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An informative and interactive live and on-demand webinar series to address laboratory challenges
Charged Aerosol Detection Symposium Series | On-demand now
Webinar
Jun 08, 2022
- Jun 22, 2022
Are you looking for a sensitive, universal detection method with near-uniform response independent of the chemical structure? Do any of your analytes lack chromophores? Do you need to run non-volatile and semi-volatile analysis down to sub-nanogram?
Charged aerosol detection (CAD) measures analytes that cannot be seen by UV and may not be readily detected with other detection techniques. Dive into the technical capabilities of this unique HPLC detector, discover the extent of its use, and see how easily CAD works with any HPLC system, regardless of provider.
Agenda
Basics and beyond
Chris Tuczemskyi | Applications & Technical Support Specialist, Thermo Fisher Scientific
Chris Tuczemskyi is a chromatography specialist at Thermo Fisher Scientific, based in Cambridge, UK. After spending a number of years building up his experience with chromatography instruments in a water testing laboratory, he joined Thermo Fisher Scientific in 2014 as a chromatography service engineer for Unity Lab Services. Here he developed his passion for supporting customers using HPLC and in 2018 moved into the application specialist team. As a chromatography specialist, his role includes working with customers in developing applications to help to enable them to make the world healthier, cleaner and safer. In 2009, Chris graduated from the University of Essex in Biochemistry (Bsc Hons).
Polysorbate analysis in drug products
Georg Schuster | Senior scientist, Coriolis Pharma
Georg Schuster is senior scientist and group leader at Coriolis Pharma, a science-driven contract research organization, where he focusses on protein characterization and analytic method development for biopharmaceuticals with LC and CE based separation techniques and polysorbate characterization via LC coupled to charged aerosol detection. Georg has received his PhD degree in analytical chemistry from the University of Vienna, Austria, in the field of HILIC stationary phase development and further worked as post-doctoral scientist at the Australian Centre for Research on Separation Science, Tasmania. Prior to working at Coriolis Pharma (2016), he was a scientist engaged in protein separation method development at Novo Nordisk, Denmark.
In biopharmaceuticals, surfactants are often used to stabilize proteins against interfacial stress and/or to prevent adsorption. Among the approved non-ionic surfactants for parenteral applications polysorbate 20 and 80 (also known as Tween) are the most common ones. However, polysorbates can oxidize and/or hydrolyze on long-term stability and generate subvisible and visible particles which impact drug product stability. In this talk, we will discuss the investigation of polysorbate degradation pathways by application of a fast RP-UPLC-CAD characterization method.
- Polysorbates are complex heterogeneous mixtures, contain impurities and are prone to degradation
- Quality and consistency of neat polysorbate batches must be considered/are crucial for formulation studies and DP manufacturing
- LC-CAD is a key working horse for PS quantification and subclass analysis
CAD in pharmaceutical analysis
Ruben Pawellek | PhD Student, University of Wuerzburg, Germany
Ruben Pawellek received his pharmacy degree at the university of Wuerzburg in 2016, followed by one year of practical training in the quality control unit of Boehringer Ingelheim and in a public pharmacy. Since 2017, he pursues his PhD studies in pharmaceutical chemistry at the university of Wuerzburg. His research is mainly focused on the application of HPLC-CAD in pharmaceutical analysis and on the optimization of the detector’s performance. In 2020, he completed a three-year professional training in pharmaceutical analysis.
During the last decade, CAD has become an established detection technique in the field of pharmaceutical analysis. Recently, the European Pharmacopoeia introduced the detector for the analysis of weakly chromophoric drugs. This presentation provides an overview of recent CAD applications for compendial quality control purposes focusing on the impurity profiling of drug substances. In this regard, the in-line coupling of UV-CAD offers numerous advantages when impurities with opposing physico-chemical properties are analysed simultaneously, e.g. volatile impurities and impurities with weak chromophores.1
The application of the CAD in a regulated environment requires careful selection of the detector settings to comply with the demands for robust and sensitive methods.2 Here, we present optimization strategies for the PFV setting of the CAD that can help to linearize the detector signal in a manner conforming to GMP regulations.3 Moreover, we include a brief discussion about pros and cons of IPC and HILIC for impurity profiling focusing on the impact of the respective separation technique on CAD sensitivity.
