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AI in drug Discovery

SAE Media Group is proud to present the 7th Annual AI in Drug Discovery Conference on 9th-10th March 2026, in London, UK. Join us for the biggest AI in drug discovery event in the UK, that brings together the highest number of big pharma speakers for focused discussions and networking.


With the global AI in drug discovery market expected to reach 7.94 billion by 2030, AI is leading technological advancement across the pharmaceutical sector, and is expected to transform pre-clinical drug discovery.
 

Are you ready for this transformative period?


With ever-increasing pressures on drug pipelines, strategies for faster, cheaper and more successful R&D are required – this conference will showcase how AI-driven technologies are turning these strategies into reality. Through detailed case-study presentations and interactive panel-discussion sessions, we will navigate data volume and quality challenges, create strategies for increasing efficiency of R&D, and explore the impact of generative AI on drug discovery pipelines.


This year’s event will feature hot topics including applications of AI/ML within target identification and computational drug design, the impact of generative AI on ways of working and clinical updates from the first AI-designed drug candidates.


Our two-day agenda offers you peer-to-peer networking with industry experts from an extensive selection of big pharma and breakthrough biotech’s in the field, including directors and heads of informatics, data & AI, molecular design, and computational chemistry. Don’t miss the chance to hear the latest advancements from leaders in the industry!

 

FEATURED SPEAKERS

Anna Macintyre

Anna Macintyre

Senior Data Scientist, Novo Nordisk
Christoph Grebner

Christoph Grebner

Senior Principal Scientist, Sanofi
Graeme Robb

Graeme Robb

Director, Computational Chemistry, AstraZeneca
Haruna Iwaoka

Haruna Iwaoka

Head, Advanced Modeling & Assays, Innovation Core Lab, Astellas Pharma
James Lumley

James Lumley

Head of Cheminformatics, GSK
Le Mu

Le Mu

MLOps Lead, Computational Sciences Center of Excellence, gRED, Roche
Lewis Vidler

Lewis Vidler

Senior Director - Structure Based Drug Design, Eli Lilly and Company
Martin Buttenschoen

Martin Buttenschoen

Researcher, University of Oxford
Martin Redhead

Martin Redhead

Associate Vice President Primary Pharmacology, Recursion
Paul Mortenson

Paul Mortenson

Senior Research Associate, Computational Chemistry, Astex Technology
Pedro J. Ballester

Pedro J. Ballester

Royal Society Wolfson Fellow & Associate Professor, Department of Bioengineering, Imperial College London, UK
Peter Clark

Peter Clark

VP, Computational Drug Design, Novo Nordisk
Petrina Kamya

Petrina Kamya

Global Head of AI Platforms, VP, Insilico Medicine
Reiko Wada

Reiko Wada

Senior Scientist, Astellas Pharma Inc.
Sammeli Liikkanen

Sammeli Liikkanen

Director, Digital Medicine, Orion Corporation Orion Pharma
Simone Fulle

Simone Fulle

Head CADD, Basel, Novartis
Teresa de Haro

Teresa de Haro

Principal Scientist, UCB
Thierry Dorval

Thierry Dorval

Head of Data Sciences & Data Management, Servier Pharmaceuticals
Tim Hohm

Tim Hohm

Associate Director Digital Science External Partnerships, Novo Nordisk
Venkatesh Pilla Reddy

Venkatesh Pilla Reddy

Senior Director, Global PKPD and Pharmacometrics, Eli Lilly
Yogesh Sabnis

Yogesh Sabnis

Director of Lead Design, UCB Biopharma srl

Anna Macintyre

Senior Data Scientist, Novo Nordisk
Anna Macintyre

Anna Macintyre is a Senior Data Scientist at Novo Nordisk, specialising in computational structure-based protein design. She holds a PhD in Computational Biology from Duke University, where she developed algorithms for protein design in the lab of Bruce Donald. Anna received the PhRMA Foundation predoctoral fellowship and has extensive experience in the field, previously working at GSK on antibody design and at InstaDeep applying AI and machine learning approaches to biological problems. Her research focuses on protein-protein interactions, contributing to advancements in drug discovery and therapeutic development.

