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	<title>Ondalys</title>
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	<link>https://ondalys.fr/en/</link>
	<description>Analyse de données et Machine Learning pour les données spectroscopiques, de laboratoire et de procédé</description>
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		<title>March 10, 2026 &#8211; Webinar Optimization et interpretation of ML models</title>
		<link>https://ondalys.fr/en/march-10-2026-webinar-optimization-et-interpretation-of-ml-models/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Mon, 26 Jan 2026 09:59:58 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/?p=22394</guid>

					<description><![CDATA[<p>Optimization and interpretation of Machine Learning models for spectral data We invite you to our next webinar on Machine Learning methods and the interpretation of ML<span class="excerpt-hellip"> […]</span></p>
<p>The post <a href="https://ondalys.fr/en/march-10-2026-webinar-optimization-et-interpretation-of-ml-models/">March 10, 2026 &#8211; Webinar Optimization et interpretation of ML models</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
]]></description>
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<h2 class="wp-block-heading has-text-align-center"><strong><font color="#00646F"><strong>Optimization and interpretation of <br>Machine Learning models for spectral data</strong></font></strong></h2>



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<p>We invite you to our next webinar on Machine Learning methods and the interpretation of ML models developed on spectral databases on March 10, 2026 at 4 p.m. (CET).</p>



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<h4 class="wp-block-heading has-text-align-center"><strong>Would you like to learn more about how to make your <br>Machine Learning models built on spectroscopic data more reliable?</strong>&nbsp;</h4>



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<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex">
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<p>This webinar is focusing on:</p>



<ul class="wp-block-list">
<li>Why and when use Machine Learning methods to analyze spetra</li>



<li>How optimize the model understanding using interpretability methods to avoid the black-box effect of some methods (explainable Machine Learning)</li>



<li>Use cases developed on spectral data </li>
</ul>
</div>



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<h2 class="wp-block-heading has-text-align-center">📆<strong><mark style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-black-color">March 10, 2026 </mark></strong></h2>



<h2 class="wp-block-heading has-text-align-center">🕚 <strong><mark style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-black-color">4.00pm (CET)</mark></strong></h2>



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<div class="wp-block-buttons is-horizontal is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-67e932e3 wp-block-buttons-is-layout-flex">
<div class="wp-block-button"><a class="wp-block-button__link has-background wp-element-button" href="https://events.teams.microsoft.com/event/b5f05300-17c3-4b60-b653-db9ee204fc3d@6dbd8c0e-ac29-4bd4-a81c-8c9d9079d614" style="background-color:#00646f" target="_blank" rel="noreferrer noopener"><font size="6">Registration</font></a></div>
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<h3 class="wp-block-heading">Webinar program:</h3>



<ul class="wp-block-list">
<li>Why use Machine Learning (ML) models?</li>



<li>The interest of ML models interpretability</li>



<li>Overview of ML methods</li>



<li>Principles and applications of kernel methods and neural networks</li>



<li>Overview of interpretability methods of ML models</li>



<li>Principles and applications of interpretability methods (SHAP, etc.) to spectroscopic data</li>



<li>Q&amp;A session</li>
</ul>



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<div class="wp-block-image">
<figure class="aligncenter size-large"><img fetchpriority="high" decoding="async" width="1024" height="613" src="https://ondalys.fr/wp-content/uploads/2026/01/Wbnr-ML-InterP-news-ENG-1024x613.png" alt="Webinar Optimization and interpretation of Machine Learning models for spectral data" class="wp-image-22435"/></figure>
</div>


<p><strong>Dr. Astrid Maléchaux</strong>, <strong>Data Scientist at Ondalys </strong>for several years and expert in Machine Learning and model interpretability, will present this webinar. With her, you will discover how to avoid the black box effect of some Machine Learning models on spectral data and ensure the reliability of these models.</p>



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<p>Experts in spectral calibration and in developing Machine Learning methods adapted to spectral data (NIR, MIR, Raman, &#8230;), Ondalys team supports you in analyzing your <a href="/en/data-analysis/measurement/spectral-data/" target="_blank" rel="noreferrer noopener">spectroscopic data</a> and developing <a href="/en/data-analysis/applications/spectroscopic-calibrations/" target="_blank" rel="noreferrer noopener">spectral calibrations</a>.</p>



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<p>The post <a href="https://ondalys.fr/en/march-10-2026-webinar-optimization-et-interpretation-of-ml-models/">March 10, 2026 &#8211; Webinar Optimization et interpretation of ML models</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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		<title>February 17-19, 2025 : Chimiometrie 2026 Congress in Nancy, France</title>
		<link>https://ondalys.fr/en/feb-17-19-2025-chimiometrie-2026-congress/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Thu, 25 Sep 2025 09:39:51 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/?p=21907</guid>

					<description><![CDATA[<p>This year again, Ondalys is sponsoring the 25th Chimiometrie Conference. Come and discuss with our team at this event. 2 occasions to discuss Chemometrics with our<span class="excerpt-hellip"> […]</span></p>
<p>The post <a href="https://ondalys.fr/en/feb-17-19-2025-chimiometrie-2026-congress/">February 17-19, 2025 : Chimiometrie 2026 Congress in Nancy, France</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
]]></description>
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<h2 class="wp-block-heading has-text-align-center"><font color="#00646F">This year again, Ondalys is sponsoring the 25th Chimiometrie Conference. Come and discuss with our team at this event.</font></h2>



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<p class="has-text-align-center"><font size="5">2 occasions to discuss Chemometrics with our team !</font></p>



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<p class="has-text-align-center"><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color"><strong><font size="5">February 17, 2026<br>Pre-conference courses</font></strong></mark></p>



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<p>Come and attend the course which led by <strong>Dr Sylvie Roussel</strong>, an expert in Machine Learning and Chemometrics for more than 20 years, entitled :</p>



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<h3 class="wp-block-heading has-text-align-center"><strong><font color="#010c35"><font size="5">Review of the main methods <br>of Machine Learning (ML)</font></font></strong></h3>