1 R. Pawellek, K. Schilling, U. Holzgrabe, Impurity profiling of l-aspartic acid and glycine using high-performance liquid chromatography coupled with charged aerosol and ultraviolet detection, J. Pharm. Biomed. Anal. 183 (2020) 113149.
2 K. Schilling, R. Pawellek, K. Lovejoy, T. Muellner, U. Holzgrabe, Influence of charged aerosol detector instrument settings on the ultra-high-performance liquid chromatography analysis of fatty acids in polysorbate 80, J. Chromatogr. A 1576 (2018) 58-66.
3 R. Pawellek, T. Muellner, P. Gamache, U. Holzgrabe, Power function setting in charged aerosol detection for the linearization of detector response – optimization strategies and their application, J. Chromatogr. A 1637 (2021) 461844.
- CAD is essential for the impurity profiling of weakly chromophoric drugs
- Optimization of CAD settings is crucial for the development of robust and reproducible methods for a compendial application
- UV-CAD can be easily applied to broaden the detection scope
High Throughput Analysis (HTA) for small molecule libraries with the Thermo Scientific Vanquish Duo UHPLC
Thomas Dann | Analytical Scientist, Charles River Labs
Matthew Gill | Charles River Labs
Thomas Dann, graduating from the University of East Anglia with an MChem degree, he went on to complete a PhD there focusing on electroanalytical chemistry, where he synthesised organometallic compounds, characterising them by NMR, mass spectrometry and electrochemical techniques. From this he moved into industry working in a Compound Management lab where the role included QC by LCMS for newly solubilised compounds. Building on this experience, Thomas then progressed onto a full analytical science role at Charles River.
Matthew graduated in BSc (Hons) Chemistry through the ICI Agrochemicals day release training scheme in 1995 and remained at Jealott’s Hill Research Station with Syngenta for 13 years as a synthetic chemist working on Fungicide and Herbicide projects. Matthew joined the Automated Synthesis group led by Dr Gary Walters, for his last two years, exploring his interest in technology and its application in synthetic chemistry. He joined Argents Discovery, drug discovery CRO, in 2002 as a principal scientist. Following the acquisition of Argenta Discovery by Charles River Laboratories in 2014, Matthew increased his focus on technology through becoming Group Leader for Analytical Sciences at both the Harlow and Chesterford Research Park CRL Early Discovery sites, driving a range of projects such as challenging the acceleration of drug discovery through process efficiencies, leading a cross departmental New Technologies Group and supporting the next generation of technicians through CRL’s Scientific Apprenticeship program.
At Charles River Early Discovery, we acquired a Thermo Scientific Vanquish Duo UHPLC system in 2020 to strengthen our HTA capability supporting CRL’s HTS Biology business. The system has been set up to report compound purity/identification through UV detection and the ISQEC mass, as a reflection of our other UPLC -MS systems, with the aim of linking into third party Virscidian software for automated data processing.
Our talk will describe progress on linking to external thirdparty software and other developments, such as: the use of ACE columns technology to reduce workload and comments on plans to exploring the potential for the CAD to enhance analysis of fragment and small polar molecules that typically demonstrate weak chromophores.
- Limitations of Tandem Method
- Complexity of integration with third party software
- Support for development of bespoke processing
- Application of mass hunting for variable entities
- Potential for a Chromeleon User Group
Peptide quantification by CAD
Kilian Conde Frieboes | Principal Scientist, Novo Nordisk
Killian studied Chemistry in Kiel/Germany.Doctor of Science in 1992 (Asymmetric Synthesis)Post docs at the University of Frankfurt and University of California, San Diego (1992-1995).Assistant at the ETH Zurich (1995-1997).Joined Novo Nordisk in 1997.
A UPLC-CAD setup with an inverse gradient has been used to quantify solutions of modified peptides and proteins.
- A CAD can accurately quantify new peptides
- The build-in exponential function should be used instead of a non-linear curve fit
- The usual problems are the biggest source of error, e.g. sample preparation, recovery from column
LC-Charged aerosol detector in early and late-stage pharmaceutical development: Selection of regression models at optimum power function value
Imad Haidar Ahmad | Merck Research Laboratories
Paul Gamache | Director Research Development, Thermo Fisher Scientific
Imad A. Haidar Ahmad received his Ph.D. from Florida State University under the mentorship of Dr. André Striegel. He completed his postdoctoral research with Prof. Peter Carr at University of Minnesota. He is currently an Associate Principal Scientist and supervisor in the Analytical Chemistry Enabling Technology group within MRL’s AR&D department.
