Propionic Acid Outperforms Formic and Acetic Acid in MS Sensitivity for High-Flow Reversed-Phase LC-MS Bottom-Up Proteomics

<p><strong>This study introduces a quantitative workflow for multielement single-cell analysis by mass cytometry using metal-loaded, multielement-barcoded polystyrene beads as calibration standards. Online mixing allows bead and cell events to be distinguished by TOF-MS, enabling elemental concentrations in labeled cells to be quantified from bead responses.</strong></p><p>The approach was demonstrated with Lu-, Nd-, and Ir-labeled cancer cells and extended through a polynomial calibration model to elements not directly included in the beads. Agreement with external calibration highlights the method’s potential as a universal quantitative strategy for mass cytometry and single-cell ICP-TOF-MS.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article/98/31/22966/5231419/Quantitative-Single-Cell-Multielemental-Analysis#249383980"><strong>Quantitative Single-Cell Multielemental Analysis Using Metal-Loaded Microparticles: toward a Universal Quantification Workflow in Mass Cytometry</strong></a></h4><p>Ángela de la Rosa-Díaz; Carlos López-Portugués; Mario Corte-Rodríguez*; María Montes-Bayón *</p><p>Anal. Chem. (2026) 98 (31): 22966–22976</p><div><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acs.analchem.6c02340">https://doi.org/10.1021/acs.analchem.6c02340</a></div><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><div><div><div><div><p>Understanding the biochemical and functional heterogeneity of individual cells is a central challenge in modern biology, immunology, oncology, and clinical translational research. Flow cytometry, and, more recently, spectral flow cytometry, (<a href="javascript:;">1</a>) have become essential tools for high-dimensional single-cell analysis. However, obtaining robust quantitative information at the single-cell level remains challenging, particularly when comparing measurements across experiments and laboratories. Quantitative approaches have been developed for fluorescence flow cytometry, typically relying on calibration beads and standardized antibody conjugates to improve interexperimental comparability. (<a href="javascript:;">2−4</a>) Nevertheless, the accuracy of these methods remains influenced by fluorophore-specific properties and labeling variability, highlighting the need for alternative quantitative single-cell analytical strategies.</p></div><div><p>Mass cytometry, or cytometry by time-of-flight (CyTOF), which was introduced by the team of Bandura in 2009, has emerged as a technological breakthrough by substituting fluorophores with isotopically pure metal tags, whose signals are detected by TOF elemental mass spectrometry (MS) using an inductively coupled plasma as ion source (ICP–TOF–MS). (<a href="javascript:;">5</a>) This technology has allowed to remove nearly all spectral overlaps and enabled experiments that can routinely include 40–60 parameters, including not only protein biomarkers but also DNA markers and metallodrugs or nanoparticles. (<a href="javascript:;">6, 7</a>) Numerous studies have taken advantage of the highly multiplex capabilities of CyTOF to investigate immune responses, characterize tumor-infiltrating lymphocytes, or follow hematopoietic differentiation with greater resolution than was previously possible. (<a href="javascript:;">8−10</a>) Indeed, the technique has become central to many multiparametric immunology pipelines by facilitating deeper functional analyses, from mapping subtle cell-cycle states (<a href="javascript:;">11</a>) to profiling intracellular cytokine signatures and activation markers (<a href="javascript:;">12</a>) that are often difficult to resolve by fluorescence-based approaches. (<a href="javascript:;">13</a>)</p></div><div><p>Beyond its multiplexing capability, an often overlooked advantage of mass cytometry is its potential for elemental quantification. Unlike fluorescence-based approaches, ICP–MS-based detection enables direct conversion of signal intensities into elemental amounts through established calibration strategies. This principle, successfully applied for single-cell elemental analysis by ICP–MS (SC–ICP–MS), has shown to be suitable in different applications. Thus, quantification of intrinsic (<a href="javascript:;">14−17</a>) or exogenous (<a href="javascript:;">18−20</a>) elements, as well as protein biomarkers following metal-labeling strategies (<a href="javascript:;">21, 22</a>) compare well with the bulk analyses on the same cell suspension. However, despite the efforts made to develop quantitative strategies, mass cytometry remains as a mainly qualitative strategy, where very few approaches have explored its unquestionable quantification potential. (<a href="javascript:;">4, 23−25</a>)</p></div><div><p>CyTOF data quality depends critically on managing instrumental variability. Plasma fluctuations, partial clogging of the sample introduction system or injector and periodic retuning, introduce changes in sensitivity that can obscure biological differences between samples measured at different times or in different instruments. To mitigate these effects, CyTOF applies multielement calibration polymeric beads, such as EQ six-element calibration beads, that are mixed with every sample at a fixed concentration before nebulization. (<a href="javascript:;">26, 27</a>) These beads, containing defined quantities of yttrium, indium, cerium, terbium, lutetium and bismuth, allow computational normalization and provide a reference signal that corrects for shifts in sensitivity over time. More recently, approaches using frozen antibody master mixes, unified acquisition templates, and sophisticated normalization algorithms have been introduced to enable reproducible multibatch studies and harmonize data sets across different research centers. (<a href="javascript:;">27, 28</a>)</p></div><div><p>Since the sought beads that contain multiple elements in a wide mass range (from <sup>89</sup>Y to <sup>209</sup>Bi) are commercially available and show high reproducibility, they could serve as quantitative (single-point) analytical standards (once characterized accordingly). This use would increase their analytical value not only as mere drift correctors but also as calibrants that are present within the sample (matrix-matched). Such a strategy is aligned with recently proposed particle-based calibration approaches in SP/SC–ICP–MS, which exploit transient events of the same nature as the analyte to avoid transport-efficiency-related uncertainties. (<a href="javascript:;">29</a>) In this way, the estimation of parameters like transport efficiencies of the ionic standards is eliminated, reducing the associated uncertainties. Moreover, since the beads are routinely added to all samples in CyTOF, any raw data file could be reprocessed at any time to extract any quantitative information without any additional measurements.</p></div><div><p>Despite their routine use for signal normalization, CyTOF calibration beads have not been systematically explored as quantitative standards for single-cell elemental analyses. Their use for quantification implies several analytical challenges, including the accurate characterization of their elemental content, the translation of bead-derived responses into cellular elemental amounts, and the extension of the calibration strategy to isotopes that are not present in the beads. Addressing these challenges is essential before calibration beads can be used as reliable quantitative reference.</p></div><div><p>An interesting additional feature of plasma-based techniques is their relatively uniform sensitivity across the entire mass range. It has been described that the observed instrumental response in most ICP–MS can be fitted to a simple equation as a function of the <i>m</i>/<i>z</i> of the isotope to be measured for the elements with similar ionization in the plasma, such as the lanthanides. (<a href="javascript:;">30, 31</a>) If the transient signals of the multielemental beads are used to obtain the instrumental responses and these are empirically modeled across the monitored <i>m</i>/<i>z</i> range, a practical route toward multielemental quantification strategy is obtained. This would represent a quantification workflow for multiplex single-cell elemental analysis that repurposes multielement CyTOF calibration beads as generic standards. Such an approach seeks to address the limitations in calibration procedures and, ultimately, to enhance the quantitative applications of high-dimensional single-cell MS that can be applied not only to CyTOF-based analysis but could also be extended to any other SC–ICP–MS analysis using any other TOF mass analyzers.</p><h4><strong>Experimental Section</strong></h4><h5><strong>Instrumentation</strong></h5><div><p>The single-particle ICP–MS measurements were performed by using the <a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/products/1206"><strong>iCAP TQ triple quadrupole ICP–MS system</strong></a> from Thermo Fisher Scientific (Bremen, Germany). All measurements were done using the standard configuration for sample introduction, including the Micro-Mist nebulizer at a sample flow rate of 0.4 mL min<sup>–1</sup> and a cyclonic spray chamber. The sample introduction setup was used together with a T<strong>eledyne Cetac ASX-560 autosampler.