FUTURELAB – The Digital Lab of the Future

FUTURELAB – The Digital Lab of the Future

FutureLab is a project aiming at using modern software tools to create a cloud environment connecting all R&D elements of the chemical, pharmaceutical and biotech manufacturing industries to increase their productivity and efficiency, transcending geographical barriers. Analytical chemistry and chemometric technology will connect chemists, biochemists and other support positions in these traditional industries with their counterparts in academic institutions and Custom Research Organizations (CROs), as well as analytical equipment manufacturers. This will create a global community and marketplace fostering collaboration and service exchange, with individuals, entities and instrumentation directly interacting with each other, regardless of their location. The data in the system can be exploited by Artificial Intelligence technologies, including Machine and Deep Learning, while preserving confidentiality. This will facilitate automation in the value chain and increase predictive science.

The project is funded by the Galician Innovation Agency (GAIN), through the Industrias do Futuro programme and the European Regional Development Fund (ERDF). It also has the support of the Consellería de Economía, Emprego e Industria.

Objective 1: Development of the cloud architecture and infrastructure needed to ensure data integrity, fluid communication between teams, users’ transactions, including offer and hiring of services.

Objective 2: Module connecting instruments to the environment, resulting in an inventory of instruments and experiments available. It will allow services and maintenance management, as well as the creation of a marketplace for the analytical instruments time.

Objective 3: Chemical reaction module, designed to collect, store and manage information for all type of chemical reactions and to show information about the different components of a reaction (reagents, solvents, products, reaction conditions, yield, analytical data, suppliers, etc).

Objective 4: Transform Mnova in the market reference for processing and analysis of data derived from several analytical techniques by including new ones and integrating third parties’ contribution to the software.

Objective 5: Implementation of workflows adapted to industry, with scalable modules, easy to configure and customize. This will allow the storage of data, as well as the extraction of information using algorithms developed as part of Objective 4.

Objetivo 6: Development of a module that will allow the environment to use data, ensuring its confidentiality, and to develop tools based in Artificial Intelligence and Automatic Learning for decision-making.

Objective 7: Integration of a chemometric system in the cloud for multivariate analysis of spectral data. Integración de un sistema quimiométrico basado en la nube para el análisis multivariable de datos espectroscópico.

Advances during 2019

All milestones set for the first months of the project have been achieved, including the definition of the main functionalities of all modules described in the working plan and draft verification and validation plans. New algorithmia has been added to Mnova and work to include new analytical techniques to our suite is progressing, as well as the connection to instruments via a cloud system. The first tests of automation of processing and analysis, as well as the databasing of results, have been succesful.

Advances during 2020

  • The trading platform linked to the project has been established.
  • Improvements have been developed in the integration components with instruments to support compound experiments or data integrity checks, as well as new functionalities.
  • A management console application was developed to verify GxP installations.
  • In Mbook, and its evolution Mdrive, automatic integration with analysis instruments has been completed, with the possibility of defining standard work procedures.
  • The functionalities that will allow the deployment of tools in regulated markets have been included: GxP.
  • New algorithms for analyzing digital signals and artificial intelligence methods have been developed for the analysis of both small molecules and biomolecules (such as monoclonal antibodies) using NMR techniques.
  • Substantial improvements have also been made to mass spectrometry, optical spectroscopy and chromatography modules.
  • A new module has been developed for the automatic analysis of drugs using low-field NMR relaxometry techniques and new fully automated workflows have been implemented.
  • New versions of the automation platform and automated workflows have been launched.
  • Systems that provide new automated workflows and analytics have continued to be developed.
  • The automation platform continues to improve thanks to internal and customer feedback.

Advances during 2021

  • Instrument access components evolved to improve Tospin and Icon-NMR integration.
  • New GxP verification console process and Mdrive improvements.
  • Designed new solution for no Bruker instruments integration according to generic arquitecture.
  • Implemented new Mnova Server base solution features including support for different techniques.
  • Created new Mnova Server based on generic integration platform.
  • Continuation on GxP work, integration with instruments and workflow procedures.
  • New versions of the automation platform and automated workflows have been launched.
  • Development of new automated workflows have started.
  • Systems that provide new automated workflows and analytics continued to be developed.
  • The automation platform continues to improve thanks to internal and customer feedback.
  • The functionality of the software for chemometric treatment using NMR data has been completed, as well as the development of new algorithms and machine learning models for the analysis, detection, quantification and elucidation of molecular structures, both in terms of their 2D topology and to its three-dimensional configuration.
  • Likewise, the capabilities of the software have also been expanded to treat data from optical spectroscopy, chromatography and mass spectrometry as well as the IUPAC nomenclature of organic compounds.
  • Lastly, we have developed a functional prototype of a Web version of the Mnova platform.

Advances during 2022 

  • A complete security audit has been carried out to ensure that the construction and test processes performed are in accordance with the OWASP specification. 
  • Implementation of a platform for visualizing the platform metrics to collect all the relevant information at the level of modules deployed in the general architecture. 
  • The permissions and roles associated with the tasks carried out in the analytical module have been modified and corrected in order to restrict certain actions by each of the actors involved in the platform. 
  • Management of the CMR risk classification of the compounds in inventory. 
  • Final implementation of the functionality for regulated environments (GxP). 
  • New highly specialized analytical services. 
  • Completion of actions on the workflows in the laboratory with the consolidation of the algorithms for the automatic management of data. 
  • New automatic analysis methods have been included. 
  • Development of a prototype chemo informatics operations server.
  • Development of integration modules with chemo informatics solutions and automation tools. 
  • Design of a general-use web interface adaptable to different types of operations or workflows and development of an application. 
  • Development and implementation of analytical instrumentation data converters (NMR, LC/GC/MS, IR/UV/Raman, EPR, etc).
  • The development of a complete chemometrics module for 1D and 2D NMR data has been completed.
  • Artificial intelligence modules for 2D and 3D elucidation of small organic molecules, as well as automated structural verification, have been completed.
  • IUPAC nomenclature: naming of more classes of compounds, including steroids, terpenes, amino acids, peptides, etc.
    Automation in the generation of reports through more powerful templates.

The FutureLab project has been funded by the Galician Innovation Agency (GAIN), through the Industries of the Future 4.0 Program and co-financed by the European Regional Development Fund (ERDF) under the FEDER Galicia 2014-2020 operational program. It also has the support of the First Vice-Presidency and Regional Ministry of Economy, Industry and Innovation.