Mnova BioHOS

Mnova BioHOS

Mnova BioHOS is a specialized NMR data analysis solution for assessing the higher-order structure of biologics or biosimilars such as monoclonal antibodies and other recombinant proteins. It enables objective comparison of test and reference samples using fingerprinting, peak-based metrics, and chemometric approaches applied to 1D and 2D NMR data. By combining advanced spectral processing with statistical modeling, Mnova BioHOS supports robust similarity assessment, classification, and trend detection, helping laboratories ensure structural consistency, product quality, and regulatory confidence throughout development and manufacturing.

Apply Established HOS Strategies: Asses higher-order structure using fingerprint comparison, peak movements, or chemometric analysis against representative reference spectra in one interface.

One Consistent Assessment Framework: Apply fingerprinting, peak-based metrics, and chemometrics under the same preprocessing rules, reducing method-to-method variability.

Reusable Automated Methods: Save, validate and reuse analysis methods to standardize workflows, reduce manual effort and turnaround time.

Reduced Manual Effort and Fewer Transfer Errors: Avoid exporting data to external packages, reformatting matrices, or reprocessing spectra multiple times, which cuts errors and saves time.

Advanced Multivariate Modeling: Analyze complex relationships across multiple variables using proven techniques such as PCA, SIMCA, and PLS for clearer, more reliable insights.

Link Statistics to Spectra with PCA and PLS: Use loadings plots to pinpoint the spectral regions driving dissimilarity and support confident sample classification.

Clear Results Visualization: Review each analysis through contextual plots and linked data tables in a tabbed Workspace, switching between analyses easily without leaving the platform.

Cross-Validation of Conclusions: Confirm findings with complementary approaches, for example ECHOS as a global fingerprint, CCSD for peak movements, PCA or SIMCA for class separation, and Profile for subtle 1D changes.

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