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AI In Drug Discovery 2021 (Virtual Conference)
15 March - 16 March 2021

Post event on demand access to recorded presentations will be available to all attendees 5 working days from the end date of the event.

AI In Drug Discovery 2021 (Virtual Conference)

SAE Media Group is proud to announce the 2nd annual AI in Drug Discovery virtual conference taking place on 15th and 16th March 2021

With the global Artificial Intelligence (AI) in Drug Discovery Market size expected to exceed $3,900 million by 2027, this year’s agenda will encompass key drivers leading the way into a shorter, cheaper, and more successful R&D era. The conference will cover hot topics including; machine learning techniques for improving early drug discovery, effective prediction of ADMET properties, data quality, and innovative applications of AI for undruggable targets.


This year’s event will focus on 4 key themes: machine learning and automation for improved drug discovery pipelines; effective prediction of compound properties; data robustness and curation; innovative use of AI for rare and undruggable diseases. The agenda will highlight key case studies across these themes, uncovering key developments in pharma of data optimization and to aid therapeutic discovery. Real-world examples of AI in structure-based drug design and patient relevant data will be explored.
 

This two-day agenda offers you peer-to-peer networking with industry experts including directors and heads of informatics, data & AI, molecular design, and computational chemistry, to explore the latest developments in the industry, regulatory updates, and case studies from leading pharmaceutical and biotechnology companies.

FEATURED SPEAKERS

Andreas Bender

Andreas Bender

Lecturer for Molecular Informatics, University of Cambridge
Barun Bhhatarai

Barun Bhhatarai

Investigator, Novartis Institute of Biomedical Research, Novartis Institutes for BioMedical Research
Christophe  Chabbert

Christophe Chabbert

Senior Bioinformatics Scientist, pRED, Roche
ChuangKee Ong

ChuangKee Ong

Associate Director, Information Architect Lead, AstraZeneca
Ed Addison

Ed Addison

Chairman and CEO, Cloud Pharmaceuticals
Hugo Ceulemans

Hugo Ceulemans

Scientific Director Discovery Data Sciences, Janssen Global Services, LLC
Igor  Tetko

Igor Tetko

CEO, BigChem GmbH
Lili Peng

Lili Peng

Associate Director Scientific Ecosystem Analytics Lead, Biogen
Maria Luisa Pineda

Maria Luisa Pineda

CEO and Co-founder, Envisagenics
Mark DePristo

Mark DePristo

CEO & CoFounder, BigHat BioScinces
Naheed Kurji

Naheed Kurji

CEO, Cyclica
Noor Shaker

Noor Shaker

Founder & CEO, Glamorous AI
Peter Henstock

Peter Henstock

Machine Learning & AI Lead, Pfizer Global Pharmaceuticals
Philipe Moingeon

Philipe Moingeon

Department head, Servier Pharmaceuticals
Simone Fulle

Simone Fulle

Head of Molecular modelling & Design, Novo Nordisk
Steve Smith

Steve Smith

Principal Computational Biology Data Scientist, Teva Pharmaceuticals
Yugal Sharma

Yugal Sharma

Senior Director, Custom Services, CAS

Andreas Bender

Lecturer for Molecular Informatics, University of Cambridge
Andreas Bender

Dr Andreas Bender is a Reader for Molecular Informatics with the Centre for Molecular Science Informatics at the Department of Chemistry of the University of Cambridge, as well as an Associate Director for Computational Safety within Clinical Pharmacology & Safety Sciences (CPSS) at AstraZeneca. In his work, Andreas is involved with the integration and analysis of chemical and biological data, aimed at understanding phenotypic compound action (such as cellular readouts, and also organism-level effects) on a mechanistic level, predicting molecular properties related to both compound effiacy and toxicity, as well as drug repurposing. He received his PhD from the University of Cambridge and worked in the Lead Discovery Informatics group at Novartis in Cambridge/MA as well as at Leiden University in the Netherlands before his current post.

Barun Bhhatarai

Investigator, Novartis Institute of Biomedical Research, Novartis Institutes for BioMedical Research
Barun Bhhatarai

Dr. Bhhatarai is an Investigator for Pharmacokinetic Sciences (PKS) department at Novartis Institute for Biomedical Research (NIBR) at Cambridge, MA. He has over 10 years of experience on using various ML and data analytics techniques to support small molecule drug discovery projects. At Novartis, he guides project team members from several therapeutic areas, to mitigate ADMET and PK/PD related issues during the lead optimization and drug candidate selection stages. Prior to that, Dr. Bhhatarai was Systems Toxicology Informatics Fellow in the Predictive Safety Assessment Center at The Dow Chemical Company in Midland, MI. Here, he was responsible for the development, assessment and implementation of novel in-silico alternative approaches aimed at predicting potential mammalian and environmental health effects. He was involved in various Systems Toxicology research projects. He also contributed actively in various workshops related to acute toxicity advocating Alternative Approaches for Identifying Acute Systemic Toxicity. Dr. Bhhatarai is a member of the American Society for Cellular and Computational Toxicology (ASCCT), the American Chemical Society (ACS), IQ consortium and the Society of Toxicology (SOT). He has authored 25+ peer-reviewed publications and several presentations.

