Commentary For reprint orders, please contact [email protected]
Cosmetic bioanalysis using LC–MS: challenges and future outlook “This review will focus on the challenge and future perspective of cosmetic bioanalysis by LC–MS techniques including targeted analysis, non-targeted analysis, matrix effects, carryover, and method validation.” Keywords: carryover n cosmetics n LC–MS n matrix effects n weighting factor
Cosmetic products are used on their skin, hair, nails and teeth on a daily basis by many consumers. The world cosmetics market reached US$325 billion in 2011 and is growing at approximately 3% per year [1]. Therefore, safety of cosmetic products is a serious international concern. The main ingredients of cosmetics include acids, preservatives, oils, surfactants, moisturizing agents, emulsifiers, hair dyes, pigments and fragrances. The analysis of cosmetic ingredients in biological matrix is often challenging because of their complex matrices. With the advance of new MS technologies, LC–MS has become a widely applied technique for bioanalysis of cosmetics because it is more sensitive and selective than other techniques [2]. This review will focus on the challenge and future perspective of cosmetic bioanalysis by LC–MS techniques including targeted analysis, nontargeted analysis, matrix effects, carryover, and method validation. Targeted analysis As in other fields, the application of LC–MS for cosmetic bioanalysis can be divided into targeted and nontargeted analyses. A targeted analysis is a conventional analysis which includes identification and quantification of known analytes of interest. Targeted analysis is accomplished by developing a method with authentic standards prior to analyzing real samples and cannot readily identify compounds not defined in the developed method [3]. SRM (often called MRM), is preferred for targeted analysis due to its selectivity, sensitivity and reproducibility. Although SRM mode is highly selective, it is good practice to define a second transition for confirmation of identification of each analyte. The EU and the US FDA recommend a minimum of four identification points for positive identification of each analyte in an analytical method [101,102]. This recommendation was followed in a study using LC–MS/MS to determine low 10.4155/BIO.13.246
parts per billion (ppb) levels of peptides found in anti-wrinkle cosmetics for an in vitro skin penetration study [2]. Quadrupole linear ion-trap MS (QLT–MS) and high-resolution MS (HRMS), such as time of flight (TOF) and Orbitrap MS, can also be used for targeted analyses. HRMS can analyze a virtually unlimited number of analytes because it can be performed in full-scan mode and can reconstruct any desired ion chromatograms using the same full-scan data file. Accurate mass of characteristic fragement ions can be used for the confirmation of identity of analytes. ESI is commonly used for relatively polar compounds. Since less polar or neutral analytes may have lower ionization efficiencies and lower sensitivities when using ESI, APCI or atmospheric pressure photo‑ionization (APPI) may be alternatives to ESI. In addition, some new ionization techniques, including extractive ESIMS (EESI-MS), have been used for the direct analysis of cosmetic products [1]. The combination of neutral desorption (ND) sampling with EESI-MS techniques is highly sensitive, highly selective and suitable for rapid analysis because it requires minimal sample preparation. In an ND process, a sample is isolated from a direct bombardment by charged particles or energetically metastable atoms. ND can be used on biological surfaces such as human skin, animal tissues, hair and plant leaves without changing the condition of these biological samples, and can transfer the analytes over relatively long distances (e.g., 5–20 m) to reach an EESI source.
