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Learn how we're pioneering a new wave of precision medicine, explore our collection of publications, disease studies, webinars, thought leadership, and more

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COVID-19 Disease Study

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How can mechanistic patient stratification inform R&D in complex chronic diseases?

Groundbreaking disease biology and drug discovery insights revealed by stratifying patients using combinatorial analytics

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Publication

Genetic Risk Factors for ME/CFS Identified using Combinatorial Analysis

Groundbreaking study published in the Journal of Translational Medicine provides the first detailed genetic insights into the mechanisms underpinning ME/CFS

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Disease Study

Alzheimer's Disease Study

Understanding disease mechanisms to identify novel targets and patient stratification biomarkers - improving the probability of future clinical trial success in Alzheimer's disease

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Webinar

Disease Mechanisms and Novel Target Discovery

Watch on-demand as PrecisionLife CEO, Dr Steve Gardner, joins Cyclica CEO, Naheed Kurji, to explore disease mechanisms and novel target discovery

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Blog

Our Philosophy

A deep dive into our unique approach and our mission to find better treatment options for patients with unmet medical needs

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Publication

Cell Patterns: INDx Systematic Indication Extension

Paper demonstrating the potential of indication extension to systematically reposition hundreds of drugs into new indications

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Publication

Combinatorial analytics: An Essential Tool for the Delivery of Precision Medicine

An Opinion, published in the new Open Access Journal Artificial Intelligence in the Life Sciences from Elsevier, describes the need to extend our current analytical methods to effectively interrogate population data sets

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Disease Study

COVID-19 Disease Study

Understanding the disease biology of COVID-19 to find novel drug targets and new treatment options

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Blog

Proving the Power of Combinatorial Analytics

A summary of how >70% of associated novel gene targets for severe COVID-19 identified with combinatorial analytics in May 2020 have now been independently validated

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