Christophe Chabbert

Senior Bioinformatics Scientist, pRED, Roche
Christophe  Chabbert

After graduating from an engineering school, Mines Paristech in Paris, Christophe received a PhD in molecular biology and bioinformatics from the University of Heidelberg/EMBL. Passionate about applying advanced analytics and machine learning to answer complex research questions in Oncology, Christophe worked in several large research and pharmaceutical organizations such as AstraZeneca and ETH Zurich. He has been leading collaborative projects around data integration and AI Ops in Roche over the past 2.5 years.

ChuangKee Ong

Associate Director, Information Architect Lead, AstraZeneca
ChuangKee Ong

ChuangKee (CK) is a proven research and informatics leader in the life science and pharmaceutical industry with solid technical leadership and excellent track records in informatics projects delivery. In his current role as Associate Director, Early Science Information Architecture (Bioinformatics) AstraZeneca UK Ltd, he provides bioinformatics domain leadership to drive the company’s data strategy in target identification and pre-clinical space to achieve FAIRification of research data. He is also responsible for informatics solutions delivery, focusing on the 2 million genomes initiative. Previously he worked on high impact projects such as Ensembl and OpenTargets. Most recently, Data Integration Manager at OpenTargets, a pre-competitive collaboration between EBI, GSK, Sanger Institute, Takeda et al. There, he is responsible for data provision across different EBI teams, that supply various datatypes from genomic, clinical trial, literature, multi-omics, etc. He also led the data integration efforts through common disease ontology. Other roles he has held previously are Principal Scientist, VP at Sime Darby Technology Center, Senior Associate Scientist at Eli Lilly
and Bioinformatics Scientist at Medical Research Council in Edinburgh, Scotland.
 

Darren Green

Director of Molecular Design, GSK
Darren Green

Djork-Arne Clevert

Director, Bayer AG
Djork-Arne Clevert

Djork-Arne´ is the Director of the Machine Learning Research department at Bayer AG. He has a background in computer science and received his doctorate on machine learning for computational biology. In earlier years, his research was mainly in the field of computational biology. Later he shifted this research focus to predicting biological effects of compounds using methods such as deep neural networks and invented Exponential Linear Units (ELUs), which have become a de facto standard in Deep Learning. He is promoter of multiple master and doctoral projects as well as of 6 completed postdoctoral projects. He is author of more than 40 publications in international peer-reviewed journals and books.

Ed Addison

Chairman and CEO, Cloud Pharmaceuticals
Ed Addison

Ed Addison, is Chairman and CEO of Cloud Pharmaceuticals, a Research Triangle Park company from Duke University that applies AI to drug design and discovery, achieving unprecedented results. Cloud Pharmaceuticals has designed new drug candidates for cancer, metabolic diseases and other indications. With over 30 years experience, Ed is on the advisory board and/or board of directors of a number of companies deploying exponential technologies in life sciences, and artificial intelligence, including Drug Logic, Parallel Profile, New Life Cures, and Quantum Cures Foundation.

Hugo Ceulemans

Scientific Director Discovery Data Sciences, Janssen Global Services, LLC
Hugo Ceulemans

As Scientific Director Discovery Data Sciences Hugo currently heads a multidisciplinary team that supports drug discovery with machine learning approaches. This team advises on impactful data generation and combines new with existing data to formalize and improve biological and chemical criteria for molecule selection design, and propose attractive and efficiently synthesizable molecules to make and test. Hugo holds the degrees of MD, MSc in Bioinformatics and PhD in Molecular Biology, and prior to joining Janssen in 2008, he completed postdoctoral fellowships in molecular and computational biology at the University of Leuven and in structural bioinformatics at the European Molecular Biology Laboratories in Heidelberg.

Igor Tetko

CEO, BigChem GmbH
Igor  Tetko

Dr. Tetko is CEO of BIGCHEM GmbH, associative editor of ChemResTox as well as coordinator of the Marie Sklodowska-Curie Innovative Training Network European Industrial Doctorate Horizon2020 project “Advanced machine learning for Innovative Drug Discovery” http://ai-dd.eu. He received MSc degree from Moscow Institute of Physics and Technology, PhD in chemistry from the Ukrainian Academy of Sciences as well as habilitation in cheminformatics from the University of Strasbourg. His research interests include machine learning, neural networks, chemoinformatics, application of machine learning to predict physico-chemical properties and toxicity of molecules, drug-design and Big Data analysis.

James Mault

Founder and CEO, BioIntelliSense, Inc.
James Mault

Lili Peng

Associate Director Scientific Ecosystem Analytics Lead, Biogen
Lili Peng

Dr. Lili Peng is currently the Associated Director of Analytics in Biogen’s External Innovation unit, where she is applying science, data, informatics, and technology to facilitate data-driven decision-making towards expanding Biogen's drug portfolio. She was formerly a strategy and technology consultant, Booz Allen Hamilton, where she executed data science and software implementation projects at the FDA and NIH. Prior to that, Dr. Peng worked as an informatics scientist at AstraZeneca providing analytics solutions in drug discovery and development. Dr. Peng completed her postdoctoral training in computational chemistry and bioinformatics, respectively, at University of California, San Francisco and Stanford University. She completed her Ph.D. thesis in theoretical chemistry from the University of California, San Diego. She graduated Tau Beta Pi from the Massachusetts Institute of Technology with a bachelor’s in chemical engineering.