Wanlong Zhou US FDA, Center for Food Safety & Applied Nutrition, Office of Regulatory Science, 5100 Paint Branch Parkway, College Park, MD 20740, USA
Perry G Wang Author for correspondence: US FDA, Center for Food Safety & Applied Nutrition, Office of Regulatory Science, 5100 Paint Branch Parkway, College Park, MD 20740, USA Author for correspondence: Tel.: +240 4021609 Fax: +301 436 2694 E-mail: [email protected]
Nontargeted analysis Nontargeted analysis can identify any compounds, expected or unexpected, present in a sample including ingredients related to metabolites, contamination products, impurities, or transformation products generated when cosmetics undergo biological, chemical and Bioanalysis (2014) 6(4), 437–440
ISSN 1757-6180
437
Commentary |
Zhou & Wang photochemical degradation during production, storage, or in vivo or in vitro processes. Such analyses are more complicated and challenging than targeted analyses. Due to the complexity of identifying unknown compounds, HRMS techniques such as TOF and Orbitrap MS, especially Q-TOF/Q-Orbitrap and ion-trap MS, are often employed for this purpose. Nontargeted analysis focuses on evaluating molecular formulae by obtaining accurate mass readings using LC–HRMS and identifying these formulae by performing MS/MS fragmentation and searching databases or libraries [4]. After extracting the peaks of all possible compounds using automated deconvolution and merging different ions (e.g., [M+H]+, [M+Na]+ and [M+NH4]+) into one feature, the resulting dataset is analyzed using statistical methods to evaluate the most relevant features by comparing different samples with blanks. The most probable molecular formulae are produced by calculating the elemental composition based on the relevant features and matching the isotope pattern. The molecular formulae are searched in MS/MS databases or libraries to identify the proposed formulae. In most cases, there is no match in the database or library, so large chemical databases, such as PubChem [103] and ChemSpider [104], are checked. These large databases may produce several hundred to several thousand hits for a possible structure. In such cases, special software is used to produce computational fragment spectra. The computational fragment spectra are compared with the measured MS fragments, but unequivocal identification requires either standards or complementary information from other techniques such as NMR analysis.
“Due to the complexity of identifying unknown compounds, HRMS techniques such as TOF and Orbitrap MS, especially Q-TOF/Q-Orbitrap and ion trap MS, are often employed for this purpose.” Since ion-trap MS can provide large amounts of structural information by performing multiple MS/MS (or MSn) fragmentation steps on a single precursor ion and its product ions to create a cascade of product-precursor ion relationships, it is widely used to identify unknown compounds. Chemical techniques, including hydrogen–deuterium exchange and the derivatization of functional groups, can be used to help MS predict 438
Bioanalysis (2014) 6(4)
unknown metabolite structures when NMR techniques are not available. Matrix effects The greatest drawback of LC–MS techniques is the occurrence of matrix effects for both targeted and nontargeted analyses, especially with ESI. Matrix effects are the alteration of ionization efficiencies of analytes in the presence of co-eluting compounds in the same matrix. These can result in either a reduction in the target signal (ion suppression) or a gain in the signal (ion enhancement). Matrix effects influence detection capability, precision and/or accuracy of measurement for the analytes of interests. Evaluation and minimization of matrix effects are generally necessary during method development and validation. There are two common ways to evaluate matrix effects. The first way is use of post-column infusion, in which an infusion pump delivers a constant amount of analyte into the LC stream entering the ion source of the mass spectrometer. The second way is use of post-extraction spikes, in which matrix effects are quantitatively accessed by comparing the response of an analyte in neat solution to the response of the analyte spiked into a blank matrix extract produced by carrying the sample through the preparation process. Various techniques are used to minimize matrix effects. The most common technique is the use of stable isotopically labeled analogues. The analogues and analytes have almost identical structures, which result in similar chemical and chromatographic properties. However, labeled analogues may be costly and are not always commercially available. Use of dilution and/or reduced injection volumes are a simple way to minimize matrix effects if the analytes can tolerate the dilution. Different sample preparation techniques have also been widely used to minimize matrix effects, including SPE, LLE and solid-phase microextraction (SPME). Other approaches to correct for matrix effects include use of the method of standard additions, use of the same sample matrix to prepare standard and QC solutions, use of structurally similar unlabeled compounds that elute close to the analytes of interest as IS, and modification in chromatographic conditions. Several approaches are often combined to obtain better results [2]. Carryover Carryover is the appearance (i.e., chromatographic peak) of an analyte in a determination future science group
Cosmetic bioanalysis using LC–MS: challenges & future outlook when a blank containing no analyte is injected [5]. Although carryover cannot be completely eliminated, it should be minimized to an acceptable level, such as to less than 20% of the LLOQ. Otherwise, carryover may result in false positive results. One common source of carryover in LC–MS analyses is the autosampler. Carryover from an autosampler comes from residual analytes contained in samples which remain in the system, such as in an injection port from a previous injection. This type of carryover can often be minimized by injecting a blank solution after injection of a sample high in analyte.
