John Jumper, PhD, from Google's DeepMind talks about AlphaFold2
September 12, 2024
We were thrilled to welcome Nobel Prize winner, Dr John Jumper, who kicked-off our 2024/2025 Seminar Series with his talk,
"Extending
AlphaFold
to make predictions across the universe of biomolecular interactions". John is one of the key pioneers behind the development of Google’s DeepMind
AlphaFold - an artificial intelligence model to predict protein structures from their amino acid sequence with high accuracy.
This in-person event was an incredible opportunity to hear from one of the foremost innovators in AI and biology.
Seminar Series Event:
Extending AlphaFold to make predictions across the universe of biomolecular interactions
Date and Time:
14:00 – 15.00, Thursday 10 October 2024
Location:
The Council Room, 2nd floor, The King’s Building, Strand Campus
Registration:
Limited to EPSRC DRIVE-Health students in the first instance. Please email
drive-health-cdt@kcl.ac.uk
to check availability.
Abstract:
The high accuracy of AlphaFold 2 in predicting protein structures and protein-protein interactions raises the question of how to extend the success of AlphaFold to general biomolecular modeling, including protein-nucleic and protein-small molecule structure predictions as well as the effects of post-translational modification. In this talk, I will discuss our latest work on AlphaFold 3 to develop a single deep learning system that makes accurate predictions across these interaction types, as well as examine some of the remaining challenges in predicting the universe of biologically-relevant protein interactions.
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We’re pleased to announce that Dr Petroula Laiou from King's College London , will deliver our May Seminar Series with her talk, "Bridging the Gap: Turning Academic Research into Clinical Innovation " . Petroula will share her journey of translating cutting-edge academic research into a mission-driven MedTech company. The spinout is pioneering a novel approach to forecasting and preventing seizures in people with drug-resistant epilepsy - an innovation rooted in years of interdisciplinary work at the intersection of clinical neuroscience, signal processing, and artificial intelligence. Dr. Laiou will take the audience through the full translational pathway: from identifying an unmet clinical need, designing and analysing first-in-human studies, and developing a seizure prediction algorithm, to securing translational funding, navigating the intellectual property landscape, and filing an international patent (PCT/GB2024/052456). She will reflect on key lessons learned during her time in the King’s MedTech Accelerator Programme - where the team won the Best Innovation award - and share insights on building bridges between academia and industry, shaping a commercialization strategy, and transitioning from researcher to entrepreneur. The talk will also highlight the challenges and rewards of launching a spinout in the healthcare sector and offer practical advice for PhD students and early-career researchers considering the entrepreneurial route. Seminar Series Event: "Bridging the Gap: Turning Academic Research into Clinical Innovation" Date and Time: Wednesday 7 May 2025, 15:00 – 16.00 hrs (BST) Location: The Lorna Wing Room, SGDP Building, Denmark Hill Campus, London, SE5 8AF Attendance: Mandatory for all DRIVE-Health students, therefore please accept the calendar invitation. Registration: Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend. Dr. Petroula Laiou is a Research Fellow in Predictive Modelling and Clinical Neuroscience at King’s College London. With a background in mathematics, computational physics, and a PhD in signal analysis, her research bridges computer science, neuroscience, and machine learning. Her work focuses on developing predictive models and digital biomarkers for neurological and psychiatric disorders, including epilepsy and depression. Dr. Laiou led the development of a novel seizure forecasting algorithm using intracranial EEG and cortical responses to electrical stimulation—research that led to the filing of an international patent (PCT/GB2024/052456). She is the recipient of multiple research grants, including an MRC award as Principal Investigator, and her translational work was recognised by the King’s MedTech Accelerator Programme, where her team won the Best Innovation award. She has authored over 40 peer-reviewed publications, presented at major international conferences, and actively contributes to interdisciplinary collaborations across academia, hospitals, and industry.
We were thrilled to welcome Charles Friedman from the University of Michigan Medical School , who delivered our March Seminar Series with his talk, "Why AI and Learning Health Systems Need Each Other " . Charles began by advancing the idea that, while both are extremely important: AI is a means and Learning Health Systems (LHS) are an end--and why it is most important to maintain that distinction. He introduced the socio-technical infrastructure required for high-functioning learning systems and argue that this infrastructure provides a framework, actually a schematic, for successfully implementing AI into healthcare. Charles Friedman is Professor of Learning Health Sciences at the University of Michigan Medical School, where he directs the Knowledge Systems Laboratory. He was formerly Founding Chair of the Department of Learning Health Sciences and the Josiah Macy Jr. Professor of Medical Education. He holds joint appointments in the Schools of information and Public Health. He is editor-in-chief of the open-access journal Learning Health Systems and co-chair of the multi-national movement to Mobilize Computable Biomedical Knowledge. Throughout his career, Friedman has developed and studied methods to improve health, education, and research through innovative applications of information technology. Most recently, Friedman has focused his academic interests and activities on the concept of Learning Health Systems that improve health by marrying discovery to implementation, and the socio-technical infrastructure required to sustain these systems. Friedman is a Distinguished Fellow of the American College of Medical Informatics, and a founding fellow of the International Academy of Health Sciences Informatics. He holds an honorary doctorate from the University of Lucerne in Switzerland for his contributions to the science of Learning Health Systems. Prior to coming to Michigan, Friedman held executive positions at the Office of the National Coordinator for Health IT (ONC) in the U.S. Department of Health and Human Services. Immediately prior to his work in the government, he was Associate Vice Chancellor for Biomedical Informatics, and Founding Director of the Center for Biomedical Informatics at the University of Pittsburgh. Seminar Series Event: "Why AI and Learning Health Systems Need Each Other" Date and Time: Wednesday 26 March 2025, 10:00 – 11.00 hrs (BST) Location: The Anatomy Museum, King's Building, Room K6.36, Strand Campus, Strand, London, WC2R 2LS Attendance: Mandatory for all DRIVE-Health students, therefore please accept the calendar invitation. Registration: Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend.
