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Why early participant engagement is now a top priority in genetic disease research

pharmaphorum

In 2016, scientists behind a study called the Resilience Project analysed genetic data from 589,000+ people and found 13 adults who carried genetic variants that should have resulted in serious – even deadly – childhood disease, but who were apparently healthy. First, start co-development with participants early on in the process.

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Can genetic data be a magic bullet for drug R&D?

pharmaphorum

Drug development has long been an issue for the pharma industry, due to the expense and the high failure rate of potential treatments. Ben Hargreaves finds that the vast amount of genetic data that exists today could help provide a faster, more targeted way of developing new drug candidates.

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Study reveals first genetic links in ME and Chronic Fatigue Syndrome

Drug Discovery World

A new study has provided the first detailed genetic insights into the pathophysiological mechanisms underpinning Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). . The results were presented at the ME Genetics Research Summit organised by ME charity, Action for ME and the MRC Human Genetics Unit, University of Edinburgh. .

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Biorepositories as a Guiding Resource for Research & Drug Discovery

XTalks

Data generated through high-throughput omics approaches paired with clinical patient records can give rise to remarkably robust datasets to inform and guide disease insights and development of targeted therapeutics. Biobanks are used for the coordination of high-yield patient sample collection.

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HFpEF vs. HFrEF: How To Improve Heart Failure Drug Development

XTalks

Experts from Servier and Genuity Science recently spoke on a webinar about using genomics data to drive drug development in heart failure and identify new targets for novel therapeutics. The reverse could also be true whereby the development of coronary artery disease may impact heart rate. HFrEF vs. HFpEF.

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How biomarkers can help discover new treatments for women’s health

Drug Discovery World

RA: You’ve recently announced a collaboration with the University of Oxford to access genotype data on women with endometriosis. We previously conducted a hypothesis-free study using genotype data from the UK Biobank, which resulted in the first mechanism-based stratification of endometriosis patients.

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