Funding available until: 18 November 2017
This Solution received CRACK IT Solutions funding. For further information about the project and impacts see our science pages.
CRISP is a comparative in silico structural/functional platform that offers potential for identifying species differences in liver activity. It enables users to screen a candidate compound against proteins of the liver to identify predicted molecular interactions (“hits”) and then compare them in terms of affinity, binding orientation, protein function, and downstream metabolic and signalling pathway effects, to hits in other organisms for the purpose of selecting the most appropriate animal model for subsequent trials. Moleculomics seek industry partners to help validate the technology using in vitro and in vivo hepatotoxicity data.
It is widely acknowledged that animal models are not always accurate predictors of the effects of a substance on humans, other animals or the environment. Species of high phylogenetic linkage (mouse-rat or primate-man), do not necessarily possess the same biochemical mechanisms or physiological responses to a particular compound . The FDA states that 9 in 10 compounds fail in clinical studies “because we cannot accurately predict how they will behave in people based on laboratory and animal studies” . This attrition limits the development of safe and effective new chemical entities (NCEs) and therapeutics and is a major financial burden, providing significant incentive to develop an in silico platform that can inform researchers as to the most appropriate model system (if any) for investigating the efficacy or toxicity of a given compound.
Moleculomics offer structurally-based whole proteome lead discovery, toxicity screening and protein network identification. These tools have been integrated for the purpose of developing a CRISP prototype that can be used to compare activities of key liver proteins and downstream metabolic and signalling pathways across different species. The platform comprises structural models for all liver proteins; around 1,100 each of mouse, rat and human liver (mouse and rat account for 84% of all animal tests in the UK ). CRISP facilitates the identification of target proteins that share high structural homology across the three organisms and those that share broad structural homology but may possess critical structural differences affecting activity/specificity. Incorporation of an in vitro knowledgebase aggregating five established databases (IntAct, BioGRID, Reactome, KEGG, CTD) provides downstream signalling and metabolic pathway information, cementing CRISP as a leading biosimulation tool for the identification of the most suitable animal model for a given NCE development program.
Moleculomics has extensive experience of developing innovative Biosimulation solutions. As a catalyst for the advancing of alternative technologies for compound development, Moleculomics has delivered bespoke Biosimulation platforms for a range of high profile customers. Two projects of specific interest include: 1) NC3Rs CRACK IT challenge (sponsored by Unilever and Dow AgroSciences) to link molecular initiation events to adverse outcome pathways using in silico methods. 2) Moleculomics has successfully completed a Centre for Defence Enterprise project for the development of a multi-genome platform for the identification of drug targets common to key microorganisms. These two proof-of-concept studies demonstrate practice of innovative algorithms, high throughput structural modelling and screening, translation to alternative organisms and prototype development.
With ambition to facilitate whole proteome analysis, CRISP is initially focusing on the liver, as drug induced liver injury (DILI) has been the most frequent single cause of safety-related drug marketing withdrawals for the past 50 years  and effects on the liver are often used in the setting of reference doses for agrochemical risk assessments . With applications across the agricultural and pharmaceutical industries, regulatory bodies such as FDA and EFSA agree that an approach is needed to distinguish compounds likely to cause severe DILI from compounds unlikely to do so .
Whilst in vivo or clinical drug trials are generally required in the legislative approval and dosage recommendations of new compounds, this systemic approach provides restricted mechanistic information regarding molecular mode of action, and therefore limited capacity to predict pathological, physiological and pharmacological consequences. In contrast, in vitro and in silico tests offer molecular level understanding of biological processes and as a result are increasingly employed in compound discovery and development , the shortcoming in the past being a lack of whole proteome coverage.
Alternative protein structure-based in silico solutions, formulated on analysis of a handful of key proteins only (such as CYPs) do not offer the scale or breadth of CRISP, which spans the entire liver set of multiple proteomes. Such scale enables the Moleculomics approach to predict the Molecular Initiation Event (MIE) – the predicted binding of a compound with a protein, then return all proteins implicated in the pathway of the MIE before performing a structural similarity search to identify the similarities/differences with respect to structure and function of every protein implicated in the binding event between different species. Other in silico offerings are approached from a cheminformatics perspective, like quantitative structure activity relationship (QSAR) models which, although incorporating extensive knowledge of chemical structure and its linkage to general biological activity, do not benefit from mechanistic knowledge of specific protein-ligand interactions at the whole organ scale. This mechanistic knowledge, combined with the capacity for inter-species comparison, provides more meaningful information for scientific and commercial decisions involving animal testing.
These advances will result in a system which enables comparison of structure and function of drug receptors and associated pathway analysis to reduce inappropriate use of an animal model for tests which may be of limited or no scientific value, while confirming the most appropriate animal, if any, for in vivo testing.
