Deep Integration Between Mestrelab MNova and ZONTAL

Modern laboratories generate vast amounts of analytical data, yet the challenge is not simply collecting it—it is making that data usable, accessible, and meaningful across different stakeholders. In this session, ZONTAL and Mestrelab explore how integrating Mnova with the ZONTAL platform, supported by Allotrope data standards, creates a unified approach to managing, analyzing, and reusing analytical data across the digital lab.

Balancing the Needs of Scientists, IT, and Data Science

Analytical data serves different purposes depending on who is using it. Scientists at the bench need fast access to data in tools that help them make immediate decisions about their experiments. At the same time, compliance and regulatory teams require secure, traceable, and long-term storage of that data. Data scientists, meanwhile, depend on standardized formats that allow them to analyze and extract insights without spending time on data transformation.

These competing priorities often create friction in traditional lab environments. Systems designed for compliance can slow down scientific workflows, while tools optimized for speed may lack the structure required for long-term reuse. The goal of this integration is to eliminate that trade-off by delivering a solution that satisfies all stakeholders simultaneously.

A Unified Approach Through ZONTAL, Mnova, and Allotrope

The integration between Mnova and the ZONTAL platform is built on a shared foundation of FAIR data principles and Allotrope standards. ZONTAL provides a centralized data hub that connects laboratory instruments, workflows, and applications, while Mnova delivers advanced analytical capabilities for techniques such as NMR, LC-MS, and spectroscopy.

Allotrope data formats serve as the bridge between these systems, enabling proprietary instrument data to be converted into standardized, vendor-neutral representations. This ensures that data can be seamlessly exchanged, interpreted, and reused across systems without loss of meaning or context.

Automating Data Processing and Analysis

A key capability demonstrated in this integration is the ability to automate data processing at the point of ingestion. As analytical data enters the ZONTAL platform, it can be automatically routed to Mnova for processing, transformation, and validation.

For example, workflows such as structure verification can be executed automatically, comparing analytical results against expected molecular structures and generating confidence scores. At the same time, raw data is converted into standardized formats and enriched with metadata, ensuring that it is immediately ready for downstream use. This reduces manual effort and accelerates the time required to move from data acquisition to insight.

Enabling Seamless Scientist Interaction

While automation is critical, not all analytical decisions can or should be automated. Scientists still need the ability to interact with data, explore results, and apply domain expertise to interpret findings.

The integration enables this by allowing users to access ZONTAL-hosted data directly within the Mnova interface. Scientists can open datasets, perform analyses, adjust parameters, and validate results without needing to move data between systems. Once analysis is complete, results can be written back into the ZONTAL platform, preserving both the raw data and the analytical context in a single, unified environment.

Creating a Continuous Digital Workflow

This bidirectional integration supports a fully digital laboratory workflow, where data flows seamlessly from experiment planning to acquisition, processing, analysis, and storage. Requests for analysis can be initiated through user interfaces or APIs, enabling integration with ELNs, LIMS, and other enterprise systems.

As data moves through this workflow, it remains consistently structured and traceable, with all relevant metadata, processing steps, and outputs captured within standardized containers. This ensures that every stage of the analytical process is connected, reproducible, and accessible.

Delivering Value Across the Organization

By combining ZONTAL’s data platform, Mnova’s analytical capabilities, and Allotrope’s standardization framework, this integration delivers measurable value across the organization. Scientists benefit from faster access to data and streamlined analysis workflows. IT and compliance teams gain confidence in data integrity, traceability, and long-term accessibility. Data scientists are empowered with standardized, analysis-ready datasets that support advanced modeling and insight generation.

Ultimately, this approach transforms analytical data from isolated outputs into reusable digital assets that support collaboration, efficiency, and innovation across the enterprise.