Folin-Ciocâlteu, RP-HPLC (reverse phase-high performance liquid chromatography), and LC-MS (liquid chromatography-mass spectrometry) provide complementary information for describing cider (Malus spp.) apple juice

<p><strong>When I think about what it takes to keep a high-performing MS laboratory running—especially those dealing with tight timelines, strict regulations, and ever-expanding datasets—I’m reminded that the software we rely on isn’t just a tool. It’s the backbone of our workflows, our decisions, and ultimately, our results.</strong></p><p>Whether you’re in pharma, environmental testing, or food safety, managing the complexity of targeted mass spectrometry workflows while maintaining accuracy, compliance, and efficiency requires a lot of work.</p><p>That’s where a purpose-built solution makes a difference. I’ve worked closely with labs that are navigating these challenges—and from the many conversations and experiences, I put together five main capabilities you should look for in your software when it comes to targeted MS quantitation:</p><h3><strong>1. Simplified data and workflow management</strong></h3><p>Too many labs are still relying on disconnected systems or folder-based setups that can lead to inconsistent methods and reports. When utilizing modern software solutions, everything—methods, templates, data, reports—can be centrally managed, reducing errors and training time while ensuring everyone is working from the same validated workflows.</p><p>It’s a big plus if the software also supports multi-consensus reporting, making it easy to compare results across sequences and analyses for greater confidence in the data. By packaging complete workflows and setting predefined views, labs can streamline routine operations and ensure method repeatability, so anyone can run the analysis reliably and consistently.</p><h3><strong>2. Controlled access in and out of the lab</strong></h3><p>Many labs are still tied to legacy setups that make remote work challenging. Researchers often rely on standalone workstations that store data locally, making it hard to access critical results when off-site. Transferring data via USB drives or external hard disks not only adds inefficiency, but it can also raise serious security concerns. These outdated practices slow down collaboration and increase the risk of data loss or breaches.</p><p>Hybrid work is here to stay. With the ability to control and access instruments and data, users can securely set up runs, review results, and manage workflows from anywhere. You’re no longer tied to a specific bench, workstation, or even building. Productivity doesn’t have to stop when you step out of the lab.</p><p><i>“Managing all our instruments and work with data remotely via a centralized server means we don’t need to be in the laboratory to access our data.” – Dr. Kayleigh Arthur, Owlstone Medical Ltd.</i></p><h3><strong>3. It’s built for MS workflows</strong></h3><p>Whether you’re running triple quads, high-res accurate mass, or both—life’s much easier when working with software solutions that give you native instrument control and deep integration for targeted workflows. That includes support for MSⁿ, intact mass deconvolution, spectral libraries, and high-throughput quantitation.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_5_Things_to_Consider_When_Selecting_Software_for_Targeted_MS_Quantitation_9e5e9dc842.jpg" alt="Thermo Fisher Scientific: 5 Things to Consider When Selecting Software for Targeted MS Quantitation." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_5_Things_to_Consider_When_Selecting_Software_for_Targeted_MS_Quantitation_9e5e9dc842.jpg 245w," sizes="100vw" width="1536" height="411"></p><p>Just as important is what happens after data acquisition. Integrated, built-in reporting capabilities—paired with customizable reporting options—should make it easy to flag results and automate the necessary calculations, all within the software. You need a powerful combination that can streamline review and ensures consistency across analyses.</p><h3><strong>4. Scalability</strong></h3><p>From small bioanalytical teams to global enterprises, can it be scaled up or down without the need for reinstallation or manual data transfer? It should be built to handle complex, multi-site deployments with ease.</p><p>Add to that network resilience, automated data protection, and centralized updates—and you’ll get a system designed to grow with your organization.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_5_Things_to_Consider_When_Selecting_Software_for_Targeted_MS_Quantitation_2_8ec325678b.jpg" alt="Thermo Fisher Scientific: 5 Things to Consider When Selecting Software for Targeted MS Quantitation." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_5_Things_to_Consider_When_Selecting_Software_for_Targeted_MS_Quantitation_2_8ec325678b.jpg 245w," sizes="100vw" width="1200" height="660"></p><article><div><h3><strong>5. Stress-free compliance</strong></h3><p>Let’s face it, if you have to do it, compliance is non-negotiable, but it can be time-consuming. The system should include built-in features that support GxP, 21 CFR Part 11, and audit readiness—like audit trails, version control, and detailed user management.</p><p>The ability to query and interrogate data within the system would ensure that data integrity requirements are met, delivering full traceability, and verification of data throughout its lifecycle. Your QA team will be very pleased!</p><h3><strong>Conclusion</strong></h3><p>Managing targeted MS quantitation shouldn’t feel like assembling a puzzle with missing pieces. A modern software should bring together everything you need—scalable infrastructure, powerful MS data tools, and built-in compliance features—into one cohesive solution. It must support your science, your team, and your business goals.</p><p>If you’re ready to rethink how your lab handles MS data, this is the right time to explore what’s possible.</p><blockquote><p>Join our <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5232"><strong>upcoming webinar</strong></a> to learn about networked software for MS labs.</p><p><strong>Visit us on&nbsp;</strong><a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/showcase/72003132/admin/dashboard/"><strong>LinkedIn:</strong></a>&nbsp;#targetedquantitation #compliance #massspectrometry #control</p></blockquote></div></article><section><blockquote><h4><strong>Laercio Fernandes</strong></h4><p>Laércio Fernandes is a Product Marketing Manager for software at Thermo Fisher Scientific. With a background rooted in analytical chemistry, Laércio has over 20 years of experience in the analytical field with a focus on chromatography instrumentation, enterprise software and compliance. His background in sales and support has enabled him to have a good overview and understanding of different processes and challenges that laboratories may face, which has allowed him to better support our customers in order to improve their workflows and productivity.</p></blockquote></section>