CRISP defines the potential of a small molecule compound to interact with metabolically crucial liver enzymes and receptors across a range of different species. Understanding the differences in structure, binding function and metabolic pathway effects of major biological importance across different organisms will enable informed selection of the most appropriate animal model. CRISP, once validated, will result in a wealth of molecular data and knowledge of the relative appropriateness/biological relevance of the testing of a given compound in a particular organism, through the integration of high throughput structural modelling of proteins, molecular docking and in silico pathway analysis. This will facilitate rapid decision making within the R&D pipeline, assisting problematic compounds to fail sooner by modelling and flagging up of protein-ligand interactions that evoke undesirable pathway outcomes.
CRISP is presented here as a proof-of-concept prototype, applied to a single organ (the liver) and the most commonly used animal species involved in clinical trials (rodent models). Following successful completion of this proof-of-concept, CRISP will provide a comprehensive tool for early flagging of protein-mediated efficacies and toxicity issues of compounds in relation to the liver, on a large scale and comparatively across human and two commercially and scientifically important model systems. We then plan to scale the technology to whole proteome analyses for human, cross referenced to all species used in animal testing, to realise the true potential of the technology.
CRISP has the potential to be a valuable tool for efficient development of safe and innovative products in several high impact sectors such as agro-industries, pharmaceutical, biotechnology and defence. However, it is appreciated that industry will only adopt our tool if utility is demonstrated.
Moleculomics seek project collaborators to assist in validation by providing information on a small number of “blind” small molecule test compounds for which in vitro protein assay and in vivo liver toxicity endpoint data is available. This will supply Moleculomics with valuable information required to both train and test the prototype to enable commercialisation of the technology, and will provide a robust foundation upon which the technology can be scaled in order to facilitate whole proteome analysis across a broad range of animal species frequently involved in preclinical trials.
In addition to the proposed validation using in vitro and in vivo hepatotoxicity data, long-term partnerships are sought to apply CRISP for the purpose of decision making in toxicology risk assessment. Partnerships are sought with companies whose work involves extensive compound discovery and/or appropriation, and for whom in the longer term, the platform would form an integral part of their compound -selection and/or risk assessment.
Moleculomics confirm the IP required to deliver the predictive molecular interaction components of work is proprietary and that other information used in this project exists in the public domain.
Moleculomics seek to overcome poor animal/human correlation, a key contributor responsible for the 90% of drugs which fail in human trials despite passing traditional toxicology tests involving rats , through reliably predicting similarities and differences between human and animal models for the purpose of selecting more appropriate tests. CRISP will enable the elimination (or cautionary advising) of tests where the animal model used would provide a poor representation of the human biochemistry, and allow the selection of more appropriate animal models to both negate unnecessary and repeated tests and simultaneously improve the efficiency of the compound development process.
This will act to address the unnecessary use of animals in the measurement of toxic and therapeutic effects of chemical compounds. Additionally, new molecular knowledge that can be assimilated through CRISP will broaden scientific understanding of the mechanistic actions of NCEs and could negate the need to observe some systemic symptoms. For example, in the case of the Draize test and when applied to whole proteome analyses, CRISP has potential to predict which proteins of the human eye may be implicated through exposure to a candidate chemical compound and compare the structure and pathway data to that of rabbit for the purpose of evaluating the relevance of the rabbit model. The aspiration is to develop the technologies to support the objectives of the NC3Rs and place in silico screening at the centre of how new compound based products are developed.
- Heywood R, (1990). Clinical toxicity - could it have been predicted? in Animal Toxicity Studies: their relevance for man, (Lumley and Walker, Eds) p57-67.
- FDA Press Release “FDA Issues Advice to Make Earliest Stages Of Clinical Drug Development More Efficient”. http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/2006/ucm108576. htm accessed 16/2/16.
- Home office Report –Annual statistics of scientific procedures on living animals – Great Britain, 2013; https://www.gov.uk/government/statistics/statistics-of-scientific-procedures-on-living-animals-great-britain-2013.
- Guidance for Industry Drug-Induced Liver Injury: Premarketing Clinical Evaluation, U.S. Department of Health and Human Services - Food and Drug Administration Center for Drug Evaluation and Research (CDER) Center for Biologics Evaluation and Research (CBER) July 2009 Drug Safety. https://www.fda.gov/downloads/Drugs/.../Guidances/UCM174090.pdf.
- Investigation of the state of the art on identification of appropriate reference points for the derivation of health-based guidance values (ADI, AOEL and AAOEL) for pesticides and on the derivation of uncertainty factors to be used in human risk assessment. https://www.efsa.europa.eu/en/supporting/pub/en-413.
- World Biosimulation Market - Opportunities and Forecasts, 2014 – 2022 https://www.mordorintelligence.com/industry-reports/global-biosimulation-market-industry?gclid=Cj0KEQjwhpnGBRDKpY-My9rdutABEiQAWNcslI9Hjdqagli5TubBTsPpAS2pIrwnGdvLUjRRbqqaBxMaAkdA8P8HAQ.
- Sankar U (2005). The Delicate Toxicity Balance in Drug Discovery. The Scientist 19:32.