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An advanced webinar on "Multivariate Analysis Software: SIMCA" (Regression Model OPLS) will be held on September 26, 2025, from 15:00 to 15:30. SIMCA is a multivariate analysis software that is well-regarded in fields handling large data sets, offering features for overview, regression, discrimination, and classification. In this webinar, we will focus on 'Regression: OPLS' and include short demonstrations and case studies (three are planned). ● OPLS: Orthogonal Partial Least Squares A superior model to PLS. By rotating so that the Y variable becomes the first axis, interpretation is made easier. This model allows for the prediction of target variables and factor analysis. Example of OPLS usage: * Set the coffee quality evaluation score as the target variable, find the factors that contribute most from the metabolic profile GC/MS data, and further predict the quality evaluation score from the GC/MS data. * While PLS was able to identify the most contributing factors, determining the second and third most contributing factors was difficult. In contrast, OPLS made this identification easy.

AnalyzerPro XD is a data processing software for GC/MS and LC/MS that supports data formats from major mass spectrometry (MS) manufacturers. It is widely used to enhance the efficiency of analytical tasks in research and development as well as manufacturing. 1. Reading major MS data 2. Extraction of component spectra through deconvolution 3. Library search in NIST format 4. Comprehensive non-target analysis 5. Creation and utilization of target libraries 6. Alignment of multiple samples 7. Visualization and feature component exploration through statistical and multivariate analysis 8. Data processing for 2D chromatographic MS and direct MS (optional) In this webinar, we will introduce an overview of AnalyzerPro XD and demonstrate the processing of GC/MS data from food samples, showing how to quickly and easily visualize information from complex sample data to aid in decision-making. Participation is free. Please feel free to join us.

We will hold a basic webinar on "Multivariate Analysis Software: SIMCA" on August 26, 2025 (15:00 to 15:30). SIMCA is used in research, development, and manufacturing environments that handle large amounts of data, equipped with various algorithms and tools that provide excellent analytical capabilities and quickly visualize results with easy mouse operations. There are many users, especially in fields such as omics data (GC/MS, LC/MS, NMR, RNA-seq, etc.), mixture analysis data (MS, NMR, IR, NIR, etc.), and sensory evaluation analysis. In this webinar, we will not only introduce an overview of SIMCA (projection methods, principal component analysis, regression, discrimination) but also present our advanced technical support services that assist with customer data analysis, which started last year, and our Python script creation service, along with a Q&A session. We will answer questions such as, "I want to start multivariate analysis but don't know how," "I've heard of SIMCA in chemometrics but don't know the details," and "Can I analyze mass spectrometry or sensory evaluation data using multivariate analysis?"

We will be exhibiting at the "1st Pharma DX EXPO Tokyo (Interfex Week Tokyo 2025)." The main products on display are as follows: - Cloud-based Electronic Lab Notebook (ELN) 'Labstep' *We will also be introducing various DX products for pharmaceutical companies. If you attend, please be sure to stop by our booth.

SIMCA is a multivariate analysis software that handles large data sets and is well-regarded in research, development, and manufacturing for its features in overview, regression, discrimination, and classification. In this webinar, we will focus on the highly praised features from our customers: 'Regression: OPLS', 'Discrimination: OPLS-DA', and 'Multi-block Overview Analysis: MOCA', accompanied by short demonstrations. ● OPLS An enhanced version of PLS. By rotating so that the Y variable becomes the first axis, it facilitates interpretation. ● OPLS-DA An enhanced version of PLS-DA. By rotating to make the axis that best separates the classes the first axis, it makes discrimination between classes easier. Additionally, using the S-plot allows for the instant visualization of reliable marker candidates that are difficult to assess from loading plots. ● MOCA An integrated overview analysis targeting block data obtained from multiple analyses and methods on the same samples. It can be used in cases such as: Food: Mass spectrometry + sensory evaluation Manufacturing: Process signals + spectral analysis + raw material composition Omics: Gene expression (transcripts) + proteomics (protein expression) + metabolomics (quantitative values of metabolites)