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SMi group presents the launch of the inaugural AI in Drug Discovery conference taking place in London on 16th-17th March, 2020.

AI-empowered machine learning technologies hold the potential of reducing drug discovery associated costs by US$ 70 billion in the upcoming 10 years. With an estimated +39% CAGR, AI in drug discovery is leading the way into a shorter, cheaper and more successful R&D era where compound generation is automated, drug synthesis is predictable and undruggable diseases are finally being targeted.

 The presence of AI in drug discovery is tangible with the majority of drug discovery scientist already working with AI-enabled platforms using machine learning and deep learning, neural networks and natural language processing. However, there is a long journey ahead of optimizing AI-human connections and understanding the full potential of AI-enabled tools and platforms.

Those who work in the field know that there is no AI revolution without tackling the field’s number one challenge: DATA. It is crucial now more than ever to come together and discuss strategies to achieve data revolution for further advancing R&D.

Join us at SMi’s inaugural AI in Drug Discovery 2020 Conference and explore the latest AI-enabled approaches for lead compound screening, multi parameter optimization, disease modelling, drug synthesis and design.

  • Listen to case studies form industry leader pharmaceutical and biotechnology that have already incorporated AI into their work
  • Explore how Deep Learning Methods can be leveraged for compound screening, de novo design, multiparameter optimization/ ADME toxicity property predictions, chemical synthesis route predictions
  • Discover strategies for overcoming data-related challenges such as lack of consistent and quality data at the heart of AI and strategies for improving data access
  • Define unique discovery approaches such as fragment-based drug discovery and network-driven drug discovery 
     

VP, Head, Manager, Director, Scientist in


• Artificial Intelligence
• Machine Learning/Deep Learning
• Drug Discovery
• R&D
• Medicinal Chemistry
• Cheminformatics
• Computational Chemistry
• Molecular AI
• AI design
 

Abbvie; AbbVie Deutschland GmbH & Co. KG; Anima Biotech ; Astrazeneca Neuroscience; Axxam S.p.A; Bayer; Bayer AG; Bayer Healthcare; BenevolentAI; Berg LLC; Biogen; Cylenium Pharma; Drug Discovery Chemistry Laboratories Neuroscience Drug Discovery Unit; F Hoffmann-La Roche; Galapagos SASU; Glaxo Smith Kline; GlaxoSmithKline; GSK; Heptares Therapeutics Ltd; Independent; Janssen Pharmaceuticals; Nanna Therapeutics Ltd; Nick Camp Consulting Ltd; Novartis; Nuevolution A/S; Orion Corporation Orion Pharma; RSD; Selvita Ltd.; Storm Therapeutics; UCB; UCB Celltech; Vernalis Research Ltd;

Conference programme

8:30 Registration & Coffee

9:00 Chair's Opening Remarks

Alexander Hillisch

Alexander Hillisch, Director, Medicinal Chemistry, Head of Computational Chemistry, Bayer
View Bio

9:10 Where is the Drug Discovery field heading in 2020? – an industry outlook

Stephen  Pickett

Stephen Pickett, Scientific Director, Computation Sciences, GSK
View Bio

• Reviewing the challenges for pharmaceutical R&D
• Highlighting the opportunities for machine learning
• Showing examples of progress
• Discussing obstacles that need to be overcome

9:50 Integration of AI in drug design: Strategies and challenges

Christian Tyrchan

Christian Tyrchan, Teamleader Computational Chemistry, AstraZeneca Sweden
View Bio

• Augmented Drug Design is here
• Application of AI in Drug Design
• Case studies from AstraZeneca
• Future outlook: Drugs in days?

10:30 Morning Coffee

11:00 AI in Drug Safety and Metabolism

Graham Smith

Graham Smith, Senior Medicinal Chemist, AstraZeneca
View Bio

• Machine Learning and Deep Learning are now commonplace in drug discovery
• There is great value in property and activity predictions available at the point of design
• We will compare the performance of newer AI methods on real world data
• AI is used to enhance many safety outcome measures

11:40 Chemists and computers in harmony: how to surf the wave?

