Italy’s Axxam and Molecular Health have partnered to identify and validate new therapeutic targets in drug development.
Their partnership will integrate Dataome, the digital drug development platform of Molecular Health, into Axxam’s integrated early drug discovery process, DiscoveryMAXX, creating a combination of computational clinical-molecular insight and biological validation for the pharma and biotech industry.
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The Dataome platform integrates and structures molecular, clinical and phenotypic data from various datasets.
It provides causal insights that assist pharmaceutical firms in enhancing the development processes of drugs, predicting their safety, optimising trials, and enabling data-driven investment decisions.
The use of AI by Molecular Health enables the analysis of complex datasets, helping its clients identify potential drug targets.
The computational predictions will be integrated into Axxam’s discovery platform, which has expertise in biology, assay development, compound profiling, and phenotypic and target-based screening.
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By GlobalDataThe collaboration ensures that AI-derived targets are subjected to experimental validation using in vitro technologies, such as induced pluripotent stem cell (iPSC)-based models, to confirm their biological and disease relevance and their translational value.
Axxam CEO Ciriaco Maraschiello stated: “This strategic partnership between a biology powerhouse like Axxam and a precision medicine-focused AI company like Molecular Health is enabling a new level of accuracy and efficiency in the early drug discovery process, allowing our clients to make more informed decisions faster in both preclinical and clinical development.”
Axxam is a provider of integrated discovery services in the life sciences industry, supporting a diverse range of clients including pharma and biotech firms, start-ups, patient foundations and academic groups.
Molecular Health provides data-driven software technologies and its Pharma AI solutions power various aspects of drug development, from indication and biomarker discovery to trial design and safety prediction.