Maria Luisa Pineda

CEO and Co-founder, Envisagenics
Maria Luisa Pineda

Maria Luisa Pineda, PhD, is the CEO and co-founder Envisagenics. Maria Luisa began her career as a life science venture capital investor before starting the company. Under her leadership, Envisagenics has received nearly $3.5M in non-dilutive SBIR grants and revenue, raised $7.5M from investors, and won several prestigious competitions for excellence in artificial intelligence, including the JLABS Artificial Intelligence for Drug Discovery QuickFire Challenge. Maria Luisa secured the company’s first commercial partnership with The Lung Cancer Initiative at Johnson & Johnson that was announced in April, 2020.

Mark DePristo

CEO & CoFounder, BigHat BioScinces
Mark DePristo

Mark DePristo is Founder and CEO of BigHat Biosciences, an early-stage Bay Area startup reimagining antibody discovery and engineering with synthetic biology and machine learning to create better antibodies faster and undertake novel designs far beyond what's possible today. Mark founded and led the Genomics team in Google Brain, was Vice President of Informatics at SynapDx, and co-director of Medical and Population Genetics at the Broad Institute. He has a BA in Computer Science and Math from Northwestern University, a PhD in Biochemistry from the University of Cambridge as a Marshall Scholar, and was a Damon Runyon Fellow at Harvard University in evolutionary biology. Dr. DePristo's academic articles are widely published and have received more than 73,000 citations.

 

Naheed Kurji

CEO, Cyclica
Naheed Kurji

Naheed Kurji is a Co-founder, and the President and CEO of Cyclica, a Toronto-based venture-backed biotechnology company that leverages its integrated AI-augmented drug discovery platform to advance the discovery of new and better medicines. He is passionate about building AI-augmented technologies that enable researchers to make more strategic and informed decisions in healthcare and the life sciences. Naheed is also a co-founder of The Alliance for Artificial Intelligence in Healthcare (AAIH), of which he is 1 of 4 appointed Executive Officers. He was named by Technology Innovators as one of the top 50 Healthcare Technology CEOs of 2019.

Noor Shaker

Founder & CEO, Glamorous AI
Noor Shaker

Noor is a serial biotech entrepreneur with a track record achievements in AI having held an Assistant Professorship from Aalborg University. Noor has published >50 papers cited >2000 times and is an inventor on a handful of patents. She is passionate about science and on a mission to cure cancer with the power of data and AI. Her work at GlamorousAI pushes the boundaries to what is possible with AI to cure challenging diseases. She is MIT innovator under 35 and in BBC 100 women for 2019.

 

Peter Fedichev

CEO & Founder, Gero.ai
Peter Fedichev

Ph.D. from the University of Amsterdam. Co-founder of Gero, a data-driven longevity biotech company, that develops new drugs against aging and other complex diseases using AI-platform. An author of 75+ published papers in multiple domain areas.

Peter Henstock

Machine Learning & AI Lead, Pfizer Global Pharmaceuticals
Peter Henstock

Peter Henstock is a member of Pfizer’s Quantitative Data Sciences group and serves as the Machine Learning & AI Lead. His work has mostly been at the intersection of statistics, software engineering, visualization and AI to solve problems in drug discovery. Peter holds a PhD in Artificial Intelligence from Purdue University and 6 Master’s degrees. He teaches graduate AI, Software Engineering, and Computer Vision courses at Harvard.

 

Philipe Moingeon

Department head, Servier Pharmaceuticals
Philipe Moingeon

Philippe MOINGEON received his PhD in immunology from Paris XI University, and an MBA from Open University Business School (UK). He was formerly Resident of Paris Hospitals (1981-1986), Post-doctoral fellow (1987-1990) and Assistant Professor at the Harvard Medical School (Boston, USA, 1991-1994).

He acquired expertise in the development of biologicals, with several positions held in the vaccine industry, such as Director for 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 S.A (2003-2017).

He joined Servier Pharmaceuticals in the Paris area in 2017, to head the therapeutic area immuno-inflammation. His current research focuses on the application of artificial intelligence in support of new drug development against auto-immune diseases.
 

Scott Bembenek

Founder, CEO, CSO, Denovicon Therapeutics
Scott Bembenek

Scott Bembenek has a PhD in theoretical chemical physics, was a National Research Council Fellow and is an expert drug discovery scientist with over 18 years in industry drug discovery and computational chemistry. In that time, he has been a key member of the teams that developed several clinical candidates; developed a computational approach that – within only two years – resulted in a clinical candidate for oncology (currently entering Phase 2); and has been a leader on multiple high-profile projects from hit identification to clinical candidacy. Currently, he is the Founder and CEO of Denovicon Therapeutics, which uses their proven computational platform, state-of-the-art hardware infrastructure, and proprietary AI–molecular modeling algorithm to accelerate and improve the development of small-molecule therapeutics.

Simone Fulle

Head of Molecular modelling & Design, Novo Nordisk
Simone Fulle

Simone is heading the ’Molecular Modelling & Design’ department at Novo Nordisk, which is focusing on in silico driven design and engineering of biologics by employing Molecular Modelling, Data Science, and Machine Learning approaches. Activities also include engaging with external collaborations in the field of AI-driven drug discovery and compound design.