Robert Young

Robert Young, Account Manager, Blue Burgundy
View Bio

• Drug Discovery is a game of establishing facts, recognising patterns and following principles.
• A chemist’s eyes, skill and experience can be augmented by good design and prediction.
• Don’t place your faith in models or models of models; treat/interpret data with caution.
• Compound quality is a destination not a journey.

12:20 Networking Lunch

13:20 PANEL DISCUSSION: The AI paradigm shift – is it just a hype?

Tobias Gabriel

Tobias Gabriel, Global Head of External Drug Discovery, Novartis Institutes for BioMedical Research, Inc.
View Bio

• Artificial intelligence promises to accelerate the drug discovery process and reduce costs, and opportunities to apply ML occur in all stages of drug discovery. Examples include target validation, prospective analysis of chemical reactivity, facilitating the rapid identification of compounds, identification of prognostic biomarkers and analysis of digital pathology data in clinical trials.
• Recently, multi-objective de novo design, more recently referred to as generative chemistry, has had a resurgence of interest. Deep generative models are machine learning techniques that use neural networks to produce new data objects and promise to revolutionize the design-make-test-analyse cycle and dramatically improve research productivity.
• How broadly are these models applied and where do they maximally impact productivity today and in the near future?

14:00 Artificial intelligence in compound design

Gerhard Hessler

Gerhard Hessler, Head of Synthetic Molecular Design, Sanofi
View Bio

• Artificial intelligence and machine learning offer significant potential for compound optimization
• Artificial intelligence can systematically exploit available data for compound design by property prediction
• Different machine learning approaches will be compared
• AI-based de novo design will be discussed

14:40 Leveraging Machine Learning for in silico ADMET Prediction

Alexander Hillisch

Alexander Hillisch, Director, Medicinal Chemistry, Head of Computational Chemistry, Bayer
View Bio

• Multiparameter optimization and virtual compounds
• Overview of ADMET models
• The machine learning triade: data, descriptors, algorithms
• ADMET modeling strategy
• Selected examples of ADMET models and their application in projects

15:20 Afternoon Tea

15:50 Deep / Machine Learning in Early Drug Safety Assessment

Friedemann Schmidt

Friedemann Schmidt, Senior Scientist, Preclinical Safety, Sanofi
View Bio

• This talk will be outlining the potential of Machine Learning applications for toxicological profiling
• We will describe a Deep Learning framework implemented and broadly validated in support of drug research projects.
• Multitask”-DNNs can be tweaked to describe multiple endpoints simultaneously in a single framework, further improving the performance of individual models.
• Typical applications are the early identification of drug liabilities, and contribution to understanding of liabilities, such as safety pharmacology, hepatobiliary metabolic toxicity; off-target mediated clastogenicity; pre-/clinical photosafety.

16:30 Applications of AI/ML approaches in drug discovery and development

Vishal Sahni

Vishal Sahni, Director, Discovery Research, MSD
View Bio

• Overview of AI/ML applications across the drug discovery & development value chain
• Case studies
• Future outlook

17:10 How does AI enable for the Prediction of Favorable Chemical Synthesis Routes?

Govinda  Bhisetti

Govinda Bhisetti, Head of Computational Chemistry, Biogen
View Bio

• Addressing the need for AI-enabled methods in exploring more favorable reaction routes for drug synthesis
• Exploiting the role of AI in understanding what can and cannot be synthesized
• Explaining the step-by-step process of using Machine Learning and Deep Learning for predicting chemical assembly
• Highlighting future strategies of employing AI for improved chemical assembly

17:50 Chair's closing remarks

Alexander Hillisch

Alexander Hillisch, Director, Medicinal Chemistry, Head of Computational Chemistry, Bayer
View Bio

8:30 Registration & Coffee

9:00 Chair's Opening Remarks

Darren Green

Darren Green, Director of Molecular Design, GSK
View Bio

9:10 5 years down the AI road in Discovery: challenges encountered (e.g. data!) and benefits achieved