Christoph Grebner

Senior Principal Scientist, Sanofi
Christoph Grebner


I am working as a computational chemist in drug design ranging from early hit discovery until lead optimization and candidate selection.
My research interests focus around deep learning, large language models, and AI-based technologies for drug design processes like property prediction and de novo design.
 

Graeme Robb

Director, Computational Chemistry, AstraZeneca
Graeme Robb

Graeme Robb is Director of Computational Chemistry at AstraZeneca in Cambridge and has been at the leading edge of computer-aided drug design for over 20 years. Graeme has contributed to the invention of several clinical candidates and led multidisciplinary teams across oncology research and globally. Through his focus on enabling capabilities, he has delivered transformative and widely adopted design tools to the organisation and is now at the forefront of deploying AI tools to all AstraZeneca drug designers.

Haruna Iwaoka

Head, Advanced Modeling & Assays, Innovation Core Lab, Astellas Pharma
Haruna Iwaoka

Haruna Iwaoka is the head of Advanced Modeling & Assays, Innovation Core Lab at Astellas Pharma Inc. She leads digital transformation of drug testing platforms using AI and robotics. Joining Yamanouchi Pharmaceutical Co., Ltd., now Astellas, in 1994, she has been involved in target discovery, assay development, and advanced cell models. She obtained her Ph.D. in agricultural chemistry from Tokyo University of Agriculture in 2019. Recently, she has attracted worldwide attention for developing the unique drug discovery platform (SLAS Technol. 2021; 26(5): 441-453; 2023; 28(5), 351-360).

James Lumley

Head of Cheminformatics, GSK
James Lumley

James is Head of Cheminformatics at GSK leading a team delivering project support across multiple modalities via the development of proprietary methods, models & platforms for automated design. The team have responsibility for GSK’s validated automated design platform BRADSHAW and the underlying machine learning platform QSAR Studio. His initial career includes 10 years in Biotech as Head of Computational Chemistry, Arrow therapeutics then later as a ReViral Ltd cofounder. He has inventorship on multiple antiviral drug candidates including AZD-7295 and later Sisunatovir (RV521). In 2010 James joined Eli Lilly responsible for global Cheminformatics support. He led projects delivering award winning projects across small molecule research including multiple CIO awards and a BioIT World Innovative Practice Award (Research.Data 2020). James has a PhD in Computational Chemistry and over 25 years experience in drug discovery Research.

Le Mu

MLOps Lead, Computational Sciences Center of Excellence, gRED, Roche
Le Mu

Having worked 10+ years in digitalization across different industries, Le (Muller) Mu is combining his IT experience with his knowledge in molecular biology to help accelerate the drug discovery process in Roche Pharma Research and Early Development (pRED). He is currently the product line manager for End-to-End AI/ML and product owner and tech lead for the Roche pRED MLOps Service team, driving the operationalization of many different machine learning models, which helps to bring better future medicines faster into the hands of the patients.

Lewis Vidler

Senior Director - Structure Based Drug Design, Eli Lilly and Company
Lewis Vidler

Dr Lewis Vidler is a Senior Director of Structure Based Drug Design at Eli Lilly. He achieved a first-class chemistry degree at the University of Oxford in 2009 and subsequently completed his PhD in Computational Medicinal Chemistry at the Institute of Cancer research in London in 2013. He joined Eli Lilly later that year and spent an initial duration of 7 years there, during which he progressed to Senior Research Scientist. Following shorter stints as a computational chemist at UCB and Amphista Therapeutics, he returned to Lilly in 2023, to further progress his career.

Martin Buttenschoen

Researcher, University of Oxford
Martin Buttenschoen

Martin Buttenschoen recently completed his doctorate at the University of Oxford under the supervision of Professors Charlotte Deane, Garret Morris, and Michael Bronstein. His research primarily revolved around biases in mache learned-based methods for de-novo drug design, specifically small molecule pose prediction, also known as small molecule docking.