Before joining Novo Nordisk, Simone was group leader at the BioMed X Innovation centre in Heidelberg, where she developed together with her team computational methods that support the rational design of selective kinase inhibitors. Simone obtained her PhD in the field of Computational Chemistry from the Goethe-University, Frankfurt/Main, and did a PostDoc in the course of a Marie Curie program at a spin-out company from the University of Oxford.
 

Steve Smith

Principal Computational Biology Data Scientist, Teva Pharmaceuticals
Steve Smith

Steve is a Principal Computational Biology Data Scientist within the Translational Medicine Statistics group at Teva Pharmaceuticals in West Chester, PA, where he supports the company’s efforts in biologics discovery, development, and other non-clinical statistics R&D functions. His specialties include biomarker identification, gene expression analysis, and AI graph neural network development for novel target and disease indication prioritization. He holds a PhD in Biological Sciences from the University of Maryland.

Ton van Daelen

BIOVIA Life Sciences Portfolio Director, Dassault Systemes BIOVIA
Ton van Daelen

Ton is the Portfolio Lead for Scientific Informatics at Dassault Systèmes BIOVIA. He has helped pharmaceutical and biotech customers implement cloud solutions to address internal and external research collaboration challenges. Previously, Ton helped grow the Pipeline Pilot product in various support and product management functions to become the industry standard it is today. Ton has a Ph.D. in theoretical chemistry from the University of Eindhoven, The Netherlands.

Yugal Sharma

Senior Director, Custom Services, CAS
Yugal Sharma

PhD in Biophysics from the University of Cincinnati and over 15-years’ experience applying data science and machine learning approaches in healthcare from the NIH, to start-ups, and consulting firms. Today, he is the Sr. Director for CAS Custom Solutions creating tailored approaches for your unique scientific information challenges.

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Conference agenda

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8:30

Registration & Coffee

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9:00

Chairman's Opening Remarks

Darren Green

Darren Green, Director of Molecular Design, GSK

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9:10

Applications of data science and AI in drug discovery - an industry outlook

Darren Green

Darren Green, Director of Molecular Design, GSK

  • Challenges facing drug discovery pipelines in pharmaceutical R&D
  • Opportunities for data analysis and predictive modelling in drug design
  • Examples of progress
  • Emerging applications of AI for early drug discovery
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    9:45

    AI(d) in informing drug discovery

    Hugo Ceulemans, Scientific Director Discovery Data Sciences, Janssen Global Services, LLC

  • Microscopy images as a data source to drive drug discovery
  • Towards better combining chemistry and biology
  • MELLODDY: federated and privacy-preserving machine learning across pharma
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    10:20

    In silico peptide and protein design

    Simone Fulle, Head of Molecular modelling & Design, Novo Nordisk

  • Applications and opportunities for AI/ML in biologics design
  • Machine learning techniques for peptides
  • Challenges for the implementation of AI in pharmaceutical R&D
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    10:55

    Morning Break Virtual Exhibition Hall Open

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    11:25

    Recent advances in machine learning for ADMETox prediction

    Igor Tetko, CEO, BigChem GmbH

  • Multitask learning, data integration
  • NLP, transformers, and other descriptor-less modelling
  • Interpretation of ADMETox models; explainable AI
  • Estimation of the accuracy of predictions and applicability domain
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    12:00

    Using ML/AI and data analytics tools to accelerate drug discovery by mitigating ADMET issues

    Barun Bhhatarai, Investigator, Novartis Institute of Biomedical Research, Novartis Institutes for BioMedical Research

  • How ML can be used to predict compound properties
  • Using ML/QSP tools to predict interactions between drug and target and enhance safety outcomes
  • How to use prediction data proactively to design enhanced therapeutics
  • Case study: use of ML/AI in ADMET prediction and impact on enhancing compound design
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    12:35

    Bringing operational AI to pre-clinical research workflows

    Christophe Chabbert, Senior Bioinformatics Scientist, pRED, Roche

  • Machine learning and deep learning models are rapidly being adopted throughout the entire drug discovery value chain
  • Deploying business models in business processes is a critical step towards generating business value and transforming pharma research
  • Handling productive deployments and managing models throughout their life cycle requires dedicated and collaborative efforts
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    13:10

    Networking Break Virtual Exhibition Hall Open

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    14:10

    AI for AID: artificial intelligence in support of new drug development for autoimmune diseases

    Philipe Moingeon, Department head, Servier Pharmaceuticals

  • AI-based disease modelling from patient molecular profiling data
  • AI-educated target identification, drug discovery and repurposing
  • First steps towards in silico clinical studies
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    14:45

    Deep Drug Discovery

    Djork-Arne Clevert, Director, Bayer AG

  • De novo design molecules under multi-parametric objectives
  • Predicting protein-ligand interactions using unsupervised learned representations
  • Solving inverse molecular problems
  • Predicting molecular properties with multitask graph convolutional networks
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    15:20

    Combining Machine Learning and Molecular Modeling for Enhanced Active Learning in Small-Molecule Drug Design