Friedrich Rippmann

Friedrich Rippmann, Director, Global Computational Chemistry & Biology, Merck
View Bio

• >300 Predictive Models generated, by Machine Learning, including Deep Learning
• Data collection and curation is central to quality models (garbage in, garbage out)
• Major interface development necessary for making models used by all scientists
• AI-based generation of novel molecules meeting predefined requirements becomes a reality

9:50 Data quality, scale and organisation for machine learning in the life sciences

Andrew Leach

Andrew Leach, Head of Chemistry Services, EMBL-EBI
View Bio

• An overview of the data landscape in drug discovery & development
• What do we mean by “data quality” and what is the current state-of-the art?
• What are the future opportunities that will help drive machine learning and AI?
• What should we do now to address these opportunities?

10:30 Morning Coffee

11:00 Drug Discovery Data for AI

John  Overington

John Overington, Drug Discovery Informatics, Medicines Discovery Catapult
View Bio

• The need for speed and agility in data provisioning
• Strategies to rapidly index and curate data on demand
• Automated curation and data validation approaches
• Examples of application to AI drug optimisation

11:40 Artificial Intelligence in Drug Discovery – Opportunities and Pitfalls

Andreas Bender

Andreas Bender, Lecturer for Molecular Informatics, University of Cambridge
View Bio

  • Chemical and Biological Data – quantity, quality, and predictive value in discovery and safety
  • Life science data is not black and white – why ‘AI in drug discovery’ is not trivial
  • Using data in drug discovery: Case studies from repurposing, discovery and safety
  • 12:20 Networking Lunch

    13:20 Drug discovery, strategic thinking and the Centaur Chemist

    Willem Van Hoorn

    Willem Van Hoorn, Chief Decision Scientist, Exscientia
    View Bio

    • Trajectory of hit to candidate is the most expensive part of drug discovery
    • Exscientia has successfully combined AI tech with human strategic thinking into the Centaur Chemist(TM)
    • The Centaur ChemistTM has delivered multiple clinical candidates in less than a year

    14:00 Integrating Artificial Intelligence and Fragment-Based Drug Discovery

    Marcel Verdonk

    Marcel Verdonk, Senior Director, Astex Pharmaceuticals
    View Bio

    14:40 Afternoon Tea

    15:10 How AI is revolutionising drug discovery and development

    Bryn Williams-Jones

    Bryn Williams-Jones, Director of Exploratory Research, Benevolent AI

    • Outlining the hurdles of bringing a new medicine to market; 10+ years, $2.5bn spent, 90% likelihood of failure
    Overview of The Benevolent Platform® which is used by our scientists and technologists
    • Finding new ways to treat disease
    • Improving the efficacy and lowering the development time and costs of new treatments

    15:50 Deep Learning Applied to Ligand-Based De Novo Design: A Real LIfe Lead Optimization Case Study

    Quentin Perron

    Quentin Perron, Co-Founder & CSO, Iktos
    View Bio

    • Introduction to AI in chemistry and drug design in particular
    • Generative AI applied to de novo drug design
    • Presentation of a real life LO project solved with our approach (11 endpoints)
    • Some perspectives on AI in chemistry and future developments

    16:30 Network-Driven drug discovery

    Jonny Wray

    Jonny Wray, Head-áof Discovery Biology, e-Therapeutics PLC
    View Bio

    • Conceptual foundations of a practical, in silico approach to early drug discovery based on modelling biological processes as networks and looking for agents able to perturb those networks
    • Details of the informatics platform implementing the network-driven approach based on the integration of multiple data sources combined with network analytics
    • Successful validation via multiple discovery projects across a range of indications and biological mechanisms

    17:20 Accelerating treatments for rare diseases

    Andrea Pierleoni

    Andrea Pierleoni, Head of Artificial Intelligence, Healx Limited
    View Bio

    • Introduction to HealNet: end-to-end AI-driven platform for drug repurposing
    • Machine Learning as the key to scale up the discovery process
    • Use case study – discovering novel treatments for Fragile X Syndrome