Martin Redhead

Associate Vice President Primary Pharmacology, Recursion
Martin Redhead

Paul Mortenson

Senior Research Associate, Computational Chemistry, Astex Technology
Paul Mortenson

Paul obtained his degree and PhD from the University of Cambridge, graduating in 2001. He started his career as a molecular modeller at Evotec, during which time he worked on a wide variety of different drug discovery projects. Since 2006 he has worked for Astex Pharmaceuticals where his first project was a collaboration with Novartis on CDK4/6 inhibitors that led to the discovery of the marketed drug Kisqali® (ribociclib). In the 20 years since, he has worked on many targets in the areas of oncology and neurodegeneration, as well as making numerous contributions to Astex’s significant internal informatics platform.

Pedro J. Ballester

Royal Society Wolfson Fellow & Associate Professor, Department of Bioengineering, Imperial College London, UK
Pedro J. Ballester

Dr. Ballester is a Royal Society Wolfson Fellow and Associate Professor at Imperial College London, leading the Artificial Intelligence for Healthcare research group. His work focuses on investigating effective computational tools, grounded in machine learning and specialized pattern-recognition techniques, to analyze and predict how small molecules modulate protein and cellular function. These methods have been applied to translational challenges in drug discovery and broader healthcare problems. He joined Imperial after an Assistant Professorship at INSERM in France, following postdoctoral fellowships at the University of Oxford, the University of Cambridge and the European Bioinformatics Institute in the UK. More about his group and projects can be found at https://ballestergroup.github.io/

Peter Clark

VP, Computational Drug Design, Novo Nordisk
Peter Clark

Peter Clark carried out his PhD at the University of Drexel. Following this he served as an Immunogenetics Fellow at Children’s Hospital of Philadelphia and Director of Bioinformatics at University of Pennsylvania School of Medicine, before spending 4 years at Janssen as Head of Computational Sciences & Engineering, Therapeutics Discovery. Peter Clark is currently VP Computational Drug Design at Novo Nordisk.

Petrina Kamya

Global Head of AI Platforms, VP, Insilico Medicine
Petrina Kamya

Petrina Kamya, PhD, is the Global Head of AI Platforms and President of Insilico Medicine Canada, overseeing Insilico’s end-to-end generative AI-driven drug discovery platform, Pharma. AI.
Before joining Insilico, Dr. Kamya had a career in Market Access and held several positions at a software company that developed CADD tools for drug discovery and development.
She holds a Ph.D. in theoretical chemistry and a BS in biochemistry from Concordia University.
 

Reiko Wada

Senior Scientist, Astellas Pharma Inc.
Reiko Wada

Reiko Wada is a senior scientist at Astellas Pharma Inc. She has extensive experience in early-stage drug discovery, including assay development in CNS, endocrine, and infectious disease areas, high-throughput screening (HTS), compound optimization, and ADME/tox evaluation. Since May 2024, she has been focused on the cross-functional implementation of next-generation automation and AI technologies to accelerate drug discovery and create new value.

Sammeli Liikkanen

Director, Digital Medicine, Orion Corporation Orion Pharma
Sammeli Liikkanen

Simone Fulle

Head CADD, Basel, Novartis
Simone Fulle

Teresa de Haro

Principal Scientist, UCB
Teresa de Haro

Teresa de Haro received her Master of Science in Chemistry from the Autonomous University of Madrid, Spain, in 2007. Following a medicinal chemistry internship at Eli & Lilly in Madrid, she pursued her doctoral studies under the supervision of Professor Cristina Nevado at the University of Zurich, Switzerland, earning her Ph.D. in Organic Chemistry with distinction in 2012.
Dr. de Haro then joined the research group of Professor Alois Fürstner at the Max Planck Institute for Coal Research in Mülheim, Germany, where she focused on the total synthesis of natural products. In 2013, she returned to Eli & Lilly, this time in Surrey, UK, before moving to UCB in Slough, UK, in 2014 as a Senior Scientist.
Since 2018, Dr. de Haro has been serving as a Principal Scientist at UCB in Braine-l'Alleud, Belgium, where she continues to contribute to the field of medicinal chemistry. In 2023, she was awarded the EFMC Prize for a Young Medicinal Chemist in Industry for her outstanding scientific career.