“…it is not justifiable only to report r2 or r without considering accuracy or error…” Carryover may also originate when an injection valve rotor or needle in the system adsorbs analytes. Simply injecting one blank solution will not automatically minimize this type of carryover. In studies that determined the levels of hexapeptides in cosmetic products and explored whether the peptides could penetrate the skin of hairless guinea pigs in vitro, the researchers used a washing procedure with a shorter gradient program and optimized needle washing solutions to minimize serious carryover [2,6]. An injector needle surface also has an important influence on carryover. A platinum-coated needle reduced carryover 40-fold compared to commonly used stainless steel alloy needles [5]. Method validation A review of reported analytical methods for estrogens over the past decade mentioned that the majority of the authors of reviewed publications did not completely validate their methods [7]. For example, LLOQ values were not evaluated and established using the same sample matrix as the analyzed samples. Some methods lacked intra- or inter-day validation data and/or recoveries. The recovery test was not performed or evaluated at lower levels close to the LLOQ because recoveries for higher levels usually produced much better results than those obtained at lower levels close to the LLOQ [105]. The selection of appropriate weighting factors for calibration curves has become a general practice for bioanalysis [105]. As discussed in detail elsewhere [6], it is not justifiable only to report r2 or r without considering accuracy or error future science group
| Commentary
because a reported concentration at the lower end may be erroneous and misleading, especially for a wider calibration range. A calibration curve can be generated and expressed by the following equation: y = ax + b where y and x are the response (signal intensity) and concentration, respectively, of an analyte, a is the slope and b is the intercept. Since an LC–MS/MS calibration curve usually covers several orders of magnitude, higher r 2 or r values do not guarantee higher accuracy for the calibration curve and the value of r 2 or r cannot be used as a unique indicator of linearity. This is because the values of slope, intercept and r 2 (or r) are mainly determined by the higher concentration points [8]. In order to improve the accuracy of a calibration curve, especially for the lower concentration points, a suitable weighting factor, such as 1/x or 1/x 2, must be applied, where x represents the concentration of an analyte. Future perspective for cosmetic analysis and bioanalysis In addition to LC–MS/MS techniques using SRM, LC coupled to HRMS – such as TOF and Orbitrap MS, especially Q-TOF and Q-Orbitrap MS – will play a more important role in the future for targeted and nontargeted analysis of cosmetics. For analyzing possible metabolites and other unknown compounds, LC-Q-TOF or LC-Q-Orbitrap can provide accurate mass measurements for a molecular ion and its fragment ions, which can help to elucidate the structure of an unknown compound by searching databases or libraries. Since UHPLC systems using sub-2 µm particle columns can offer much shorter analytical time with higher resolution, higher sensitivity, less solvent consumption and less matrix effect, they will become standard LC systems in the near future. The use of HILIC-SPE for sample preparation and analytical HILIC columns for separation will continue to be developed as alternatives to reversed phase SPE and LC–MS for polar analytes that have poor retention on reversed phase SPEs and columns. Acknowledgements The authors wish to thank JI Rader, AJ Krynitsky, WG Wamer, SR Milstein, PA Hansen and LM Katz (US FDA, Center for Food Safety and Applied Nutrition) for helpful discussions. www.future-science.com
439
Commentary |
Zhou & Wang Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This
includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.
References 1
2
3
4
Zhang XL, Wang NN, Zhou, YF et al. Extractive electrospray ionization mass spectrometry for direct characterization of cosmetic products. Anal. Methods 5(2), 311–315 (2013). Zhou W, Wang PG, Ogunsola OA et al. Rapid determination of hexapeptides by hydrophilic interaction LC–MS/MS for in vitro skin-penetration studies. Bioanalysis 5(11), 1353–1362 (2013). Malik AK, Blasco C, Picó Y. Liquid chromatography–mass spectrometry in food safety. J. Chromatogr. A 1217(25), 4018–4040 (2010). Zedda M, Zwiener C. Is nontarget screening of emerging contaminants by LC–HRMS successful? A plea for compound libraries and computer tools. Anal. Bioanal. Chem. 403(9), 2493–2502 (2012).