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<p>She will provide an overview of the different Machine learning methods that can be used for the analysis of instrumental data. She will define the difference between Machine Learning and Chemometrics. And she will present several Machine Learning methods, such as <a href="/en/scientific-resources/machine-learning-methods/#ANN" target="_blank" rel="noreferrer noopener">Artificial Neural Networks</a> (<strong>ANN</strong>), the <a href="/en/scientific-resources/machine-learning-methods/#SVM" target="_blank" rel="noreferrer noopener">Support Vector Machine</a> Method (<strong>SVM</strong>), the <a href="/en/scientific-resources/machine-learning-methods/#CART" target="_blank" rel="noreferrer noopener">Regression Trees</a> methods (Classification and Regression Tree &#8211; <strong>CART</strong>) and <a href="/en/scientific-resources/machine-learning-methods/#RF" target="_blank" rel="noreferrer noopener">Random Forests</a> (<strong>RF</strong>);</p>



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<div class="wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-16018d1d wp-block-buttons-is-layout-flex">
<div class="wp-block-button"><a class="wp-block-button__link has-background has-medium-font-size has-text-align-center has-custom-font-size wp-element-button" href="https://chemom2026.sciencesconf.org/resource/page/id/2" style="border-top-left-radius:60px;border-top-right-radius:60px;border-bottom-left-radius:60px;border-bottom-right-radius:60px;background-color:#00646f" target="_blank" rel="noreferrer noopener">Register to the<br>Chimiométrie 2026 <br>pre-conference courses</a></div>
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<p class="has-text-align-center"><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color"><strong><font size="5">February 18, 2026<br>Scientific oral </font> </strong></mark></p>



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<p><strong>Jordane Poulain</strong>, Data Scientist, will present our latest work carried out in collaboration with the L&#8217;Oréal Research and Innovation Center and Synchrotron Soleil, on the theme :</p>



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<h3 class="wp-block-heading has-text-align-center"><strong><font color="#010c35"><font size="5">Automated histological segmentation of hair follicles via hierarchical PLS-DA and FTIR hyperspectral imaging</font></font></strong></h3>



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<p>This work aims to automate the identification of the different tissues composing the hair follicle using hyperspectral imaging in order to better assess the impact of cosmetic active ingredients on follicular health. The multivariate analysis of the data, based on <a href="/en/scientific-resources/machine-learning-methods/#PLS-DA" target="_blank" rel="noreferrer noopener">hierarchical discrimination models (PLS_DA)</a>, has demonstrated its high relevance for the automatic segmentation of the different hair follicle tissues. This methodology offers a robust framework for future studies evaluating the molecular impact of cosmetic active ingredients on hair growth in each of the tissues that compose it.</p>



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<div class="wp-block-button"><a class="wp-block-button__link has-background has-medium-font-size has-text-align-center has-custom-font-size wp-element-button" href="https://ondalys.fr/wp-content/uploads/2026/01/Chimiometrie_2026-Oral-LOreal-Ondalys.pdf" style="border-top-left-radius:60px;border-top-right-radius:60px;border-bottom-left-radius:60px;border-bottom-right-radius:60px;background-color:#00646f" target="_blank" rel="noreferrer noopener">Look at <br>the abstract of <br> the presentation </a></div>
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<p>The 2026 Chimiometrie congress is organized by the <strong>École Nationale Supérieure des Industries Chimiques (<a href="https://ensic.univ-lorraine.fr/fr">ENSIC</a>)</strong> on the Grandville campus in downtown Nancy, France.</p>



<p>This annual meeting of industrial and academic scientifics interested in Chemometrics and data analytics will give our team the opportunity to share with you our expertise on the topics covered during the oral presentations:</p>



<ul class="wp-block-list">
<li><a href="/en/data-analysis/applications/spectroscopic-calibrations/" target="_blank" rel="noreferrer noopener">Spectroscopic data analysis</a>,</li>



<li><a href="/en/data-analysis/measurement/imaging/" target="_blank" rel="noreferrer noopener">Hyperspectral imaging analysis</a>,</li>



<li><a href="/en/data-analysis/measurement/doe/" target="_blank" rel="noreferrer noopener">Design of Experiments &#8211; DoE</a> </li>



<li><a href="/en/data-analysis/measurement/physico-chemical-analysis/" target="_blank" rel="noreferrer noopener">OMICS data analysis</a> (LC-MS, GC-MS, GCxGC, etc.),</li>



<li><a href="/en/data-analysis/applications/industry-4-0/" target="_blank" rel="noreferrer noopener">Process monitoring and optimisation</a></li>



<li>and many other Chemometrics methods</li>
</ul>



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<h3 class="wp-block-heading has-text-align-center"><strong>More information soon</strong></h3>
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<h4 class="wp-block-heading has-text-align-center">See more details on the <span style="text-decoration: underline;"><a href="https://chemom2026.sciencesconf.org/?forward-action=index&amp;forward-controller=index&amp;lang=en" target="_blank" rel="noreferrer noopener">Chimiometrie 2026 conference website</a></span>.</h4>
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<p>The 2026 edition of the conference will be held in Nancy on the Grandville campus of the École Nationale Supérieure des Industries Chimiques (<strong><a href="https://ensic.univ-lorraine.fr/fr">ENSIC</a></strong>).</p>
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<p>Ondalys offers data analysis services and training and distributes some of the most widely used and recognized Chemometrics software, such as <strong><a href="/en/software/#pls_toolbox">PLS_Toolbox®</a></strong> and <a href="/en/software/#pls_toolbox"><strong>SOLO®</strong></a> for Chemometrics,<strong> <a href="/en/software/#MIA">MIA Toolbox®</a> </strong>for hyperspectral image analysis from <span style="color: #00646f;">EigenVector Research Inc.</span>, and <a href="/en/software/#DoE"><strong>Design-Expert®</strong></a> software from <span style="color: #00646f;">Stat-Ease</span> for Design of Experiments.</p>
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<p><strong>The Chemometrics</strong> <strong>Art </strong></p>
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<p data-start="62" data-end="396">At the heart of data analysis lies <strong data-start="97" data-end="113">Chemometrics</strong>, a discipline that focuses on the complex relationships between different variables. In a context where data is vast and often intertwined, Chemometrics provides a powerful way to explore interactions between variables and discover those that have a significant impact on outcomes.</p>
<p data-start="398" data-end="629">Rather than examining variables individually, Chemometrics seeks to capture the dynamics of interactions. This approach offers a holistic view of the data, uncovering hidden patterns and complex correlations.</p>
<p data-start="631" data-end="897">By analyzing how variables interact with each other, Chemometrics makes it possible to identify those with the greatest influence on final results. These key variables may directly affect product quality, process performance, or other critical industrial metrics.</p>
<p data-start="899" data-end="1225">Chemometrics offers sophisticated techniques such as <a href="/en/scientific-resources/machine-learning-methods/#PCA"><strong data-start="952" data-end="990">Principal Component Analysis (PCA)</strong></a>, <strong data-start="992" data-end="1034"><a href="/en/scientific-resources/machine-learning-methods/#PLS">Partial Least Squares regression (PLS)</a>,</strong> and <a href="/en/scientific-resources/machine-learning-methods/#MachineLearning"><strong>other advanced methods</strong></a> to unravel complex interactions. These approaches provide deeper insights into relationships between variables, thereby supporting better decisions and actions.</p>
<p data-start="1227" data-end="1520">By integrating the art of Chemometrics into your industrial data analysis, raw datasets are transformed into actionable knowledge. By recognizing hidden influences and dependencies among variables, you can make informed decisions that drive your business toward efficiency and competitiveness.</p>
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<p><!-- /wp:paragraph --></p><p>The post <a href="https://ondalys.fr/en/feb-17-19-2025-chimiometrie-2026-congress/">February 17-19, 2025 : Chimiometrie 2026 Congress in Nancy, France</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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		<title>Sept 2025 &#8211; Publication : Online monitoring  of mAbs&#8217; CQAs using Raman.</title>
		<link>https://ondalys.fr/en/sept-2025-cqas-online-monitoring-using-raman/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Wed, 24 Sep 2025 09:55:21 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/?p=22037</guid>

