| CHEMICAL INDUSTRY JOURNAL |
| environmental & health and safety |
‘Omics’ spinout brings new era in chemical safety Mounting pressures across the globe to allow more cost-effective, higher throughput, non-vertebrate chemical safety testing are at last bringing much needed change. The US Environmental Protection Agency has made commitments to reduce vertebrate animal testing, and in 2021 the European Parliament adopted a Resolution calling on the European Commission to establish an EU-wide Action Plan for the active phase-out of the use of animals in experiments. University of Birmingham spinout, Michabo Health Science Ltd, talks to Chemical Industry Journal about its novel work to accelerate the safety assessments of industrial chemicals. The company’s founders, Professor Mark Viant, Chair of Metabolomics, and Professor John Colbourne, Chair of Environmental Genomics have specialised for two decades in developing novel laboratory and computational methods to deliver higher throughput precision toxicity testing.
However, complementing conventional grouping with grouping based on biological response data, which provides molecular information of the mode(s) of action (MoA) of chemicals, can significantly increase confidence in the grouping hypothesis2,3.
BIOLOGICAL RESPONSE DATA
FAILED RISK ASSESSMENTS
The team at Michabo Health Science has been working with chemical regulators since 2018 to develop a procedure to incorporate molecular data into chemical grouping. This New Approach Methodology (NAM) uses laboratory and computational methods developed over the last decade by researchers from the University of Birmingham’s School of Biosciences.
“Grouping and read-across” is the most widely used nonanimal testing method for industrial chemicals in Europe. It is based upon having toxicity data for one chemical (the source substance) that can be copied across to predict the toxicity of the chemical that is being risk assessed (the target substance). To do this reliably, however, the two chemicals must be categorised as belonging to the same group; the scientific justification for this is called the “grouping hypothesis”.
NAMs are methods that bring greater robustness, throughput and mechanistic knowledge into risk assessment, and enable more relevant decision making for human health and the environment, and the European Chemicals Agency (ECHA)’s ECHA’s Director of Hazard Assessment has recently commented positively on the conceptual progress being made in NAMs for regulatory chemical risk assessment4.
Conventionally, forming a group has been attempted by comparing the chemicals’ physico-chemical properties and/ or structures, and if they are similar enough, then the toxicity data can be read across from the source to the target.
Central to the company’s NAMs are ‘omics’ technologies, which measure thousands of molecular responses to chemical exposure, coupled with data interpretation procedures to analyse the molecular data to group chemicals and predict their potential hazards.
Michabo Health Science focuses on supporting the regulation of groups of chemicals, thereby reducing the costs associated with vertebrate animal testing – and speeding up risk assessment for new and existing chemicals.
Yet regulators currently reject the majority of industry’s risk assessment dossiers, and commonly cite lack of confidence in the ‘grouping hypothesis’ as a reason for rejection1. Professor John Colbourne
Professor Mark Viant
Omics technologies were developed over 20 years ago and have become a central pillar of biomedical research and more recently for medical diagnostics. Deployed in chemical safety science, they can also measure a broad range of molecular responses of a biological test system to chemical exposure. The NAMs employed by Michabo Health Science include transcriptomics – which measure how thousands of genes in a cell, tissue or organism respond, providing information on the ‘upstream’ parts of a chemical’s mode-of-action. Michabo also uses metabolomics, which characterise how thousands of small-molecule metabolites involved in biochemical processes respond to chemical exposure, providing information on the ‘downstream’ MoA, which is closer to traditional measures of adversity.
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