    17:50 Chairman’s Closing Remarks and Close of Day Two

    Darren Green

    Darren Green, Director of Molecular Design, GSK
    View Bio

    +

    FEATURED SPEAKERS

    Alexander Hillisch

    Alexander Hillisch

    Director, Medicinal Chemistry, Head of Computational Chemistry, Bayer
    Andrea Pierleoni

    Andrea Pierleoni

    Head of Artificial Intelligence, Healx Limited
    Andreas Bender

    Andreas Bender

    Lecturer for Molecular Informatics, University of Cambridge
    Andrew Leach

    Andrew Leach

    Head of Chemistry Services, EMBL-EBI
    Christian Tyrchan

    Christian Tyrchan

    Teamleader Computational Chemistry, AstraZeneca Sweden
    Christine Richardson

    Christine Richardson

    Principal Scientist, Computational Chemistry, Domainex
    Darren Green

    Darren Green

    Director of Molecular Design, GSK
    Friedemann Schmidt

    Friedemann Schmidt

    Senior Scientist, Preclinical Safety, Sanofi
    Friedrich Rippmann

    Friedrich Rippmann

    Director, Global Computational Chemistry & Biology, Merck
    Gerhard Hessler

    Gerhard Hessler

    Head of Synthetic Molecular Design, Sanofi
    Govinda  Bhisetti

    Govinda Bhisetti

    Head of Computational Chemistry, Biogen
    Graham Smith

    Graham Smith

    Senior Medicinal Chemist, AstraZeneca
    John  Overington

    John Overington

    Drug Discovery Informatics, Medicines Discovery Catapult
    Jonny Wray

    Jonny Wray

    Head-áof Discovery Biology, e-Therapeutics PLC
    Marcel Verdonk

    Marcel Verdonk

    Senior Director, Astex Pharmaceuticals
    Quentin Perron

    Quentin Perron

    Co-Founder & CSO, Iktos
    Robert Young

    Robert Young

    Account Manager, Blue Burgundy
    Stephen  Pickett

    Stephen Pickett

    Scientific Director, Computation Sciences, GSK
    Tobias Gabriel

    Tobias Gabriel

    Global Head of External Drug Discovery, Novartis Institutes for BioMedical Research, Inc.
    Vishal Sahni

    Vishal Sahni

    Director, Discovery Research, MSD
    Willem Van Hoorn

    Willem Van Hoorn

    Chief Decision Scientist, Exscientia

    Alexander Hillisch

    Director, Medicinal Chemistry, Head of Computational Chemistry, Bayer
    Alexander Hillisch

    Alexander Hillisch is a Director of Medicinal Chemistry and Head of Computational Chemistry at Bayer AG, Wuppertal, Germany. His team supports drug discovery in cardiology and ophthalmology indication areas with computational chemistry, chemoinformatics, in silico ADMET and structural bioinformatics techniques.
    From 1998 to 2003 he headed a research group at EnTec GmbH, Jena, Germany, a subsidiary of Schering AG, Berlin. There he was project manager in preclinical research and involved in the computer-aided design and pharmacological characterization of drugs against gynecological diseases and cancer.
    He conducted his Ph.D. thesis at the Institute of Molecular Biotechnology (IMB), Jena in the area of biophysics (NMR, FRET) and molecular modeling. Alexander Hillisch received his Ph.D. in Biochemistry with Prof. Peter Schuster in 1998 and his diploma in Pharmacy in 1995 from the University of Vienna, Austria.
    He is author of 43 research papers, 61 patents and 2 books. Alexander teaches “Molecular pharmacology and Drug Design” at the University of Cologne from which he received a honorary professorship in 2010.

    Andrea Pierleoni

    Head of Artificial Intelligence, Healx Limited
    Andrea Pierleoni

    Andrea Pierleoni is Head of Artificial Intelligence at Healx a next-generation biotech using the latest advancements in AI to discover life-changing treatments for rare disease patients.
    Andrea has 15 years experience in applying machine learning techniques on biomedical big data to deliver novel solutions for drug discovery both in academia and industry. Before joining Healx he played a key role in the development of the Open Targets Platform, a precompetitive target discovery effort between several large Pharma companies and leading academic institutions.
    Andrea has a degree in Pharmaceutical Biotechnology and a PhD in Computational Biology from the University of Bologna.

