hill Road, Kenilworth, NJ 07033-1300, USA. peijuan.penny.zhu@spcorp.com
authors.forename: Peijuan
authors.initials: P
authors.lastname: Zhu
authors.forename: Wei
authors.initials: W
authors.lastname: Ding
authors.forename: Wei
authors.initials: W
authors.lastname: Tong
authors.forename: Anima
authors.initials: A
authors.lastname: Ghosal
authors.forename: Kevin
authors.initials: K
authors.lastname: Alton
authors.forename: Swapan
authors.initials: S
authors.lastname: Chowdhury
mesh_terms: D000465:Algorithms; D000818:Animals; D002853:Chromatography, Liquid / Q000379:methods / Q000592:standards*; D004008:Diclofenac / Q000737:chemistry / Q000378:metabolism; D006801:Humans; D007052:Ibuprofen / Q000737:chemistry / Q000378:metabolism; D017336:Loratadine / Q000737:chemistry / Q000378:metabolism; D008297:Male; D013058:Mass Spectrometry / Q000379:methods / Q000592:standards*; D004364:Pharmaceutical Preparations / Q000737:chemistry* / Q000378:metabolism*; D051381:Rats; D017207:Rats, Sprague-Dawley
chemical_list: D004364:Pharmaceutical Preparations; D004008:Diclofenac; D017336:Loratadine; D007052:Ibuprofen