 

Thierry Dorval

Head of Data Sciences & Data Management, Servier Pharmaceuticals
Thierry Dorval

Thierry Dorval received a Ph.D. in image analysis and Artificial Intelligence from University Pierre & Marie Curie and then joined the institut Pasteur Korea in 2005 as a group leader specialized in High Content Screening applied to cellular differentiation and toxicity prediction.
In 2012 he joined AstraZeneca, where his activities were about developing and advising on quantitative image and data analysis solutions in support of high content phenotypic screening.
In 2015 he joined Servier, France, where he is currently leading the Data Sciences & Data Management research unit. He is in charge of optimizing early stages of drug discovery by taking advantage of cutting-edge computational approaches. This includes usage of Artificial Intelligence, knowledge graph for molecular entities selection, design & optimization.
 

Tim Hohm

Associate Director Digital Science External Partnerships, Novo Nordisk
Tim Hohm

Tim is a trained computational biologist with a decade of experience at the intersection of AI and digital in the life sciences combining experience from large pharma, biotech and software/tech companies with a BD and strategy background.

Venkatesh Pilla Reddy

Senior Director, Global PKPD and Pharmacometrics, Eli Lilly
Venkatesh Pilla Reddy

Dr. Venkatesh Pilla Reddy is a Senior Director in the Global PKPD and Pharmacometrics group at Eli Lilly and Company in the UK. At Lilly, Venkatesh provides MIDD/PKPD Lead support for projects in oncology ADC and RLT projects and immunology.
He earned his PhD in Pharmacometrics through a collaborative program involving Pfizer, Janssen Pharmaceuticals, and Merck via TI Pharma in the Netherlands. Since then, he has made substantial contributions to the Quantitative Pharmacology and Pharmacometrics groups at Merck, AstraZeneca and at Lilly.

He was a Deputy Topic Leader at ICH, shaping ICH M12 DDI guideline. He is playing a leading role in influential cross-industry working groups, such as IQ TALG, ISOP, ASCPT, and ISSX M&S. He also serves as an Editorial Board Member for the Biopharmaceutics and Drug Disposition Journal and is a reviewer for clinical pharmacology/PKPD M&S-related journals.
 

Yogesh Sabnis

Director of Lead Design, UCB Biopharma srl
Yogesh Sabnis

Yogesh currently leads a team of computational scientists at UCB. His team is responsible for contributing toward candidate molecules across multiple therapeutic projects and building computational technologies with the ambition of “Faster to Candidate”.

sponsors

Conference agenda

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8:00

Registration & Coffee

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8:50

Chair's Opening Remarks

Peter Clark, VP, Computational Drug Design, Novo Nordisk

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9:00

Opening Address: Developing Actionable, Lab-Tractable Generative Designs to Accelerate Candidate Discovery

James Lumley, Head of Cheminformatics, GSK

  • Bridging in silico and in vitro workflows by generating molecular designs that align with real-world synthesis constraints and experimental feasibility
  • Leveraging structure-based and ligand-based generative models to propose novel compounds optimised for activity, selectivity, and developability
  • Accelerating iteration cycles through AI-guided design prioritisation, reducing reliance on brute-force screening and enhancing early candidate quality
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    9:30

    Session Reserved for Lead Sponsor

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    10:00

    Applications of AI in a Structure-Rich Environment

    Paul Mortenson, Senior Research Associate, Computational Chemistry, Astex Technology

  • Using proprietary structural data to evaluate and improve state-of-the-art co-folding models
  • Characterising binding sites with a novel protein language model to generate debiased training and test sets for protein-ligand structure prediction
  • Seamlessly integrating predictive and generative models into FBDD
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    10:30

    Morning Coffee & Networking Break

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    11:00

    Practical Applications of AI in Drug Discovery: Bridging Biology and Chemistry

    Thierry Dorval, Head of Data Sciences & Data Management, Servier Pharmaceuticals

  • Integrating AI methodologies in biological data analysis
  • Enhancing chemical compound discovery through AI-driven algorithms
  • Case studies: successful AI implementations in drug discovery pipeline
  • Future perspectives: the evolving role of AI in pharmaceutical research
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    11:30

