Dr Abhi Pratap October Seminar Series

October 22, 2025
We were thrilled to welcome Dr Abhi Pratap - Global Clinical Development Lead at Boehringer Ingelheim who delivered our October Seminar Series. In his talk “Why Mental Health Needs More Than New Drugs: Using Digital Health to Bring Patient-Centredness to Research and Care",  Abhi shared case examples from emerging clinical studies to show how digital health can bridge the gap between clinical research and patient care in mental health. We will explore digital health solutions that help quantify the real-world experiences of health that matter to people - bringing us closer to understanding what treatments work for whom, why, when, and for how long.

Abstract: Innovation in mental health treatment has been strikingly limited compared to other fields of medicine. In the last 15 years, fewer than five truly novel psychiatric drugs have received regulatory approval. This stagnation reflects multifaceted challenges linked to heterogeneity of psychiatric disorders often lacking biological markers grounded in disease biology. Additionally, there is significant reliance on subjective clinician-, rater-, or patient-reported outcomes, which increases variability in trial outcomes and poses challenges in patient selection and endpoint determination. Clinical studies also encounter persistent obstacles, such as high dropout rates, poor generalizability, and endpoints that frequently do not reflect what patients and their families value most. Consequently, there is a critical gap in new treatment development that are patient-centered, enhancing quality of life in real-world settings.

Use-case-centered implementation of digital health technologies offers a realistic path to address many of these barriers. Real-world data collected from smart devices can enable the continuous and ecologically valid capture of mood, cognition, behavior, and functioning, augmenting traditional, episodic assessments. This richer measurement framework can enhance sensitivity to change, reduce trial inefficiencies, and ground outcomes more directly in patients lived experience. In addition, the same smart devices can be used to deliver digital adaptations of psychosocial interventions, expanding access to evidence-based care and offering personalized and scalable options for populations that have been historically underserved due to stigma, geography, or cost.

Dr. Abhi Pratap is the Global Clinical Development Lead at Boehringer Ingelheim, where he oversees clinical development programs for digital therapeutics aimed at addressing unmet needs in serious mental illnesses. Before joining Boehringer, he worked at Biogen, managing one of the largest decentralised studies on cognitive trajectories in real-world settings in collaboration with Apple.

With over 15 years of experience in translational biomedical research, Dr. Pratap has led numerous health research studies that promote partnerships between academia and industry. His primary focus is on using digital health technologies to gain a deeper understanding of the real-life experiences of individuals with neurological and psychiatric disorders. His cross-sector research aims to accelerate patient-centered clinical development in central nervous system (CNS) disorders. Most recently, he led a successful pivotal Phase III trial targeting experiential negative symptoms of schizophrenia (NCT05838625) using a digital therapeutic. This study is among the first confirmatory trials to show improvement in negative symptoms to date.

Additionally, Dr. Pratap serves as an adjunct faculty member at the University of Washington in Seattle and Boston University, and he is a visiting research fellow at King’s College London.

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April 28, 2026
Bridging Academia and Industry: Turning Health Data into Health Solutions Please join us for the EPSRC DRIVE‑Health CDT Summer Symposium & Partner Showcase 2026 , a two‑day event dedicated to bridging academia and industry and accelerating the journey from health data research to real‑world solutions. This year’s theme, “Bridging Academia and Industry: Turning Health Data into Health Solutions", brings together our vibrant community of students, King’s academics, industry partners, clinicians and policymakers to explore how collaboration can unlock new insights, innovation and impact across health and care. Event details 📅 11 & 12 June 2026 📍 Science Gallery London, Guy’s Campus, King’s College London, Great Maze Pond, London SE1 9GU Timings: ⏰ 10:00–16:00 each day ☕ Refreshments available from 09:30 👉 Please be seated by 09:50 for a prompt 10:00 start Please secure your place here: Register Now Programme highlights KEYNOTE ✨ Dr Luis Garcia‑Gancedo , Executive Director & Head of Digital Medicine – Respiratory, Immunology & Inflammation, GSK INTERACTIVE DEBATE ✨ Student‑led interactive debate exploring AI within the context of the event theme: “Bridging Academia and Industry: Turning Health Data into Health Solutions.” PANEL DISCUSSION & POSTER JUDGING ✨ “What does industry actually need from health data PhDs - and how can industry partner with academia for maximum impact?” Panelists confirmed so far: Dr Laura Acqualagna , Director of AI/ML Engineering, GSK R&D Dr Chris Callaghan , Consultant Transplant Surgeon, Guy’s Hospital Dr Nina Sesto , CEO & Co‑Founder, MEGI Health Dr Srinivasan Vairavan , Director of Data Science & Digital Health, JNJ Innovative Medicine R&D, and Visiting Adjunct Faculty, King’s College London Dr Nicolas Huber , Director, King’s Innovation Catalyst PLUS ✨ Student lightning talks (across both days) ✨ 3‑minute Student Spotlight Slides (across both days) ✨ Poster showcase & networking session (Friday) ✨ Prizes for outstanding contributions (Friday) Please secure your place here: Register Now If you are no longer able to attend the event, please email drive-health-cdt@kcl.ac.uk so that we can reallocate to our waiting list.
March 12, 2026
We are looking forward to welcoming Professor Honghan Wu, Professor of Health Informatics and AI at the University of Glasgow, who will deliver his talk “Large language model and Radiology: how to facilitate human and AI collaboration? " as part of our Seminar Series. Abstract: In this upcoming talk, Professor Honghan Wu explores the essential shift from viewing AI as a potential replacement for radiologists to recognizing it as a critical collaborative partner. Moving beyond basic tasks like detection and triage, the presentation highlights how AI can address practical clinical "pain points," such as reducing automated protocoling time by up to 60% and decreasing the time spent communicating with providers and patients by 30%. Professor Wu will present recent research on using knowledge-retrieval and Large Language Models for clinical report error correction and generation. The session concludes with an examination of the real-world deployment lifecycle, discussing the challenges of monitoring the over 700 FDA-cleared radiology AI devices currently in practice Seminar Series Event : “Large language model and Radiology: how to facilitate human and AI collaboration?" Date and Time: Thursday 25 June 2026, 15:00 – 16.00 hrs (BST) Location: Large Committee Room, Hodgkin Building, Guy's Campus Attendance: Mandatory for all DRIVE-Health students; a calendar invitation has already been sent. 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. Biography Honghan Wu is a Professor of Health Informatics and AI, based in the School of Health and Wellbeing of the University of Glasgow, where he leads the research theme of data science and AI. Prof Wu is a co-director of Health Data Research Scotland. He also is an honorary professor at Hong Kong University, an honorary associate professor at Institute of Health Informatics, UCL, and a former Turing Fellow of The Alan Turing Institute, UK's national institute for data science and artificial intelligence. Prof Wu holds a PhD in Computing Science. His current research focuses on machine learning, natural language processing, knowledge graph and their applications in medicine.