Bio-renewable Formulation Information and Knowledge Management System

Lead Research Organisation: University of Manchester
Department Name: Computer Science

Abstract

The project will build a demonstration information and knowledge management system (IKMS) to facilitate innovation with
new and replacement chemical materials from renewable biomass in formulated products. The IKMS will enable functional
ingredients from simple transformations of feedstocks to be identified more quickly and recommend the best feedstocks for
a particular function. If successful, it will repair a disconnection in the supply chain for exploitation of bio-based and
renewable materials as functional ingredients in formulated products, creating significant business benefit to the commercial partners and, following dissemination and further development, to the UK bio-based materials sector and
formulated products businesses as a whole. The demonstrator will focus on a search for bio-surfactant innovations, and will
be innovative in itself by both integrating several IT tools for the first time in a radical approach to formulated product design
and by being the first of its kind to be applied across a chemical using industry supply chain.
The ambition of the system is that it will collate and manage existing data with new data recovered from the experimental
measurements and use this to update the models applied by the search tools. An automated data-driven modelling tool will
be developed and integrated into the system for this purpose. As data is added and as models are improved, the
performance of the selection algorithms will improve along with the chances that the selected ingredient and formulation
candidates will meet downstream commercialisation criteria. It is important to note that modelling methods used here are
quite different but complementary to those to be developed under the TSB funded ICT project 101508, which are physicsbased
rather than data-driven, and will provide powerful capability for fast selection of novel chemistries against a subset of
filter criteria and provide mechanistic insights to sharpen these filters for better precision and better experimental assay
design.
To achieve its objectives, the project will extend the 101508 information model and add a repository to store formulation
information (composition and assembly) and property data (experimental and computed) to complement the feedstock and
transformation repositories. The information model and repository will need to be chemically intelligent, use readily
extensible RDF and triple store technologies, and incorporate semantic search capabilities to facilitate integration.
Modelling tools will be adapted and implemented using modern machine learning methods to find the mathematical
relationships between ingredient structure and properties, and between formulation composition and assembly with
application performance. The models will be built on data created during the project and added to the 101508 model
repository. The 101508 tools for enumerating ingredient options (from feedstocks and chemical transformation processes)
will be extended to enumerating formulations (from ingredients and assembly processes). The enumeration tools will be
coupled to a global many-objective search tool using diversity or chemical structure/formulation composition/assembly -
property models for efficient exploration of the combinatorial ingredient/formulation space.
We will also develop tools to help maintain and grow the IKMS with minimal overhead to future projects. These include
semantic search and semi-automated extraction of appropriate data from literature and other available resources, and for
ontological integration and semi-autonomous building of ontologies where these do not exist.
In order to demonstrate how this system will work in practice, novel bio-surfactants identified in 101508 will be made and
their properties measured, a selected sub-set formulated and evaluated and the data and derived models used to drive
another cycle of bio-surfactant selection and formulation optimisation.

Planned Impact

The main impacts of this work are the environment and manufacturing business. Underlying the proposal is the aim of
reducing reliance on oil based ingredients and greater exploitation of waste materials from plants. Meeting such goals will
help address the green agenda of both the manufacturing partners and the UK government. The manufacturing sector
benefit by reduced costs, reduced reliance on oil for their ingredients, as well as the access to a greater variety of
functional formulated products apparent in plant based feedstocks. The producers of such feedstocks and formulated
products benefit from a greater market potential for their products. Inside the consortium the minimal ECONOMIC benefit to
Unilever is the estimated low scenario NPV of £13.3m from a 2016 launch to 2020 for a bio-surfactant exploited in a
laundry liquid detergent. It is anticipated that these benefits will be much greater from the globalisation of bio-surfactant
containing products and other functional ingredients in other product types. Croda and British Sugar should also benefit
where they participate in these supply chains over all these scenarios and other supply chains for other chemical using
sectors than home and personal care. Unilever publically declared an ambition to reduce GHG by 50% in 2020. Innovation
is key to achieving this and the IKMS will support this environmental benefit explicitly by consideration of sustainable
materials & energy consumption in sourcing and processing, and utilisation of waste (and therefore avoiding its disposal).
Outside the consortium it is anticipated that similar and/or greater economic benefit will flow to other in chemical using
industries from the use of the IKMS to select functional ingredients for other applications. It is also anticipated that the
academic advances in information management and analysis and many criteria search and optimisation could be applied to
many ECONOMIC (e.g. more effective & efficient innovation inengineering), SOCIAL (e.g. diagnosis and treatment in
health care) and environmental (e.g. more effective and efficient innovation in water and energy management) domains.
Outside the consortium environmental and social gains will be derived through reduced road transport (congestion, noise
and emissions (see TSB Project TP/ZEE/7/N0036A) because reduced amounts of bio-surfactant compared with existing
materials will be used, resulting also in decreased impact on water treatment facilities. Reduced energy and solvent use will
also benefit the environment and reduce energy costs to the industrial partners within the consortium, while also
decreasing dependence on non-renewable petroleum-derived materials. Cybula could expect economic benefit from
commercial use of the IKMS and increased commercial use of its YouShare platform. The establishment of this IKMS in the
local research ecosystem provides SOCIAL benefit in further demonstrating Unilever, Croda and AB Sugar's commitment
to supporting R&D activity in the UK with its concomitant benefits to society and the economy. SOCIAL benefits will come
from improved consumer products, with additional functionality that these materials offer to the consumer like mildness.

Publications

10 25 50
 
Description The development of the Integrated Knowledge Management System has demonstrated that it is possible to find potential ingredients for body care products from biorenewable sources. Managing the knowledge of the chemical composition and the potential transformations of those chemicals enables an exploration of possible routes to developing surfactants.
Exploitation Route The demonstrator developed in this project has potential for chemical engineers to explore routes to sustainable manufacturing of chemicals at a lowered cost.
Sectors Agriculture, Food and Drink,Chemicals,Digital/Communication/Information Technologies (including Software),Environment,Healthcare,Manufacturing, including Industrial Biotechology,Retail

 
Description 4th UK Ontology Network Meeting, Leeds 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Demetriou, G., Nenadic, G., Read, W. J., Stevens, R. & Winter, J. (2015). The BioHub Ontology for Sustainable Bio-Feedstocks.
Year(s) Of Engagement Activity 2014
 
Description SWAT4LS International 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Read, W. J., Demetriou, G., Nenadic, G., Ruddock, N., Stevens, R. & Winter, J. (2015). The BioHub Knowledge Base: Ontology and Repository for Sustainable Biosourcing.
Year(s) Of Engagement Activity 2015
 
Description Talk at the 5th UK Ontology Network Meeting, Newcastle upon Tyne 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Demetriou, G., Read, W. J., Nenadic, G., Ruddock, N., Fletcher, M., Jackson, T., Stevens, R. & Winter, J.(2016). Integrating literature mining and curation for ontology-driven knowledge discovery. Talk at the 5th UK Ontology Network Meeting, Newcastle upon Tyne, UK, April 14.
Year(s) Of Engagement Activity 2014
 
Description The Ninth International Biocuration Conference, Geneva 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Demetriou, G., Read, W. J., Fletcher, M., Ruddock, N., Nenadic, G., Jackson, T., Stevens, R. & Winter, J.(2016). A Curation Pipeline for Bio-derived Chemical Feedstocks. The Ninth International Biocuration Conference, Geneva, Switzerland, April 10-14.
Year(s) Of Engagement Activity 2016
URL https://www.sib.swiss/events/biocuration2016/posters#none