    Session Reserved for Sponsor

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    12:00

    Mega-Scale Benchmark of De Novo Design Tools for Developing Protein-Based Therapeutics

    Anna Macintyre, Senior Data Scientist, Novo Nordisk

  • Recent explosion in the options available for generative AI-based protein design
  • Comparing the in silico and in vitro success of out-of-the-box combinations of various tools, approaches and parameters
  • Retrospective evaluation of experimental results to further optimise the selection of validation criteria
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    12:30

    Large Language Models in Drug Discovery: From Design to Chemical Reasoning

    Christoph Grebner, Senior Principal Scientist, Sanofi

  • Exploring LLMs’ potential in generating, analysing, and optimising chemical structures with improved efficiency
  • Advancing chemical reasoning from large language models for molecular design
  • Transforming drug discovery workflows by conversational AI
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    13:00

    Networking Lunch

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    14:00

    Holistic de Novo Design: Integrating Human Insight, AI, and Physics to Accelerate Drug Discovery at UCB

    Teresa de Haro, Principal Scientist, UCB

  • Combining human design, AI, and physics-based methods to enhance drug discovery
  • Using high-performance computing and predictive tools for synthesizable compounds
  • A centralised platform for data-driven decision-making and collaboration
  • Improved compound design, enhanced DEL readouts, and successful application of FEP+ in solving medium-resolution cryo-EM structures
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    14:30

    Session Reserved for Sponsor

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    15:00

    Biasing and Debiasing Protein-Ligand Complex Prediction for Drug Discovery

    Martin Buttenschoen, Researcher, University of Oxford

  • Highlighting how biases in training data and model architecture can distort protein-ligand interaction predictions, impacting drug discovery outcomes
  • Exploring biasing techniques used to guide models toward chemically relevant interactions and improve predictive focus
  • Presenting methods to identify and mitigate unwanted biases, such as data augmentation, adversarial training, or reweighting schemes
  • Reviewing how balancing biasing and debiasing enhances model generalisability, leading to more accurate and robust candidate screening
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    15:30

    Afternoon Networking Break

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    16:00

    Session Reserved for Sponsor

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    16:30

    Supercomputing & Quantum Horizons: Accelerating Pharma’s Next Leap

    Le Mu, MLOps Lead, Computational Sciences Center of Excellence, gRED, Roche

  • Exploring why mid-sized pharma must rely on external HPC infrastructure over in-house builds
  • Showcasing LUMI and LUMI v2 supercomputing capabilities for pharma R&D
  • Highlighting the Orion use case: unlocking new performance gains with HPC
  • Framing the roadmap: quantum computing developments and practical next steps
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    17:00

    Supercomputing & Quantum Horizons: Accelerating Pharma’s Next Leap

    Sammeli Liikkanen

    Sammeli Liikkanen, Director, Digital Medicine, Orion Corporation Orion Pharma

  • Exploring why mid-sized pharma must rely on external HPC infrastructure over in-house builds
  • Showcasing LUMI and LUMI v2 supercomputing capabilities for pharma R&D
  • Highlighting the Orion use case: unlocking new performance gains with HPC
  • Framing the roadmap: quantum computing developments and practical next steps
  • clock

    17:30

    Chair’s Closing Remarks and Close of Day One

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    8:30

    Registration & Coffee

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    8:50

    Chair's Opening Remarks

    Peter Clark, VP, Computational Drug Design, Novo Nordisk

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    9:00

    Opening Address: Autonomous Agents in the Field of Drug Discovery – How Useful Are They? And Where Are We Likely to See the Biggest Impact?

    Petrina Kamya, Global Head of AI Platforms, VP, Insilico Medicine

  • Reviewing where autonomous agents are delivering value in drug discovery today
  • Exploring how agents can automate target selection, compound screening, and data analysis
  • Understanding the roadblocks and current limitations such as trust, transparency, and integration, and potential approaches for overcoming them
  • Outlook on where autonomous agents are poised to make the biggest impact next
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    9:30

    Session Reserved for Gold Sponsor

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    10:00

    Panel Discussion: The Lab of the Future – Closing the Loop Between AI and Automation

  • Orchestrating experiment design, execution, and analysis in real time
  • Integrating robotic systems with AI decision engines for autonomous workflows
  • Building feedback-driven cycles and enhancing data quality and speed through sensor fusion and process control
  • Lewis Vidler, Senior Director - Structure Based Drug Design, Eli Lilly and Company

    Haruna Iwaoka, Head, Advanced Modeling & Assays, Innovation Core Lab, Astellas Pharma

    Reiko Wada, Senior Scientist, Astellas Pharma Inc.