  • Combine AI, machine learning and molecular modelling to design, test and optimise lead molecules rapidly in silico
  • Learn how to reduce turnaround time for laboratory synthesis and screening whilst reducing the number of V+R cycles
  • Discover how AI and machine learning approaches can help to identify the best synthesis routes and improve ADME/TOX and other property predictions
  • Ton van Daelen, BIOVIA Life Sciences Portfolio Director, Dassault Systemes BIOVIA

    Scott Bembenek, Founder, CEO, CSO, Denovicon Therapeutics

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    16:00

    Afternoon Break Virtual Exhibition Hall Open

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    16:30

    AI-driven drug discovery platform for splicing driven diseases

    Maria Luisa Pineda, CEO and Co-founder, Envisagenics

  • Introduction to Envisagenics' SpliceCore drug discovery platform, integrating machine learning, high performance computing, and RNA-splicing analytics to identify new therapeutic targets
  • Hybrid business model - ability to partner with biopharmaceutical companies and develop in-house therapeutic pipelines
  • scalable cloud computing that enables efficient and cost effective processing of RNA-sequencing datasets
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    17:05

    Antibody design using synthetic biology and machine learning at BigHat Biosciences

    Mark DePristo, CEO & CoFounder, BigHat BioScinces

  • An introduction to AI/ML in drug discovery
  • An overview of the outstanding challenges in antibody design and engineering
  • Integrating a high-speed wet lab and machine learning for antibody design and engineering
  • Case studies of creating antibodies on BigHat's platform
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    17:40

    Chairman’s Closing Remarks and Close of Day One

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    8:30

    Registration & Coffee

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    9:00

    Chairman's Opening Remarks

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    9:10

    AI in drug discovery - where do we currently stand, and what might be missing?

    Andreas Bender, Lecturer for Molecular Informatics, University of Cambridge

  • AI in drug discovery - available data and problem setting from discovery to safety/efficacy stages
  • Chemical and biological data, and the problem of labelling what we have
  • Some examples and case studies
  • How to move on from here: From ligand discovery to drug discovery
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    9:45

    How does AI help to utilize Genetic, Transcriptomic And Clinical Data for Target Identification in Complex Diseases?

    Peter Fedichev, CEO & Founder, Gero.ai

  • Disease target identification is among the most challenging issues in biomedicine
  • The sheer size of the genetic signal poses a nearly insurmountable challenge in terms of the number of samples required for meaningful association studies
  • We demonstrate the application of a state-of-the-art deep neural network for feature selection (dimensionality reduction) and non-biological variance (batch) removal in transcriptomic signals
  • We showcase the integration of vast experimental data involving gene expression variation in response to genetic knockdowns, ultra-rare damaging mutations from whole-exome sequences, and large clinical data from large human cohorts to prioritize molecular targets associated with a disease
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    10:25

    AstraZeneca's 2 million genomes initiative and the relevance of FAIR data principles in pharmaceutical R&D

    ChuangKee Ong, Associate Director, Information Architect Lead, AstraZeneca

  • The importance of transparent, robust data architecture in pharmaceutical R&D
  • The relevance of FAIR data principles as an enabler for new AI analytics to access data for machine learning and prediction
  • Cast study: AstraZeneca's 2 Million Genomes Initiative has utilised FAIR data principles to enhance productivity in their pharmaceutical R&D
  • Utilising data design to maximise value and deliver enhanced R&D
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    11:00

    Morning Break Virtual Exhibition Hall Open

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    11:30

    Natural Language Processing: an overview of NLP opportunities and challenges in pharma

    Peter Henstock, Machine Learning & AI Lead, Pfizer Global Pharmaceuticals

  • Review some of the fundamental Natural Language Processing subproblems
  • Describe some interesting areas where pharma companies can leverage text mining
  • Discuss some of the challenges faced in some use cases
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    12:05

    Drug Discovery crawler - a new platform for AI and Big Data in drug discovery with the objective of accelerated starts in new drug design

    Ed Addison, Chairman and CEO, Cloud Pharmaceuticals

  • System “crawls” published databases, the literature and GWOS data to identify and discover novel targets
  • Runs a multitude of software programs to identify hits and leads for each from Simulation, AI, known databases and open source contributions
  • Stores target properties (on target effects, pathways, etc.) and lead properties (Pk, solubility, off target effects, toxicity score, etc.)
  • Considers traditional targeted therapeutics, but also poly pharmacy, novel design, repurposing, and modulated biology discovery paradigms
  • Covers small molecules, peptides, protein-protein interactions and large molecules
  • Drug safety of similar drugs
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    12:40

    Drug design with machine learning for challenging targets

    Noor Shaker, Founder & CEO, Glamorous AI

  • Why do we need AI for drug discovery?
  • Recent advances in the use of AI for drug design and optimisation
  • Challenges in ML-driven drug design
  • Use cases for the design of novel small-molecules on a challenging target
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    13:15

    Networking Break Virtual Exhibition Hall Open

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    14:15

    Challenges and opportunities in applying Ml/AI to drug discovery and development

    Steve Smith, Principal Computational Biology Data Scientist, Teva Pharmaceuticals

  • Challenges and opportunities in integrating genetic, genomic, clinical and biological analysis for drug discovery and development
  • Working with ML/AI to create meaningful and actionable data interpretations
  • Drawing on traditional statistics to get better mileage from AI
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    14:50

    Discover new chemistry with more efficient exploration of chemical space

    Yugal Sharma, Senior Director, Custom Services, CAS

  • Anticipate common challenges and adjust approaches to data for improved prediction outcomes
  • The impact of high-quality training data on the predictive power of machine learning models in synthesis planning is demonstrated by enriching a large training set with reactions targeting specific reaction types (case study)
  • How better molecular descriptors improved algorithm performance on predicting biological activity across multiple algorithmic approaches (case study)
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    15:30

    How can AI be exploited to identify the right biological targets?

