Taxonomy3®
Discover & validate proprietary drug targets using human genetic data

Taxonomy3® is a novel in silico platform technology that utilises proprietary ground-breaking mathematical algorithms to perform complex multivariate analysis of genetic data. As part of plans to significantly increase its pipeline, the Company added this unique target discovery and validation platform to its drug discovery capabilities in March 2016 through the acquisition of Adorial Ltd.

taxonomy3 progression

Taxonomy3® is used to analyse complex genetic datasets to identify and characterise novel drug target candidates. Since these novel targets are based on human genetic data, the resulting drugs have a greater probability of successful clinical development and product realisation. By performing highly sensitive in silico mining and analysis of publicly available DNA databases, Taxonomy3® is able to identify previously unknown genetic linkages and interactions between genes and biological pathways in a broad range of diseases. This enables the discovery of targets that cause disease, rather than those that are simply associated with its symptoms, and thereby provides the best starting point for drug discovery, biomarker identification and patient stratification, and ultimately improving the chances of clinical success.

taxonomy3 multivariate approach

Compared to univariate approaches, which are standard in the field, the multivariate approach employed by Taxonomy3® provides greater sensitivity and therefore reveals more disease targets. Additionally, it allows gene-gene interactions to be explored to potentially highlight critical biological pathways having a causal nature in disease.

Taxonomy3® was co-developed with academic experts from the universities of Oxford and Lille and has been used in partnership with several of the world’s largest pharmaceutical companies, including Takeda and UCB Pharma. Multiple new targets in rheumatoid arthritis, Parkinson’s disease and ophthalmology have been discovered using the technology.