Paul is an analytical chemist who joined Thermo Fisher Scientific in 2011 through acquisition of Dionex Corporation. He is a Director of R &D responsible for development of analytical technologies with primary focus on charged aerosol detection (CAD) and electrochemical detection (ECD) for LC. Prior to joining Dionex in 2009, Paul led the development of first- and second-generation Corona CAD products. He has published more than 50 articles and book chapters and was co-awardee of an NIH Roadmap grant for development of hyphenated EC and LC-MS technologies for metabolomics research. Paul is editor and contributing author to the book “Charged Aerosol Detection for Liquid Chromatography and Related Separation Techniques” published in 2017 by John Wiley & Sons, Inc.
Quantitative LC-CAD in highly regulated laboratories (GLP, GMP, etc.), through utilizing first-order regression via interpolation can be a safe and simple choice. A highly overlooked parameter in LC-CAD is the power function value (PFV), whose optimization enables a detection signal that is more linear with higher signal-to-noise ratio (S/N) and lower relative standard deviation (RSD) of area counts. Herein, a systematic investigation of different regression models (log-log, first-and second-degree polynomial) by both interpolation and extrapolation process in conjunction with PFV optimization throughout the development of LC-CAD assays is reported.
CAD Tips and Tricks
Paul Gamache | Director Research Development, Thermo Fisher Scientific
Paul is an analytical chemist who joined Thermo Fisher Scientific in 2011 through acquisition of Dionex Corporation. He is a Director of R &D responsible for development of analytical technologies with primary focus on charged aerosol detection (CAD) and electrochemical detection (ECD) for LC. Prior to joining Dionex in 2009, Paul led the development of first- and second-generation Corona CAD products. He has published more than 50 articles and book chapters and was co-awardee of an NIH Roadmap grant for development of hyphenated EC and LC-MS technologies for metabolomics research. Paul is editor and contributing author to the book “Charged Aerosol Detection for Liquid Chromatography and Related Separation Techniques” published in 2017 by John Wiley & Sons, Inc.
A UHPLC-PDA-CAD-HRMS Platform for Comprehensive Identification and Quantitation of Constituents in Complex Mixtures for Safety Risk Assessments
Dr. Jason Price | Procter & Gamble R&D
Jason Price received his Ph.D. in Chemistry from Purdue University in 2002 where he worked with Professor Hilkka Kenttämaa to understand the factors that influence the fundamental reactivity of organic radicals and biradicals via their ion-molecule reactions in Fourier transform ion cyclotron resonance mass spectrometers. After graduation, Jason joined Procter & Gamble in Cincinnati, OH working in Beauty Analytical to drive upstream technologies to in-market products across Personal Cleansing, Skin Care and Hair Care categories. He developed expertise in quantifying deposition and bioavailability of actives to guide formulation development and claim support. Jason is currently a Principal Scientist in P&G’s Trace Analytical Capability where he has worked since 2009. In this role, he supports all P&G businesses by leading (1) the development of quantitative LC-MS/MS assays and (2) the identification of unknowns (e.g., impurities, degradation products, contaminants) in complex mixtures by high-resolution mass spectrometry.
To support in silico assessments that guide the need for more expensive in vitro or in vivo safety studies, we have developed a comprehensive approach to identify and quantitate the constituents of complex mixtures (including natural products and extracts of assembled products and polymers). The methodology utilizes separation by UHPLC, followed by UV, charged aerosol detection (CAD) and high-resolution mass spectrometry (with MS/MS and MS3). CAD provides quantitation for analytes where analytical reference standards are not available. Quantitation is facilitated by the addition of an inverse gradient stream which compensates for the known sensitivity of the detector to mobile phase composition. The identification of unknown compounds is accomplished using high resolution mass spectrometry to obtain molecular formulae coupled with database searching. The value of orthogonal data (e.g., UV absorbance spectra) to aid compound identification will also be highlighted.