  • Harnessing the power of machine learning to decode complex biology and identify the most effective targets
  • Technological advances that allow innovations with curative potential
  • Drug design of the future & the important of collaboration
  • Darren Green

    Darren Green, Director of Molecular Design, GSK

    Maria Luisa Pineda, CEO and Co-founder, Envisagenics

    Noor Shaker, Founder & CEO, Glamorous AI

    Peter Henstock, Machine Learning & AI Lead, Pfizer Global Pharmaceuticals

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    16:10

    Afternoon Break Virtual Exhibition Hall Open

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    16:10

    Driving Efficiencies with Data Science in R&D Labs

    Ton van Daelen, BIOVIA Life Sciences Portfolio Director, Dassault Systemes BIOVIA

    Science-driven BioPharma companies are increasingly recognizing the value of Artificial Intelligence (AI) and Machine Learning (ML) in leveraging knowledge resources, accelerating R&D and improving operations. Traditionally, computational experts were the primary users of these tools. Only recently have research organizations been making these tools available directly to end users. With this “democratization” of AI tools, computational experts are no longer the AI gatekeepers. Most importantly, the combination of domain expertise with AI (the “human-in-the-loop” approach) promises to deliver much improved results. Insights gleaned from advanced models and analytics are fueling discoveries, automating complex tasks and transforming an array of industries.
    In this webinar, you will learn about:

  • The important AI/ML techniques in drug discovery
  • Deep learning methods for automated protein crystal detection
  • Reducing the time needed to prepare, assemble and submit CMC documentation for regulatory approval
  • Bringing together multiple data sources and automating complex data processing tasks
  • Teams sharing and reusing best practices across the organization
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    16:40

    Data-driven external innovation for a biotech company

    Lili Peng, Associate Director Scientific Ecosystem Analytics Lead, Biogen

  • Review which external models of R&D innovation are gaining recognition as a valuable strategy for pipeline-building and enabling creative business development engagements
  • Hear how Biogen’s External Innovation Unit uses various disparate data sources and descriptive and predictive analytics (AI/ML) capabilities to identify innovation opportunities
  • Discuss the challenges and lessons learned during the software implementation of an analytics platform
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    17:15

    Advancing Drug Discovery with Machine learning and Polypharmacology to strengthen Patient outcomes

    Naheed Kurji, CEO, Cyclica

  • Bridging knowledge- and structure-based approaches to enable greater predictive performance and expedite drug discovery cycles
  • Advantages of going wide with a polypharmacology-enabled approach to de-risk off-target effects and design small molecules with greater precision
  • Ushering business model innovation to Create the Biotech Pipeline of the Future and the race to address unmet patient needs
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    17:50

    Chairman’s Closing Remarks and Close of Day Two

    Darren Green

    Darren Green, Director of Molecular Design, GSK


    Lecturer for Molecular Informatics
    University of Cambridge
    Investigator, Novartis Institute of Biomedical Research
    Novartis Institutes for BioMedical Research
    Senior Bioinformatics Scientist
    pRED, Roche
    Associate Director, Information Architect Lead
    AstraZeneca
    Director of Molecular Design
    GSK
    Director
    Bayer AG
    Chairman and CEO
    Cloud Pharmaceuticals
    Scientific Director Discovery Data Sciences
    Janssen Global Services, LLC
    CEO
    BigChem GmbH
    Founder and CEO
    BioIntelliSense, Inc.
    Associate Director Scientific Ecosystem Analytics Lead
    Biogen
    CEO and Co-founder
    Envisagenics
    CEO & CoFounder
    BigHat BioScinces
    CEO
    Cyclica
    Founder & CEO
    Glamorous AI
    CEO & Founder
    Gero.ai
    Machine Learning & AI Lead
    Pfizer Global Pharmaceuticals
    Department head
    Servier Pharmaceuticals
    Founder, CEO, CSO
    Denovicon Therapeutics
    Head of Molecular modelling & Design
    Novo Nordisk
    Principal Computational Biology Data Scientist
    Teva Pharmaceuticals
    BIOVIA Life Sciences Portfolio Director
    Dassault Systemes BIOVIA
    Senior Director, Custom Services
    CAS

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    AI Drug Discovery 2021 Brochure

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    Attendee List 2021 AI in Drug Discovery

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    Speaker Interview - Yugal Sharma, CAS

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    Speaker Interview - Christophe Chabbert, Roche

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    Speaker Interview - Steve Smith, Teva Pharmaceuticals

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    Speaker Interview - Peter Henstock, Pfizer