5
Dolan JW. Autosampler carryover. LC GC N. Am. 24(8), 754–760 (2006).
6
Zhou W, Wang PW, Krynitsky AJ, Rader JI. Rapid and simultaneous determination of
440
hexapeptides (Ac-EEMQRR-amide and H2N-EEMQRR-amide) in anti-wrinkle cosmetics by hydrophilic interaction liquid chromatography–solid phase extraction preparation and hydrophilic interaction liquid chromatography with tandem mass spectrometry. J. Chromatogr. A 1218(44), 7956–7963 (2011). 7
8
Gäbet V, Miège C, Bados P et al. Analysis of estrogens in environmental matrices. TRAC-Trend. Anal. Chem. 26(11), 1113–1131 (2007). Kiser MM, Dolan JW. Selecting the best curve fit. LC GC N. Am. 22(2), 112–117 (2004).
Websites 101 EU COMMISSION. Implementing Council
Directive 96/23/EC concerning the performance of analytical methods and the interpretation of results. http://eur-lex.europa.eu/LexUriServ/ LexUriServ.do?uri=OJ:L:2002:221:0008:00 36:EN:PDF
Bioanalysis (2014) 6(4)
102 US FDA Office of Regulatory Affairs. ORA-
WIDE PROCEDURE. Guidance for the analysis and documentation to support regulatory action on pesticide residues. http://inside.fda.gov:9003/downloads/ORA/ OfficeofRegionalOperations/ DivisionofFieldScience/UCM189632.pdf 103 National Center for Biotechnology
Information. www.ncbi.nlm.nih.gov 104 ChemSpider.
www.chemspider.com 105 US FDA Center for Drug Evaluation and
Research (CDER), Center for Veterinary Medicine (CVM), Guidance for Industry Bioanalytical Method Validation. www.fda.gov/downloads/drugs/ guidancecomplianceregulatoryinformation/ guidances/ucm368107.pdf
future science group
Cosmetic bioanalysis using LC–MS: challenges and future outlook “This review will focus on the challenge and future perspective of cosmetic bioanalysis by LC–MS techniques including targeted analysis, non-targeted analysis, matrix effects, carryover, and method validation.” Keywords: carryover n cosmetics n LC–MS n matrix effects n weighting factor
Cosmetic products are used on their skin, hair, nails and teeth on a daily basis by many consumers. The world cosmetics market reached US$325 billion in 2011 and is growing at approximately 3% per year [1]. Therefore, safety of cosmetic products is a serious international concern. The main ingredients of cosmetics include acids, preservatives, oils, surfactants, moisturizing agents, emulsifiers, hair dyes, pigments and fragrances. The analysis of cosmetic ingredients in biological matrix is often challenging because of their complex matrices. With the advance of new MS technologies, LC–MS has become a widely applied technique for bioanalysis of cosmetics because it is more sensitive and selective than other techniques [2]. This review will focus on the challenge and future perspective of cosmetic bioanalysis by LC–MS techniques including targeted analysis, nontargeted analysis, matrix effects, carryover, and method validation. Targeted analysis As in other fields, the application of LC–MS for cosmetic bioanalysis can be divided into targeted and nontargeted analyses. A targeted analysis is a conventional analysis which includes identification and quantification of known analytes of interest. Targeted analysis is accomplished by developing a method with authentic standards prior to analyzing real samples and cannot readily identify compounds not defined in the developed method [3]. SRM (often called MRM), is preferred for targeted analysis due to its selectivity, sensitivity and reproducibility. Although SRM mode is highly selective, it is good practice to define a second transition for confirmation of identification of each analyte. The EU and the US FDA recommend a minimum of four identification points for positive identification of each analyte in an analytical method [101,102]. This recommendation was followed in a study using LC–MS/MS to determine low 10.4155/BIO.13.246
parts per billion (ppb) levels of peptides found in anti-wrinkle cosmetics for an in vitro skin penetration study [2]. Quadrupole linear ion-trap MS (QLT–MS) and high-resolution MS (HRMS), such as time of flight (TOF) and Orbitrap MS, can also be used for targeted analyses. HRMS can analyze a virtually unlimited number of analytes because it can be performed in full-scan mode and can reconstruct any desired ion chromatograms using the same full-scan data file. Accurate mass of characteristic fragement ions can be used for the confirmation of identity of analytes. ESI is commonly used for relatively polar compounds. Since less polar or neutral analytes may have lower ionization efficiencies and lower sensitivities when using ESI, APCI or atmospheric pressure photo‑ionization (APPI) may be alternatives to ESI. In addition, some new ionization techniques, including extractive ESIMS (EESI-MS), have been used for the direct analysis of cosmetic products [1]. The combination of neutral desorption (ND) sampling with EESI-MS techniques is highly sensitive, highly selective and suitable for rapid analysis because it requires minimal sample preparation. In an ND process, a sample is isolated from a direct bombardment by charged particles or energetically metastable atoms. ND can be used on biological surfaces such as human skin, animal tissues, hair and plant leaves without changing the condition of these biological samples, and can transfer the analytes over relatively long distances (e.g., 5–20 m) to reach an EESI source.