</strong> SP-ICP-MS characterizacion of the lanthanide-loaded polystyrene beads was carried out setting a dwell time of 5 ms. Daily optimization of ICP–MS was performed to enhance signal sensitivity, ensuring that the generation of oxide ions and doubly charged species remained below 3% and 5%, respectively.</p></div><div><p>The CyTOF experiments were conducted in a <strong>CyTOF XT</strong> (Standard BioTools, San Francisco, CA, USA). This instrument is an ICP–MS that operates TOF mass analyzer with a shortened mass coverage from <i>m</i>/<i>z</i> 75 to 209. The samples are placed in a refrigerated carousel at 4 <span>°</span>C and injected into the CyTOF with a hydraulic autosampler that is able to handle sample introduction and system washing. The autosampler automatically adds the EQ6 calibration beads (Standard BioTools) to every sample at a 1:10 dilution. After mixing, the bead-containing sample is injected at 30 μL·min<sup>–1</sup> through a pneumatic nebulizer and a spray chamber that is heated at 200 <span>°</span>C. using a constant sample flow of at 10 μL min<sup>–1</sup>. Microparticle imaging was carried out with a <strong>JEOL JEM-2100F transmission electron microscope.</strong></p><h4><strong>Results and Discussion</strong></h4><h5><strong>BiRM: An Interpolated Model for Multielement Quantification</strong></h5><p>Taking advantage of the multielemental composition of the beads uniformly distributed along the CyTOF measuring range, their molar response factors can be estimated and plotted against the <i>m</i>/<i>z</i> of each of the isotopes contained on the beads. This is possible thanks to the high ionization efficiency achievable in the plasma for the elements of the beads that is close to 100%. In that case, previous publications demonstrated that the ICP–MS molar response can be modeled using different theoretical equations. (<a href="javascript:;">30, 31</a>) Consequently, the molar responses (<i>n</i><sub>resp</sub>) for all the 8 isotopes of the 6 elements contained in the beads (typically &gt;5000 events) were calculated as in <a href="javascript:;">eq 3</a> and represented against the mass-to-charge ratio (<i>m</i>/<i>z</i>). The molar response, differently to the previously reported response factor (α<sub>i</sub>), takes into account the atomic mass of the element and isotope, the isotope abundance, and the concentration. This response was fitted empirically to polynomial functions of degree 2, 3, 4, and 5, resulting in the quartic function the one with the best correlation (<i>r</i><sup>2</sup> = 0.99) while avoiding overfitting of the data. The response factors for all the isotopes are represented in <a href="javascript:;">Figure 4</a> (every data point considered for the fitting corresponds to the average intensity obtained for a minimum of 5000 bead events and the corresponding standard deviation), together with the fitted quartic polynomial function of <a href="javascript:;">eq 4</a>. This behavior showing a mass-dependent response with a slight decrease at high <i>m</i>/<i>z</i> is also consistent with published results using ICP–TOF–MS instruments. (<a href="javascript:;">34</a>) The fourth-order polynomial was used as an empirical interpolation of the instrumental response within the calibrated mass range in our specific CyTOF instrument, without physical significance of the coefficients.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_31_22966_22976_Figure_4_Molar_response_factors_for_every_isotope_in_the_beads_b8317c3de7.jpg" alt="Anal. Chem. (2026) 98 (31): 22966–22976: Figure 4. Molar response factors for every isotope in the beads as a function of m/z and the quartic function model (dashed line) that fits such data obtained using CyTOF results. Standard deviation of each data point is also included (only distinguishable in the case of 140Ce)." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_31_22966_22976_Figure_4_Molar_response_factors_for_every_isotope_in_the_beads_b8317c3de7.jpg 245w," sizes="100vw" width="996" height="492"></p><p>Using the <i>m</i>/<i>z</i> of the isotope of interest and by interpolation in the curve, it is possible to estimate its molar response on each sample (matrix matched). Out of the obtained molar response and taking the integrated dual counts obtained for such isotope in the sample, inferring its mass in a single cell event is straightforward. <a href="javascript:;">Figure 5</a>A shows the correlation between the predicted (using <a href="javascript:;">eq 4</a>) and the experimental value (using <a href="javascript:;">eq 3</a>) for the molar responses of the isotopes contained in the beads. A good correlation can be observed (<i>R</i><sup>2</sup> = 0.99), with a slope of 0.99, suggesting an excellent ability of the model to calculate the molar sensitivity of these isotopes.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Anal_Chem_2026_98_31_22966_22976_Figure_5_A_Plot_showing_the_correlation_between_the_Bi_RM_predicted_and_the_experimental_molar_response_for_the_multielemental_beads_6acfc9378b.jpg" alt="Anal. Chem. (2026) 98 (31): 22966–22976: Figure 5. (A) Plot showing the correlation between the BiRM-predicted and the experimental molar response for the multielemental beads and (B) the correlation of 8200 individual cell events obtained by BiRM versus calibration with 175Lu standards. Error bars were omitted for clarity. Experimental uncertainties associated with the molar response factors are reported in Table 2." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Anal_Chem_2026_98_31_22966_22976_Figure_5_A_Plot_showing_the_correlation_between_the_Bi_RM_predicted_and_the_experimental_molar_response_for_the_multielemental_beads_6acfc9378b.jpg 116w," sizes="100vw" width="997" height="1336"></p><p>Although it is possible to perform the described calculations using a datasheet like from microsoft excel, Google Sheets, or LibreOffice Calc, the BiRM interpolation and quantification workflow becomes increasingly cumbersome as the number of isotopes, events and biological replicates grows. For this reason, an in-house script has been developed in R, which is provided as <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/ancham/article-supplement/5231419/pdf/ac6c02340_si_001/">Supporting Information</a>. The script, which is fully transparent and open-access, operates directly on the data matrix generated for either cell events or calibration-bead events after standard CyTOF preprocessing (see the Experimental section). By introducing the elemental information required for BiRM calculations as described in the accompanying “Readme” file, the script automatically computes the molar or mass amount of each element per cell. In addition, it generates summary statistics, diagnostic figures and histograms for rapid quality assessment. This implementation ensures reproducibility, minimizes operator-dependent variability and allows users to reprocess previously acquired data sets without any additional experimental steps. A continuously updated version of software will be made available in a public repository, where future improvements, extension and documentation will be deposited. Because the isotopes used in <a href="javascript:;">Figure 5</a>A were also employed to construct the BiRM model, an additional leave-one-out validation was performed to assess its predictive capability. In each iteration, one calibration isotope was excluded from the fitting procedure and its molar response factor was subsequently predicted using a model constructed from the remaining isotopes. The predicted values were then compared with the experimentally determined molar response factors. The leave-one-out validation yielded a mean absolute relative error (MARE) of 14.3%, compared with 8.3% for the all-in model. As expected, prediction errors increased when an isotope was excluded from the model construction. However, the obtained deviations remained within a reasonable range considering the limited number of calibration points available for model fitting.</p><h4><strong>Conclusion</strong></h4><p>This study presents a practical route to quantitative mass cytometry by repurposing the multielement calibration beads that are routinely added to CyTOF samples as in-tube quantitative standards that can be extended not only to CyTOF but also to any other TOF-based ICP–MS instruments. Two complementary strategies were proposed. First, BaQS performs single-point calibration for bead-encoded isotopes to obtain the absolute mass of lanthanide per cell. Second, the BiRM makes use of the multielement bead signature to empirically model the instrumental response across the monitored <i>m</i>/<i>z</i> window, enabling the prediction of response factors for isotopes that are not present in the beads. The results indicate that both strategies provided accurate results with no statistically significant differences with the validated external standards calibration for the quantification of bead-contained and noncontained lanthanides, being BaQS and BiRM simpler, faster, more efficient, and ready to be applied to already acquired data with no additional measurements needed.</p></div></div></div></div></div></div>

