Digital Analytical Methods (with Allotrope)

Executive summary

Phase 1 of this project develops and demonstrates a standardized, machine-readable digital method, built on a reusable ASM data model, that lets analytical methods move seamlessly between software systems, while improving data integrity and eliminating manual effort via automation. The goal is to establishes the foundation for digital analytical methods that are FAIR across research and commercial laboratories and deliver the first practical implementation of a reusable framework that can be extended to techniques such as HPLC, GC, LC-MS, dissolution, titration and spectroscopy. This project lays the groundwork for vendor-neutral digital method exchange, automated laboratory execution, AI-enabled method optimization, and interoperable analytical data across the pharmaceutical industry.

The Problem

Analytical methods are still described by hand in prose or tabular files that pass manually from scientist to scientist and lab to lab. Every manual step risks introducing mistakes, inconsistencies and incomplete information that are then unintentionally carried forward each time a method is transferred or reused. Because methods stay locked in human-readable formats and vendor-specific systems, they cannot interact directly with software, cannot be reliably searched or exchanged, and cannot be linked cleanly to the results they produce.

To meet today’s digital challenges, analytical methods must be standardized, machine-readable instructions featuring all relevant details, versioning, and interoperability, so that data integrity, automation and reuse become the default workflow, rather than the exception.

Our Solution

Digital Analytical Methods is a multi-phase, pre-competitive collaboration between the Pistoia Alliance and the Allotrope Foundation to make analytical methods FAIR: complete, machine-readable digital assets rather than static documents. The overall program is planned across three phases:

Phase 1 establishes a standardized, vendor-neutral representation of analytical methods and demonstrates exchange across systems
Phase 2 uses that representation to improve method transfer and the consistency of method execution between laboratories
Phase 3 explores how digital methods, combined with process and results data, can support analysis, troubleshooting and decision-making.

The current phase 1 delivers the first practical implementation. Work in this phase will build a complete, vendor-neutral and machine-readable representation of two analytical methods, including a moderate-complexity UV/Vis spectroscopy case, using an Allotrope Simple Model (ASM). Where needed, the Allotrope Foundation Ontologies (AFO) and ASM schema will be extended. Finally, working with vendors, our goal is to demonstrate the method inside an Electronic Lab Notebook (ELN) for R&D and/or a Digital Method Execution/Laboratory Execution System (DME/LES) for commercial operations.

Crucially, the planned digital method captures far more than experimental parameters. It includes materials, product specifications, sample preparation, system suitability, metadata and external references, all linked directly to analytical results. Two to three representative method types will be used to test how well the model generalizes and to confirm that the right high-level scaffold exists for other techniques.

Planned milestones and deliverables for this phase:

Agreed phase scope and success criteria: The minimum viable use case for two representative method types, including UV/VIS.
Prototype implementations: Digital methods uploaded or imported, stored, searched, retrieved and presented within selected platforms.
Cross-platform validation: confirmation that the same vendor-neutral method representation is interpreted consistently across participating systems.
Published phase outputs: Refined ASM and AFO updates if required, example method files, and implementation guidance and recommendations for the next phase.

Who & Why

This project is for everyone who creates, runs, transfers or builds software for analytical methods: analytical scientists and method-development teams, laboratory and quality leaders across both R&D and commercial operations, data and informatics owners driving digital-lab transformation, standards bodies, and software vendors whose tools need to interoperate.

Benefits for pharmaceutical and laboratory organizations:

Improved data integrity, reproducibility, and compliance by replacing manual method documentation with standardized, machine-readable methods.
Reduced method development, operation, and transfer effort, with accompanying cost and time efficiency.
Vendor-neutral interoperability and reusable digital assets that support AI/ML applications.

Benefits for software vendors:

Demonstrated interoperability with an emerging industry standard.
Meet customer demand for standardized digital methods and position solutions for automated laboratory workflows and digital method exchange.

Benefits for the wider standards community:

Real-world validation and extension of AFO and ASM
Expanded reusable ontology terms and schema building blocks that strengthen the standard for future analytical methods.