Category Archives: Commentary

Debugging code for science: Fantastic Bugs and Where to Find Them.

The simulation results make no sense … My proteins are moving through walls and this dihedral angle is negative; my neural network won’t learn anything, I’ve tried for days to install this software and I still get an error.

Feel familiar? Welcome to scientific programming. Bugs aren’t just annoying roadblocks – they’re mysterious phenomena that make you question your understanding of reality itself. If you’ve ever found yourself debugging scientific code, you know it’s a different beast compared to traditional software engineering. In the commercial software world, a bug might mean a button doesn’t work or data isn’t saved correctly. In scientific computing, a bug might mean your climate model predicts an ice age next Tuesday, or your protein folding algorithm creates molecular structures that couldn’t possibly exist in our universe (cough).

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The business of health: research and funding from academia to big pharma

In a world in which the probability of clinical success is just 10%-20% for new medicines, pharmaceutical multinationals increasingly turn to academia and biotech as a source of “de-risked” technology for their pipelines. This exchange of ideas, equity and capital depends on firm relationships between entities having apparently divergent interests: from not-for-profit research to international commerce.

As a former pharma contract negotiator, I spent much of my past life attempting to find common ground with university researchers and biotech leadership teams. In 2021, I had the privilege of returning to academia in the UK after a prolonged hiatus, and – more recently – of working with start-ups. In this blog, I will comment on some of the surprising trends I have observed in how pharma, biotech and academics balance the conduct of meaningful research with the requirements of their respective sectors. The views herein are entirely my own.

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Diagnostics on the Cutting Edge, Software in the Stone Age: A Microbiology Story

The need to treat and control infectious diseases has challenged humanity for millennia, driving a series of remarkable advancements in diagnostic tools and techniques. One of the earliest known legal texts, the Code of Hammurabi, references the visual and tactile diagnosis of leprosy. For centuries, the distinct smell of infected wounds was used to identify gangrene, and in Ancient Greece and Rome, the balance of the four humors (blood, phlegm, black bile, and yellow bile) was a central theory in diagnosing infections.

The invention of the compound microscope in 1590 by Hans and Zacharias Janssen, and its refinements by Robert Hooke and Antonie van Leeuwenhoek, marked a turning point as it enabled the direct observation of microorganisms, thereby linking diseases to their microbial origins. Louis Pasteur’s introduction of liquid media aided Joseph Lister in identifying microbes as the source of surgical infections, whilst Robert Koch’s experiments with Bacillus anthracis firmly established the connection between specific microbes and diseases.

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Navigating Hallucinations in Large Language Models: A Simple Guide

AI is moving fast, and large language models (LLMs) are at the centre of it all, doing everything from generating coherent, human-like text to tackling complex coding challenges. And this is just scratching the surface—LLMs are popping up everywhere, and their list of talents keeps growing by the day.

However, these models aren’t infallible. One of their most intriguing and concerning quirks is the phenomenon known as “hallucination” – instances where the AI confidently produces information that is fabricated or factually incorrect. As we increasingly rely on AI-powered systems in our daily lives, understanding what hallucinations are is crucial. This post briefly explores LLM hallucinations, exploring what they are, why they occur, and how we can navigate them and get the most out of our new favourite tools.

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Why the vegans will say “I told you so…”

I am writing this on Wednesday 2nd October 2024. The news has all eyes on the middle eastern skies. Yesterday a story was circulating on BBC news warning of a drop in uptake of the seasonal flu jab.

https://www.bbc.co.uk/news/articles/c62d8r0nnl6o

Four days ago, on Friday 27th September, several news outlets reported that several healthcare workers had shown flu-like symptoms following exposure to the first patient known to have contracted avian flu (H5N1) without any animal contact. PCR testing has been inconclusive, with none of these workers testing positive for signs of the virus.

https://www.bbc.co.uk/news/articles/czd1v3vn6ero

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Our future health: A new UK health research programme

Last week I walked into Boots  and, after giving some physical measurements, including my blood pressure and cholesterol levels, I gave a blood sample to be part of the Our Future Health initiative. Our Future Health (https://ourfuturehealth.org.uk/)  is set to become the UK’s largest health research programme ever. With the aim of recruiting five million volunteers across the country, it aims to revolutionise the way we detect, prevent and treat disease.

The breadth, depth and detail of Our Future Health makes it a world-leading resource. The data collected could hold the key to a wide range of health discoveries, such as:

  • Identifying early signals to detect disease much earlier.
  • Accurately predicting who is at higher risk of disease.
  • Developing better interventions and more effective treatments and technologies.

How’s it going so far?

Since the start of recruitment in July 2022 (delyed because of Covid), the programme has recruited over one million participants where:

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Five-word stories about a world where AI dominates the world

Creative AI writing 🤖🖊️

“For sale: baby shoes, never worn.” ~ Ernest Hemingway??

This is a six-word story famously misattributed to Ernest Hemingway. According to Wikipedia, this story first appeared in 1906, when Hemingway was 7 years old, and later attributed to him in 1991, 30 years after his death. So, no chance it was his.

Regardless of its origin, I found this type of story very creative.

In this blog post, as the title says, I will dare to push the boundary to present 5-word stories on the topic of AI taking over the world, BUT with a humorous spin.

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Happily hallucinating (for humans)

Many of us in academia face worries about an uncertain future. As an undergraduate, exams, assignments, exchanging information via auditory and visual cues with other members of the species1, then as one moves through the pipeline there’s funding, publications, the expectation that you know something about something, what will I be when I eventually grow up2, and I haven’t even mentioned the perennial question that is, what am I going to cook tonight?!

I have faced all of these worries and more, and will no doubt continue to, but through talking to my peers, mentors and family, I’ve learnt a few lessons that have proved invaluable for me, and perhaps will be for you as well.

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Conference Summary: MGMS Adaptive Immune Receptors Meeting 2024

On 5th April 2024, over 60 researchers braved the train strikes and gusty weather to gather at Lady Margaret Hall in Oxford and engage in a day full of scientific talks, posters and discussions on the topic of adaptive immune receptor (AIR) analysis!

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How can FemTech help close the gender health gap?

An excellent previous blog post from Sarah [1] describes the gender data gap and touches on the fact that women experience poorer healthcare outcomes. This arises from, amongst other things, the historical exclusion of women from clinical trials and this idea of the ‘male default’, where, for example, drug dosages and diagnostic thresholds are benchmarked against men, or even surgical instruments are designed to fit male hands [2]. I thought I would follow up on Sarah’s blog post and discuss how FemTech can help to close this gender health gap.

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