Quantitative Single-Cell Multielemental Analysis Using Metal-Loaded Microparticles: toward a Universal Quantification Workflow in Mass Cytometry

<p><strong>In the week from August 31, the following webinars await you in the field of atomic and molecular spectroscopy and spectrometry</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><h5><strong>1. Technology Networks: Modern Methods for Faster Microbial Analysis</strong></h5><ul><li>Tu, 1.9.2026 11:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/webinar/6454">Registration</a></li></ul><p>Struggling to choose the right technique for microbial testing? Learn how MALDI-TOF, FTIR, and automated DNA/RNA electrophoresis accelerate identification.</p><h5><strong>2. Agilent Technologies: ICP-MS for Hybrid Photoelectrode Characterization</strong></h5><ul><li>Tu, 1.9.2026 21:30 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/webinar/6411">Registration</a></li></ul><p>Quantify catalyst loading on hybrid photoelectrodes and discover how the Agilent 7850 ICP-MS supports solar fuel research.</p><h5><strong>3. SciY/Mestrelab Research: From Legacy Workflows to Paperless Labs: Track Every Sample, Process, and Decision</strong></h5><ul><li>Th, 3.9.2026 17:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/webinar/6425">Registration</a></li></ul><p>Transform your lab from paper to digital. Learn how WebLab and LIMS workflows automate sample tracking and support laboratory compliance.</p><h5><strong>4. Agilent Technologies: Learn to Select and Apply the Proper Internal Standard in ICP-OES</strong></h5><ul><li>Th, 3.9.2026 20:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/webinar/6412">Registration</a></li></ul><p>Master the use of internal standards in ICP-OES and learn how to select suitable standards to correct matrix effects and signal drift.</p>

