Cogito

The field of radiomic biomarkers seems to be maturing with higher levels of evidence being generated through validation in randomized trials. However, these biomarkers, currently, are inductive - based on a retrospective training set, we hope the signature/model extrapolates to a new patient. It only takes one black swan (aka an unknown unknown) for the model to crash and burn. This is particularly a huge problem with deep learning approaches and I am therefore more bullish on hand-crafted radiomics. Within radiomics, I believe shape features are much more interpretable than texture features. I see the way forward as radiomic biomarkers being incorporated in the standard biomarker discovery process in earlier phases of trials. This will largely be a collaborative effort between pharmas and small/medium companies with expertise in the AI/radiomic side. However, the key point is that while prospective validation may be convincing, it might not provide sufficient immunity to black swans. ...

My first ever experience in the field of precision medicine (imaging biomarkers, to be precise) was when I landed a 6-month co-op at Biogen. Back then, the idea of a pharma company having data scientists and image processing engineers was extremely surprising to me. Why would a company that makes drugs hire people who write code? Over the 3 years of my PhD involving close collaboration with two pharma companies, countless hours of reading technical papers and Fierce Biotech newsletters, I guess I've (re)discovered the Socratic method, I've learnt to rephrase my question - what is the business sense behind investing in biomarker development teams? I believe this has gotten me closer to finding the answer: A strategic precision medicine approach, depending on the choice of biomarker, can help pharmas devise faster and potentially cheaper clinical trials through (a) biomarker enriched patient selection, (b) early response and futility assessment, (c) additional secondary endpoint ...

I still find it hard to imagine how people got around before GPS was a thing or how anyone  could  wait for days, if not weeks, to receive a response before telephones - in the not too distant past. Couple years later, would people wonder "How did people write and/or code before LLMs"? Back towards the end of 2020 as I was wrapping up my internship at Biogen (perhaps the best 6 months of my life, as of September 2024, will probably write a blog on it next time I want to procrastinate), I decided that I wanted to pursue a PhD developing interpretable, handcrafted imaging biomarkers. The struggle of writing the statement of purpose (SoP) was REAL (and I still do struggle with writing a lot)! Back then, Prof. Priya Narasimhan's tweetorials helped a lot - Link 1 , Link 2 . Perhaps the one tweet that really helped me get started was You can always edit a bad page. You can’t edit a blank page. — @jodipicoult — Prof. Priya Narasimhan (@YinzcamPriya) November 14, 2020 I spent se...