× Medicines Discovery Catapult

If you liked c1cccnc1, you’ll love c1cncnc1

One of our collaborators, Intellegens, recently published a great paper in JCIM – Imputation of Assay Bioactivity Data Using Data Learning – focusing on applying Deep Learning approaches to tackle the problem of sparse data, a recurring issue in drug discovery. Sparse data typically arise when compounds are being assayed against multiple biological targets, but […]

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A guide to sourcing biosamples

Medicines Discovery Catapult and the BioIndustry Association stated in their 2018 State of the Discovery Nation Report, that: “… over 80% of SMEs surveyed agreed that access to biosamples is hugely important for commercial development” and “… as many as 80% found accessing UK samples unexpectedly difficult…” A major recommendation of this report was that […]

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Using AI in drug discovery

In recent years, machine learning and Artificial Intelligence (AI) have become widely popularised in all areas of modern life, and drug discovery is no exception. Why AI? The benefit of AI for detecting novel drug-target interactions, or even in silico design of novel drug-like compounds, is clear. The possible chemical search space of potentially synthesizable […]

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The many ways charities can boost innovation in medical research

Among the wealth and diversity of stakeholders that bring science out of the laboratories and closer to patients, charities are usually regarded as the hands-off funders of research. However, an increasing number of biomedical research charities have been taking a more proactive and involved role in boosting innovation in the therapeutic areas they support. Action […]

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International Women’s Day – 5 questions with Dr Gemma Holliday

1. What challenges have you faced, as a woman, entering this industry? The biggest by far is Imposter Syndrome, I think most people will suffer from this at some point in their lives (and I don’t just mean women!). It’s not an easy one to overcome either – and the only advice I can offer […]

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New methods to improve the translation of biomedical science towards clinical trial success

It is now over ten years since John Ioannidis published his essay on ‘Why most published findings are false’. This paper presented statistical arguments to remind the research community that a finding is less likely to be true if: 1) study size is small, 2) effect size is small, 3) a protocol is not pre-determined […]

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The (re)emergence of an Oncology drug discovery ecosystem

Attending the recent BioNow Oncology event at Alderley Park, I was struck by the strength of an Oncology drug discovery interdisciplinary community in the North West, which hardly existed at all a few years ago. Or, perhaps more accurately, did exist but was hidden behind the tall walls of Pharma. Many ex-AstraZeneca scientists have emerged […]

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AI says no, but can you trust your model?

Any machine learning algorithm can make predictions about a quantity of interest, whether it be bioactivity, lipophilicity or solubility. But, how much confidence should you have in the model? Several quality indicators for predictive models exist; for example, how well it performs in cross validation. Cross validation is one of the key techniques used to […]

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How blood DNA, as a biomarker, is revolutionising cancer treatment

With the advent of personalised medicine, cancer research is not only a matter of finding drugs that kill cancer, but determining which patients are most likely to benefit from a given type of treatment. The finding that cancer cells release their DNA into the bloodstream revolutionised the way we gain insight into the cancer’s biology. […]

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