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Genedata Expressionist 14.0 リリース:
革新的なバイオ医薬品特性解析を支援

Enterprise software solution addresses industry challenges in characterizing novel and complex biotherapeutic molecules and monitoring their critical quality attributes

August 20, 2020
Basel, Switzerland

Genedata, the leading provider of enterprise software solutions for biopharmaceutical R&D, today announced the release of Genedata Expressionist® 14.0. The market-leading platform for mass spectrometry-based biotherapeutic characterization and quality monitoring is valued by the world’s most innovative biopharma organizations for its breadth of application coverage, including metabolomic and proteomic applications such as host cell protein analysis. Features of this new release complement the software’s particular strength in supporting Multi-Attribute Method (MAM) approaches to monitor the quality of biopharmaceuticals throughout biopharmaceutical development and manufacturing.

As biotherapeutic R&D delivers innovative biotherapeutic modalities, analytical groups are increasingly facing new challenges—not only in characterizing complex molecules with novel formats, but also in analyzing emerging classes of biotherapeutics such as oligonucleotides. To meet these evolving needs, Genedata is continuously expanding support for new modalities in Genedata Expressionist. Developed in collaboration with industry partners, Genedata Expressionist 14.0 introduces a new negative-ion deconvolution algorithm specifically designed for high-throughput characterization and quality monitoring of oligonucleotides. This new functionality enables users to leverage the analytical power of MS coupled to high performance data processing to facilitate and accelerate the development of innovative nucleotide-based therapeutics.

Genedata Expressionist 14.0 also provides improved usability and flexibility to further boost process efficiencies and sets new standards in streamlining end-to-end intact protein analysis workflows. The latest release of Genedata Expressionist includes:

  • Advanced capabilities for detecting all possible chain combinations and mapping unpaired cysteine residues to speed up the characterization of ever more complex biotherapeutic constructs.
  • Automated and seamless retrieval of sequences and relevant metadata related to the molecules under investigation directly from molecule information systems, leveraging the open architecture of Genedata Expressionist.
  • Intuitive review functionalities that streamline the curation of analysis results, facilitate the interactive evaluation of molecular characterizations, and allow the incorporation of expert knowledge into reports.
  • An all-new customizable user interface that further improves the curation process, providing complete and in-depth overviews within and across data sets and facilitating sample batch comparisons.
  • A new plugin infrastructure for customized reporting, enabling effortless transfer of data and results into any reporting system to deliver truly end-to-end workflows for processing, analyzing, and reporting hundreds of complex samples per week.

"The latest release of Genedata Expressionist reinforces our continued commitment to support biopharmaceutical R&D in accelerating the development process and ensuring the efficacy and safety of cutting-edge biotherapeutics by providing best-in-class characterization, even of the most advanced molecules. As an integral component of our Genedata Biopharma Platform, Genedata Expressionist enables our customers to efficiently scale up their internal data processing workflows, while at the same time improving result quality," commented Othmar Pfannes, Ph.D., CEO of Genedata. "Furthermore, we remain committed to partnering with leading technology providers to offer our joint customers new solutions to not only accelerate discovery, development, and commercialization of novel biopharmaceuticals, but ultimately also to reduce costs by streamlining and automating complex analytical processes."


Genedata Expressionist enables our customers to efficiently scale up their internal data processing workflows, while at the same time improving result quality