MCBO: Mammalian Cell Bioprocessing Ontology, A Hub-and-Spoke, IOF-Anchored Application Ontology

Abstract Mammalian cell-based biopharmaceutical manufacturing generates vast, heterogeneous datasets that remain fragmented due to the lack of a standardized metadata framework. A key challenge in biologics manufacturing is linking bioreactor conditions, cell line characteristics and recombinant product production. A datahub for mammalian cell bioprocessing, integrated by semantic technologies, will serve as a tool to understand and query the connections between these complex datasets. While existing ontologies cover general biological and experimental concepts, they often lack the operational specificity required to harmonize bioreactor conditions, cell line engineering, and product quality metrics. To address this specific gap, we present the Mammalian Cell Bioprocessing Ontology (MCBO), a hub-and-spoke application ontology built on Basic Formal Ontology (BFO) foundations and anchored to the Industrial Ontology Foundry (IOF) Core. MCBO formalizes the process-participant-quality modeling pattern, enabling precise tracking of culture environmental conditions as qualities of the physical culture system. We demonstrate the utility of MCBO through a central datahub populated with 723 curated cell culture process instances and 325 unique bioprocess samples from published studies. The framework is validated against eight competency questions implemented via SPARQL, demonstrating efficient cross-study querying of culture optimization, cell line engineering, and multi-omics integration. By providing a stable, schema-independent substrate for data harmonization, MCBO enables AI agent-powered, human-in-the-loop workflows and facilitates LLM-assisted extraction of structured metadata from legacy records. MCBO is open-source and designed for deployment behind institutional firewalls to support interoperable biomanufacturing intelligence while maintaining intellectual property sensitivity. MCBO is supported by the International Biomanufacturing Network (IBioNe), which aims to accelerate discoveries and developments by providing a network of biomanufacturing training and workforce development to educate the next generation of biomanufacturing experts. MCBO is evaluated using over 700 curated cell culture processes, validated against eight competency questions, and quality-controlled using automated ontology checks. Evaluation results and formal reasoning validation are provided in the Supplementary Materials. Availability: https://github.com/lewiscelllabs/mcbo Competing Interest Statement The authors have declared no competing interest. Glossary of Acronyms - AI - Artificial Intelligence - AO - Application Ontology - BFO - Basic Formal Ontology - BPOG - BioPhorum Operations Group - BPSA - Bio-Process Systems Alliance - CHO - Chinese Hamster Ovary (cells) - ChEBI - Chemical Entities of Biological Interest - CLO - Cell Line Ontology - CQ - Competency Question - ELN - Electronic Laboratory Notebook - FAIR - Findable, Accessible, Interoperable, Reusable - GEM - Genome-scale Metabolic Model - GPT - Generative Pre-trained Transformer - IAO - Information Artifact Ontology - ICE - Inventory of Composable Elements - IOF - Industry Ontology Foundry - IP - Intellectual Property - ISPE - International Society for Pharmaceutical Engineering - KEGG - Kyoto Encyclopedia of Genes and Genomes - LLM - Large Language Model - MCBO - Mammalian Cell Bioprocessing Ontology - MCP - Model Context Protocol - MIAPE - Minimum Information About a Proteomics Experiment - MIT - Massachusetts Institute of Technology - OBI - Ontology for Biomedical Investigations - OBO - Open Biological and Biomedical Ontologies - OWL - Web Ontology Language - pH - Potential of Hydrogen - RDF - Resource Description Framework - RNA - Ribonucleic Acid - SBO - Systems Biology Ontology - SKOS - Simple Knowledge Organization System - SPARQL - SPARQL Protocol and RDF Query Language - UO - Units Ontology