Webinars LabRulezICPMS Week 36/2026

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Mettler-Toledo

Agilent Technologies

SciY/Mestrelab Research

Waters Corporation

<header><h4><strong>Discover Useful Applications for Characterizing These Unique Materials</strong></h4></header><main><div><div><h5><strong>Program</strong></h5><ul><li>Introduction to nanomaterials</li><li>Basic properties and uses</li><li>Relevant thermal analysis techniques</li><li>Industries and suitable investigations</li><li>Application examples for industry and research (DSC, Flash DSC, TGA, and DMA)</li><li>Interactive Q&amp;A session</li></ul></div></div><div><div><div><p>Nanomaterials exhibit unique and diverse properties that enable a wide range of innovative applications. Their unique properties enhance catalysis, improve mechanical strength, and can even provide antibacterial effects in clothing. Their nanoscale size facilitates nucleation and also influences magnetic behavior.</p><p>Understanding the behavior of nanomaterials is crucial for harnessing their unique properties. This knowledge enables their use in advanced materials and innovative technological applications.</p><p><strong>Join our live webinar to explore how thermal analysis techniques can reveal the unique properties of nanomaterials.</strong></p><p>Be sure to prepare your questions for the live Q&amp;A with our experts!</p><h4><strong>Thermal Analysis Techniques for Characterizing Nanomaterials</strong></h4><ul><li><strong>DSC and Flash DSC</strong> are important techniques used to determine the glass transition, melting, crystallization behavior, reaction enthalpies and kinetics, and the influence of nanoparticle fillers.</li><li><strong>TGA</strong> is used to investigate stability, decomposition behavior and water sorption of nanomaterials.</li><li><strong>DMA</strong> is useful for characterizing the influence of nanoparticles on the mechanical behavior of viscoelastic materials as a function of time, temperature, and frequency of an oscillating stress.</li></ul><p>Don't miss the chance to deepen your understanding of thermal analysis techniques for characterizing these unique materials. Reserve your spot today!</p><h4><strong>Properties and Uses of Nanomaterials</strong></h4><p>The unique properties of nanomaterials enable diverse applications. For example, due to their high surface area, inefficient or unfavorable chemical reactions can often be improved by nanoparticle <strong>catalysts</strong>. When integrated into bulk materials, nanoparticles can <strong>tailor mechanical properties</strong> for advanced performance. Silver nanoparticles impart <strong>antibacterial qualities to clothing</strong>, preventing odors by eliminating bacteria. Additionally, their nanoscale size facilitates <strong>nucleation</strong>, aiding crystallization of larger molecules that would otherwise have difficulty crystallizing on their own.</p><p>Other uses of nanomaterials include structures such as <strong>silica gels </strong>and <strong>molecular sieves</strong> that have functional geometries on a nanoscale. Magnetic behavior can also vary with nanoparticle size, influencing <strong>magnetization dynamics</strong>.</p><p>These fascinating characteristics make nanomaterials pivotal in cutting-edge technology and materials science.&nbsp;</p></div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><div style="max-width:1px;width:100%;" id="mediaContainerWrapper_2110920040"><div style="height:1px;width:1px;" data-external-url="" id="mediaContainer_2110920040" data-advanced-option="false" data-width="1" data-height="1" data-video-id="">&nbsp;</div></div></div></div></div></div></main><div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><blockquote><div><strong>Presenter: </strong>Nicolas Fedelich</div><p>With a background in chemical engineering, Nicolas joined METTLER TOLEDO in 2009 as an application specialist for thermal analysis. Before that, he gained expertise in different laboratories implementing, developing, and validating analytical methods in both the pharmaceutical and environmental fields. Nicolas also worked for three years in the field carrying out on-site customer training and providing expert thermal analysis application support. In his present position, Nicolas expertly uses, teaches, and supports DSC, TGA, TMA, and DMA instruments at the METTLER TOLEDO head office in Switzerland.</p></blockquote></div></div></div>

Mettler Toledo: Thermal Analysis of Nanomaterials

Thermal Analysis of Nanomaterials

Join our live webinar to explore how thermal analysis techniques can reveal the unique properties of nanomaterials.

<header><h4><strong>A Guide to Choosing the Optimal Crucible for Your Experiment</strong></h4></header><main><div><div><h5><strong>Program</strong></h5><ul><li>Introduction to thermal analysis crucibles</li><li>DSC crucibles and application examples</li><li>TGA crucibles and application examples</li><li>Tips and hints for selecting the right crucible</li><li>Interactive Q&amp;A session</li></ul></div></div><div><div><div><p>Selecting the right crucible for your application can be a complex process, given the wide range of products available. Making the right choice, however, is essential for obtaining accurate results and protecting your thermal analysis module.</p><p>Using several practical examples for differential scanning calorimetry (<strong>DSC</strong>) and thermogravimetric analysis (<strong>TGA</strong>), this webinar helps you navigate through the many different choices, giving you confidence in your results.</p><p>After the presentation, you will have the opportunity to join the live Q&amp;A session with our experienced METTLER TOLEDO application specialists. &nbsp;</p><p>Want to learn more? Register for our webinar today!</p><h4><strong>Why Using the Right Crucible Is Essential</strong></h4><p>Often, the difference between an accurate and a flawed result has nothing to do with the measuring device, but rather the type of crucible used. For example:</p><ul><li>Crucible material, size, quality, and lids must be carefully selected, according to the application.</li><li>A smooth, flat base is critical to ensure perfect contact with the sample and optimal heat transfer.</li></ul><p>Join our live webinar and discover useful tips and hints on how to select the correct crucible for different types of DSC and TGA applications</p><p><strong>Don’t forget to prepare your questions for the live Q&amp;A with our experts!</strong></p></div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><div style="max-width:1px;width:100%;" id="mediaContainerWrapper_2110920040"><div style="height:1px;width:1px;" data-external-url="" id="mediaContainer_2110920040" data-advanced-option="false" data-width="1" data-height="1" data-video-id="">&nbsp;</div></div></div></div></div></div></main><div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><blockquote><div><strong>Presenter: </strong>Angela Hammer (Dr. sc. nat. ETH)</div><p>Dr. Angela Hammer received a Ph.D. in Analytical Chemistry (development of immobilized components for the use in ion-selective electrodes based on polyurethane membranes) from the Institute of Organic Chemistry at the Swiss Federal Institute of Technology in Zürich, Switzerland. She then joined Sika Technology AG in Zurich, Switzerland, as an analytical chemist. In 2007, she joined METTLER TOLEDO and has worked there since as an application specialist for Thermal Analysis. In her present position, she uses, teaches, and supports DSC, TGA, TMA, and DMA instruments for the METTLER TOLEDO’s Materials Characterization Group located at the head office in Switzerland.</p></blockquote></div></div></div>

Mettler Toledo: Crucible Selection for Thermal Analysis

Crucible Selection for Thermal Analysis

Join our live webinar and discover useful tips and hints on how to select the correct crucible for different types of DSC and TGA applications