- A multiple detector approach (PDA, CAD and HRMS) using a compensating gradient efficiently provides rich data on both the quantity and identity of individual components of complex mixtures and can be applied for multiple purposes (e.g., risk assessments, E&L, material comparisons).
- Analysis of 90 phytochemical standards showed that compounds with a BP < 350°C did not produce CAD response and that those with a BP between 350–450°C produced variable response.
- For 67 non-volatile phytochemicals, the variability of the CAD response using a compensating gradient was better than needed for risk assessments (% CV ~ 18%)
Using UHPLC-CAD and PCA to detect olive oil adulteration via triacylglycerol analysis
Hilary Green | Graduate student, Ph.D. Candidate, University of California, Davis USA
Hilary’s is a Ph.D. candidate in the Agricultural and Environmental Chemistry group at the University of California, Davis. Her interest in research interests stem from her passions for food and the environment through the lens of analytical chemistry. Her dissertation focuses on ensuring the authenticity and quality of edible oils. She has published a faster and less wasteful method to detect olive oil adulteration. She also published a work evaluating the chemical composition of avocado oils on the US market. For the final part of her dissertation, she is working to understand the natural variance in avocado oils to support the standard development effort for this oil. In addition, she is developing a better method to detect adulteration in avocado oil. Hilary’s research is closely connected to the food industry and consumers; thus, she is broadly interested in educating the public on scientific research.
Adulteration is a common fraud for extra virgin olive oil (EVOO) due to its superior economic value over other edible oils. Traditional methods of fatty acid and sterol profiling for detecting adulteration demand time from sample preparation and analysis in addition to excessive use of solvents. New methodologies are needed to determine the purity of EVOO that are both time-efficient and cost-effective. Ultra-high-performance liquid chromatography (UHPLC) with charged aerosol detection (CAD) was used to characterize EVOO and potential adulterant oils based on their triacylglycerol (TAG) profiles. Statistical analysis of these TAGs with PCA allows for a new method to determine EVOO purity. Adulteration of EVOO with cheaper vegetable oils and lower-quality olive oils was able to be detected at adulteration levels of 10% using this method. Using PCA analysis with TAGs cannot only be used to determine if an EVOO sample has been adulterated, but also predict the adulterant and the level of adulteration.
- Olive oil adulteration can be quickly detected at levels of 10% using this method
- This method saves time and resources in determining sample purity as there is no sample preparation needed other than dilution before analysis with the UHPLC-CAD
- This method can predict the level of adulteration and the adulterant, which traditional purity detection methods cannot
Basics and beyond
Chris Tuczemskyi | Applications & Technical Support Specialist, Thermo Fisher Scientific
Chris Tuczemskyi is a chromatography specialist at Thermo Fisher Scientific, based in Cambridge, UK. After spending a number of years building up his experience with chromatography instruments in a water testing laboratory, he joined Thermo Fisher Scientific in 2014 as a chromatography service engineer for Unity Lab Services. Here he developed his passion for supporting customers using HPLC and in 2018 moved into the application specialist team. As a chromatography specialist, his role includes working with customers in developing applications to help to enable them to make the world healthier, cleaner and safer. In 2009, Chris graduated from the University of Essex in Biochemistry (Bsc Hons).
Polysorbate analysis in drug products
Georg Schuster | Senior scientist, Coriolis Pharma
Georg Schuster is senior scientist and group leader at Coriolis Pharma, a science-driven contract research organization, where he focusses on protein characterization and analytic method development for biopharmaceuticals with LC and CE based separation techniques and polysorbate characterization via LC coupled to charged aerosol detection. Georg has received his PhD degree in analytical chemistry from the University of Vienna, Austria, in the field of HILIC stationary phase development and further worked as post-doctoral scientist at the Australian Centre for Research on Separation Science, Tasmania. Prior to working at Coriolis Pharma (2016), he was a scientist engaged in protein separation method development at Novo Nordisk, Denmark.
In biopharmaceuticals, surfactants are often used to stabilize proteins against interfacial stress and/or to prevent adsorption. Among the approved non-ionic surfactants for parenteral applications polysorbate 20 and 80 (also known as Tween) are the most common ones. However, polysorbates can oxidize and/or hydrolyze on long-term stability and generate subvisible and visible particles which impact drug product stability. In this talk, we will discuss the investigation of polysorbate degradation pathways by application of a fast RP-UPLC-CAD characterization method.