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    AI in Drug Discovery Past Attendee List

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    Chair Invite Letter - Darren Green, GSK

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    Speaker Interview - Maria Luisa Pineda, Envisagenics

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    Speaker Interview - Philippe Moingeon, Servier Pharmaceuticals

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    Speaker Interview - Mark Depristo

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    2021 Conference Programme

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    2020 Past Presentation from Sanofi - speaker 2

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    2020 Past Presentation from Schrödinger

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    2020 Past Presentation from Sanofi - speaker 1

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    CAS

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    CAS, a division of the American Chemical Society, specializes in scientific information solutions to help R&D organizations globally plan, innovate, and protect their innovations, and predict how new markets and opportunities will evolve. Scientific researchers, intellectual property professionals and business leaders around the world across commercial, academic and government sectors rely on our solutions and services to advise discovery and strategy. Leverage our unparalleled content, specialized technology and unmatched human expertise for solutions that will give your organization an information advantage. With more than 110 years' experience, no one knows more about scientific information than CAS.


    Dassault Systèmes

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    Dassault Systèmes, the 3DEXPERIENCE Company, provides business and people with virtual universes to imagine sustainable innovations. By creating ‘virtual experience twins’ of the real world with our 3DEXPERIENCE platform and applications, our customers push the boundaries of innovation, learning and production. Dassault Systèmes helps Life Sciences companies shift the focus to deliver superior, patient-centric, outcome-driven experiences and creating the processes to support them transforms how therapies are discovered, developed, produced, commercialized and used. The group brings value to over 270, 000 customers of all sizes, in all industries, in more than 140 countries.


    Gero.ai

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    Gero is the next-gen AI drug discovery company utilizing real-world big clinical, genetic (WES), and molecular data from vast human cohorts instead of animal models to help our partners create revolutionary medicines against complex diseases. The genetic link between target and disease increases the chances of passing the Phase II clinical trial almost twice. At Gero, we know how to do drug discovery from Whole-Exome Sequencing data to improve clinical trial success much more than that. We identify cause and effect relationships between mutations, disease progression models, targets, and drugs related to them.

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    Select Science

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    SelectScience is an independent, online information resource for the worldwide scientific community, and the home of trusted information for laboratory scientists. Discover impartial, expert opinion and trusted reviews about latest laboratory equipment and techniques; plus videos, application notes and science news from around the world. Become a member for free today.


    IPI

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    http://www.ipimediaworld.com

    IPI – International Pharmaceutical Industry Established by professionals with over 30 years experience in the Pharmaceutical and Life sciences publishing sectors. We have identified the needs of these dynamic industries, and have listened carefully to our readers and advertisers. With strong collaboration between Pharmaceutical and Life sciences Industry Associations we have created a global distribution network. We give you a promise to become a reliable extension of your marketing and communication arm. If necessary we will integrate our expertise with your needs. Incorporating new and innovative communication methods we will help to highlight your expertise.


    SciDoc Publishers

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    SciDoc Publishers is a major source provider of e-journals in the field of Science, Technology and Medicine (STM). The nature of journals - Open Access and Peer-reviewed. We are aimed with a sole motive in making a mark in the field of Open Access, by propagating the knowledge to the scientific community. Our prime concern involves, the knowledge to reach millions of readers and give them access to scientific publications - online.


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    Labsave is the leading savings website for Laboratory Equipment and Lab Supplies. We work closely with the top suppliers in the world to bring you the best products at the most competitive prices. We are constantly striving to secure the biggest and most exclusive offers that you won’t find anywhere else! http://www.labsave.com/


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    PharmaVision offers a consultancy service providing independent pharmaceutical thematic research to the healthcare industry, the investment community and competitive intelligence specialists. We perform due diligence research and provide expert commentary in healthcare. Our reports combine scientific analysis in drug delivery, R&D technologies and pharmaceutical products including patient modelling, product/technology forecasts and market trends evaluation.


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    pharmaphorum drives innovation within the pharmaceutical industry, by bringing healthcare together through a suite of media services that help produce and disseminate thought leadership, combined with an online platform for communicating messages to a global audience.Visit www.pharmaphorum.com


    Pharmalicensing

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    Pharmalicensing (www.pharmalicensing.com) is the premier biopharmaceutical Open Innovation resource designed for professionals involved with partnering, licensing and business development worldwide. Actively supporting all forms of partnering and in- and out-licensing activities, Pharmalicensing utilizes the unique online Showcase Profiling & Discover services, as well as its renowned Partnering Search service leveraging its global network of industry experts, to enable companies to identify and engage with appropriate partners around the world. Pharmalicensing is actively utilized by many tens of thousands of industry professionals each month. Pharmalicensing is a division of Cognis Group, Inc.