<header><h4><strong>Useful Techniques for Identification and Characterization</strong></h4></header><main><div><div><h5><strong>Program</strong></h5><ul><li>What are thermosets? Basic properties and formation</li><li>Thermal analysis techniques for studying thermosets</li><li>Application examples using DSC, TGA, TMA, and DMA</li><li>Which technique should be used in your analysis?</li><li>Interactive Q&amp;A session</li></ul></div></div><div><div><div><p>A thermoset is a polymer that undergoes a particular chemical reaction, known as curing, to form a permanent, heavily cross-linked structure. The material cannot be melted or remolded to form a new shape, even at high temperatures. Thermosets are typically rigid and insoluble, with high mechanical strength and temperature stability. Examples include epoxy resins, phenolic resins, polyesters, and polyurethanes.</p><p>Due to their highly temperature-dependent physical behavior, thermal analysis is an ideal set of techniques for identifying and characterizing these materials.</p><p>This webinar discusses the most important thermal properties of thermosets and describes useful thermal analysis techniques used to analyze them.</p><p><strong>Register now to secure your spot and join the live Q&amp;A!</strong></p><h4><strong>How to Characterize Thermosets</strong></h4><p>Different thermal techniques can be used to determine the key properties of these materials:</p><ul><li><strong>DSC:</strong> Useful for determining glass transition, melting, reaction enthalpies, curing and thermal stability.</li><li><strong>TGA:</strong> Mainly used for composition analysis, thermal stability, decomposition, evaporation, and desorption behavior.</li><li><strong>TMA: </strong>Typically used to study mechanical behavior such as expansion, shrinkage, softening, plus glass transition.</li><li><strong>DMA: </strong>Best for studying viscoelastic behavior, glass transition, and frequency-dependent effects.</li></ul><h4><strong>What is a Typical Analysis of a Thermoset?</strong></h4><p>A typical and important analysis of a thermoset is the characterization of epoxy resin materials. In this case, determining the glass transition temperature (Tg) and investigating the curing reaction are highly important. This information can be used in manufacturing, for example testing the process conditions required to properly cure thermosets. It can also be used in quality control, to check the expected Tg of a known material.&nbsp;</p></div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><div style="max-width:1px;width:100%;" id="mediaContainerWrapper_2110920040"><div style="height:1px;width:1px;" data-external-url="" id="mediaContainer_2110920040" data-advanced-option="false" data-width="1" data-height="1" data-video-id="">&nbsp;</div></div></div></div></div></div></main><div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><blockquote><div><strong>Presenter: </strong>Dr. Teresa Dennenwaldt</div><p>Dr. Teresa Dennenwaldt obtained her PhD in chemistry in 2013 and completed a postdoc at the Ecole Polytechnique Fédérale de Lausanne, Switzerland in the field of electron microscopy and spectroscopy. In 2018, she joined METTLER TOLEDO as an application specialist for Thermal Analysis. In her current position, she expertly uses, teaches, and supports DSC, TGA, TMA, and DMA instruments at the METTLER TOLEDO head office in Switzerland.</p></blockquote></div></div></div>

Mettler Toledo: Thermal Analysis of Thermoset Materials

Thermal Analysis of Thermoset Materials

This webinar discusses the most important thermal properties of thermosets and describes useful thermal analysis techniques used to analyze them.

<header><h4><strong>Learn Basic DSC Principles and Find Useful Applications for Your Workplace</strong></h4></header><main><div><div><h5><strong>Program</strong></h5><ul><li>Basic principles of DSC with an explanation of power compensation and heat flux modes</li><li>Important components of the DSC measurement cell, the innovative sensor, and modules for specialized applications</li><li>Measurement parameters such as the temperature program and choice of atmosphere</li><li>Why you should use DSC for your analysis</li><li>Application examples for different industries</li><li>Live Q&amp;A session</li></ul></div></div><div><div><div><p><strong>Differential Scanning Calorimetry (DSC)</strong> is used to study the behavior of materials as they respond to a defined temperature program. The technique measures the heat, in mW, absorbed or released by a sample as it is heated, cooled, or held at a constant temperature. Measurement results are presented in the form of a curve, from which the glass transition, crystallization, melting, and many other thermal properties can be determined.</p><p>The DSC technique has applications in a wide range of industries. For example, checking the “fingerprint” of a measurement curve is a common application for quality control purposes. Other applications include investigating the influence of additives or different processing methods on a substance.</p><p>Join our webinar on DSC to gain knowledge and get the opportunity to ask our experts your questions!</p></div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><div style="max-width:1px;width:100%;" id="mediaContainerWrapper_2110920040"><div style="height:1px;width:1px;" data-external-url="" id="mediaContainer_2110920040" data-advanced-option="false" data-width="1" data-height="1" data-video-id="">&nbsp;</div></div></div></div></div></div></main><div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><blockquote><div><strong>Presenter: </strong>Dr. Teresa Dennenwaldt</div><p>Dr. Teresa Dennenwaldt obtained her PhD in chemistry in 2013 and completed a postdoc at the Ecole Polytechnique Fédérale de Lausanne, Switzerland in the field of electron microscopy and spectroscopy. In 2018, she joined METTLER TOLEDO as an application specialist for Thermal Analysis. In her current position, she expertly uses, teaches, and supports DSC, TGA, TMA, and DMA instruments at the METTLER TOLEDO head office in Switzerland.</p></blockquote></div></div></div>

Mettler Toledo: Differential Scanning Calorimetry

Differential Scanning Calorimetry

Join our webinar on DSC to gain knowledge and get the opportunity to ask our experts your questions!

<header><h4><strong>Practical Applications and Tips to Determine the Purity of a Substance</strong></h4></header><main><div><div><h5><strong>Program</strong></h5><ul><li>What does purity mean and how does it impact your products?</li><li>The basics of DSC and the van’t Hoff law for purity analysis</li><li>Advantages of DSC compared to other techniques</li><li>Application examples – real-world purity determinations</li><li>Interactive Q&amp;A with our experts</li></ul></div></div><div><div><div><p>The purity of ingredients, especially in pharmaceuticals and food products, is a critical quality attribute. High impurity levels can affect product efficacy, cause unexpected reactions, or even generate harmful compounds. Therefore, accurate purity determination is essential for the pharmaceutical, food, chemical, and plastics industries.</p><p>In this webinar, we will explain why differential scanning calorimetry (DSC) is a reliable technique for assessing the purity of organic substances, based on the thermodynamics of eutectic systems.</p><p><strong>Join us to enhance your knowledge, ask us your questions, and discover practical applications for your industry!</strong></p><h4><strong>What You Will Learn from This Webinar</strong></h4><p>In this session, you will learn how DSC is used to determine the purity of organic substances based on the <strong>thermodynamics of a eutectic system</strong>. We explain how the purity of a substance can be determined from a single DSC measurement using the <strong>van’t Hoff equation</strong>. Importantly, DSC purity measurements are rapid and easy to perform.</p><p>This versatile technique can be used across different industries and workplaces, including research and development, industrial synthesis, and quality control. Typical determinations by DSC include:</p><ul><li>Purity of ibuprofen</li><li>Purity of p-hydroxybenzoic acid (PHBA)</li><li>Determination of eutectic impurities such as benzoic acid in dimethyl terephthalate (DMT)</li></ul><p>Register for our upcoming live webinar to learn more about using DSC for purity determination. The webinar will conclude with a <strong>live Q&amp;A session</strong>, so get your questions ready!</p></div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><div style="max-width:1px;width:100%;" id="mediaContainerWrapper_2110920040"><div style="height:1px;width:1px;" data-external-url="" id="mediaContainer_2110920040" data-advanced-option="false" data-width="1" data-height="1" data-video-id="">&nbsp;</div></div></div></div></div></div></main><div><div><div data-advanced-option="false" data-has-preview-image="false" data-video-id="" data-component-id="2110920040"><blockquote><div><strong>Presenter: </strong>Nicolas Fedelich</div><p>With a background in chemical engineering, Nicolas joined METTLER TOLEDO in 2009 as an application specialist for thermal analysis. Before that, he gained expertise in different laboratories implementing, developing, and validating analytical methods in both the pharmaceutical and environmental fields. Nicolas also worked for three years in the field carrying out on-site customer training and providing expert thermal analysis application support. In his present position, Nicolas expertly uses, teaches, and supports DSC, TGA, TMA, and DMA instruments at the METTLER TOLEDO head office in Switzerland.</p></blockquote></div></div></div>

