Enterprise Ontologies and Scientific data management: Scibite CENtree with Benchling

Overview

A leading EU-based pharmaceutical company sought to strengthen enterprise ontology management and scientific data governance to support scalable drug discovery workflows. The objective was to streamline ontology integration and improve scientific data management within the Benchling platform, enabling consistent terminology, accurate data capture, and faster access to trusted scientific insights. By leveraging modern scientific informatics solutions, the organization aimed to enhance productivity, data accuracy, and long-term interoperability.

Our client

The client is a renowned EU-based pharmaceutical organization recognized for its innovation in drug discovery and development. With a strong focus on advancing scientific knowledge and improving patient outcomes, the company required robust ontology-driven data standardization supported by enterprise-grade lab informatics services. Their digital strategy emphasized scalable ELN/LIMS-enabled workflows and standardized vocabularies to support enterprise-wide research collaboration.

Client’s challenge

The client faced challenges in efficiently implementing an ontology management platform that could support evolving scientific vocabularies and integrate seamlessly with Benchling. Updating ontology entities, pushing controlled vocabulary updates, and migrating legacy data resulted in prolonged processes and potential inconsistencies. These issues increased operational costs, delayed data management activities, and limited adherence to FAIR data principles in life sciences, ultimately hindering innovation and accelerating drug development timelines.

Client’s goals

The primary goal was to establish enterprise ontologies and controlled vocabularies that would standardize scientific terminology across research programs. The client aimed to enhance data accuracy, enable seamless ontology updates within Benchling, and implement a scalable scientific data management system (SDMS) capable of supporting long-term digital transformation and ontology-driven research workflows.

Our approach

Excelra, a leading data science company, is comprised of qualified scientists and data engineers who have devised a comprehensive approach:

Evaluation of ontology management system:

• We conducted a comprehensive evaluation of the various ontology management systems, including Scibite’s CENtree against predefined functional and non-functional requirements.
• CENtree demonstrated superior performance in:
◦ Managing Scientific Ontology Access (SOA) ontologies and vocabularies.
◦ Meeting data security and scalability needs.
◦ Aligning with the client’s existing infrastructure and future roadmap.

Building controlled vocabulary:

• Collaborated with ontology analysts and domain experts, we identified specific requirements for controlled vocabularies to standardize data.
• We developed guidelines for Uniform Resource Identifiers (URIs) for the entities within these vocabularies and established versioning protocols to ensure data integrity and consistency.
• Designed a data model to align with the specific use-cases.
• We leveraged public databases and ontologies to populate the initial versions of the controlled vocabularies.

Pushing updated entities to benchling:

• Validated, updated using controlled vocabulary, and correctly extracted each newly requested entity.
• Pushed extracted entities to Benchling using either the Benchling SDK or Pipeline Pilot.

Our Solution

Excelra delivered an enterprise-ready ontology and data management solution centered on Scibite CENtree and Benchling. Controlled vocabularies were established to standardize scientific terms, legacy data was migrated using automated pipelines, and updated ontology entities were pushed to Benchling via SDK or Pipeline Pilot. The solution enabled consistent metadata capture, improved interoperability, and strengthened scientific application development for drug discovery across research teams.