Wanlong Zhou US FDA, Center for Food Safety & Applied Nutrition, Office of Regulatory Science, 5100 Paint Branch Parkway, College Park, MD 20740, USA
Perry G Wang Author for correspondence: US FDA, Center for Food Safety & Applied Nutrition, Office of Regulatory Science, 5100 Paint Branch Parkway, College Park, MD 20740, USA Author for correspondence: Tel.: +240 4021609 Fax: +301 436 2694 E-mail: [email protected]
Nontargeted analysis Nontargeted analysis can identify any compounds, expected or unexpected, present in a sample including ingredients related to metabolites, contamination products, impurities, or transformation products generated when cosmetics undergo biological, chemical and Bioanalysis (2014) 6(4), 437–440
ISSN 1757-6180
437
Commentary |
Zhou & Wang photochemical degradation during production, storage, or in vivo or in vitro processes. Such analyses are more complicated and challenging than targeted analyses. Due to the complexity of identifying unknown compounds, HRMS techniques such as TOF and Orbitrap MS, especially Q-TOF/Q-Orbitrap and ion-trap MS, are often employed for this purpose. Nontargeted analysis focuses on evaluating molecular formulae by obtaining accurate mass readings using LC–HRMS and identifying these formulae by performing MS/MS fragmentation and searching databases or libraries [4]. After extracting the peaks of all possible compounds using automated deconvolution and merging different ions (e.g., [M+H]+, [M+Na]+ and [M+NH4]+) into one feature, the resulting dataset is analyzed using statistical methods to evaluate the most relevant features by comparing different samples with blanks. The most probable molecular formulae are produced by calculating the elemental composition based on the relevant features and matching the isotope pattern. The molecular formulae are searched in MS/MS databases or libraries to identify the proposed formulae. In most cases, there is no match in the database or library, so large chemical databases, such as PubChem [103] and ChemSpider [104], are checked. These large databases may produce several hundred to several thousand hits for a possible structure. In such cases, special software is used to produce computational fragment spectra. The computational fragment spectra are compared with the measured MS fragments, but unequivocal identification requires either standards or complementary information from other techniques such as NMR analysis.