Mettler Toledo: Purity Determination by Differential Scanning Calorimetry (DSC)

Purity Determination by Differential Scanning Calorimetry (DSC)

In this webinar, we will explain why DSC is  reliable technique for assessing purity of organic substances, based on thermodynamics of eutectic systems.

Purity Determination by Differential Scanning Calorimetry

<p><strong>This webinar is co-hosted by SciY (a Bruker company) and Novalix, who have jointly developed and will deliver the content of the session.</strong></p><p><strong>“Confused” (or perhaps overwhelmed) when hearing semantics, ontologies, schema, knowledge graphs and digital twins? This webinar is different. As experimental scientists, Julien Marin (Novalix) and Anna Codina (SciY) will focus on how automation and AI-powered experimentation are applied in day-to-day experimental settings, from discovery to manufacturing.</strong></p><p>Through concrete examples, we will show how labs are moving beyond isolated automation toward connected, end‑to‑end workflows: integrating data directly from instruments, enriching it with scientific context, applying automated analysis, and using AI to guide the next experimental step.</p><p>We will walk through practical scenarios such as reaction screening, structure verification, and closed loop experimentation, as well as their extension into AI piloted self-contained distributed manufacturing. The emphasis is not on theory, but on what works in practice: what has been built, what has been tested, and what delivers value today.</p><p>Attendees will come away with a clear understanding of how to move from fragmented tools and manual workflows to connected experimentation systems where data, automation, and AI are combined to accelerate decisions.</p><h4><strong>Learning Points</strong></h4><ul><li>What real workflow automation looks like beyond concept diagrams</li><li>How to connect instruments, data, and systems into end-to-end experimental workflows</li><li>How experimental data is captured, structured, and reused to enable automation and AI</li><li>How closed loop experimentation works in practice</li><li>How AI can move from post data analysis to actively guiding experiments and processes</li><li>How these approaches extend from R&amp;D into process optimisation and continuous manufacturing</li></ul><h4><strong>Who should attend</strong></h4><p>This webinar is ideal for professionals who want to move from concepts to real implementation:</p><ul><li>Scientists and lab leads working with automation or high throughput experimentation</li><li>R&amp;D and digital lab leaders looking to turn strategy into execution</li><li>Automation, robotics, and workflow engineering teams</li><li>Data, informatics, and AI teams supporting experimental workflows</li><li>Process development, PAT, and manufacturing innovation teams</li><li>CRO/CDMO leaders interested in scalable, connected experimental platforms</li></ul><blockquote><p><strong>Presenter:</strong> Julien Marin, PhD (Chief Operating Officer, Novalix)</p><p>Julien Marin is Senior Vice President and Chief Operating Officer at Novalix. He joined the company in 2006, and, over two decades, has held progressive leadership roles, including Head of Synthetic Chemistry, Business Unit Director for Chemistry, and Director of Research Services.</p><p>Throughout the first part of his career, Julien oversaw collaborations in research services, primarily in drug discovery, within the pharmaceutical sector, but also in agrochemicals, cosmetics, and fine chemicals. He has led multidisciplinary R&amp;D teams in Belgium, France, and Spain, deployed new services, and played a key role in talent development. Currently, Julien is contributing to developing the Novalix strategic roadmap and ensuring its deployment and implementation across the company.</p><p>Julien holds a PhD in Chemistry from Strasbourg University and a Master’s degree in Strategic Business Unit Management from HEC Paris. He completed postdoctoral training with S. Hanessian at the University of Montreal, where he worked on various projects in asymmetric synthesis and medicinal chemistry, including a drug discovery program with a pharmaceutical company.</p></blockquote><blockquote><p><strong>Presenter:</strong> Anna Codina, Ph.D. (Senior Director Strategy and Business Development, SciY)</p><p>Anna Codina is Senior Director of Strategy and Business Development at SciY, where she focuses on enabling data-driven orchestration across the pharmaceutical value chain. With a background in experimental science, analytical development, and digital innovation, she works at the intersection of data, automation, and AI to accelerate scientific workflows and decision-making.</p><p>Anna holds a Ph.D. in protein NMR from the University of Barcelona and completed postdoctoral research at the MRC Laboratory of Molecular Biology in Cambridge. She spent seven years in Analytical R&amp;D at Pfizer, specializing in reaction monitoring, impurity characterization, and regulatory submissions, and was recognized with a Pfizer Worldwide Achievement Award for implementing NMR-based reaction monitoring in an open-access environment.</p><p>Since joining Bruker, Anna has held multiple leadership roles across applications, product management, and biopharma business development and market management. In her current role at SciY, she drives strategy for vendor-agnostic data platforms and digital solutions that connect instruments, robotics, and enterprise systems enabling orchestration, AI-powered experimentation and scalable workflows across R&amp;D, CROs/CDMOs, and manufacturing.</p></blockquote>

SciY: No More Boxes on Slides. Examples of Workflow Orchestration and Their Impact from R&D to Production on Demand

No More Boxes on Slides. Examples of Workflow Orchestration and Their Impact from R&D to Production on Demand

Learn how SciY and Novalix apply AI-powered automation to experimental workflows. Move from isolated tools to connected, closed-loop R&D systems