					<description><![CDATA[<p>New scientific article! Monitoring of monoclonal antibody critical quality attributes and free amino acids in CHO bioprocesses using Raman spectroscopy and DUPLEX-based PLS modeling.&#160; Published in<span class="excerpt-hellip"> […]</span></p>
<p>The post <a href="https://ondalys.fr/en/sept-2025-cqas-online-monitoring-using-raman/">Sept 2025 &#8211; Publication : Online monitoring  of mAbs&#8217; CQAs using Raman.</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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<p></p>



<h2 class="wp-block-heading has-text-align-center"><span class="VIiyi" lang="fr"><span class="JLqJ4b ChMk0b" data-language-for-alternatives="fr" data-language-to-translate-into="en" data-phrase-index="0">New scientific article! </span></span></h2>



<h2 class="wp-block-heading has-text-align-center"><span class="VIiyi" lang="fr"><span class="JLqJ4b ChMk0b" data-language-for-alternatives="fr" data-language-to-translate-into="en" data-phrase-index="0">Monitoring of monoclonal antibody critical quality attributes and free amino acids in CHO bioprocesses using Raman spectroscopy and DUPLEX-based PLS modeling.&nbsp;</span></span></h2>



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<p>Published in <strong>Microchemical Journal</strong> in late September, this article presents work carried out on the <strong><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color">online monitoring of Critical Quality Attributes (CQAs) of monoclonal antibodies (mAbs) and free amino acids in CHO cultures using Raman spectroscopy.</mark></strong></p>



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<p>The <a href="/en/scientific-resources/machine-learning-methods/#PLS" target="_blank" rel="noreferrer noopener"><strong>PLS</strong></a> (Partial Least Square) modeling made it possible the<strong><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color"> prediction of the final quality criteria</mark></strong>, the following CQAs: :</p>



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<ul class="wp-block-list">
<li><strong>Aggregates </strong>– multimeric monoclonal antibodies which affect stability and immunogenicity.</li>



<li><strong>Fragments </strong>– degradation or cleavage products of the mAb, impacting purity and efficiency.</li>



<li><strong>Glycoforms </strong>– variations in glycosylation profile, influencing pharmacokinetics and bioactivity.</li>



<li><strong>Charged variants</strong> – isoforms resulting from post-translational modifications (e.g., deamidation, amidation, C-terminal lysine), which affect stability and therapeutic performance.</li>
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<figure class="wp-block-image size-full"><img decoding="async" width="402" height="495" src="https://ondalys.fr/wp-content/uploads/2025/11/Publication-Suivi-culture-CHO-Raman-partiel.png" alt="" class="wp-image-22024" srcset="https://ondalys.fr/wp-content/uploads/2025/11/Publication-Suivi-culture-CHO-Raman-partiel.png 402w, https://ondalys.fr/wp-content/uploads/2025/11/Publication-Suivi-culture-CHO-Raman-partiel-244x300.png 244w, https://ondalys.fr/wp-content/uploads/2025/11/Publication-Suivi-culture-CHO-Raman-partiel-61x75.png 61w" sizes="(max-width:767px) 402px, 402px" /></figure>
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<p><strong>🧪 </strong>Moreover, the developed models have also made it possible to predict <strong>free amino acids</strong> in the culture medium (dynamic nutritional profile), which allows <strong>simultaneous monitoring of cellular metabolism and product quality</strong>.</p>



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<p><strong><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color">Morandise Rubini</mark></strong> conducted this research as part of the CLIMBIN project with various researchers from the <strong>University of Tours</strong>,<strong> Indatech-Chauvin Arnoux Group</strong>, <strong>Servier Technology</strong>, and <strong>Ondalys</strong>. <mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color"><strong>Jordane Poulain</strong></mark> and <strong><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color">Sylvie Roussel</mark></strong>, co-authors of this article, contributed their expertise in Machine Learning. </p>



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<p><em>Morandise Rubini, Anaïs Berger, Thomas Saillard, Fabrice Cantais, Martin Soucé, <strong>Jordane Poulain,</strong> <strong>Sylvie Roussel</strong>, Julien Louet, Fabien Chauchard-Rios, Sylvain Arnould, Igor Chourpa. (2025). <strong>Monitoring of monoclonal antibody critical quality attributes and free amino acids in CHO bioprocesses using Raman spectroscopy and DUPLEX-based PLS modeling</strong>. Microchemical Journal 218 (2025) 115583</em></p>
<p>The post <a href="https://ondalys.fr/en/sept-2025-cqas-online-monitoring-using-raman/">Sept 2025 &#8211; Publication : Online monitoring  of mAbs&#8217; CQAs using Raman.</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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		<title>Sept. 9-12, 2025 &#8211; Colloquium Chemiometricum Mediterraneum</title>
		<link>https://ondalys.fr/en/9-to-12-september-2025-colloquium-chemiometricum-mediterraneum/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Thu, 24 Jul 2025 15:11:26 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/?p=21613</guid>