“Due to the complexity of identifying unknown compounds, HRMS techniques such as TOF and Orbitrap MS, especially Q-TOF/Q-Orbitrap and ion trap MS, are often employed for this purpose.” Since ion-trap MS can provide large amounts of structural information by performing multiple MS/MS (or MSn) fragmentation steps on a single precursor ion and its product ions to create a cascade of product-precursor ion relationships, it is widely used to identify unknown compounds. Chemical techniques, including hydrogen–deuterium exchange and the derivatization of functional groups, can be used to help MS predict 438
Bioanalysis (2014) 6(4)
unknown metabolite structures when NMR techniques are not available. Matrix effects The greatest drawback of LC–MS techniques is the occurrence of matrix effects for both targeted and nontargeted analyses, especially with ESI. Matrix effects are the alteration of ionization efficiencies of analytes in the presence of co-eluting compounds in the same matrix. These can result in either a reduction in the target signal (ion suppression) or a gain in the signal (ion enhancement). Matrix effects influence detection capability, precision and/or accuracy of measurement for the analytes of interests. Evaluation and minimization of matrix effects are generally necessary during method development and validation. There are two common ways to evaluate matrix effects. The first way is use of post-column infusion, in which an infusion pump delivers a constant amount of analyte into the LC stream entering the ion source of the mass spectrometer. The second way is use of post-extraction spikes, in which matrix effects are quantitatively accessed by comparing the response of an analyte in neat solution to the response of the analyte spiked into a blank matrix extract produced by carrying the sample through the preparation process. Various techniques are used to minimize matrix effects. The most common technique is the use of stable isotopically labeled analogues. The analogues and analytes have almost identical structures, which result in similar chemical and chromatographic properties. However, labeled analogues may be costly and are not always commercially available. Use of dilution and/or reduced injection volumes are a simple way to minimize matrix effects if the analytes can tolerate the dilution. Different sample preparation techniques have also been widely used to minimize matrix effects, including SPE, LLE and solid-phase microextraction (SPME). Other approaches to correct for matrix effects include use of the method of standard additions, use of the same sample matrix to prepare standard and QC solutions, use of structurally similar unlabeled compounds that elute close to the analytes of interest as IS, and modification in chromatographic conditions. Several approaches are often combined to obtain better results [2]. Carryover Carryover is the appearance (i.e., chromatographic peak) of an analyte in a determination future science group
Cosmetic bioanalysis using LC–MS: challenges & future outlook when a blank containing no analyte is injected [5]. Although carryover cannot be completely eliminated, it should be minimized to an acceptable level, such as to less than 20% of the LLOQ. Otherwise, carryover may result in false positive results. One common source of carryover in LC–MS analyses is the autosampler. Carryover from an autosampler comes from residual analytes contained in samples which remain in the system, such as in an injection port from a previous injection. This type of carryover can often be minimized by injecting a blank solution after injection of a sample high in analyte.
“…it is not justifiable only to report r2 or r without considering accuracy or error…” Carryover may also originate when an injection valve rotor or needle in the system adsorbs analytes. Simply injecting one blank solution will not automatically minimize this type of carryover. In studies that determined the levels of hexapeptides in cosmetic products and explored whether the peptides could penetrate the skin of hairless guinea pigs in vitro, the researchers used a washing procedure with a shorter gradient program and optimized needle washing solutions to minimize serious carryover [2,6]. An injector needle surface also has an important influence on carryover. A platinum-coated needle reduced carryover 40-fold compared to commonly used stainless steel alloy needles [5]. Method validation A review of reported analytical methods for estrogens over the past decade mentioned that the majority of the authors of reviewed publications did not completely validate their methods [7]. For example, LLOQ values were not evaluated and established using the same sample matrix as the analyzed samples. Some methods lacked intra- or inter-day validation data and/or recoveries. The recovery test was not performed or evaluated at lower levels close to the LLOQ because recoveries for higher levels usually produced much better results than those obtained at lower levels close to the LLOQ [105]. The selection of appropriate weighting factors for calibration curves has become a general practice for bioanalysis [105]. As discussed in detail elsewhere [6], it is not justifiable only to report r2 or r without considering accuracy or error future science group