    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, leading a group of about 22 postdocs, PhD and graduate students and academic visitors. 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. In 2013 he was awarded an ERC Starting Grant to model mixture effects of chemical structures in biological systems using mechanistic approaches, an area currently very little understood.

    Andrew Leach

    Head of Chemistry Services, EMBL-EBI
    Andrew Leach

    Andrew's initial research was in the field of computational chemistry at Oxford University, UCSF and the University of Southampton. In 1994 he joined GlaxoSmithKline where over the next >20 years he was involved in the development and application of new platform capabilities for drug discovery in areas including computational chemistry and cheminformatics, fragment-based drug discovery, cardiovascular safety, proteomics and biological mass spectrometry. He also contributed to multiple therapeutic projects and led GSK’s early Discovery portfolios against protease, ion channel and epigenetic targets. He is currently Head of Chemistry Services at the European Bioinformatics Institute where his responsibilities include the EBI’s chemogenomics resources (ChEMBL, SureChEMBL), other biologically relevant small molecules and metabolomics.

    Bryn Williams-Jones

    Director of Exploratory Research, Benevolent AI
    Bryn Williams-Jones

    Christian Tyrchan

    Teamleader Computational Chemistry, AstraZeneca Sweden
    Christian Tyrchan

    Christian received his PhD in Chemistry from the Department of Biochemistry in Cologne, with specialization in Pharmacology and Biochemistry. After joining AstraZeneca, he held different computational chemistry roles, contributing to drug discovery projects and building chemoinformatic as machine learning capabilities across the company. He is currently leading the Early RIA Computational Chemistry team and has a keen interest in the application of computational methods and chemoinformatics to drug development.

    Christine Richardson

    Principal Scientist, Computational Chemistry, Domainex
    Christine Richardson

    Christine is a Computational Chemist with 25 years’ experience in industry-based drug discovery. She has worked in a range of organisations including contract research organisations, biotech companies and the pharmaceutical sector and is currently a Principal Scientist at Domainex. She has experience of a wide range of therapeutic areas, although particularly anti-infectives, oncology and the CNS.

    Christine has co-authored 20 publications and is a co-inventor on patents in the tRNA synthetase and GPCR fields.

    She is also a Member of the Royal Society of Chemistry and former Chair of the Molecular Graphics and Modelling Society.

    Darren Green

    Director of Molecular Design, GSK
    Darren Green

    Darren Green is Director of Molecular Design and Senior Fellow, GlaxoSmithKline. Based at Stevenage, his group specialises in the application of molecular design, machine learning, predictive modelling and chemoinformatics methods to drug discovery. Darren also leads the Compound Collection Enhancement strategy for GSK.
    Darren has a PhD in Theoretical Chemistry from the University of Manchester. He is a Fellow of the Royal Society of Chemistry and chair of the Advisory Board for the Hartree Centre, the UK national laboratory for high performance computing, simulation and cognitive science.

    Friedemann Schmidt

    Senior Scientist, Preclinical Safety, Sanofi
    Friedemann Schmidt

    Friedemann Schmidt received his Ph.D. in 2001 for Physical and Computational Chemistry from the
    Technical University of Darmstadt in Germany. In 2001 he started his career as Research Scientist in Chemoinformatics at Aventis Pharma. Since 2004 he held different positions of increasing responsibility at Sanofi R&D, in Computer-Aided Drug Design and recently in Preclinical Safety. In 2015 he was appointed Head of Computational and Systems Toxicology at Sanofi.
    Throughout his career he put his focus on predictive computational methods, namely in the field of toxicology. He has been authoring numerous articles and chapters and has been leading technology and discovery teams in the fields of diabetes, osteoarthritis, cardiovascular and respiratory diseases.