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    10:30

    Morning Coffee & Networking Break

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    11:00

    Case Study: Mahol-A-Ba – Integrating AI, Robotics, and Human Expertise for Next-Generation Drug Discovery

    Haruna Iwaoka, Head, Advanced Modeling & Assays, Innovation Core Lab, Astellas Pharma

  • Combining AI-driven analysis, robotic execution, and expert insight to accelerate and enhance discovery workflows
  • Adapting the platform to advanced cell models and simulations in line with FDA and NIH guidelines to reduce animal use
  • Advancing toward autonomous robot control guided by AI-evaluated experimental results for greater quality and efficiency
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    11:30

    Session Reserved for Sponsor

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    12:00

    Operationalising AI at Scale: From Proof-of-Concept to Cross-Portfolio Integration

    Simone Fulle

    Simone Fulle, Head CADD, Basel, Novartis

  • Establishing MLOps systems for model versioning, testing, and monitoring
  • Fostering collaboration between domain scientists and data experts
  • Driving internal adoption through user-friendly platforms and success metrics
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    12:30

    Networking Lunch

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    13:30

    AI and ML in Clinical Pharmacology: Unlocking the Strategic Value of PK/PD Modelling

    Venkatesh Pilla Reddy, Senior Director, Global PKPD and Pharmacometrics, Eli Lilly

  • Enabling data-driven decisions on dose selection, trial design, and patient safety through AI-enhanced pharmacology models
  • Reducing late-stage attrition by improving the predictability of clinical outcomes from preclinical data
  • Driving faster, more cost-effective development pathways by embedding PK/PD insights into portfolio-level strategy
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    14:00

    Session Reserved for Sponsor

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    14:30

    Applying AI to Decode Biology

    Martin Redhead

    Martin Redhead, Associate Vice President Primary Pharmacology, Recursion

  • Unlocking complex biological mechanisms through AI-driven data integration and modelling
  • Accelerating target and biomarker discovery by linking omics, imaging, and clinical data
  • Driving translational insights that connect molecular biology to therapeutic outcomes
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    15:00

    Afternoon Networking Break

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    15:30

    Machine-Learning Scoring Functions for Structure-Based Binding Affinity Prediction: A 15-Year Perspective

    Pedro J. Ballester, Royal Society Wolfson Fellow & Associate Professor, Department of Bioengineering, Imperial College London, UK

  • Reviewing the evolution of ML-based scoring functions from early linear models to modern deep learning architectures, highlighting key milestones and breakthroughs
  • Comparing performance trends, limitations, and validation strategies across generations of models using benchmark datasets and real-world case studies
  • Pointing out common pitfalls and limitations, and the latest efforts to mitigate them
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    16:00

    Closing Panel Discussion: Charting the Next 5 Years of AI in Drug Discovery

  • Evaluating emerging technologies including causal AI, agent-based learning, and autonomous labs; establishing organisational shifts needed to fully capitalise on AI innovation
  • Discussing regulatory, ethical, and public trust considerations
  • Mapping the convergence of AI, data, and experimental science over the coming decade
  • Le Mu, MLOps Lead, Computational Sciences Center of Excellence, gRED, Roche