5 Things to Consider When Selecting Software for Targeted MS Quantitation

<h4><strong>Have you explored what’s new in </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Thermo Scientific Compound Discoverer software</strong></a><strong>, version 3.4?</strong></h4><p>In case you missed it, earlier this year we released version 3.4 – bringing new capabilities to small molecule researchers. Get ready to elevate your compound identification and analysis experience with this new version packed with groundbreaking features and enhancements.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_Why_Compound_Discoverer_3_4_Software_is_Worth_Your_Attention_c08c06da12.jpg" alt="Thermo Fisher Scientific: Why Compound Discoverer 3.4 Software is Worth Your Attention!" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_Why_Compound_Discoverer_3_4_Software_is_Worth_Your_Attention_c08c06da12.jpg 245w," sizes="100vw" width="1536" height="614"></p><article><div><h3><strong>Here’s a look at some of the key updates and why you should be excited:</strong></h3><h4><strong>1.&nbsp;LipidSearch (MKI) is now integrated</strong></h4><ul><li>The new <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1740"><strong>LipidSearch </strong></a>(MKI) node simplifies lipid identification, making it faster and more accurate. And here’s the best part: you don’t need to install separate software!</li></ul><h4><strong>2. Improved quality control for small molecule experiments</strong></h4><ul><li>A new QC node leverages internal standards to automatically detect and group in-source fragments, ensuring accurate and reliable results.</li></ul><h4><strong>3.&nbsp;Improved compound identification</strong></h4><ul><li>Connect to the latest version of the <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764"><strong>mzCloud </strong></a>Spectral database (2.0), which includes over 16.5 million spectra, 32,000 MS<sup>n</sup> trees and extensive metadata such as compound classes and CAS numbers. Providing deeper insight and better identification confidence.</li></ul><h4><strong>4.&nbsp;Performance boost</strong></h4><ul><li>Experience up to 8x faster processing speeds for various nodes, including alignment, detecting compounds, fill gaps, and <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1762"><strong>mzLogic</strong></a>, ensuring that your data analysis is completed in record time.</li></ul><h4><strong>5. New spectral library and mass list parameters</strong></h4><ul><li>Now, you can use different sets of parameters for various spectral libraries or mass lists, allowing for precise matching and prioritization.</li></ul><h4><strong>6. Smarter feature detection and component assembly</strong></h4><ul><li>Separate feature detection and component assembly for greater flexibility and performance. New nodes streamline the creation of grouped feature tables and efficiently group ions and in-source fragments.</li></ul><h4><strong>7.&nbsp;New molecular networking capabilities</strong></h4><ul><li>Inject seed compounds (a compound of interest that is not present in the data set) into your molecular networks to form clusters with related compounds, helping you interpret complex networks more effectively. This feature is particularly useful for PFAS-related studies!</li></ul><h4><strong>8.</strong>&nbsp;<strong>Seamless Integration with the Thermo Scientific Ardia Platform</strong></h4><ul><li>Connect to the<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1821"><strong>Ardia Platform</strong></a> for direct raw data access and result file uploads, streamlining your workflow and enabling easy sharing of result files!</li></ul><blockquote><h3><strong>Excited to learn more?</strong></h3><ul><li><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/4863"><strong>Take a look at our webinar</strong></a> where we dive deep into these new features and demonstrate how Compound Discoverer 3.4 Software can elevate your workflows, including pesticides. &nbsp;&nbsp;</li><li>Stay ahead with <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Compound Discoverer Software</strong></a> —where innovation meets precision!</li><li><strong>Visit us on&nbsp;</strong><a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/showcase/72003132/admin/dashboard/"><strong>LinkedIn:</strong></a><strong>&nbsp;</strong>#CompoundDiscoverer #SmallMolecules #Software</li></ul></blockquote></div></article><section><blockquote><h5><strong>Zoe Julian</strong></h5><p>Zoe Julian is a Product Marketing Manager for Chromatography and Mass Spectrometry software at Thermo Fisher Scientific. With over 12 years' experience of working with chromatography and mass spectrometry techniques with a background in GC and GC-MS(/MS) organic environmental analysis, she has helped many laboratories and industries improve their workflows through a unique understanding of their challenges. Transitioning to a focus on Chromeleon CDS she has shown customers how software solutions can improve their productivity and support their day-to-day operations.</p></blockquote></section>

