Using machine learning to super-charge anti-infective drug discovery: the case of Halicin

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Yes, it’s true. There is more to HCAI & AMR (and this blog) than COVID-19! To prove it, I’m posting on something different today – the use of AI to streamline the anti-infective drug discovery process. Scientists at MIT have used machine learning (aka “deep learning”) to improve the drug discovery process, by predicting antimicrobial activity in molecules that are different from known antibiotics. This process has yielded Halicin, a promising candidate molecule for a broad-spectrum antimicrobial agent – which is, of course, a long way from clinical trials!

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COVID-19 Preparedness Survey

After discussions on IPC measures for COVID-19, some members of ISAC’s IPC working group decided to created a survey. The group would very much appreciate your participation:

https://www.surveymonkey.com/r/COVID-19_IPC

Thanks for your help

COVID-19 and my idea on masks

Next to the idea that we see many contraptions (you can’t even call them masks) we see many people with all kind of masks, in and outside our healthcare settings. Certainly after my last flight to a WHO meeting on COVID-19, I had the feeling that it is time to write about masks.

On my way to Geneva, the gentleman to my left (yes, thanks to a canceled flight, I was in the hated middle seat) was calm, sleepy and wearing a mask. The fellow on my right, clearly had the sniffles, came from somewhere far away and was spreading his respiratory secretions in all directions, including mine. I so wanted to pull of the mask from calm-sleepy-guy, to place it on the next-seat-germ-blower.

How easy could basic prevention be? Wouldn’t it be fantastic if people would adhere to simple principles of how to cough and sneeze in public: turn away from others, use a tissue or elbow, followed by hand hygiene? Why don’t the people on buses, trains and airplanes don’t know this? If in addition, anyone who is sick gets a surgical mask while in public, we might have a way of preventing (or at least delaying) the spread of respiratory viruses. Instead, masks are worn by the healthy, leaving the sick (and soon-to-be hospital patients) without the needed protection.

Talking about masks in healthcare; Nearly every country I know off, went for maximum safety, recommending FFP2 masks (similar to N95). I would have suggested to use FFP1 for the majority of cases, and FFP2 only during high-risk procedures. But how can I, if everyone else seems to go “full safety”. Another reason, why I believe that my idea wouldn’t have been too bad, is the high probability that soon we will have a shortage of FFP2 and will have to tell our HCWs that FFP1 and surgical masks are “equally save”. Yes, I can see how they believe me and willingly expose themselves to the increasing number of patients with less than previously needed PPE! I believe that we have valid reasons to consider evidence over maximum safety, and that while we didn’t even start to talk about discomfort and physical effects associated with prolonged use of FFP2. Continue reading

Update on COVID-19: part 13, it giet oan?

In February many in my country just want to hear three words: “it giet oan”. This means that the famous eleven city ice-skating race will actually happen. Since 1909 this occurred 15 times (last time in 1997), as it needs about three weeks of continuous frost. No chance for that this year, but the words must have crossed many clinical microbiologists’ mind this weekend when the news on SARS-CoV-2 from Italy unfolded. Continue reading

Update on COVID-19 caused by SARS-CoV-2; part 12

part from its new name, nothing really happened in the last week. New confirmed cases per day remained high, seemed to decline somewhat until it became clear that there was shortage of testing capacity. Definition adapted, and then the numbers of infected patients in the affected Chinese regions exploded. So, one question answered from previous blogs: it’s big in China and we may (still) not know everything that is happening there (or in some other countries). Continue reading

Update on 2019-nCoV: part 11 – where will it end?

I’m sure we’ve all been following the emerging story of the 2019-nCoV outbreak closely, with the third cases reported in the UK yesterday (pleased to see this is where you’d expect the UK to be based on Marc’s post earlier)! There’s been a small explosion of publications in the peer reviewed literature. I’ve chosen one slightly randomly to discuss today: a short modelling study providing some insight on the likely volume of unreported cases (very much the ice berg and not the tip!) and some sense of where this outbreak will end (it depends on how we respond, globally).

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