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Patient X, suffering from an untreatable gastrointestinal disease, chats with a large language model called GPT for advice. GPT suggests looking at clinical trials and Patient X finds 10 active recruiting trials but is unsure which to choose. Patient X consults his doctor who recommends a trial from a pharmaceutical company. What could go wrong?
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At SciBite, we are passionate about enabling organizations to make full use of their data to help them make evidence-based decisions, especially to help organizations overcome their healthcare digital transformation challenges. To support organizations on this journey, we offer a suite of products to help organizations adopt FAIR data standards.
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Precision medicine is changing the way that we think about the treatment of disease, moving from broad-acting therapies to therapies tailored to the individual patient. This increasingly relies on real-world data (RWD), encompassing a diverse range of sources, spanning multi-omic molecular characterisation of the patient’s condition, clinical presentation, treatment, and broader medical histories.
ReadIn this piece we'll show how natural language processing can be applied to build a searchable database of disease biomarkers, presented in the context of their corresponding scientific publications. To illustrate the power of this approach we'll focus on examples of protein biomarkers relating to Breast Cancer.
ReadThroughout this blog we highlight some complexities that exist in extracting meaningful information from patents and show various solutions, making use of SciBite technology alone or, augmented by or delivered by our partners.
ReadIn this blog, we explain more about our Immunonc vocabulary, comprising the concepts relating to this field, which enables our customers to be better informed about the current advances and emerging trends in cancer immunotherapy research, keeping them at the forefront of cancer treatment.
ReadIn this blog post, discover how Pfizer have integrated SciBite’s semantically enriched vocabularies into their Data Commons project, which has the goal of enabling scientists to develop and refine hypotheses by investigating correlations between genetic and phenotypic data.
ReadSciBite's latest TERMite 6.3 release includes a new set of clinical ontologies as it introduces a set of CDISC vocabularies.
ReadThe work presented here describes the winning entry to a challenge set by ARM, Atos and Cavium at the Wellcome Genome Campus Hackathon 2018.
ReadOnly 50-75% patients respond beneficially to first-line drug therapy, causing unnecessary costs to healthcare providers and, more importantly, adversely impacting a patient’s quality of life.
ReadGet in touch with us to find out how we can transform your data
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