					<description><![CDATA[<p>Explainable ML: Machine learning interpretability methods applied to spectroscopic data Sylvie Roussel presents Ondalys&#8217; latest work on the interpretability of machine learning models built on NIR<span class="excerpt-hellip"> […]</span></p>
<p>The post <a href="https://ondalys.fr/en/9-to-12-september-2025-colloquium-chemiometricum-mediterraneum/">Sept. 9-12, 2025 &#8211; Colloquium Chemiometricum Mediterraneum</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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<h2 class="wp-block-heading has-text-align-center">Explainable ML: Machine learning interpretability methods <br>applied to spectroscopic data</h2>



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<p> <strong><font color="#00646F">Sylvie Roussel</font></strong> presents Ondalys&#8217; latest work on the <strong>interpretability of machine learning models built on NIR spectra</strong> within the Mediterranean Chemometrics community in Porquerolles.</p>



<p>How can the black box effect can be avoided when developing <a href="/en/scientific-resources/machine-learning-methods/#MachineLearning" target="_blank" rel="noreferrer noopener">advanced Machine Learning methods</a> such as <a href="/en/scientific-resources/machine-learning-methods/#SVM" target="_blank" rel="noreferrer noopener">Support Vector Machines</a>, <a href="/en/scientific-resources/machine-learning-methods/#ANN" target="_blank" rel="noreferrer noopener">Artificial Neural Networks</a> and <a href="/en/scientific-resources/machine-learning-methods/#Boosting" target="_blank" rel="noreferrer noopener">Boosting</a> methods?</p>



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<p>Ondalys team worked on the<strong> interpretability of ML models developed on near-infrared spectroscopic</strong> <strong>data</strong>, in other words, the &#8220;post-hoc explanation&#8221; of ML models.</p>



<p>The objective was to develop methods to: </p>



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<li>understand and interpret the spectral models, </li>



<li>avoid overfitting</li>
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<p>Several regression methods (<a href="https://ondalys.fr/en/scientific-resources/machine-learning-methods/#SVM" target="_blank" rel="noreferrer noopener">SVM</a>, <a href="https://ondalys.fr/en/scientific-resources/machine-learning-methods/#ANN" target="_blank" rel="noreferrer noopener">ANN</a>, <a href="https://ondalys.fr/en/scientific-resources/machine-learning-methods/#Boosting" target="_blank" rel="noreferrer noopener">XG-Boost</a>) were trained and compared with classical <a href="/en/scientific-resources/machine-learning-methods/#PLS" target="_blank" rel="noreferrer noopener">PLS</a> calibration models. The idea was to adapt <strong>Explainable AI</strong> (X-AI) methods to spectroscopic models to increase the reliability of predictive model results.</p>
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<p class="has-text-align-center"><font size="6"><font color="#00646F"><strong>Discover the results of this study</strong></font></font></p>



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<figure class="aligncenter size-full is-resized"><img decoding="async" width="800" height="461" src="https://ondalys.fr/wp-content/uploads/2025/07/CCM2025.png" alt="" class="wp-image-21635" style="width:700px" srcset="https://ondalys.fr/wp-content/uploads/2025/07/CCM2025.png 800w, https://ondalys.fr/wp-content/uploads/2025/07/CCM2025-300x173.png 300w, https://ondalys.fr/wp-content/uploads/2025/07/CCM2025-768x443.png 768w, https://ondalys.fr/wp-content/uploads/2025/07/CCM2025-130x75.png 130w, https://ondalys.fr/wp-content/uploads/2025/07/CCM2025-480x277.png 480w" sizes="(max-width:767px) 480px, (max-width:800px) 100vw, 800px" /></figure>
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<p>The <strong>Colloquium Chemiometricum Mediterraneum</strong> is a scientific event that discusses the latest innovations in Chemometrics, with presentations by French, Spanish, Portuguese, and Italian chemometricians in their respective own languages. The CCM is a place to intiate new international collaborations within the chemometrics community.</p>



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<p class="has-text-align-right">Learn more about CCM 2025 on the Colloquium website</p>



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<div class="wp-block-button has-custom-width wp-block-button__width-75"><a class="wp-block-button__link has-background has-text-align-center wp-element-button" href="https://ccm2025.sciencesconf.org/?lang=en" style="background-color:#00646f" target="_blank" rel="noreferrer noopener"><strong><font size="4">Colloquium Chemiometricum Mediterraneum 2025</font></strong></a></div>
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<p>The post <a href="https://ondalys.fr/en/9-to-12-september-2025-colloquium-chemiometricum-mediterraneum/">Sept. 9-12, 2025 &#8211; Colloquium Chemiometricum Mediterraneum</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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		<title>July 23, 2025 &#8211; Webinar: Implementing Online Spectroscopy</title>
		<link>https://ondalys.fr/en/july-23rd-2025-webinar-implementing-online-spectroscopy/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Wed, 02 Jul 2025 14:49:43 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/?p=21526</guid>

					<description><![CDATA[<p>Best Practices for Implementing Online Spectroscopy We are happy to announce our next webinaire jointly given with our partner, the spectrometer manufacturer Metrohm USA. In this<span class="excerpt-hellip"> […]</span></p>
<p>The post <a href="https://ondalys.fr/en/july-23rd-2025-webinar-implementing-online-spectroscopy/">July 23, 2025 &#8211; Webinar: Implementing Online Spectroscopy</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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<h2 class="wp-block-heading has-text-align-center"><strong><font color="#00646F">Best Practices for <br>Implementing Online Spectroscopy</font></strong></h2>



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<p>We are happy to announce our next webinaire jointly given with our partner, the spectrometer manufacturer <strong>Metrohm USA</strong>.</p>



<p id="block-fd6bfa28-c073-424a-a603-368b9ece4d4b">In this webinar, you will discover how to<strong> implement Online Spectroscopy techniques</strong> such as <strong>Raman</strong> and <strong>NIR </strong>to :</p>



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<li>improve process control</li>