    Friedrich Rippmann

    Director, Global Computational Chemistry & Biology, Merck
    Friedrich Rippmann

    Friedrich Rippmann is Director of Computational Chemistry & Biology at Merck in Darmstadt, Germany. Previously he was head of Bio- and Chemoinformatics at Merck, with responsibility for groups in Germany, France and Switzerland. He was also responsible for the set-up of bioinformatics and protein crystallography in Darmstadt.
    In his academic career he worked at the National Institute for Medical Research, MRC London, and at the German Cancer Research Center in Heidelberg, Germany.
    Several major software developments originated in his group, among them RELIBASE, a comprehensive database of protein-ligand complexes; and more recently DoGSite Scorer, a druggability prediction server; TRAPP, a webtool for analysis of transient binding pockets in proteins; and a panel of methods for selective kinase inhibitor generation. Currently he is working on digitizing many aspects of the early discovery research, including the integration into coherent workflows. Machine Learning, especially Deep Learning, and other aspects of Artificial Intelligence are central to this. Two recent press releases highlight his commitment to making latest AI technologies available to Merck’s drug discovery process.

    Gerhard Hessler

    Head of Synthetic Molecular Design, Sanofi
    Gerhard Hessler

    Dr. Gerhard Hessler is head of Synthetic Molecular Design at Sanofi in Frankfurt. He is responsible for a team of medicinal chemists, computer-based drug design, structural biology and data management. Before, he headed teams in computer-aided drug design and structural biology since 2008. He joined Aventis in 2001 as a computational chemist, after working for four years in the computational chemistry group of the Central Research at Bayer AG.
    Dr. Gerhard Hessler did his Ph.D. at Technical University of Munich in NMR-based conformational analysis of biologically active peptides and oligonucleotides. During his industrial career the main focus of his work is the application of ligand- and structure-based design techniques to the development of drugs.

    Govinda Bhisetti

    Head of Computational Chemistry, Biogen
    Govinda  Bhisetti

    Govinda Bhisetti is a Principal Investigator and Head of Computational Chemistry department at Biogen since 2014. Previously, he worked at Vertex Pharmaceuticals for 22+ years where he led drug design efforts on several drug discovery projects. His research at Vertex led to the discovery of three FDA approved drugs: Agenerase, Lexiva and Incivek. He is a co-inventor of these drugs and named inventor on 26 patents. He has also published 72 research papers including review articles and book chapters. His current activities include application of state of the art computational methods in the discovery of novel drugs for CNS diseases.

    Graham Smith

    Senior Medicinal Chemist, AstraZeneca
    Graham Smith

    Graham F. Smith, PhD CChem FRSC, is currently team leader of computational safety and DMPK, Drug Safety and Metabolism, AstraZeneca, Cambridge, UK. He is active scientifically in the areas of chemical toxicology, DMPK, AI, small molecule lead discovery, chemical technologies and medicinal chemistry. His previous roles were as director medicinal chemistry at Merck in Boston, head of chemical technologies at Pfizer in Sandwich and as a senior scientist at Sanofi, London. He graduated from the University of Nottingham with BSc and Ph.D. with Prof. Gerry Pattenden and completed post-doctoral studies at the Ohio State University with Prof. Leo Paquette.

    John Overington

    Drug Discovery Informatics, Medicines Discovery Catapult
    John  Overington

    John studied Chemistry and then completed a PhD in protein modelling and sequence-structure relationships, he then joined Pfizer,leading the Molecular Informatics Structure and Design department. This was followed by Inpharmatica, where he led the development of a series of computational and data platforms to improve drug discovery. In 2008 John was central to the transfer of this technology to the EMBL-EBI, as the ChEMBL database. John then joined Artificial Intelligence technology company - Stratified Medical (later renamed BenevolentAI), applying machine learning to the development of biomedical data extraction and integration strategies. In 2017 John joined the Medicine Discovery Catapult as CIO, where he leads the development and application of informatics approaches to promote and support application of informatics to drug discovery.

