Accelerate Insight Generation from High-Throughput (HT) Mass Spectrometry (MS) Data

High-throughput mass spectrometry (HT-MS) delivers significant value to the biopharma industry, including analytical labs, by enabling in-depth analysis for applications such as biotherapeutic characterization, product quality monitoring, contaminant detection, or bioprocess control, and more. Scientists depend on this powerful technology to derive comprehensive insights, but the path from raw data to actionable results is often obstructed by major challenges. Massive, complex datasets, time-consuming manual processing, and the lack of standardized workflows across instruments and labs lead to inconsistent results and hinder collaboration. Each step, from data acquisition and processing to annotation and spectral quantification, is prone to variability. In high-throughput experimental settings, these challenges are amplified. Without a scalable infrastructure and automated analysis pipelines, cross-sample comparison and assay-level quality control and standardization become bottlenecks, slowing insight generation and delaying critical decision-making.

Automate MS Analytics – Unlock Speed, Increase Throughput, Improve Decisions

To meet the requirements of HT-MS and accelerate the generation of biological insights, Genedata delivers a cloud-deployed, enterprise-grade platform designed for optimal performance in MS data-intensive workflows such as large-scale screening assays. Its scalable architecture and enhanced computing power streamline every step of the MS data lifecycle—from ingestion to interpretation.

As an instrument-agnostic solution, the platform integrates seamlessly with existing corporate infrastructure, enabling standardized and automated data capture and efficient information exchange with centralized data management systems. This connectivity eliminates silos and supports collaborative decision-making across teams and sites. Raw data is processed automatically and consistently, producing structured outputs ready for downstream analysis.

A flexible analytical workflow engine with built-in configurable components enables end-to-end harmonized MS data analysis tailored to a wide range of scientific applications. The software supports 24/7 unattended operation and automatically triggers routine workflows, ensuring continuous throughput and operational efficiency. Throughout the process, interactive real-time spectral visualization allows researchers to comprehensively interrogate the data, perform quality control at scale, and uncover meaningful biological insights. Generated results undergo automated assessment, ensuring that QC-reviewed outputs are ready for reporting. Customizable reports streamline documentation and support efficient collaboration.

Beyond MS data processing and analysis, the platform supports high-throughput results aggregation and cross-assay data integration. This comprehensive approach enables biological interpretation of HT-MS data and informed decision-making across the biopharma value chain.

Resources

Chemical Liability Screening for Biotherapeutic Proteins – Using a Proteomic Approach and High-Throughput Data Analysis to Identify Antibody Chemical Liabilities in Early-Stage Discovery

In this webinar, learn how Sanofi is transforming early-stage drug discovery by integrating high-throughput chemical liability screening into its antibody development workflows. This innovative approach boosts screening throughput by up to 100-fold, enabling earlier identification of candidates with favorable developability profiles.

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Automating MS Analysis of Therapeutic Oligonucleotide Biotransformations

In this case study, reaserachers from Novartis developed and implemented an automated solution for processing, analyzing, and reporting MS data that enables comprehensive insights into the metabolism of oligonucleotide therapeutics while delivering significant time savings.

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