We often take our health for granted. The cells and tissues in our bodies work steadily and reliably in the face of constant challenge. This stability comes about because the underlying molecules (such as proteins and nucleic acids) are organised to function in complex, robust networks, giving rise to reliable and predictable behaviour (a phenotype). Even when we develop a disease. The underlying networks remain robust and difficult to change.
Modelling and analysis of these networks provides a novel approach to drug discovery that explicitly considers the true complexity of biology. By representing, as closely as possible, the biological systems we are seeking to disrupt we increase the likelihood of identifying and developing effective therapies.
Our platform is a combination of large-scale, proprietary databases and a suite of powerful computational tools that employ network analysis, data mining, machine learning, Al and optimisation. The novelty of our biology-centred approach, underpinned by integration of multiple disparate data sets, enables the characterisation of currently intractable or undruggable disease processes and the identification of the best ‘network-aware’ intervention strategies.
We have the capability to address some of the key challenges of our industry, including extracting value from big data, addressing complex disease and other areas of unmet need and improving translatability in R&D.
We perform in silico phenotypic screens to generate sets of small molecules that are enriched in active compounds ensuring high in vitro hit rates in complex phenotypic screens. The ability to deploy representative assays that replicate human disease biology more closely in early screening greatly improves translatability and helps avoid extremely costly late-stage failures.
Our technology enables us to create actionable insights from GWAS data by considering the long and often difficult-to-interpret lists of genes in the context of the biological networks they belong to. This allows us to identify key disease-related biological processes and pathways that can support a target identification or an NDD project, depending on the preferred therapeutic modality and discovery approach.