Why Compound Discoverer 3.4 Software is Worth Your Attention!

<p><strong>A critical first step in quantitation is tuning the instrument to identify the optimal fragment ions that deliver both sensitivity and specificity. This is true regardless of the use of triple quadrupoles, ion traps, or accurate mass systems.&nbsp;Traditionally, this process requires physical standards and, in the case of large panels of analytes, can be time-consuming.</strong></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_Generating_Quantitative_Methods_Automatically_From_Spectral_Library_Data_262243e285.jpg" alt="Thermo Fisher Scientific: Generating Quantitative Methods Automatically From Spectral Library Data" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_Generating_Quantitative_Methods_Automatically_From_Spectral_Library_Data_262243e285.jpg 245w," sizes="100vw" width="1024" height="512"></p><h3><strong>But what if we could generate methods without needing all the standards on hand or even tuning them at all?&nbsp;</strong></h3><p>Doing so would require having a source of data that captures the optimal fragments and energies for all compounds.&nbsp;Enter <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764"><strong>mzCloud</strong></a>, a spectral library that includes up to 20 collision energies for high-energy collisional dissociation MS<sup>2</sup> on every compound in the library.</p><p>Although generated from full scan accurate mass instruments, this information contains the energy-dependent fragment formation using a fragment technique common to triple quadrupoles and other instruments.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_8_9199b4056a.jpg" alt="Thermo Fisher Scientific: Generating Quantitative Methods Automatically From Spectral Library Data: Thermo Scientific mzCloud Mass Spectral Library" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Scientific_mz_Cloud_Mass_Spectral_Library_8_9199b4056a.jpg 224w," sizes="100vw" width="270" height="188"></p><ul><li>Extensively curated, high-quality <strong>free online library</strong></li><li><strong>Multiple fragmentation energy levels </strong>represented</li><li><strong>Covers a wide chemical space </strong>to include compounds relevant to all applications</li><li><strong>For both research and targeted screening</strong> workflows</li><li>Contains <strong>over 32,000 compounds and 16,500,000 spectra</strong></li></ul><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_Generating_Quantitative_Methods_Automatically_From_Spectral_Library_Data_2_bcac20a85c.jpg" alt="Thermo Fisher Scientific: Generating Quantitative Methods Automatically From Spectral Library Data: Figure 1. Breakdown curves for the top 6 fragment ions from Melatonin showing maximum energy for each fragment ion. X-axis is fragmentation energy, Y-axis is fragment intensity." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_Generating_Quantitative_Methods_Automatically_From_Spectral_Library_Data_2_bcac20a85c.jpg 245w," sizes="100vw" width="1024" height="367"></p><h3><strong>So, could we transfer the information from the library into a usable method for an instrument such as a triple quadrupole?</strong></h3><p><strong>The answer is yes</strong>. The first step is to determine if any offset in the collision energy (eV) exists between the platform used to generate the library and the target quantitative instrument.&nbsp; This can be easily assessed with a small selection of compounds across the mass range to ensure that the optimal collision energy remains the same or, in cases where they are different, a correction factor can be calculated.&nbsp; Once this is done, it is a relatively simple matter of taking the top N most intense fragment ions from the library curves and creating the corresponding quantitative instrument methods.</p><p>In fact, we have already successfully implemented this approach: <strong>all recent triple quadrupoles from Thermo Fisher Scientific now come with a built-in database of methods generated in this fashion</strong>.&nbsp; The creation of a quantitative acquisition method is as simple as selecting compounds, polarity, and number of transitions from the database and proceeding with acquisition.</p><p>By automating the generation of quantitative methods from spectral library data, we significantly reduce the time and effort required for method development. This enables our customers to focus on their core research and analysis, improving productivity and accelerating scientific discovery.</p><p>For more information, join us at the upcoming <a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/content/lifetech/global/en/home/events/proteome-discoverer-compound-discoverer-users-meetings.html"><strong>user meeting</strong></a> or go to<strong> </strong><a target="_blank" rel="noopener noreferrer" href="https://www.mzcloud.org/"><strong>mzCloud.org</strong></a> or see the advantages of using mzCloud with Thermo Scientific <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Compound Discoverer software</strong></a>.</p><ul><li><strong>Visit us on&nbsp;</strong><a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/showcase/72003132/admin/dashboard/"><strong><u>LinkedIn:</u></strong></a>&nbsp;#mzCloud #MassSpectralLibraries</li></ul><blockquote><h5><strong>Tim Stratton</strong></h5><p>Tim is a University of Minnesota graduate with over a decade of experience in pharmaceutical analysis and research, specializing in structure elucidation and interpretation of fragmentation. After roles at Solvay Pharmaceuticals and Abbott Laboratories spanning regulated analysis, method validation, and drug metabolism/pharmacokinetics, Tim joined Thermo Fisher Scientific. Over the past decade, he has focused on supporting hardware and software development, as well as building high-resolution, accurate mass spectral libraries to advance unknown identification in research.</p></blockquote>

