Cambridge MedAI Seminar - January 2025

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• Greta Markert and Dr Karen Sayal
• Wednesday 29 January 2025, 11:45-13:00
• Jeffrey Cheah Biomedical Centre (Main Lecture Theatre), University of Cambridge.

If you have a question about this talk, please contact Hannah Clayton.

Sign up for this seminar on Eventbrite: https://www.eventbrite.co.uk/e/cambridge-medai-seminar-series-tickets-1142276031359?aff=oddtdtcreator

Join us for the Cambridge AI in Medicine Seminar Series, hosted by the Cancer Research UK Cambridge Centre and the Department of Radiology at Addenbrooke’s. This series brings together leading experts to explore cutting-edge AI applications in healthcare—from disease diagnosis to drug discovery. It’s a unique opportunity for researchers, practitioners, and students to stay at the forefront of AI innovations and engage in discussions shaping the future of AI in healthcare.

This month’s seminar will be held on Wednesday 29 January 2025, 12-1pm at the Jeffrey Cheah Biomedical Centre (Main Lecture Theatre), University of Cambridge and streamed online via Zoom. A light lunch from Aromi will be served from 11:45. The event will feature the following talks:

AI in Histopathology: Practical Lessons from an Unconventional Case Study – Greta Markert, PhD student, Cancer Research UK Cambridge Institute/University of Cambridge

Greta studied both Chemistry and Pharmaceutical Sciences at ETH Zurich with a strong focus on computational approaches. During her master’s thesis at IBM Research, she explored AI for drug discovery, which sparked her passion for artificial intelligence. Currently, she is in the final year of her PhD at the Cancer Institute in Cambridge, working under Prof. Florian Markowetz and Prof. Rebecca Fitzgerald at the Early Cancer Institute, working on AI in histopathology. Before starting her PhD, she worked in management consulting and in the patents department of Roche.

Abstract: Artificial intelligence in histopathology has predominantly focused on traditional biopsy samples. My research, however, applies AI to whole slide images derived from the capsule sponge, a minimally invasive alternative to endoscopy. The capsule sponge collects random cellular material along the esophagus, presenting distinct analytical challenges. Our work involves three stains—H&E for quality control and atypical features, TFF3 for detecting Barrett’s esophagus, and TP53 for tumor progression assessment—each addressing specific diagnostic questions. By integrating these stains and analyzing corresponding cellular structures, we enhance risk stratification and advance early detection of esophageal cancer. This presentation will outline the novel computational strategies developed to tackle this unique and complex application.

Next generation technology for next generation trials – Dr Karen Sayal, Senior Director in AI-driven Clinical Development and Clinical Translation at Recursion Pharmaceuticals & Honorary Consultant in Clinical Oncology, Cambridge University NHS Foundation Trust

Dr Karen Sayal is a Senior Director in AI-driven Clinical Development and Clinical Translation at Recursion Pharmaceuticals where she is focused on implementing high-throughput industrial scale clinical trials. She is also a honorary consultant in Clinical Oncology at Cambridge University NHS Foundation Trust.

Dr Sayal completed medical school at the University of Cambridge (Gonville and Caius college). Her specialist clinical training spanned across Cambridge and Oxford, which included being the first NIHR -funded academic clinical fellow in Clinical Oncology at Oxford. She completed a CRUK -funded DPhil in advanced sequencing technologies and machine learning at the University of Oxford. Prior to joining Recursion, Dr Sayal was a Fellow in Deep Learning in the AI/ML division of GSK . She is the first and only clinician to have embarked on the GSK AI fellowship scheme where she worked across technical AI research, clinical trial design, clinical data networks and AI regulation.

Abstract: Clinical trials are being transformed through an evolving suite of innovative AI-driven technologies combined with data-driven insights on the clinical and biological profile of disease. Such transformation is a reflection of a more fundamental shift where technology, drug development and patient care are coming together to redefine how we view and manage perturbed states of human physiology. In the next Cambridge MedAI seminar, Dr Karen Sayal will give an overview of the current landscape of trial-ready AI tools. She will also spotlight emerging growth areas for clinical AI technologies, and offer critical insights into the challenges we must collectively address to ensure AI innovation is deployed in a safe and meaningful way for patients.

This is a hybrid event so you can also join via Zoom:

https://zoom.us/j/99050467573?pwd=UE5OdFdTSFdZeUtIcU1DbXpmdlNGZz09

Meeting ID: 990 5046 7573 and Passcode: 617729

We look forward to your participation! If you are interested in getting involved and presenting your work, please email Ines Machado at im549@cam.ac.uk

For more information about this seminar series, see: https://www.integratedcancermedicine.org/research/cambridge-medai-seminar-series/

This talk is part of the Cambridge MedAI Seminar Series series.

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