Connected Experimentation: Lab Automation and AI in Practice

<p><strong>The Indian pharmaceutical industry is constantly seeking faster, more efficient ways to ensure product quality while reducing testing time and operational costs. Traditional methods such as HPLC are highly effective but can be time-consuming and require extensive sample preparation.</strong></p><p>Join this webinar to discover how the Agilent TRS100 Quantitative Pharmaceutical Analysis System uses Transmission Raman Spectroscopy to provide rapid, non-destructive analysis of intact tablets and capsules. Learn how TRS100 enables fast content uniformity testing, assay, identification, and solid-state analysis with minimal sample handling, helping laboratories improve throughput and accelerate decision-making.</p><h4><strong>Why Attend?</strong></h4><ul><li>Learn how to perform rapid content uniformity testing on intact tablets and capsules.</li><li>Reduce analysis time and eliminate sample preparation.</li><li>Increase laboratory productivity while reducing solvent and consumable use.</li><li>Explore applications in assay, identification, polymorph, and crystallinity analysis.</li><li>Understand how TRS complements existing HPLC workflows in pharmaceutical QC.</li></ul><h4><strong>Who Should Attend?</strong></h4><ul><li>QC and QA Managers</li><li>Analytical and Pharmaceutical Scientists</li><li>Formulation and R&amp;D Scientists</li><li>Manufacturing and Process Development Teams</li><li>Regulatory and Compliance Professionals</li></ul><h4><strong>What You Will Learn</strong></h4><ul><li>Fundamentals of Transmission Raman Spectroscopy</li><li>How the Agilent TRS100 performs whole-tablet analysis</li><li>Applications in content uniformity and solid-state characterization</li><li>Benefits of implementing rapid, non-destructive testing in pharmaceutical laboratories</li></ul><p>Join us to see how the Agilent TRS100 is helping pharmaceutical laboratories in India accelerate quality control while maintaining confidence in analytical results.</p><blockquote><p><strong>Speaker:</strong> Sounik Saha (Dr., Dr. Reddy’s Laboratories, India)</p><p>Dr. Sounik Saha, PhD, is a Material Science Expert and analytical R&amp;D leader at Dr. Reddy’s Laboratories, India with extensive experience in advanced material characterization.</p><p>He completed his PhD from the Indian Institute of Science, Bangalore in 2011, followed by postdoctoral research at internationally renowned institutions including UT Southwestern Medical Center, Dallas, USA, and Mayo Clinic, Rochester, USA. He joined Dr. Reddy’s Laboratories in 2015 as part of the Advanced Characterization Technology Laboratory, where he has contributed significantly to strengthening advanced analytical capabilities for complex pharmaceutical product development. He led the Analytical Material Sciences Team at Novartis, India from 2021 to 2025 before joining back at Dr. Reddy’s Laboratories.</p><p>Dr. Saha specializes in state-of-the-art spectroscopic and microscopic characterization techniques and plays a key role in designing robust analytical strategies for complex generic product development. He has been instrumental in implementing Near-Infrared Spectroscopy and Transmission Raman Spectroscopy-based PAT initiatives across R&amp;D and manufacturing at Dr. Reddy’s Laboratories, contributing to successful regulatory filings and approvals for multiple high-value oral solid dosage products.</p><p>His work effectively bridges advanced materials science, analytical innovation, regulatory expectations, and practical product development outcomes.</p><p>Title of talk “Non-Destructive Analytical Technologies as Alternatives to Conventional approaches: Regulatory Expectations and Practical Insights”</p></blockquote><blockquote><p><strong>Speaker:</strong> Ms. Vijaya Jyothi (Product Specialist - Spectroscopy, Agilent Technologies India Pvt. Ltd.)</p><p>Vijaya Jyothi is a seasoned product specialist at Agilent Technologies. She manages the spectroscopy division, having extensive expertise in spectroscopy applications across diverse industries, offering deep insights and solutions tailored to varied analytical needs.</p></blockquote>

Agilent Technologies: Fast, Non-Destructive Pharmaceutical Analysis with the Agilent TRS100

Fast, Non-Destructive Pharmaceutical Analysis with the Agilent TRS100

Optimize pharmaceutical QC with the Agilent TRS100. Replace tedious sample prep with rapid, non-destructive analysis of whole tablets and capsules

Rapid Non-Destructive Pharma Analysis: Agilent TRS100

<p><strong>Laboratories are under growing pressure to handle increasing volumes of samples and data while operating under tighter regulatory inspection, all without compromising turnaround times or traceability. In this context, many organizations attempt to extend existing workflows and legacy tools, which can introduce inefficiencies, increase manual effort, and create compliance risks. At the same time, it is not always clear which digital solutions are best suited to address these challenges.</strong></p><p>This presentation illustrates how modern digital laboratory environments streamline routine activities by minimizing manual tasks and embedding compliance directly into everyday workflows. Drawing on a real-world use case, we show how automated capture of data from multiple sample measurements at the point of execution enables a continuous, sample-centric workflow.</p><p>By removing manual interventions and paper-based processes, laboratories can improve efficiency and visibility, support faster and more reliable decision-making while remaining responsive to evolving customer demands.</p><h4><strong>Learning Points</strong></h4><ul><li>The role of different systems (LIMS, SDMS, ELN) within the digital lab landscape and how they differ from each other's</li><li>How WebLab manages laboratory operations from a sample perspective, enabling you to track every sample, stage, and next action across workflows</li><li>How automated data capture from connected instruments helps reduce errors, lower contamination risks, and accelerate sample processing</li><li>You will see, through a real-life example, how integrated digital workflows improve data quality, accelerate reporting, and increase operational efficiency</li></ul><h4><strong>Who should attend</strong></h4><p>Professionals working in small to mid‑sized laboratories, including:</p><ul><li>Directors and Managers of Analytical, QC, or Contract Labs</li><li>Lab Operations and QA/QC Leaders</li><li>Digitalization and IT at organizations transitioning from paper, Excel, or legacy systems to LIMS</li></ul><blockquote><p><strong>Presenter:</strong> Peter Bellstedt, PhD (Director of Business Development and Product Manager at SciY)</p><p>Peter studied Biochemistry at the University of Jena before completing a PhD on the structural characterization of a DNA repair protein using solution and solid-state NMR. He was then appointed as the head of the NMR Spectroscopy Platform in Jena, Germany, where he pioneered the implementation of modern, highly efficient data-driven workflows. After five years, he moved to the University of Zurich, Switzerland, as a principal investigator, where his lab focused on structure-based drug discovery. This year, he brought his wealth of experience to the LOGS by SciY team, focusing on efficient workflow solutions for research labs and facilities on a global scale.</p></blockquote>