<li>ensure consistent product quality&nbsp;</li>



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<p><strong>Elena Hagemann</strong>, Product Manager Process Spectroscopy at Metrohm USA, and <strong>Sylvie Roussel</strong>, Ondalys CEO, will present practical guidances for identifying suitable applications, defining technical requirements for robust interface design, <strong>developing reliable prediction models</strong>, and integrating spectroscopy into existing control systems, all to <strong>support confident decision-making and enhance process performance</strong>.</p>
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<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" width="338" height="406" src="https://ondalys.fr/wp-content/uploads/2025/07/elena-hagemann-metrohm-1.png" alt="Elena Hagemann, Metrohm USA" class="wp-image-21531" style="width:200px" srcset="https://ondalys.fr/wp-content/uploads/2025/07/elena-hagemann-metrohm-1.png 338w, https://ondalys.fr/wp-content/uploads/2025/07/elena-hagemann-metrohm-1-250x300.png 250w, https://ondalys.fr/wp-content/uploads/2025/07/elena-hagemann-metrohm-1-62x75.png 62w" sizes="auto, (max-width:767px) 338px, 338px" /></figure>
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<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" width="329" height="406" src="https://ondalys.fr/wp-content/uploads/2025/07/Sylvie-Roussel-Ondalys-1.png" alt="" class="wp-image-21533" style="width:202px;height:auto" srcset="https://ondalys.fr/wp-content/uploads/2025/07/Sylvie-Roussel-Ondalys-1.png 329w, https://ondalys.fr/wp-content/uploads/2025/07/Sylvie-Roussel-Ondalys-1-243x300.png 243w, https://ondalys.fr/wp-content/uploads/2025/07/Sylvie-Roussel-Ondalys-1-61x75.png 61w" sizes="auto, (max-width:767px) 329px, 329px" /></figure>
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<p id="block-524679eb-68fe-4b22-a3fd-6e74121c9c50">This webinar will focus on these Key points:</p>



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<li><strong>Implementation Strategy:</strong> Learn how to assess feasibility, avoid common pitfalls, and plan for long-term success with online spectroscopy.</li>



<li><strong>System Design &amp; Integration</strong>: Explore best practices for sampling interface design and seamless integration with DCS/PLC systems.</li>



<li><strong>Calibration &amp; Reliability</strong>: Understand how to develop robust calibration models and maintain analyzer accuracy through monitoring, diagnostics, and lifecycle support.</li>
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<h2 class="wp-block-heading has-text-align-center"><mark style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-black-color"><strong>Join us on </strong> </mark></h2>



<h2 class="wp-block-heading has-text-align-center"><strong><mark style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-black-color">July 23rd, 2025 at 1:00pm (EDT)</mark></strong></h2>
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<div class="wp-block-button"><a class="wp-block-button__link has-background wp-element-button" href="https://event.eu.on24.com/wcc/r/8000143828/DB416C1160491845C5A20B3AAE318C22?partnerref=ondalys" style="background-color:#00646f" target="_blank" rel="noreferrer noopener"><font size="6">Register now !</font></a></div>
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<p>Expert in spectral data analysis (NIR, MIR, Raman, UV), the Ondalys team supports you for all your issues of <a href="/en/data-analysis/measurement/spectral-data/" target="_blank" rel="noreferrer noopener">spectroscopic data processing</a> and <a href="/en/data-analysis/applications/spectroscopic-calibrations/" target="_blank" rel="noreferrer noopener">spectral calibration development</a>. </p>



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<p>The post <a href="https://ondalys.fr/en/july-23rd-2025-webinar-implementing-online-spectroscopy/">July 23, 2025 &#8211; Webinar: Implementing Online Spectroscopy</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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		<title>June 8-12, 2025 &#8211; NIR2025 international congress in Roma, Italy</title>
		<link>https://ondalys.fr/en/june-2025-nir2025-conference/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Wed, 26 Mar 2025 14:38:52 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/?p=21324</guid>

					<description><![CDATA[<p>Interpretability of Machine Learning methods and methodology for analyzing hyperspectral images, discover the 2 Ondalys&#8217; scientific communications at the NIR2025 conference in June 2025, in Roma.<span class="excerpt-hellip"> […]</span></p>
<p>The post <a href="https://ondalys.fr/en/june-2025-nir2025-conference/">June 8-12, 2025 &#8211; NIR2025 international congress in Roma, Italy</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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<h2 class="wp-block-heading has-text-align-center"><strong>Interpretability of Machine Learning methods</strong> and <strong>methodology for analyzing hyperspectral images</strong>, discover the 2 Ondalys&#8217; scientific communications at the NIR2025 conference in June 2025, in Roma.<br></h2>



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<p>Organized by <a href="http://www.sisnir.org" target="_blank" rel="noreferrer noopener">SISNIR </a>– Società Italiana di Spettrosocopia NIR,  the <strong>22<sup>nd</sup> International Conference on Near Infrared Spectroscopy – NIR2025</strong>, will be held from <strong>June 8<sup>th</sup></strong> to<strong>June 12<sup>th</sup> 2025</strong> in Roma, Italy.</p>



<p>Expert in <strong>Chemometrics and Machine Learning methods</strong> applied to spectral data, the ondalys team will attend this conference to discuss about spectroscopic data analysis and will present 2 communications on the following themes :</p>



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<h2 class="wp-block-heading has-text-align-center"><font size="6"><font color="#00646F">Machine Learning interpretability methods applied to calibration models developed on NIR spectroscopic data </font></font></h2>



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<p>In the past decades, Machine Learning (ML) models have become more and more complex, leading to improvements in their predictive performance. However, these models can often be described as “black boxes”, in the sense that it is very difficult to explain how results are obtained by a model from the input data. As complex Machine Learning models are increasingly used to make decisions, for instance in industrial or medical applications, there is a growing need to improve their <strong>interpretability </strong>in order to have greater confidence in their results, providing the so-called<strong> Explainable AI</strong> (Artificial Intelligence). </p>



<p>This study is focused on the i<strong>nterpretability of Machine Learning models after model calibration on near-infrared spectroscopic</strong> data, a.k.a. the “post-hoc explanation” of ML models.</p>



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<p class="has-text-align-center"><font size="5"><font color="#00646F"><strong><a href="/en/scientific-resources/machine-learning-methods/#MachineLearning" target="_blank" rel="noreferrer noopener">Learn more about the advanced Machine Learning methods</a> </strong></font></font></p>



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<figure class="aligncenter size-medium"><a href="/wp-content/uploads/2025/03/ML-interpretability-Ondalys-ICNIRS2025.pdf"><img loading="lazy" decoding="async" width="300" height="120" src="https://ondalys.fr/wp-content/uploads/2025/03/button-interpretability-of-ML-methods-300x120.png" alt="" class="wp-image-21325" srcset="https://ondalys.fr/wp-content/uploads/2025/03/button-interpretability-of-ML-methods-300x120.png 300w, https://ondalys.fr/wp-content/uploads/2025/03/button-interpretability-of-ML-methods-150x60.png 150w, https://ondalys.fr/wp-content/uploads/2025/03/button-interpretability-of-ML-methods-480x192.png 480w, https://ondalys.fr/wp-content/uploads/2025/03/button-interpretability-of-ML-methods.png 587w" sizes="auto, (max-width:767px) 300px, 300px" /></a></figure>
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<h2 class="wp-block-heading has-text-align-center"><font size="6"><font color="#00646F">Machine Learning methods for sugar quantification in grapes based on NIR Hyperspectral Imaging</font></font></h2>