    Jonny Wray

    Head-áof Discovery Biology, e-Therapeutics PLC
    Jonny Wray

    Jonny Wray is Head of Discovery Informatics at e-therapeutics where he has been responsible for the conceptual development of their network driven drug discovery approach, and the design and implementation of the software platform embodying that approach. Jonny has over 30 years’ experience in developing and applying computational approaches to complex biological problems, both in academia and the drug discovery industry.

    Marcel Verdonk

    Senior Director, Astex Pharmaceuticals
    Marcel Verdonk

    Marcel Verdonk received his PhD from Utrecht University in 1995. He then spent four and a half years at the Cambridge Crystallographic Data Centre (CCDC), where he was responsible for the development of a number of structure-based design tools. Since November 2000, Marcel has been at Astex Pharmaceuticals, where he heads up a group developing informatics and structure-based design software applications.

    Quentin Perron

    Co-Founder & CSO, Iktos
    Quentin Perron

    Quentin Perron is a medicinal chemist by training. He holds a PhD in organometallic chemistry from
    the University of Geneva. As a postdoc at UCLA he worked on the total synthesis of
    Brasillicardin A, a complex natural product having a potent immunosuppressive activity.
    After working as medicinal chemist at Laboratoires Servier, he switched to data
    science and chemoinformatics at Quinten, a company specialized in data science services. In 2016,
    with his business partners Yann Gaston-Mathé and Nicolas Do Huu, he co-founded Iktos, a start-up
    company developing AI technologies for new drug design. He is now the CSO of the company.
     

    Robert Young

    Account Manager, Blue Burgundy
    Robert Young

    Rob Young joined Wellcome on Valentine’s day 1990, after completing his undergraduate and D.Phil studies at University of Oxford and Post Doc at Ben May Institute, University of Chicago. His industrial career navigated many changes, mergers and acquisitions, charting significant contributions to six development candidates before moving to early stage discovery.
    Productive partnership with Alan Hill (Physical Properties) culminated in the establishment of Chrom logD and PFI as GSK standards. Author/inventor on approaching 100 publications/ patent applications and visiting Professor, University of St Andrews.
    Rob took early retirement from GSK in July 2019 and set up Blue Burgundy Consulting.

    Stephen Pickett

    Scientific Director, Computation Sciences, GSK
    Stephen  Pickett

    Dr Stephen Pickett is a Scientific Director within the Computational Sciences department, based in Stevenage. He has a degree and PhD in Chemistry and over 25 years’ experience in computational chemistry and cheminformatics applied to drug discovery at Rhone Poulenc, Roche and GSK. Since joining GSK in 2001 he has been involved in a number of initiatives including screening collection design, HTS data analysis, compound attrition, fragment based drug discovery and, most recently, has been developing the science and platforms for automated molecule generation and design. He is an author of over 50 peer-reviewed scientific articles and is a named author on six patent applications. In 2016 he was elected a GSK Fellow.

    Tobias Gabriel

    Global Head of External Drug Discovery, Novartis Institutes for BioMedical Research, Inc.
    Tobias Gabriel

    Tobias Gabriel is the Global Head of External Drug Discovery for Global Discovery Chemistry, Novartis Institutes for BioMedical Research.
    Prior to his current role Tobias was Head of Oncology Chemistry, Basel and Shanghai.
    Tobias joined Novartis ten years ago from Roche where he held positions in Medicinal Chemistry in Palo Alto and as Director of Research Strategy in Basel.
    Tobias studied Chemistry in Berlin and completed his Ph.D. in Organic Chemistry in Munich, followed by postdoctoral studies in nanotechnology at the Hebrew University of Jerusalem.
     

    Vishal Sahni

    Director, Discovery Research, MSD
    Vishal Sahni

    International pharmaceutical R&D professional who has successfully led innovative pre-clinical, clinical and commercial projects across the EU, USA and Asia, with a passion for helping team members to realise their potential and to create high-performing R&D teams and cultures. Former GSK employee from 2017-2019, started a new position in the MSD Neuroscience department as Director of Discovery Research.

