Digital Transformation in Biomanufacturing: mAbxience Partners with Genedata to Automate Global CDMO Workflows

Genedata, mAbxience, Danaher, bioprocess, CDMO, biosimilars, SaaS, biopharmaceutical, R&D, data integrity, automation, cloud computing

By: AXL Media

Published: Mar 11, 2026, 6:44 AM EDT

The Integration of Enterprise Software in Bioprocessing

Genedata, a Danaher subsidiary and prominent provider of biopharmaceutical R&D software, has entered into a strategic agreement with mAbxience to implement its specialized bioprocess platform. This partnership is designed to structure and harmonize developmental data across the entirety of mAbxience’s operations. As a global Contract Development and Manufacturing Organization (CDMO) with a primary focus on biosimilars, mAbxience requires a sophisticated digital framework to manage the increasing complexity of biological drug manufacturing. The move signals a shift toward total digital integration within the highly regulated biopharmaceutical sector.

Creating a Unified Digital Backbone for CDMO Operations

The implementation of Genedata Bioprocess, utilized as a Software-as-a-Service (SaaS) solution, establishes what the companies describe as a unified digital backbone. This system connects disparate stages of production, ranging from cell line development to final formulation. According to Ivan Sánchez de Melo, R&D Director at mAbxience, the organization needed a single platform capable of analyzing data across upstream and downstream processes. By consolidating these workflows, the company can ensure that experimental results and process parameters are tracked within a single source of truth, eliminating data silos that often hinder large-scale manufacturing.

Automation and the Path Toward AI Modeling

A primary driver for this technological adoption is the automation of labor-intensive processes that historically required manual documentation. By operating within the Genedata Cloud, mAbxience intends to enhance data integrity and traceability, which are critical for meeting international regulatory standards. The transition is not merely about current efficiency but is a preparatory step for advanced process modeling. According to Sánchez de Melo, this foundational system allows the organization to scale its output while laying the groundwork for future AI-driven optimization and predictive analytics in bioprocessing.