A good entrepreneur has a canny intuition for their True North. I’ve heard this from many good investors.
Personally I’ve always believed it. One of the bases through which I judge my professional contacts is on their decision making ability. Some people seem to always make good choices. Others, faced only with good outcomes, somehow still manage to find a more painful outcome.
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Marco Schmidt, the CSO of Biotx.ai, and I have published an opinion article in the Pharma Boardroom online trade journal. We have been discussing the topic ever since my first keynote talk at the launch of the Charité Digital Health Forum in 2018 (a video of the same talk is available from PyData 2018).
We title the article: Pharma’s Data Problem.
Continue reading “New article: Pharma’s Data Problem”
I am asked quite often how I see Data Science in the biomedical industry. I have, of course, many answers each of which is context dependent. However one theme which I find frequently recurring is a sort of straw-man debate which seems to inherently attract technical practitioners.
The debate is usually structured as follows:
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How do you see the validation of medical AI products working in practice?
Answer: clinical trials, test-validation sets, blah, blah
But doesn’t this lead to enormous overheads?
Answer: yes, but there are shortcuts
But if you take these shortcuts then don’t you run the risk of running into costly failures when you finally run the clinical trials?
It goes on….
Randomised controlled trials (RCTs) have been the gold standard for statistical evidence, of treatment effect, for over 100 years. Their strength is in their attempt to avoid major sources of bias in a comparison of the evidence. However, they are costly to run, particularly in the domain of personalised medicine, to which medical AI products typically belong.
Continue reading “RCTs vs Real-World Evidence for medical AI”
I have been invited to speak at the Dynamics of Immune Responses workshop/seminar/conference in May-June 2020. The invitation arose through my previous efforts to found a company in this space.
There is a growing awareness in the field of immunology of the potential for using mathematical techniques. The wedge-issue here is the cascade of data appearing via new cytometry techniques; large-data looks like a math issue to most people. I of course come from the other side of a spectrum – everything looks like a math issue to me – I wanted to stimulate drug development which engages with immune system dynamics by founding my company.
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First a mea culpa, I have a huge backlog of relatively heavy articles that I really want to add to the blog. But I’ve been busy getting married – congratulations to me – and I didn’t have enough time. I strongly believe in following relatively strict guidelines on writing and editing articles, where I set myself deadlines and avoid over-writing on topics – it is just a blog after all – but for deep insights I do also have a minimum standard that I want to be able to produce before I’m willing to hit the Publish button.
Continue reading “Build – Test – Move”