| Commentary
because a reported concentration at the lower end may be erroneous and misleading, especially for a wider calibration range. A calibration curve can be generated and expressed by the following equation: y = ax + b where y and x are the response (signal intensity) and concentration, respectively, of an analyte, a is the slope and b is the intercept. Since an LC–MS/MS calibration curve usually covers several orders of magnitude, higher r 2 or r values do not guarantee higher accuracy for the calibration curve and the value of r 2 or r cannot be used as a unique indicator of linearity. This is because the values of slope, intercept and r 2 (or r) are mainly determined by the higher concentration points [8]. In order to improve the accuracy of a calibration curve, especially for the lower concentration points, a suitable weighting factor, such as 1/x or 1/x 2, must be applied, where x represents the concentration of an analyte. Future perspective for cosmetic analysis and bioanalysis In addition to LC–MS/MS techniques using SRM, LC coupled to HRMS – such as TOF and Orbitrap MS, especially Q-TOF and Q-Orbitrap MS – will play a more important role in the future for targeted and nontargeted analysis of cosmetics. For analyzing possible metabolites and other unknown compounds, LC-Q-TOF or LC-Q-Orbitrap can provide accurate mass measurements for a molecular ion and its fragment ions, which can help to elucidate the structure of an unknown compound by searching databases or libraries. Since UHPLC systems using sub-2 µm particle columns can offer much shorter analytical time with higher resolution, higher sensitivity, less solvent consumption and less matrix effect, they will become standard LC systems in the near future. The use of HILIC-SPE for sample preparation and analytical HILIC columns for separation will continue to be developed as alternatives to reversed phase SPE and LC–MS for polar analytes that have poor retention on reversed phase SPEs and columns. Acknowledgements The authors wish to thank JI Rader, AJ Krynitsky, WG Wamer, SR Milstein, PA Hansen and LM Katz (US FDA, Center for Food Safety and Applied Nutrition) for helpful discussions. www.future-science.com
439
Commentary |
Zhou & Wang Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This
includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.
References 1
2
3
4
Zhang XL, Wang NN, Zhou, YF et al. Extractive electrospray ionization mass spectrometry for direct characterization of cosmetic products. Anal. Methods 5(2), 311–315 (2013). Zhou W, Wang PG, Ogunsola OA et al. Rapid determination of hexapeptides by hydrophilic interaction LC–MS/MS for in vitro skin-penetration studies. Bioanalysis 5(11), 1353–1362 (2013). Malik AK, Blasco C, Picó Y. Liquid chromatography–mass spectrometry in food safety. J. Chromatogr. A 1217(25), 4018–4040 (2010). Zedda M, Zwiener C. Is nontarget screening of emerging contaminants by LC–HRMS successful? A plea for compound libraries and computer tools. Anal. Bioanal. Chem. 403(9), 2493–2502 (2012).
5
Dolan JW. Autosampler carryover. LC GC N. Am. 24(8), 754–760 (2006).
6
Zhou W, Wang PW, Krynitsky AJ, Rader JI. Rapid and simultaneous determination of
440
hexapeptides (Ac-EEMQRR-amide and H2N-EEMQRR-amide) in anti-wrinkle cosmetics by hydrophilic interaction liquid chromatography–solid phase extraction preparation and hydrophilic interaction liquid chromatography with tandem mass spectrometry. J. Chromatogr. A 1218(44), 7956–7963 (2011). 7
8
Gäbet V, Miège C, Bados P et al. Analysis of estrogens in environmental matrices. TRAC-Trend. Anal. Chem. 26(11), 1113–1131 (2007). Kiser MM, Dolan JW. Selecting the best curve fit. LC GC N. Am. 22(2), 112–117 (2004).
Websites 101 EU COMMISSION. Implementing Council
Directive 96/23/EC concerning the performance of analytical methods and the interpretation of results. http://eur-lex.europa.eu/LexUriServ/ LexUriServ.do?uri=OJ:L:2002:221:0008:00 36:EN:PDF
Bioanalysis (2014) 6(4)
102 US FDA Office of Regulatory Affairs. ORA-
WIDE PROCEDURE. Guidance for the analysis and documentation to support regulatory action on pesticide residues. http://inside.fda.gov:9003/downloads/ORA/ OfficeofRegionalOperations/ DivisionofFieldScience/UCM189632.pdf 103 National Center for Biotechnology
Information. www.ncbi.nlm.nih.gov 104 ChemSpider.
www.chemspider.com 105 US FDA Center for Drug Evaluation and
Research (CDER), Center for Veterinary Medicine (CVM), Guidance for Industry Bioanalytical Method Validation. www.fda.gov/downloads/drugs/ guidancecomplianceregulatoryinformation/ guidances/ucm368107.pdf
future science group