    Willem Van Hoorn

    Chief Decision Scientist, Exscientia
    Willem Van Hoorn

    Willem van Hoorn gained an MEng in chemical engineering and a PhD in computational chemistry at the University of Twente, the Netherlands followed by a postdoc at Yale with Bill Jorgensen. He subsequently spent a decade at Pfizer Sandwich focusing on computational techniques for HTS triage and combinatorial library design. This was followed by a position as an IT consultant at Accelrys (now Biovia) assisting a range of clients from small biotech to big pharma. Since 2013 he is pursuing his long term interest of applying computer algorithms to drug discovery at Exscientia.

    Workshops

    Practical application of predictive properties in drug design
    Workshop

    Practical application of predictive properties in drug design

    Copthorne Tara Hotel
    18th March 2020
    London, United Kingdom

    VENUE

    Copthorne Tara Hotel

    Scarsdale Place, Kensington, London, United Kingdom

    The Copthorne Tara Hotel London Kensington is an elegant contemporary four-star hotel in prestigious Kensington, located just a two minutes walk from High Street Kensington underground station, making exploring easy. The hotel offers well-appointed and comfortable guest rooms combining Standard, Superior and Club accommodation. Club rooms offer iconic views over the city and include Club Lounge access for complimentary breakfast and refreshments. Guests can sample the authentic Singaporean, Malaysian and Chinese cuisine at Bugis Street, traditional pub fare at the Brasserie Restaurant & Bar or relax with a delicious drink at West8 Cocktail Lounge & Bar.

    The Copthorne Tara Hotel boasts 745 square meters of flexible meeting space, consisting of the Shannon Suite and the Liffey Suite, ideal for hosting conferences, weddings and social events. Facilities include access to the business centre 24 hours a day, fully equipped fitness room, gift shop, theatre desk and Bureau de Change. With ample onsite parking outside the London congestion charge zone and excellent transport links via Heathrow Airport, the hotel is the perfect location for business or leisure stays. The hotel is within close proximity to the shops of High Street Kensington, Knightsbridge and Westfield London, Olympia Conference Centre, Royal Albert Hall, Kensington Palace and Hyde Park.

     

    A number of our clients have been approached by third party organisations offering to book hotel rooms. We would advise that you do not book through them as they are not representing the SMi Group. SMi Group books all hotel rooms directly. If you are approached by a third party organisation then please contact us before making any bookings. If you have already booked a hotel room using a third party organisation, we would highly recommend contacting the hotel you were booked into to ensure a booking has been made for you. We would also advise you to please check the terms and conditions of the booking carefully.
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    Copthorne Tara Hotel

    Scarsdale Place
    Kensington
    London W8 5SR
    United Kingdom

    Copthorne Tara Hotel

    The Copthorne Tara Hotel London Kensington is an elegant contemporary four-star hotel in prestigious Kensington, located just a two minutes walk from High Street Kensington underground station, making exploring easy. The hotel offers well-appointed and comfortable guest rooms combining Standard, Superior and Club accommodation. Club rooms offer iconic views over the city and include Club Lounge access for complimentary breakfast and refreshments. Guests can sample the authentic Singaporean, Malaysian and Chinese cuisine at Bugis Street, traditional pub fare at the Brasserie Restaurant & Bar or relax with a delicious drink at West8 Cocktail Lounge & Bar.

    The Copthorne Tara Hotel boasts 745 square meters of flexible meeting space, consisting of the Shannon Suite and the Liffey Suite, ideal for hosting conferences, weddings and social events. Facilities include access to the business centre 24 hours a day, fully equipped fitness room, gift shop, theatre desk and Bureau de Change. With ample onsite parking outside the London congestion charge zone and excellent transport links via Heathrow Airport, the hotel is the perfect location for business or leisure stays. The hotel is within close proximity to the shops of High Street Kensington, Knightsbridge and Westfield London, Olympia Conference Centre, Royal Albert Hall, Kensington Palace and Hyde Park.

     

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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, SMI 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@smi-online.co.uk

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