We’re thrilled to announce that John Jumper, PhD , will kick-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 promises to be 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.

We are thrilled to invite John Vardakis to speak at our EPSRC DRIVE-Health CDT's summer symposium next month. John joins us from Science Card to talk about " Exploring the Frontier: The future of GenAI Investments and Collaborations in Industry and Academia ." John Vardakis, PhD , has a diverse work experience, primarily in the field of scientific research. John is currently serving as the Head of Science Card Investment Group at Science Card, where they are involved in innovative banking. Previously, they worked as a Research Scientist at the University of Glasgow, where they focused on simulation-driven microelectromechanical systems design. John also worked as a Research Scientist at INSERM, investigating tumor mechanics and vascular fractality quantification. At the Center for Computational Imaging & Simulation Technologies in Biomedicine (CISTIB), they conducted research in cardiovascular and cerebrovascular biomechanics. Their work at UCL involved computational modeling of dementia and image-guided neurosurgery for epilepsy. John completed their DPhil in Biomedical Engineering at the University of Oxford, where their research focused on fluid transport in the brain. John also gained experience in the fields of vascular diagnosis and market research at the University of Heidelberg and P2i, respectively. Additionally, they worked as a Mechanical Engineer at Enactus and completed a placement at King's College London's Centre for Robotics Research. John Vardakis, PhD has a strong educational background in engineering and innovation. John obtained their Bachelor of Engineering (BEng) degree in Mechanical Engineering from King's College London in the years 2005 to 2008. John then pursued further education at the University of Oxford, where they completed the Centre for Doctoral Training in Healthcare Innovation from 2009 to 2010. Following this, they earned a Doctor of Philosophy (PhD) degree in Biomedical/Medical Engineering from the University of Oxford from 2010 to 2014. During their time at Oxford, they also pursued a diploma in Strategy & Innovation (Science Innovation Plus programme) from Saïd Business School, University of Oxford, from 2011 to 2012. In addition to their academic degrees, John Vardakis has obtained additional certifications. In December 2010, they received a Mathwork Training Certificate for completing the "Deploying MATLAB Based Applications - .NET Edition" course. John also obtained another Mathwork Training Certificate in December 2010 for completing the "MATLAB Programming Techniques" course. Registration is required, please email drivecdt@kcl.ac.uk for further event details. Our annual Symposium is a one-day face-to-face event for all DRIVE-Health students, academic supervisors, stakeholders and partners. Our aim is to discuss translating scientific and technological innovations in AI and data science, from research to clinical practice and commercial enterprise. The symposium will feature keynote talks, panel discussions, and poster presentations showcasing cutting-edge research and successful case studies. We will also celebrate our coming together with networking drinks at the end of the symposium. The EPSRC DRIVE-Health Centre for Doctoral Training is training the next generation of PhD health data scientists to become the innovation leaders of tomorrow. Our students work within an active NHS environment, and develop new models of data-driven care, whilst leveraging significant recent investment and infrastructure in Health Data Research within the UK. By registering for this event, you give consent to provide your name, e-mail address and registration information with King's College London for the purposes of managing the EPSRC DRIVE-Health CDT's Summer Symposium. Your personal data will be managed by those organisations and by Eventbrite according to their published privacy policies.

We are delighted to share that one of our EPSRC DRIVE-Health CDT students and PhD candidate at the IoPPN, Dina Farran, has been awarded 1st prize presentation at the recent Royal College of Psychiatrists Faculty of Liaison Psychiatry annual conference earlier this month. Dina is working under the supervision of Professor Fiona Gaughran and Professor Mark Ashworth and is about to submit her thesis at the end of this month. In the presentation, Dina summarised her PhD project consisting of a literature review, 2 observational studies, an intervention and 2 qualitative studies. Dina provides further detail below. Background Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is associated with an increased risk of stroke contributing to heart failure and death. In this project, we aim to improve patient safety by screening for stroke risk among people with AF and co-morbid mental illness. Methods (a) Conducted a systematic review and meta-analysis on prevalence, management, and outcomes of AF in people with Serious Mental Illness (SMI) versus the general population. (b) Evaluated oral anticoagulation (OAC) prescription trends in people with AF and co-morbid SMI in King’s College Hospital. (c) Identified the recorded rates of OAC prescription among people with AF and various mental illnesses and evaluated the association between mental illness severity and OAC prescription in eligible patients in South London and Maudsley (SLaM) NHS Foundation Trust. (d) Implemented an electronic clinical decision support system (eCDSS) consisting of a visual prompt on patient electronic Personal Health Record to screen for AF-related stroke risk in three Mental Health of Older Adults wards at SLaM. (e) Assessed the feasibility and acceptability of the eCDSS by qualitatively investigating clinicians’ perspective of the potential usefulness of the eCDSS (pre-intervention) and their experiences and their views regarding its impact on clinicians and patients (post-intervention). Results (a) People with SMI had low reported rates of AF. AF patients with SMI were less likely to receive OAC than the general population. When receiving warfarin, people with SMI, particularly bipolar disorder, experienced poor anticoagulation control compared to the general population. Meta-analysis showed that SMI was not significantly associated with an increased risk of stroke or major bleeding when adjusting for underlying risk factors. (b) Among AF patients having a high stroke risk, those with co-morbid SMI were less likely than non-SMI patients to be prescribed any OAC, particularly warfarin (but not DOACs). However, there was no evidence of a significant difference between the two groups since 2019. (c) Adjusting for age, sex, stroke and bleeding risk scores, patients with AF and co-morbid SMI were less likely to be prescribed any OAC compared to those with dementia, substance use disorders or common mental disorders. Among AF patients with co-morbid SMI, warfarin was less likely to be prescribed to those having alcohol or substance dependency, serious self-injury, hallucinations or delusions and activities of daily living impairment. (d) Clinicians were asked to confirm the presence of AF, clinically assess stroke and bleeding risks, record risk scores in clinical notes and refer patients at high risk of stroke to OAC clinics. (e) Clinicians reported that the eCDSS saved time, prompted them towards guidelines, boosted their confidence, and identified patients at risk. Perceived barriers to using the tool included low admission rate of AF cases, low or insufficient visibility of the alert/awareness of the tool, and impact of the eCDSS on workload. Conclusions This study presents a unique opportunity to quantify AF patients with mental illness who are at high risk of severe outcomes, using electronic health records. This has the potential to improve health outcomes and therefore patients' quality of life.