Associate Professor @ExeterMed - precision medicine, data science and diabetes #exeterdiabetes

Exeter, England
Joined July 2014
5-drug precision prescribing for people with type 2 diabetes is here - @TheLancet our @ExeterMedmodel for optimising glucose lowering therapy using low-cost routine clinical features Paper: thelancet.com/journals/lance… Web calc: diabetesgenes.org/t2-treatme…
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John Dennis retweeted
Up front & free to read in our Oct issue #editorspicks: Type 2 diabetes subtypes for precision medicine: methodological challenges and alternative prediction‑based approaches link.springer.com/article/10…
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To prescribe or not to prescribe? #SGLT2 inhibitors slow #CKD progression but it's unclear who with #T2D and mild/no CKD truly benefits. This new model predicts individual benefit, supporting more targeted prescribing. #PrecisionMedicine link.springer.com/article/10… 🔓@Exeter_Diabetes
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The groundbreaking @Exeter_Diabetes 5-drug model accurately predicts the most effective glucose-lowering treatment for individuals with #Type2Diabetes At #EASD2025 we hear that it's been updated to include semaglutide Huge potential to transform #T2D care for millions globally – at Vienna, Austria
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Next up on the stage of #DUKPC: Professor Ines Barroso @InesBarroso4 shares insights from her #research journey, showing how her expertise in genetics is helping to answer key questions for people living with #diabetes— all in her inspiring Dorothy Hodgkin Lecture. 🧬
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📢 Can AI help pick the best glucose-lowering drug❓ "Computer says yes" 🔹 Machine-learning model predicts optimal therapy (GLP-1RA, SGLT2i, SU, DPP4i, or TZD) 🔸 Model-concordant Rx = 5.3 mmol/mol ⤵️ HbA1c at 12m vs. non-optimal choices 🔹 Better long-term outcomes: 38% ⤵️ glycaemic failure, 29% ⤵️ renal risk, 15% ⤵️ MACE-HF 🔸 Only 17.8% of UK patients currently get the model-predicted best drug❗️ 👉 Time for AI-driven personalised prescribing in #T2D? 🔗 ggdocs.co/9p2tgf 🔗diabetesgenes.org/t2-treatme…
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💥Those of us working in science comms are perhaps too fond of the word "gamechanging" but this research by @john_den_ @athattersley @Exeter_Diabetes, published today in @TheLancet and announced at #DUKPC25, truly deserves that description 💥 #Type2Diabetes #BetterCare
“This tool could mark the most significant advance in type 2 diabetes care in more than a decade, improving health outcomes for millions.” Dr Elizabeth Robertson, Director of Research and Clinical at Diabetes UK. A thread 👇
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We are hiring: a graduate research assistant and 2x postdocs for a diabetes project using advanced in vitro methods. Collab w/ @Thomaspiers and a cracking team of Co-Is GDRA: lnkd.in/eSwkfNHT PDRAx2: lnkd.in/efvA643b @ExeterMed #IPSC #Organoids #OOC
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‼️Kidney protection in diabetes: Who is going to benefit more? #EASD2024
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Fantastic #DataScience #PhD available @ExeterMed Unlocking the Power of UK Hospital Data: Leveraging Machine Learning and Natural Language Processing for Clinical Research, with application in diabetes Closing date 17th Sept - exeter.ac.uk/study/funding/a… or DM for further details
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Precision medicine in type 2 #diabetes: the causal analysis by Güdemann et al demonstrates that SGLT2 inhibitors are effective in older adults with #T2D but increase genital infections and #DKA risk tinyurl.com/p6pvhvb8 🔓 @ExeterMed @LGuedemann @angusgjones
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John Dennis retweeted
We found 14 re-analyses that delivered evidence that we considered both credible and clinically important. Many of these were IPDMA, combining databases. Among these 14, there were 10 simple ‘risk modeling’ studies. Interestingly, >half of these showed variation in both absolute AND relative effects across the different risk strata. There were also 4 ‘effect models’, that more flexibly explored treatment interactions with individual variables for subgroup identification, with credible and clinically important results. These 4 have been validated externally. Most 'effect models', however, yielded 'exploratory' results awaiting confirmation--or more likely refutation. 3/x
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Congratulations @Exeter_Diabetes @uniofexeHLS 🥂 What an amazing scoop of awards at #DUKPC24 Especially proud of our very own @ChristianaLekka funded by the SMF Grand Challenge @stevemorganfdn @JDRFUK @DUK_research
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All models are wrong and yours are useless! In case you missed my talk yesterday on how to make clinical prediction tools useful for patients, you can read all about it here. Enjoy! doi.org/10.1038/s41698-024-0…
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Precision medicine in #type2diabetes: Cardoso et al develop a new approach for phenotype-based targeting of SGLT2-inhibitors and GLP1-receptor agonists tinyurl.com/bp89t8aa🔓 @ExeterMed @john_den_ @angusgjones
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