Welcome to the AI Driven Drug Development Summit
Several high-profile partnerships between pharma and AI companies have materialized recently, but with commercial validation of approaches taking place, improving technologies will expedite this process. The AI Driven Drug Discovery Summit Europe will highlight key approaches to implementing novel AI technologies to expanding datasets. With this landscape rapidly evolving, the need to determine where and how AI can most add value has never been stronger. By uniting leaders from pharma, biotech, AI-technology companies and academia, this forum allows you to create a clear strategic vision and ambition regarding the use of AI to optimise drug discovery.
- This executive event reveals the latest technology upgrading the day-to-day tool kit of drug developers and data scientists spanning the pharmaceutical landscape.
- Understand how you can harness cutting-edge tools that provide discoverable, accessible, and transformable data analytics to guide your workflow, reducing costs, and informing decisions.
- Meet senior experts from start-ups to pharmaceutical giants and unlock the full potential of AI/ML platforms that are reshaping drug design, optimisation, and screening.
- Find out how to upgrade your presence and platform your AI services – based on your objectives we can create custom bespoke packages designed specifically for you.
AI is used along the drug discovery and development pipeline: from target discovery, drug design up to commercialization. Clinical science benefits from AI upon multiple aspects to enable trials design in a faster and more optimal way.
I am excited about being able to share some content on how AstraZeneca uses AI/ML to boost productivity and deliver business value. I am as well looking forward to hearing from other people working in my field and possibly coming home with some ideas for my projects.
When you have well curated data the potential is great. Exploring and validation the potential for prediction functional PD effects. Ultimately using clinical data and insights to design better molecules faster.
SPEAKERS
Nick Brown
Nick Brown is currently the Executive Director of Imaging and Data Analytics, working in AstraZeneca’s Clinical Pharmacology and Safety Sciences department. Nick joined over 20 years ago with a genetics and bioinformatics background to build predictive models for toxicogenomic and pathway data. Since then, he has built imaging platforms to screen high-throughput content screens and search platforms to process hundreds of millions of scientific documents in seconds, enabling drug repositioning and Key Opinion Leader identification. Additionally, Nick setup technology incubation labs for our Chief Technology Officer - focussing on bringing the latest external innovation with tech giants and scientific start-ups into AstraZeneca. He subsequently built a team of over 100 AI engineers, delivering cloud AI platforms and AI services, including knowledge graphs, deep learning, natural language processing and computer vision projects. He currently leads an Imaging and Data Analytics team that consists of both wet and dry labs, pioneering novel technology to today’s immediate business needs.
Alexander Hillisch
Emilie Louvet
I lead the Early oncology and NLP Oncology Information Practice team. The team deliver competitive intelligence data to enable Early Oncology Portfolio progression and drug development milestones investments decisions from Candidate Drug to Ph3ID, clinical design and clinical development plans via NLP& AI.
Soren Bertelsen
Søren Bertelsen holds a master in medicinal chemistry from Aarhus University and a phd in organic chemistry from the same university (awarded with the AUFF phd prize of 2010). After a postdoc at Skejby University Hospital, doing ex vivo chemical experiments and analytic development, he got hired at Novo Nordisk in 2010. Working as a process chemist in the early research laboratories, Sørens tasks included process optimizations and greenification of the choices of reagents and conditions. As a process chemist he became acquainted with DoE and later Bayesian Optimization as a modern way to ensure fast learning and modelling of the parameter-space for chemistry and related fields. In 2020, he transferred to a role in Data Science at Novo Nordisk to further focus on development and sharing of tools for generalized process optimization. Currently, Søren is Director for Process Optimization, working on making robots for autonomous process development. Among others, we have build robots for closed-loop optimization of chemical reactions, ELISA- and LOCI-assays and HPLC-gradients.
Richard Lewis
Richard A. Lewis is Director, Data Science at Novartis in Basel with interests in cheminformatics, ML, AI and generative chemistry. He earned his B.A. and Ph.D. from Cambridge University. He performed postdoctoral studies as a Fulbright scholar at UCSF and as a Royal Commission Fellow in the ICRF before joining RPR in 1991. In 1998 he joined Eli Lilly to lead the European modelling group, and then in 2004 moved to his current role. He has authored over 80 papers and patents, and is a fellow of the Royal Society of Chemistry. H-index > 32
Cathrin Pautsch
Cathrin strives to catalyze digitalization at Roche to accelerate data-driven drug discovery. She is the product owner of a synthesis planning automation (SPA) platform that leverages machine learning for predicting new synthetic routes for chemical compounds.