    Technology Networks

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    Founded in 2000, Technology Networks is established as the leading news provider for life science and drug discovery professionals. In addition, we provide unique content including webcasts, videos, application notes and posters from recent conferences. Our portfolio now includes around 30 focussed scientific communities, all of which are accessible free of charge within TechnologyNetworks.com


    Mednous

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    http://www.MedNous.com

    MedNous is a print publication and website about medical innovation in Europe. It carries exclusive interviews with companies that are at the forefront of medical technology, as well as contributor articles from prominent practitioners. Our mission is to identify significant advances in medicine and to explain how this innovation is being commercialised. In doing so, we talk to venture capitalists about what products and platforms they are supporting. We report on how regulators cope with the accelerating pace of innovation. And we regularly cover the latest developments in the discovery and development of new medical concepts in the area of antibodies, vaccines, small molecules, regenerative medicine and nanomedicines. MedNous combines the English word for medicine with the Greek word for intellect. And those with nous are readers of our publication. Visit our website: www.mednous.com


    Absave

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    http://www.absave.com

    Absave.com is the leading savings website for Antibodies and Immunological Products. Search our extensive database of Antibodies, Kits, Proteins & Peptides, Reagents, etc. to find the best savings!


    pharmanews hq

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    MedChemNet provides a unique and unparalleled platform for the medicinal chemistry community to share insights, discuss the latest research, and help move the field forward. MedChemNet covers all aspects of the drug discovery pipeline, from target identification and validation, through computer aided drug design (CADD), synthesis, screening and other biophysical techniques, to development of novel lead compounds and pre-clinical in vivo proof of concept. We also cover the design of synthetic drug delivery carriers and ADME/toxicology studies, as well as intellectual property and economic related issues. Website: Welcome to Pharma News HQ, the journal dedicated to the pharmaceutical and biopharmaceutical contract services. With regular sections on contract manufacturing, contract research, contract packaging, formulation/development services, contract analytical testing, APIs, stability testing, clinical research and other areas, we bring the most complete coverage of trends and issues in the industry. Pharmanewshq.com is the only website focusing specifically on issues relevant to pharmaceutical professionals working with technology, be it development, engineering, IT or production.


    Pharmaceutical Technology

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    Pharmaceutical-technology.com is the only website focusing specifically on issues relevant to pharmaceutical professionals working with technology, be it development, engineering, IT or production. Pharmaceutical-technology.com brings you the latest in industry projects and updates, along with the news, views and trends that leading professionals – from senior executives to manufacturing managers and heads of procurement – require to stay on top of their field.


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    PharmaCircle is an innovative knowledge management company serving the current and future global leaders in the Pharmaceutical and Biotechnology related industries. PharmaCircle is a one stop information and analysis source for pipeline, products, clinical trials, drug delivery technologies, deals and acquisitions, company financials, venture capital investments, product sales, pharmaceutical services, news, patents and more….


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    Gate2Biotech is a portal that unites biotechnological community in Central Europe. It covers all the news in the field of biotechnology. Thanks to the the portal the companies engaged in the field can easily search for research institutions and other partners to solve technical problems they are facing and here they can also present their services offer to potential partners from the Czech Republic and abroad. Gate2Biotech portal serves as a bridge connecting scientific and commercial sector. It incorporates offices and support organizations dedicated to promoting transfer of innovative technologies into a unified communication platform of Czech and international biotechnologies. As a mediator of information it draws attention to biotechnologies and support of their application and transfer into practice. It also functions as a tool for encouraging non-professionals (especially scientists and students) towards innovative business or applied research.


    Pharma Journalist

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    Pharma Journalist is a product of Kellen Media. Pharma Journalist is one of the leading website covering the need of global Pharmaceutical Industry. Articles like latest news, trends, analysis, market report, press releases, whitepapers, case studies, etc. published on pharmajournalist.com helps Industry professionals and decision makers to stay on the top of this fast-paced industry. Pharma Journalist aims of providing fast and informative articles to its readers and subscribers.


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    Contract-Biotechnology.com is a web-based platform for laboratory outsourcing solutions. It is an online R&D matching tool that connects Scientifics and service and product providers worldwide. The platform Contract-Biotechnology.com would help you in the process of finding the right partner saving time and money, because with one single and secure application you would be able to receive multiple quotes quickly, keeping your contact information confidential. Contract-Biotechnology.com is the new Collaboration Network Model for Discovery Research and Development. Contract-Biotechnology.com team has extensive experience working for pharmaceuticals, biotechs, universities and academic research institutes and can help you addressing your key gaps.


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    FarmavitaR+ is the professional network of experts and service providers. Network is gathering local consultants from 90 countries in Europe, Asia, North America, Latin America, Australia and Africa. Management of international, multi-centre projects is our core competence. FarmavitaR+ is providing solutions related to pharmaceutical, medical device, food supplement and cosmetic products. Scope of services is related to solutions for product development, quality assurance, clinical trials, product registration, portfolio analysis, lifecycle management, vigilance/risk management, pricing/reimbursing, market access and promotional compliance. FarmavitaR+ is brand name of Farmavita Regulanet Ltd. Visit https://farmavitar.com for more information. Outsource anything you can think of!


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    WHAT IS CPD?

    CPD stands for Continuing Professional Development’. It is essentially a philosophy, which maintains that in order to be effective, learning should be organised and structured. The most common definition is:

    ‘A commitment to structured skills and knowledge enhancement for Personal or Professional competence’

    CPD is a common requirement of individual membership with professional bodies and Institutes. Increasingly, employers also expect their staff to undertake regular CPD activities.

    Undertaken over a period of time, CPD ensures that educational qualifications do not become obsolete, and allows for best practice and professional standards to be upheld.

    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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