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<p>Hyperspectral imaging [1] has applications in many fields, including agriculture, environment, medicine and industry. It can be used to classify objects according to their composition, or to quantify compounds present on the surface and show their spatial distribution. This last case is often challenging as the reference is not known for each pixel. Image processing is even more important in this case to extract the Region of Interest (ROI) to build the model but also to be able to apply it on new images.</p>



<p>This scientific study presents the <strong>methodology for analyzing hyperspectral images</strong> for grape bunch maturity prediction directly in vineyards. In this example, the parameter to be predicted is the sugar content (in °Brix) on each whole bunch of grapes, providing an average measurement of sugar content per image</p>



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<p class="has-text-align-center"><font size="5"><font color="#00646F"><strong><a href="/en/data-analysis/measurement/imaging/" target="_blank" rel="noreferrer noopener">Learn more about how and why analysizing hyperspectral images &#8211; HSI</a> </strong></font></font></p>



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<figure class="aligncenter size-medium"><a href="/wp-content/uploads/2025/03/HSI_ML_Ondalys_INRAE_IFV_-ICNIRS2025.pdf" target="_blank" rel=" noreferrer noopener"><img loading="lazy" decoding="async" width="300" height="116" src="https://ondalys.fr/wp-content/uploads/2025/03/button-on-methodology-od-hsi-analysis-300x116.png" alt="" class="wp-image-21326" srcset="https://ondalys.fr/wp-content/uploads/2025/03/button-on-methodology-od-hsi-analysis-300x116.png 300w, https://ondalys.fr/wp-content/uploads/2025/03/button-on-methodology-od-hsi-analysis-150x58.png 150w, https://ondalys.fr/wp-content/uploads/2025/03/button-on-methodology-od-hsi-analysis-480x185.png 480w, https://ondalys.fr/wp-content/uploads/2025/03/button-on-methodology-od-hsi-analysis.png 518w" sizes="auto, (max-width:767px) 300px, 300px" /></a></figure>
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<p>NIR2025 will highlight all aspects of near-infrared spectroscopy, spanning from methodological and technological advances in NIR spectroscopy (near-infrared imaging and miniaturized spectrometers) to applications in various fields (agri-food, pharmaceutical, chemical, biotech, etc.) through the analysis of spectroscopic data and hyperspectral images.</p>



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<div class="wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-16018d1d wp-block-buttons-is-layout-flex">
<div class="wp-block-button"><a class="wp-block-button__link has-background wp-element-button" href="https://nir2025.sisnir.org/wp-content/uploads/2025/03/TIMETABLE2-WEB-NIR-2025.pdf" style="background-color:#00646f" target="_blank" rel="noreferrer noopener"><strong>See more information about the NIR2025 conference and program</strong></a></div>
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<p>Every two years, in fact, the <strong>International Council for Near Infrared Spectroscopy</strong> (ICNIRS – <a href="https://icnirs.org/">https://icnirs.org/</a>) organizes the main international conference dedicated to NIR spectroscopy.<br>Each edition permits to to catch up on all the NIR news (theory, applications, innovative instrumental solutions).</p>



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<p>The post <a href="https://ondalys.fr/en/june-2025-nir2025-conference/">June 8-12, 2025 &#8211; NIR2025 international congress in Roma, Italy</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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		<title>April 2025 &#8211; Scientific article: Cell culture monitoring using Raman and Machine Learning</title>
		<link>https://ondalys.fr/en/april-2025-cell-culture-monitoring-using-raman/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Wed, 26 Feb 2025 13:20:48 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/?p=22094</guid>

					<description><![CDATA[<p>This work aimed at developing a real-time cell culture monitoring method to optimize the culture conditions of CHO (Chinese hamster ovary cells) for the production of<span class="excerpt-hellip"> […]</span></p>
<p>The post <a href="https://ondalys.fr/en/april-2025-cell-culture-monitoring-using-raman/">April 2025 &#8211; Scientific article: Cell culture monitoring using Raman and Machine Learning</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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<p>This work aimed at developing a real-time cell culture monitoring method to optimize the culture conditions of CHO (Chinese hamster ovary cells) for the production of monoclonal antibodies; and to guarantee a constant quality of the main metabolic parameters and the IgG (immunoglobulins) yield for biopharmaceutical production.</p>



<p><strong>Raman spectroscopy,</strong> combined with <strong>Machine Learning methods</strong> for spectral processing, has established itself as a robust process analytical technology (PAT) tool thanks to its real-time, in-situ, and non-invasive measurement capabilities in bioreactors. This study evaluates online Raman spectroscopy and chemometric and machine learning methods for in-process prediction, with a view to monitoring the following parameters of interest: nutrients, metabolites, antibody titers, and cell density.</p>



<p>Following the development of regression models using chemometric and machine learning methods by varying cell culture conditions, this study confirms the potential of Raman spectroscopy for in-situ and real-time monitoring of bioprocesses, particularly for CHO cell cultures and monoclonal antibody production, without manual sampling. Chemometric analysis improves the accuracy and robustness of the models and enables the monitoring and even automated control of bioreactors. Raman data could enable continuous regulation of critical nutrients such as glucose, thus ensuring control of Critical Process Parameters (<strong>CPPs</strong>) during biopharmaceutical production.</p>



<p>This work was conducted within the framework of the CLIMBIN collaborative R&amp;D project, in collaboration with various researchers from the University of Tours (Dr. Morandise Rubini, Prof. Igor Chourpa), the LRGP laboratory in Nancy, the Servier Group (Anaïs Berger, Thomas Saillard, Sylvain Arnould, Muriel Vergès), the spectroscopy equipment manufacturer INDATECH (Julien Louet, Dr. Fabien Chauchard), and Ondalys (Julien Boyer, Jordane Poulain, Dr. Sylvie Roussel).</p>