Generating Quantitative Methods Automatically From Spectral Library Data

<p><i><strong>This is the second part of a multi-part Library blog series. For additional information, see blog </strong></i><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/article/6709"><i><strong>Part 1- Generating Quantitative Methods Automatically From Spectral Library Data </strong></i></a><i><strong>and stay tuned for more blogs on our website.</strong></i></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_Identification_of_Substructures_in_Unknowns_Through_M_Sn_Data_58afeccc3e.jpg" alt="Thermo Fisher Scientific: Identification of Substructures in Unknowns Through MSn Data." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_Identification_of_Substructures_in_Unknowns_Through_M_Sn_Data_58afeccc3e.jpg 216w," sizes="100vw" width="1024" height="740"></p><p>While identification of unknowns remains a significant challenge, it has become easier over the years with the growth of large MS<sup>n</sup> spectral libraries. These libraries, such as <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764"><strong>mzCloud</strong></a>, can provide substructure data on unknowns.&nbsp; Such information can help us to elucidate the structure of compounds that would previously remain unknown.</p><p>Substructure identification such as this takes advantage of the fact that a structure will always create the same fragments under a given set of fragmentation conditions regardless of if that structure was from MS<sup>1</sup> or an MS<sup>n</sup> level of fragmentation.&nbsp; While no library will ever contain fragmentation data on all possible chemicals, what we need with this approach is enough breadth of coverage in the various substructures commonly occurring to “build up” larger molecules.&nbsp; What that means is we can take the MS<sup>n</sup> data on many structurally diverse molecules and use it to identify substructures in our unknown.</p><p>As an example of using MS<sup>n</sup> data in this fashion, <strong>figure 1</strong> shows the query MS<sup>n</sup> spectra for an unknown and two of the library hits.&nbsp; The hits are from MS<sup>n</sup> spectra of two known compounds and the precursor of the specific MS<sup>n</sup> fragment spectra is shown.&nbsp; Both hits from the library provide a similar structure – an aromatic benzyne linked to either an amide or linked to a carbonyl and amine group.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_Identification_of_Substructures_in_Unknowns_Through_M_Sn_Data_2_010011961a.jpg" alt="Thermo Fisher Scientific: Identification of Substructures in Unknowns Through MSn Data: Figure 1: The MS3 spectra of the unknown (A) and two matching fragment spectra from the library search along with the precursors of those spectra (B)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_Identification_of_Substructures_in_Unknowns_Through_M_Sn_Data_2_010011961a.jpg 245w," sizes="100vw" width="1024" height="288"></p><p>While in this example, the specific orientation could not be determined, we have at least a very good starting point in our structure determination by knowing at least one piece of our unknown.&nbsp; Further searches with other MS<sup>n</sup> spectra from our molecule may uncover other substructures bringing us close to a final identification.&nbsp; In fact, the unknown in this case was isoproturon (<strong>Figure 2</strong>) which indeed has the substructure indicated from the search.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_Identification_of_Substructures_in_Unknowns_Through_M_Sn_Data_3_72dbd5fcef.jpg" alt="Thermo Fisher Scientific: Identification of Substructures in Unknowns Through MSn Data: Figure 2: Structure of Isoproturon." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_Identification_of_Substructures_in_Unknowns_Through_M_Sn_Data_3_72dbd5fcef.jpg 245w," sizes="100vw" width="1024" height="578"></p><p>By utilizing a large library of MS<sup>n</sup> reference data and acquiring the same MS<sup>n</sup> query data on our unknowns, we can begin to build up a picture based on substructures we identify.&nbsp; Visit <a target="_blank" rel="noopener noreferrer" href="https://www.mzcloud.org/"><strong>mzCloud </strong></a>to see the breadth of MS<sup>n</sup> fragmentation spectra on a diverse range of chemicals that can be used for such an approach.</p><ul><li><strong>Visit us on&nbsp;</strong><a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/showcase/72003132/admin/dashboard/"><strong><u>LinkedIn:</u></strong></a>&nbsp;#mzCloud #MassSpectralLibraries</li></ul><blockquote><h5><strong>Tim Stratton</strong></h5><p>Tim is a University of Minnesota graduate with over a decade of experience in pharmaceutical analysis and research, specializing in structure elucidation and interpretation of fragmentation. After roles at Solvay Pharmaceuticals and Abbott Laboratories spanning regulated analysis, method validation, and drug metabolism/pharmacokinetics, Tim joined Thermo Fisher Scientific. Over the past decade, he has focused on supporting hardware and software development, as well as building high-resolution, accurate mass spectral libraries to advance unknown identification in research.</p></blockquote>