Helena Andres-Terre
Helena Andres-Terre is an Associate Director at UCB, where she develops AI solutions for Clinical Research, with special interest on Deep Learning, Generative Modelling and Complex Systems.
She holds a PhD in Artificial Intelligence from the University of Cambridge, with experience in Unsupervised Learning Models for multi-modal integration on medical and healthcare data.
Bhavik Chouhan
Gautam Hotti
Philippe Moingeon
Philippe MOINGEON received his PhD in immunology from Paris XI University, and an MBA from Open University Business School (Newcastle, UK). He was formerly Resident of Paris Hospitals (1981-1986), Post-doctoral fellow (1987-1990) and Assistant Professor (1991-1994) at the Dana Farber Cancer Institute, Department of Pathology, Harvard Medical School (Boston, USA).
Philippe has extensive experience in the development of biologicals, holding several positions in the vaccine industry, including Head of the Cancer Vaccine program and General Secretary for Research and Development, at Aventis Pasteur (1994-2003), as well as Senior Vice President, Research and Pharmaceutical Development at Stallergenes (2003-2017). He joined Servier in September 2017, to head the Center for Therapeutic Innovation for immuno-inflammatory diseases.
Two vaccines registered in Europe, USA and Japan, 230 scientific publications in peer-reviewed journals, 23 patents/ patent applications.
Current scientific interests: artificial intelligence and computational modelling in support of drug development; applications to auto-immune, inflammatory and neurological diseases.
Noureddine Ben Khalaf
Andrew Buchanan
An experienced team leader and inspiring scientist with an excellent track record of leading innovative drug discovery projects and related technologies. As a leader, member or mentor of teams Andrew has delivered more than 20 CD’s of which three are launched products benefiting patients. Andrew have over 20 years of successful cross-functional and global matrix-team leadership across BioPharm (R&I, CVRM, Neuro, ID) and Onc. With colleagues he has published over 35 original manuscripts and patents.
Mazen Ahmad
Hanati Tuoken
Gian Marco Ghiandoni
Gian Marco Ghiandoni – Associate Principal Informatician (R&D IT) at AstraZeneca
I am a senior engineer with expertise in chemoinformatics and machine learning. My background knowledge includes computational, medicinal, and organic chemistry, and my work experience has brought me to explore related fields in information technology, such as software and API development, cloud architecture, and database design. I am currently working as a tech lead of the Predictive Insight Platform, a cloud-based molecular property prediction framework built in-house at AstraZeneca.
Christopher Langmead
Dr. Langmead leads Amgen’s efforts in the development and application of AI/ML-based methods for the discovery and optimization of biologics. His team at Amgen is involved with all stages of the pipeline. Prior to joining Amgen, Dr. Langmead was a tenured professor in the School of Computer Science at Carnegie Mellon University where his research concerned the development of a variety of technologies relevant to protein design and scientific automation.
David J. Bearss
Rabia Khan
Kadi Liis Saar
Claus Andersen
Uncover the latest advancements
- Expand your AI-driven capabilities across therapeutic pipelines with emerging approaches to biologics design and high-precision innovative screening platforms.
- Collaborate with emerging AI services and accelerate lead generation with predictable outcomes.
- Improve model generation from amplified quality data that generates actionable insights and functionalises the drug discovery landscape.
Understand AI integrations
- Develop the accessibility of trial analytics for clinical operators using deep learning to guide pipeline progression decision making.
- Streamline and integrate genomic and phenotypic data to impact clinical indication progression via improvements in patient enrolment, adherence and monitoring for equitable, time and cost-efficient clinical trials.
CONFERENCE PACKAGES
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Venue
15 Hatfields Chadwick Court, London, SE1 8DJ
AI-Driven Drug Development Summit Europe invites you to join us at 15Hatfields on the 26-27 April 2023.
Rooms available to attendees here.
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Based on your objectives, we can create bespoke packages designed specifically for you – from presenting your expertise on the main stage, to hosting a private dinner. You can partner with us showcase your brand and make valuable new connections. Opportunities predominantly lie in 3 main categories: Thought Leadership, Branding & Networking.
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