- Polysorbates are complex heterogeneous mixtures, contain impurities and are prone to degradation
- Quality and consistency of neat polysorbate batches must be considered/are crucial for formulation studies and DP manufacturing
- LC-CAD is a key working horse for PS quantification and subclass analysis
CAD in pharmaceutical analysis
Ruben Pawellek | PhD Student, University of Wuerzburg, Germany
Ruben Pawellek received his pharmacy degree at the university of Wuerzburg in 2016, followed by one year of practical training in the quality control unit of Boehringer Ingelheim and in a public pharmacy. Since 2017, he pursues his PhD studies in pharmaceutical chemistry at the university of Wuerzburg. His research is mainly focused on the application of HPLC-CAD in pharmaceutical analysis and on the optimization of the detector’s performance. In 2020, he completed a three-year professional training in pharmaceutical analysis.
During the last decade, CAD has become an established detection technique in the field of pharmaceutical analysis. Recently, the European Pharmacopoeia introduced the detector for the analysis of weakly chromophoric drugs. This presentation provides an overview of recent CAD applications for compendial quality control purposes focusing on the impurity profiling of drug substances. In this regard, the in-line coupling of UV-CAD offers numerous advantages when impurities with opposing physico-chemical properties are analysed simultaneously, e.g. volatile impurities and impurities with weak chromophores.1
The application of the CAD in a regulated environment requires careful selection of the detector settings to comply with the demands for robust and sensitive methods.2 Here, we present optimization strategies for the PFV setting of the CAD that can help to linearize the detector signal in a manner conforming to GMP regulations.3 Moreover, we include a brief discussion about pros and cons of IPC and HILIC for impurity profiling focusing on the impact of the respective separation technique on CAD sensitivity.
1 R. Pawellek, K. Schilling, U. Holzgrabe, Impurity profiling of l-aspartic acid and glycine using high-performance liquid chromatography coupled with charged aerosol and ultraviolet detection, J. Pharm. Biomed. Anal. 183 (2020) 113149.
2 K. Schilling, R. Pawellek, K. Lovejoy, T. Muellner, U. Holzgrabe, Influence of charged aerosol detector instrument settings on the ultra-high-performance liquid chromatography analysis of fatty acids in polysorbate 80, J. Chromatogr. A 1576 (2018) 58-66.
3 R. Pawellek, T. Muellner, P. Gamache, U. Holzgrabe, Power function setting in charged aerosol detection for the linearization of detector response – optimization strategies and their application, J. Chromatogr. A 1637 (2021) 461844.
- CAD is essential for the impurity profiling of weakly chromophoric drugs
- Optimization of CAD settings is crucial for the development of robust and reproducible methods for a compendial application
- UV-CAD can be easily applied to broaden the detection scope
High Throughput Analysis (HTA) for small molecule libraries with the Thermo Scientific Vanquish Duo UHPLC
Thomas Dann | Analytical Scientist, Charles River Labs
Matthew Gill | Charles River Labs
Thomas Dann, graduating from the University of East Anglia with an MChem degree, he went on to complete a PhD there focusing on electroanalytical chemistry, where he synthesised organometallic compounds, characterising them by NMR, mass spectrometry and electrochemical techniques. From this he moved into industry working in a Compound Management lab where the role included QC by LCMS for newly solubilised compounds. Building on this experience, Thomas then progressed onto a full analytical science role at Charles River.
Matthew graduated in BSc (Hons) Chemistry through the ICI Agrochemicals day release training scheme in 1995 and remained at Jealott’s Hill Research Station with Syngenta for 13 years as a synthetic chemist working on Fungicide and Herbicide projects. Matthew joined the Automated Synthesis group led by Dr Gary Walters, for his last two years, exploring his interest in technology and its application in synthetic chemistry. He joined Argents Discovery, drug discovery CRO, in 2002 as a principal scientist. Following the acquisition of Argenta Discovery by Charles River Laboratories in 2014, Matthew increased his focus on technology through becoming Group Leader for Analytical Sciences at both the Harlow and Chesterford Research Park CRL Early Discovery sites, driving a range of projects such as challenging the acceleration of drug discovery through process efficiencies, leading a cross departmental New Technologies Group and supporting the next generation of technicians through CRL’s Scientific Apprenticeship program.