Identification of Substructures in Unknowns Through MSn Data

<p><strong>Per- and polyfluoroalkyl substances (PFAS) have become a major global concern due to their persistence, bioaccumulation, and potential health impacts. With thousands of known PFAS compounds, and new variants continuing to emerge, identifying and quantifying them across complex environmental and biological samples is an ongoing analytical challenge.</strong></p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_From_Complexity_to_Clarity_Smarter_PFAS_Identification_Workflows_in_Compound_Discoverer_Software_2_8e83167891.jpg" alt="Thermo Fisher Scientific: From Complexity to Clarity: Smarter PFAS Identification Workflows in Compound Discoverer Software" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_From_Complexity_to_Clarity_Smarter_PFAS_Identification_Workflows_in_Compound_Discoverer_Software_2_8e83167891.jpg 245w," sizes="100vw" width="1024" height="574"></p><h3><strong>Why PFAS analysis matters</strong></h3><p>PFAS are used in everything from firefighting foams to non-stick coatings, yet their chemical stability means they persist in the environment and accumulate in living organisms. Regulators and scientists around the world are racing to better understand their distribution, fate, and toxicity.</p><p>But with tens of thousands of PFAS, many without available reference standards, traditional targeted analysis alone isn’t enough. Analysts increasingly rely on non-targeted analysis (NTA) workflows powered by high-resolution accurate-mass (HRAM) mass spectrometry and advanced software to uncover the full picture.</p><h3><strong>Addressing the challenges of PFAS identification</strong></h3><p>Successful non-targeted PFAS analysis requires overcoming several analytical hurdles:</p><ol><li>Acquiring high-quality MS¹ and MS² data with ultra-high mass resolution and accuracy.</li><li>Detecting low-abundance PFAS hidden within thousands of background compounds.</li><li>Leveraging comprehensive spectral libraries and databases for confident identification.</li><li>Applying data filtering and scoring tools to assign confidence levels to annotations.</li><li>Using visualization and statistical tools to interpret and compare complex datasets.</li></ol><p><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1759"><strong>Thermo Scientific Compound Discoverer 3.5 software </strong></a>brings together all the components needed for robust PFAS identification—integrating <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products?category=22&amp;manufacturerItems=3"><strong>HRAM Orbitrap MS</strong></a> data with an expanded suite of PFAS-specific libraries and databases.</p><p><strong>In a single workflow, users can:</strong></p><ul><li>Detect and annotate compounds automatically from LC-MS data.</li><li>Determine possible elemental formulas using isotope pattern and accurate mass information.</li><li>Compare MS² spectra against <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1764"><strong>mzCloud</strong></a>, NIST 2023, and <i>in silico</i> PFAS libraries.</li><li>Cross-reference annotations with the EPA PFAS Structure List and the NIST Suspect List of PFAS.</li><li>Use PFAS-specific fragment and neutral loss databases to strengthen identification confidence.</li></ul><p>With these resources combined, the software enables confident annotation of more than<strong> 40,000 PFAS </strong>compounds!</p><h3><strong>New tools for confident, streamlined PFAS identification</strong></h3><p>Compound Discoverer software introduces several new features designed to simplify and accelerate PFAS NTA workflows:</p><ul><li><strong>Apply PFAS Scoring Node:</strong> Automatically calculates PFAS-specific parameters and a new PFAS Score—no R scripting required.