I wrote recently about my experiences of the Pulse leadership and entrepreneurship training program for the blog of the UK BioIndustry Association (BIA). The Pulse course is organised jointly by the BIA and the Francis Crick Institute. I joined the three-day course, in its first year of operation, in 2018.
I felt that I benefited enormously from the course. I had left my postdoc position 3 months previously and I was researching ideas for setting-up a company. I subsequently took my learnings from Pulse and elsewhere, and established my first company Simmunology. So when I was contacted earlier this year I was particularly keen to write something and say thanks.
Continue reading “New article: My experience of the BIA Pulse accelerator”
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”
Something I’ve struggled with on and off over the 20 years that I have been making mathematical models is explaining those models to others. I have tried to bring people along and develop their understanding. But mainly what I observed was that, some people just got it and others did not.
I have certainly improved my own skill at explaining. This comes down to having streamlined stories and simpler take-home messages. Telling a clearer story certainly improves my audiences’ self-satisfaction, but ultimately some of them get the whole message and others do not.
Continue reading “Modelling the Modeller”
Since I managed to break my writers’ block on decision making models last week I want to follow-up with a brief discussion on the use of Narrative in presenting decision models to an audience.
In my first article on decision making models I emphasized that a model must serve a purpose. In explaining our models to others I want to highlight that there are two purposes behind explaining a model; the first is to convince the audience; the second is to convey insights into the model. This is the opposite ordering of how scientifically-trained modellers typically think about communicating results, but it is by far-and-away the prioritisation of most top scientific communicators around the world.
Continue reading “Narrative and Decision Models”
This is my third attempt, over the course of 9 months, to write this article. The first attempt foundered on my desire to go into detail on whether explanation or explanability is a good characteristic of a model or not. I confess, this was overly motivated by my personal frustration at having worked with somebody who, “never let the facts get in the way of a good story.” The second attempt got lost in a forest of anecdotes from previous projects. I was trying so hard to knit them together that I failed to make a point. Today, I want to focus on the single most important thing that I have learned about developing decision making models.
Continue reading “Decision Making Using Models 3.0”
I had quite a nice spring season of talks planned for 2020. I was invited to deliver a keynote on AI in Healthcare at Biovaria. And, I was one of the invited speakers for the Dynamics of Immune Repertoires conference where I would also have given a workshop, in Dresden. Covid-19 struck and the rest is history.
Emergencies lead to quick changes of plans. Anthony Kelly from AI in Action reached out to me asking me to take part in a special on AI in Healthcare.
Continue reading “Talks cancelled – Talks online”
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:
Continue reading “Data Science in Biomedical Industry”
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….
I had the opportunity to talk recently with a relatively advanced researcher in machine learning methods. The conversation turned briefly to the study of embeddings when he mentioned that most of his work involves things that can be embedded in Euclidean space. Since I’ve been spending a bit of time thinking about embeddings recently, I asked him some questions to get the official ML take on the subject. I was resonably gratified to learn that – although most ML engineers don’t think much about embeddings – the research on this topic considers the embedding to be tightly bound to the network architecture. It is not possible to study abstract embeddings, divorced from applications. I fully agree with this point-of-view.
Continue reading “ML Embeddings and the Neuronal Code”
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.
Continue reading “Invited Speaker: Dynamics of Immune Responses”