<p>For this article, <strong><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color">Julien Boyer</mark></strong>, <strong><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color">Jordane Poulain</mark></strong> and <strong><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color">Dr. Sylvie Roussel</mark></strong> from <strong>Ondalys </strong>contributed their expertise in Chemometrics and Machine Learning. They brought their experience for data processing using online Raman spectroscopy measurements for the bioproduction of mAbs from CHO cells under industrial conditions, in Servier laboratories, alongside the University of Tours.</p>



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<div class="wp-block-button"><a class="wp-block-button__link has-background wp-element-button" href="/en/about-ondalys/contact-us/" style="background-color:#00646f" target="_blank" rel="noreferrer noopener">Contact-us to learn more</a></div>
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<p><em>M. Rubini, <strong>J. Boyer</strong>, <strong>J. Poulain</strong>, A. Berger, T. Saillard, J. Louet, M. Soucé, <strong>S. Roussel</strong>, S. Arnould, M. Vergès, F. Chauchard-Rios &amp; I. Chourpa. <strong>Monitoring of Nutrients, Metabolites, IgG Titer, and Cell Densities in 10 L Bioreactors Using Raman Spectroscopy and PLS Regression Models</strong>. <em>Pharmaceutics 2025, Volume 17, Issue 4, 473, Avril 2025</em></em></p>
<p>The post <a href="https://ondalys.fr/en/april-2025-cell-culture-monitoring-using-raman/">April 2025 &#8211; Scientific article: Cell culture monitoring using Raman and Machine Learning</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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		<title>March 2025 &#8211; French Bioproduction Congress Polepharma &#8211; CFB 2025</title>
		<link>https://ondalys.fr/en/march-2025-france-bioproduction-polepharma-cfb-2025/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Fri, 31 Jan 2025 15:25:09 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/?p=20954</guid>

					<description><![CDATA[<p>This year again, Ondalys will be present at the France Bioproduction 2025 Congress, organized by Polepharma and Medicen Paris Région on March 19 &#38; 20, 2025<span class="excerpt-hellip"> […]</span></p>
<p>The post <a href="https://ondalys.fr/en/march-2025-france-bioproduction-polepharma-cfb-2025/">March 2025 &#8211; French Bioproduction Congress Polepharma &#8211; CFB 2025</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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<p>This year again, Ondalys will be present at the France Bioproduction 2025 Congress, organized by <a href="https://www.polepharma.com/pages/home-en" target="_blank" rel="noreferrer noopener"><strong>Polepharma</strong></a> and <a href="https://medicen.org/" target="_blank" rel="noreferrer noopener"><strong>Medicen Paris Région</strong></a> on <strong>March 19 &amp; 20, 2025</strong> at the Palais des congrès de Tours.</p>



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<p>With <strong>Igor Chourpa, </strong>Professor-Director of the Nano-Medicine and Nano-Probe Laboratory (<a href="https://nmns.univ-tours.fr/" target="_blank" rel="noreferrer noopener"><strong>NMNS</strong></a>) at the University of Tours and <strong>Thomas Saillard</strong>, Upstream Bioprocess Engineer at <strong><mark style="background-color:rgba(0, 0, 0, 0);color:#00646f" class="has-inline-color">Servier</mark></strong>, <strong>Sylvie Roussel </strong>will present an oral presentation entitled: </p>



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<h3 class="wp-block-heading has-text-align-center"><strong><font color="#00646F">PAT for bioprocess : implementation of Raman probes and Chemometrics modelling</font></strong></h3>



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<p>From the collaborative <strong><a href="/en/scientific-resources/rd-collaborative-projects/#climbin">CLIMBIN</a> </strong>project bringing together <strong>NMNS</strong>, <strong>LRGP</strong>, <strong>Servier</strong>, <strong>Ondalys </strong>and <strong>INDATECH -Chauvin Arnoux</strong>, the work presented at CFB2025 will highlight the consortium&#8217;s progress in terms of innovative solutions for real-time control of suspended cell cultures (CHO, etc.) in bioreactors.</p>



<p>Within this project, the Ondalys team was in charge of <strong>predicting Critical Process Parameters (CPPs) and Critical Quality Attributes (CQAs) using Machine Learning (ML) algorithms</strong>.</p>
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<p>👉 ALL you need to know about <a href="https://www.france-bioproduction.com/home-anglais/" target="_blank" rel="noreferrer noopener"><strong>France Bioproduction Congress 2025</strong></a></p>



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<p>With extensive experience in supporting biotechnology and biopharmaceutical manufacturers, the Ondalys team offers its expertise to address issues related to monitoring and optimizing cell bioproduction (yeasts, CHO, antibodies, etc.).</p>



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<p>Indeed, <strong>cell cultures in bioreactors</strong> generate<strong> large databases</strong> grouping together <strong>process parameters</strong> and <strong>online measurements</strong> (oxygen, pH, data from online analyzers such as<strong> Raman spectroscopy</strong>, at-line measurements, etc.).</p>



<p>The interest in using data analysis and Machine Learning methods to process these <strong>large and complex databases</strong>, in order to best characterize the behavior of the bioreactor, is now proven.</p>
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<div class="wp-block-button has-custom-width wp-block-button__width-100 is-style-fill"><a class="wp-block-button__link has-background wp-element-button" href="/en/about-ondalys/contact-us/" style="background-color:#00646f" target="_blank" rel="noreferrer noopener"><strong>Contact us to learn more about solutions to optimize bioprocessing</strong></a></div>
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<h3 class="wp-block-heading has-text-align-center">Watch Sylvie Roussel interview<br>during the 2023 France Bioproduction Congress</h3>



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<iframe loading="lazy" title="Congrès France Bioproduction 2023 de Polepharma" width="1220" height="686" src="https://www.youtube.com/embed/_qppUfmaypU?feature=oembed&#038;enablejsapi=1&#038;origin=https://ondalys.fr" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
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<p class="has-text-align-center">To learn more about Machine Learning and Data Analytics for the Biopharma and Biotech industries, <br>check out our dedicated pages.</p>



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<p><em>Polepharma is the 1st pharmaceutical cluster and aims to structure the French (bio)pharmaceutical industrial sector by supporting its transformation towards the Industry of the Future.</em></p>



<p><em>The mission that Polepharma has set itself revolves around 3 objectives:</em></p>



<ul class="wp-block-list">
<li><em>Make France the best place in the world to develop &amp; produce (bio)medicines.</em></li>



<li><em>Manufacture quality treatments in France in the best conditions and secure public health, contribute to employment and local economies.</em></li>