</li><li><strong>PFAS Plot:</strong> A visual tool that uses mass-defect metrics to highlight probable PFAS in complex datasets, following methods from Kaufman et al. (2022).</li><li><strong>Expanded suite of libraries and databases:</strong> Combines mzCloud, NIST, <i>in silico</i>, PFAS fragment databases, and a new neutral loss database for greater confidence.</li><li><strong>Advanced data visualization:</strong> Tools like Kendrick Mass Defect and Molecular Network plots reveal homologous PFAS series and related compound families.</li><li><strong>Built-in statistical analysis tools</strong>: Compare PFAS composition between samples using Principal Component Analysis, Differential analysis and Hierarchical Cluster Analysis.</li></ul><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_From_Complexity_to_Clarity_Smarter_PFAS_Identification_Workflows_in_Compound_Discoverer_Software_ed32c7f7c1.jpg" alt="Thermo Fisher Scientific From Complexity to Clarity Smarter PFAS Identification Workflows in Compound Discoverer Software" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_From_Complexity_to_Clarity_Smarter_PFAS_Identification_Workflows_in_Compound_Discoverer_Software_ed32c7f7c1.jpg 245w," sizes="100vw" width="800" height="395"></p><h3><strong>From complexity to clarity</strong></h3><p>By uniting Orbitrap HRAM data with the most comprehensive PFAS libraries available, Compound Discoverer 3.5 software streamlines non-targeted PFAS analysis—helping laboratories move from data complexity to confident chemical clarity.</p><p><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/webinar/5612"><strong>Watch the on-demand webinar</strong></a> to see the full workflow in action and learn how Compound Discoverer software can enhance your PFAS analysis.</p><ul><li><strong>Visit us on&nbsp;</strong><a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/showcase/72003132/admin/dashboard/"><strong><u>LinkedIn:</u></strong></a>&nbsp;#PFAS #CompoundDiscoverer #SpectralLibraries</li></ul><blockquote><h5><strong>Zoe Julian</strong></h5><p>Zoe Julian is a Product Marketing Manager for Chromatography and Mass Spectrometry software at Thermo Fisher Scientific. With over 12 years' experience of working with chromatography and mass spectrometry techniques with a background in GC and GC-MS(/MS) organic environmental analysis, she has helped many laboratories and industries improve their workflows through a unique understanding of their challenges. Transitioning to a focus on Chromeleon CDS she has shown customers how software solutions can improve their productivity and support their day-to-day operations.</p></blockquote>

From Complexity to Clarity: Smarter PFAS Identification Workflows in Compound Discoverer Software

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From Complexity to Clarity: Smarter PFAS Identification Workflows in Compound Discoverer Software

Identification of Substructures in Unknowns Through MSn Data

Generating Quantitative Methods Automatically From Spectral Library Data

Why Compound Discoverer 3.4 Software is Worth Your Attention!

5 Things to Consider When Selecting Software for Targeted MS Quantitation

Folin-Ciocâlteu, RP-HPLC (reverse phase-high performance liquid chromatography), and LC-MS (liquid chromatography-mass spectrometry) provide complementary information for describing cider (Malus spp.) apple juice

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Thermo Fisher Scientific Liquid Chromatography Solutions Tour

Agilent Lab Innovation Day for Academia

Is Your LC Method Ready for Today’s Biopharma Challenges? Parsippany, NJ

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The Journey of Safer Science through Safer Labs

Strategies to Mitigate Sporadic PFAS Contamination in Analytical Workflows

Tracking irrigation-related contaminants in water and soils (QTOF-MS)