SciY: From Legacy Workflows to Paperless Labs: Track Every Sample, Process, and Decision

From Legacy Workflows to Paperless Labs: Track Every Sample, Process, and Decision

Transition from paper to a paperless lab. Discover how WebLab, LIMS, and automated data capture streamline sample tracking and boost compliance

Paperless Labs & Sample Tracking: Digital LIMS Workflows

<p><strong>The challenge of developing and maintaining robust chemometric models for use within Process Analytical Technology (PAT) deployment remains a significant barrier to implementation. This webinar explores how Iterative Optimization Technology (IOT) is advancing the principles of lean chemometrics by reducing the calibration burden associated with PAT deployment. Case studies will demonstrate how these methods enable faster model deployment, improved lifecycle management, and greater operational efficiency without compromising product quality or process understanding. Attendees will gain insights into how innovative chemometric strategies can accelerate PAT adoption while supporting the industry's drive towards agile, data-driven manufacturing.</strong></p><h4><strong>Learning Points</strong></h4><ul><li>You will learn how lean chemometrics reduces model complexity and data requirements</li><li>Discover how to simplify model deployment and lifecycle management</li><li>Explore how to accelerate PAT adoption while maintaining process understanding and quality</li></ul><h4><strong>Who should attend</strong></h4><ul><li>Process development and MSAT teams scaling processes to manufacturing</li><li>PAT scientists and analytical experts developing chemometric models</li><li>Lab managers driving efficient and scalable PAT implementation</li><li>Development and manufacturing and digitalization leaders advancing data-driven operations</li></ul><blockquote><p><strong>Presenter:</strong> Jonique Samuels (Scientific Advisor for Innovations, SciY)</p><p>Jonique Samuels is a Scientific Advisor for Innovations at SciY where she leads research and development projects on new, novel functionality for synTQ, the orchestration and real-time process-control platform that enables PAT and advanced, quality-centric control strategies. Currently, Jonique's focus is on supporting sustainability initiatives with customers, which includes investigating and developing lean chemometrics methods.&nbsp;</p></blockquote><blockquote><p><strong>Presenter: </strong>Anna Codina, Ph.D. ( Senior Director Strategy and Business Development, SciY)</p><p>Anna Codina is Senior Director of Strategy and Business Development at SciY, where she focuses on enabling data-driven orchestration across the pharmaceutical value chain. With a background in experimental science, analytical development, and digital innovation, she works at the intersection of data, automation, and AI to accelerate scientific workflows and decision-making.</p><p>Anna holds a Ph.D. in protein NMR from the University of Barcelona and completed postdoctoral research at the MRC Laboratory of Molecular Biology in Cambridge. She spent seven years in Analytical R&amp;D at Pfizer, specializing in reaction monitoring, impurity characterization, and regulatory submissions, and was recognized with a Pfizer Worldwide Achievement Award for implementing NMR-based reaction monitoring in an open-access environment.</p><p>Since joining Bruker, Anna has held multiple leadership roles across applications, product management, and biopharma business development and market management. In her current role at SciY, she drives strategy for vendor-agnostic data platforms and digital solutions that connect instruments, robotics, and enterprise systems enabling orchestration, AI-powered experimentation and scalable workflows across R&amp;D, CROs/CDMOs, and manufacturing.</p></blockquote>

SciY: Advancing Lean Chemometrics: Iterative Optimization Technology as a Process Analytical Technology Tool for Reducing Calibration Burden

Advancing Lean Chemometrics: Iterative Optimization Technology as a Process Analytical Technology Tool for Reducing Calibration Burden

Reduce PAT calibration burden with Lean Chemometrics and IOT. Learn to accelerate model deployment and simplify lifecycle management in this webinar

Lean Chemometrics & IOT: Reducing PAT Calibration Burden

<h4><strong>Build Confidence in Your Laboratory Data</strong></h4><p><strong>Reliable laboratory data doesn't happen by chance, it is the result of a quality assurance program designed to detect risk, drive consistency, and support continuous improvement.</strong></p><p><strong>In this webinar, we'll explore the four foundational elements of an effective QA program: method development, analyst training, ongoing performance monitoring, and corrective action. Learn how laboratories can use precision, accuracy, control charting, trending analysis, and root cause investigations to identify issues before they impact data quality.</strong></p><p>We'll also discuss practical strategies for verifying method performance, demonstrating analyst competency, sustaining long-term process control, and using certified reference materials as independent tools to strengthen confidence in analytical results.</p><p>Whether you are building a new QA program or looking to improve an existing one, this session provides actionable guidance for creating a robust and sustainable framework for quality.</p><h5><strong>Key takeaways</strong></h5><ul><li>Build a more effective and sustainable laboratory QA program.</li><li>Use precision, accuracy, and control charting to improve data quality and identify issues early.</li><li>Apply root cause analysis and certified reference materials to strengthen performance and corrective actions.</li></ul><p><strong>Who should attend</strong></p><p>This webinar is designed for Quality Assurance (QA) and Quality Control (QC) managers, analytical chemists and laboratory scientists, laboratory managers and supervisors.</p><p>Don't miss it!</p><blockquote><p><strong>Speaker:&nbsp;</strong>Christy Abbas, PhD (Sr. Product Marketing Manager, Waters ERA)</p><p>Christy has been with Waters ERA for six and a half years. Her career spans roles at an instrument manufacturer, a biopharmaceutical laboratory, and a mining company. She earned her PhD in Applied Chemistry from the Colorado School of Mines.</p><p>Throughout her career, Christy has supported the nuclear, pharmaceutical, and chemical industries, as well as academia. Drawing on her background in analytical chemistry, product development, marketing, and sales, she is focused on expanding Waters ERA’s product portfolio to better meet evolving customer needs.</p></blockquote>

Foundations of a Sustainable, High-Performing QA Program

Build a sustainable QA program for your laboratory. Learn how control charting, root cause analysis, and reference materials drive data confidence

ICPMS webinars focusing on Academy/Principles - page 1