    Yogesh Sabnis, Director of Lead Design, UCB Biopharma srl

    Tim Hohm, Associate Director Digital Science External Partnerships, Novo Nordisk

    clock

    16:30

    Chair’s Closing Remarks and End of Conference


    Senior Data Scientist
    Novo Nordisk
    Senior Principal Scientist
    Sanofi
    Director, Computational Chemistry
    AstraZeneca
    Head, Advanced Modeling & Assays, Innovation Core Lab
    Astellas Pharma
    Head of Cheminformatics
    GSK
    MLOps Lead, Computational Sciences Center of Excellence, gRED
    Roche
    Senior Director - Structure Based Drug Design
    Eli Lilly and Company
    Researcher
    University of Oxford
    Associate Vice President Primary Pharmacology
    Recursion
    Senior Research Associate, Computational Chemistry
    Astex Technology
    Royal Society Wolfson Fellow & Associate Professor, Department of Bioengineering
    Imperial College London, UK
    VP, Computational Drug Design
    Novo Nordisk
    Global Head of AI Platforms, VP
    Insilico Medicine
    Senior Scientist
    Astellas Pharma Inc.
    Director, Digital Medicine
    Orion Corporation Orion Pharma
    Head CADD, Basel
    Novartis
    Principal Scientist
    UCB
    Head of Data Sciences & Data Management
    Servier Pharmaceuticals
    Associate Director Digital Science External Partnerships
    Novo Nordisk
    Senior Director, Global PKPD and Pharmacometrics
    Eli Lilly
    Director of Lead Design
    UCB Biopharma srl

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    Hilton London Kensington

    179-199 Holland Park Avenue
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    United Kingdom

    Hilton London Kensington

    At the heart of the Holland Park district, our hotel is 10 minutes from Westfield London shopping center. We're blocks from Shepherd's Bush Underground station, linking to central London, and Kensington Palace and Gardens are two miles from us. Enjoy 24-hour access to our fitness center.

     
    Join us in WestEleven for hearty buffet breakfast, a great way to start the day! Our Avenue Bar and Lounge serves light bites throughout the day as well as a delicious, seasonal dining menu.”
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    CPD can be undertaken through a variety of learning activities including instructor led training courses, seminars and conferences, e:learning modules or structured reading.

    CPD AND PROFESSIONAL INSTITUTES

    There are approximately 470 institutes in the UK across all industry sectors, with a collective membership of circa 4 million professionals, and they all expect their members to undertake CPD.

    For some institutes undertaking CPD is mandatory e.g. accountancy and law, and linked to a licence to practice, for others it’s obligatory. By ensuring that their members undertake CPD, the professional bodies seek to ensure that professional standards, legislative awareness and ethical practices are maintained.

    CPD Schemes often run over the period of a year and the institutes generally provide online tools for their members to record and reflect on their CPD activities.

    TYPICAL CPD SCHEMES AND RECORDING OF CPD (CPD points and hours)

    Professional bodies and Institutes CPD schemes are either structured as ‘Input’ or ‘Output’ based.

    ‘Input’ based schemes list a precise number of CPD hours that individuals must achieve within a given time period. These schemes can also use different ‘currencies’ such as points, merits, units or credits, where an individual must accumulate the number required. These currencies are usually based on time i.e. 1 CPD point = 1 hour of learning.

    ‘Output’ based schemes are learner centred. They require individuals to set learning goals that align to professional competencies, or personal development objectives. These schemes also list different ways to achieve the learning goals e.g. training courses, seminars or e:learning, which enables an individual to complete their CPD through their preferred mode of learning.

    The majority of Input and Output based schemes actively encourage individuals to seek appropriate CPD activities independently.

    As a formal provider of CPD certified activities, SAE Media Group can provide an indication of the learning benefit gained and the typical completion. However, it is ultimately the responsibility of the delegate to evaluate their learning, and record it correctly in line with their professional body’s or employers requirements.

    GLOBAL CPD

    Increasingly, international and emerging markets are ‘professionalising’ their workforces and looking to the UK to benchmark educational standards. The undertaking of CPD is now increasingly expected of any individual employed within today’s global marketplace.

    CPD Certificates

    We can provide a certificate for all our accredited events. To request a CPD certificate for a conference , workshop, master classes you have attended please email events@saemediagroup.com

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    UK Office
    Opening Hours: 9.00 - 17.30 (local time)
    SAE Media Group , Ground Floor, India House, 45 Curlew Street, London, SE1 2ND, United Kingdom
    Tel: +44 (0) 20 7827 6000 Fax: +44 (0) 20 7827 6001
    Website: http://www.smgconferences.com Email: events@saemediagroup.com
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