At Charles River Early Discovery, we acquired a Thermo Scientific Vanquish Duo UHPLC system in 2020 to strengthen our HTA capability supporting CRL’s HTS Biology business. The system has been set up to report compound purity/identification through UV detection and the ISQEC mass, as a reflection of our other UPLC -MS systems, with the aim of linking into third party Virscidian software for automated data processing.
Our talk will describe progress on linking to external thirdparty software and other developments, such as: the use of ACE columns technology to reduce workload and comments on plans to exploring the potential for the CAD to enhance analysis of fragment and small polar molecules that typically demonstrate weak chromophores.
- Limitations of Tandem Method
- Complexity of integration with third party software
- Support for development of bespoke processing
- Application of mass hunting for variable entities
- Potential for a Chromeleon User Group
Peptide quantification by CAD
Kilian Conde Frieboes | Principal Scientist, Novo Nordisk
Killian studied Chemistry in Kiel/Germany.Doctor of Science in 1992 (Asymmetric Synthesis)Post docs at the University of Frankfurt and University of California, San Diego (1992-1995).Assistant at the ETH Zurich (1995-1997).Joined Novo Nordisk in 1997.
A UPLC-CAD setup with an inverse gradient has been used to quantify solutions of modified peptides and proteins.
- A CAD can accurately quantify new peptides
- The build-in exponential function should be used instead of a non-linear curve fit
- The usual problems are the biggest source of error, e.g. sample preparation, recovery from column
LC-Charged aerosol detector in early and late-stage pharmaceutical development: Selection of regression models at optimum power function value
Imad Haidar Ahmad | Merck Research Laboratories
Paul Gamache | Director Research Development, Thermo Fisher Scientific
Imad A. Haidar Ahmad received his Ph.D. from Florida State University under the mentorship of Dr. André Striegel. He completed his postdoctoral research with Prof. Peter Carr at University of Minnesota. He is currently an Associate Principal Scientist and supervisor in the Analytical Chemistry Enabling Technology group within MRL’s AR&D department.
Paul is an analytical chemist who joined Thermo Fisher Scientific in 2011 through acquisition of Dionex Corporation. He is a Director of R &D responsible for development of analytical technologies with primary focus on charged aerosol detection (CAD) and electrochemical detection (ECD) for LC. Prior to joining Dionex in 2009, Paul led the development of first- and second-generation Corona CAD products. He has published more than 50 articles and book chapters and was co-awardee of an NIH Roadmap grant for development of hyphenated EC and LC-MS technologies for metabolomics research. Paul is editor and contributing author to the book “Charged Aerosol Detection for Liquid Chromatography and Related Separation Techniques” published in 2017 by John Wiley & Sons, Inc.
Quantitative LC-CAD in highly regulated laboratories (GLP, GMP, etc.), through utilizing first-order regression via interpolation can be a safe and simple choice. A highly overlooked parameter in LC-CAD is the power function value (PFV), whose optimization enables a detection signal that is more linear with higher signal-to-noise ratio (S/N) and lower relative standard deviation (RSD) of area counts. Herein, a systematic investigation of different regression models (log-log, first-and second-degree polynomial) by both interpolation and extrapolation process in conjunction with PFV optimization throughout the development of LC-CAD assays is reported.
CAD Tips and Tricks
Paul Gamache | Director Research Development, Thermo Fisher Scientific
Paul is an analytical chemist who joined Thermo Fisher Scientific in 2011 through acquisition of Dionex Corporation. He is a Director of R &D responsible for development of analytical technologies with primary focus on charged aerosol detection (CAD) and electrochemical detection (ECD) for LC. Prior to joining Dionex in 2009, Paul led the development of first- and second-generation Corona CAD products. He has published more than 50 articles and book chapters and was co-awardee of an NIH Roadmap grant for development of hyphenated EC and LC-MS technologies for metabolomics research. Paul is editor and contributing author to the book “Charged Aerosol Detection for Liquid Chromatography and Related Separation Techniques” published in 2017 by John Wiley & Sons, Inc.
