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Our automated machine learning system rapidly identifies the features driving variation in patient outcomes — streamlining the development of precision medicines.
About
For precision medicine, “big data” can be used to identify the genetic and clinical factors responsible for patient variation in clinical outcomes, drug response, or biomarker levels. Conventional analysis of these large datasets can, however, be very time-consuming, highly complex and may require high level bioinformatics expertise, leaving you unable to quickly move your precision medicine projects forward.Pharmacology-AI makes finding actionable insights from your data quicker and easier. Powered by an explainable machine learning platform, developed in collaboration with IBM and STFC, this automated system rapidly identifies the features driving variation in patient outcomes — streamlining the development of effective patient stratification strategies.
Key Benefits
Pharmacology-AI can identify responsive patient populationsDespite advances in ‘omics’, clinical drug attrition remains high. When used as a stand-alone platform or when combined with our h uman living tissue data, Pharmacology-AI can help identify the optimum patient population for your drug therapy. This allows you to:Identify patient profiles most likely to benefit from future trials.Enable smarter clinical trial design.Improve the chances of clinical trial success
Applications
Scientists and clinicians with clinical or genomic dataIf you are looking to obtain useful insights from your existing data, Pharmacology-AI can identify the key features driving biomarker levels, drug response, or clinical outcome. View AI analysis outputs in an easily interpretable and interactive format via a secure portal built in compliance with industry standards.Inflammatory Bowel Disease (IBD) researchersUsing human living tissue IBD assays, our IBDiscovery service offers a study with your chosen drug to generate data on your target patient population. Our scientists then analyze these data via machine learning to identify the key ‘omic’ or clinical features driving differences in drug or biomarker response.Whilst Inflammatory bowel disease is our initial area of research focus, the same concept can be applied across a number of organ systems and therapeutic areas. If you would like to utilize this technology in a different area then please contact us to discuss.