<li><em>Promote industrial cooperation between territories and laboratories, suppliers, schools, collectives, experts, talents, etc.</em></li>
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<p>The post <a href="https://ondalys.fr/en/march-2025-france-bioproduction-polepharma-cfb-2025/">March 2025 &#8211; French Bioproduction Congress Polepharma &#8211; CFB 2025</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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		<title>The Ondalys team sends you its best wishes for 2025 !</title>
		<link>https://ondalys.fr/en/the-ondalys-team-sends-you-its-best-wishes-for-2025/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Tue, 31 Dec 2024 23:01:48 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/?p=20870</guid>

					<description><![CDATA[<p>Happy new year 2025 !</p>
<p>The post <a href="https://ondalys.fr/en/the-ondalys-team-sends-you-its-best-wishes-for-2025/">The Ondalys team sends you its best wishes for 2025 !</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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<center><font color="#00646F"><font size="20">Happy new year 2025 !</font></font></center>
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<figure class="aligncenter size-large is-resized"><img loading="lazy" decoding="async" width="768" height="1024" src="https://ondalys.fr/wp-content/uploads/2024/12/Best-wishes-2025-bl-768x1024.jpg" alt="" class="wp-image-20872" style="width:700px" srcset="https://ondalys.fr/wp-content/uploads/2024/12/Best-wishes-2025-bl-768x1024.jpg 768w, https://ondalys.fr/wp-content/uploads/2024/12/Best-wishes-2025-bl-225x300.jpg 225w, https://ondalys.fr/wp-content/uploads/2024/12/Best-wishes-2025-bl-1152x1536.jpg 1152w, https://ondalys.fr/wp-content/uploads/2024/12/Best-wishes-2025-bl-56x75.jpg 56w, https://ondalys.fr/wp-content/uploads/2024/12/Best-wishes-2025-bl-480x640.jpg 480w, https://ondalys.fr/wp-content/uploads/2024/12/Best-wishes-2025-bl.jpg 1270w" sizes="auto, (max-width:767px) 480px, (max-width:768px) 100vw, 768px" /></figure>
</div><p>The post <a href="https://ondalys.fr/en/the-ondalys-team-sends-you-its-best-wishes-for-2025/">The Ondalys team sends you its best wishes for 2025 !</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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		<title>Dec. 10th, 2024 &#8211; Webinar: Raman and Machine Learning for bioprocessing</title>
		<link>https://ondalys.fr/en/10-dec-2024-webinar-raman-machine-learning-for-bioprocess/</link>
		
		<dc:creator><![CDATA[Cécile Fontange]]></dc:creator>
		<pubDate>Thu, 14 Nov 2024 10:12:19 +0000</pubDate>
				<category><![CDATA[Actualités]]></category>
		<guid isPermaLink="false">https://ondalys.fr/10-dec-2024-webinaire-raman-machine-learning-pour-la-bioproduction/</guid>

					<description><![CDATA[<p>Raman spectroscopy and Machine Learning as a PAT tool for mAbs bioprocessing. We are pleased to announce our next webinar co-hosted with Indatech and the University<span class="excerpt-hellip"> […]</span></p>
<p>The post <a href="https://ondalys.fr/en/10-dec-2024-webinar-raman-machine-learning-for-bioprocess/">Dec. 10th, 2024 &#8211; Webinar: Raman and Machine Learning for bioprocessing</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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<h2 class="wp-block-heading has-text-align-center"><strong><font color="#00646F">Raman spectroscopy and Machine Learning as a PAT tool for mAbs bioprocessing</font></strong>.</h2>



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<p>We are pleased to announce our next webinar co-hosted with <span class="VIiyi" lang="fr"><span class="JLqJ4b" data-language-for-alternatives="fr" data-language-to-translate-into="en" data-phrase-index="0"><strong>Indatech</strong> and the <strong>University of Tours</strong> dedicated to Raman Spectrosocpy and Machine Learning for bioprocessing optimization </span></span></p>



<p>During this webinar, discover how to couple <strong>in-line Raman spectroscopy </strong>with <strong>Machine Learning tools </strong>to optimize the non-destructive analysis of<strong> CHO cell cultures </strong>and the production of <strong>monoclonal antibodies (mAbs)</strong>. Through real-time monitoring of critical process parameters (CPPs) and critical quality attributes (CQAs), such as mAb, nutrient and metabolite concentrations or viable cell density , yield and batch reproducibility may be significantly improved.</p>



<p>Alongside 2 of our partners in <strong>CLIMBIN </strong>project, <strong>Julien Louet </strong>from Indatech and <strong>Pr. Igor Chourpa </strong>from the NMNS laboratory at the University of Tours, <strong>Sylvie Roussel </strong>will present the results obtained inthe context of CLIMBIN.</p>
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<p class="has-text-align-center"><strong>Sylvie Roussel, <br>Ondalys</strong> <strong>CEO</strong></p>
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<p><strong><a href="/en/scientific-resources/rd-collaborative-projects/#climbin" target="_blank" rel="noreferrer noopener">CLIMBIN</a> </strong>is a collaborative project that aims to develop an innovative solution in process analytical technology (PAT) by molecular optical spectrometry, to improve CHO-type suspension cultures in various types of bioreactors. Dedicated to the bioprodcution sector, this real-time monitoring of critical process and quality parameters offers disruptive advantages in terms of control, industrial performance and CSR.</p>



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<h2 class="wp-block-heading has-text-align-center"><strong><mark style="background-color:rgba(0, 0, 0, 0)" class="has-inline-color has-black-color">December 10<sup>th</sup> at 4.00 pm (CET)</mark></strong></h2>
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<p>Expert in spectral data analysis (NIR, MIR, Raman, UV), the Ondalys team supports you in all your issues of <a href="/en/data-analysis/measurement/spectral-data/" target="_blank" rel="noreferrer noopener">processing your spectroscopic data</a> and <a href="/en/data-analysis/measurement/process-parameters/" target="_blank" rel="noreferrer noopener">your bioproduction data</a>.</p>



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<p class="has-text-align-center"><strong><a href="/en/data-analysis/applications/industry-4-0/" target="_blank" rel="noreferrer noopener"><font size="5">To know more about bioprocessing monitoring.</font></a></strong></p>



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<p>The post <a href="https://ondalys.fr/en/10-dec-2024-webinar-raman-machine-learning-for-bioprocess/">Dec. 10th, 2024 &#8211; Webinar: Raman and Machine Learning for bioprocessing</a> appeared first on <a href="https://ondalys.fr/en/">Ondalys</a>.</p>
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