A UHPLC-PDA-CAD-HRMS Platform for Comprehensive Identification and Quantitation of Constituents in Complex Mixtures for Safety Risk Assessments
Dr. Jason Price | Procter & Gamble R&D
Jason Price received his Ph.D. in Chemistry from Purdue University in 2002 where he worked with Professor Hilkka Kenttämaa to understand the factors that influence the fundamental reactivity of organic radicals and biradicals via their ion-molecule reactions in Fourier transform ion cyclotron resonance mass spectrometers. After graduation, Jason joined Procter & Gamble in Cincinnati, OH working in Beauty Analytical to drive upstream technologies to in-market products across Personal Cleansing, Skin Care and Hair Care categories. He developed expertise in quantifying deposition and bioavailability of actives to guide formulation development and claim support. Jason is currently a Principal Scientist in P&G’s Trace Analytical Capability where he has worked since 2009. In this role, he supports all P&G businesses by leading (1) the development of quantitative LC-MS/MS assays and (2) the identification of unknowns (e.g., impurities, degradation products, contaminants) in complex mixtures by high-resolution mass spectrometry.
To support in silico assessments that guide the need for more expensive in vitro or in vivo safety studies, we have developed a comprehensive approach to identify and quantitate the constituents of complex mixtures (including natural products and extracts of assembled products and polymers). The methodology utilizes separation by UHPLC, followed by UV, charged aerosol detection (CAD) and high-resolution mass spectrometry (with MS/MS and MS3). CAD provides quantitation for analytes where analytical reference standards are not available. Quantitation is facilitated by the addition of an inverse gradient stream which compensates for the known sensitivity of the detector to mobile phase composition. The identification of unknown compounds is accomplished using high resolution mass spectrometry to obtain molecular formulae coupled with database searching. The value of orthogonal data (e.g., UV absorbance spectra) to aid compound identification will also be highlighted.
- A multiple detector approach (PDA, CAD and HRMS) using a compensating gradient efficiently provides rich data on both the quantity and identity of individual components of complex mixtures and can be applied for multiple purposes (e.g., risk assessments, E&L, material comparisons).
- Analysis of 90 phytochemical standards showed that compounds with a BP < 350°C did not produce CAD response and that those with a BP between 350–450°C produced variable response.
- For 67 non-volatile phytochemicals, the variability of the CAD response using a compensating gradient was better than needed for risk assessments (% CV ~ 18%)
Using UHPLC-CAD and PCA to detect olive oil adulteration via triacylglycerol analysis
Hilary Green | Graduate student, Ph.D. Candidate, University of California, Davis USA
Hilary’s is a Ph.D. candidate in the Agricultural and Environmental Chemistry group at the University of California, Davis. Her interest in research interests stem from her passions for food and the environment through the lens of analytical chemistry. Her dissertation focuses on ensuring the authenticity and quality of edible oils. She has published a faster and less wasteful method to detect olive oil adulteration. She also published a work evaluating the chemical composition of avocado oils on the US market. For the final part of her dissertation, she is working to understand the natural variance in avocado oils to support the standard development effort for this oil. In addition, she is developing a better method to detect adulteration in avocado oil. Hilary’s research is closely connected to the food industry and consumers; thus, she is broadly interested in educating the public on scientific research.
Adulteration is a common fraud for extra virgin olive oil (EVOO) due to its superior economic value over other edible oils. Traditional methods of fatty acid and sterol profiling for detecting adulteration demand time from sample preparation and analysis in addition to excessive use of solvents. New methodologies are needed to determine the purity of EVOO that are both time-efficient and cost-effective. Ultra-high-performance liquid chromatography (UHPLC) with charged aerosol detection (CAD) was used to characterize EVOO and potential adulterant oils based on their triacylglycerol (TAG) profiles. Statistical analysis of these TAGs with PCA allows for a new method to determine EVOO purity. Adulteration of EVOO with cheaper vegetable oils and lower-quality olive oils was able to be detected at adulteration levels of 10% using this method. Using PCA analysis with TAGs cannot only be used to determine if an EVOO sample has been adulterated, but also predict the adulterant and the level of adulteration.
- Olive oil adulteration can be quickly detected at levels of 10% using this method
- This method saves time and resources in determining sample purity as there is no sample preparation needed other than dilution before analysis with the UHPLC-CAD
- This method can predict the level of adulteration and the adulterant, which traditional purity detection methods cannot
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