February 26-28, 2018

San Francisco, USA

Speakers

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Jie Fan
CEO
Accutar Biotechnology

Dr. Fan was trained at UC, Berkeley in Biostatistics and obtained his Doctor degree from Cornell/Sloan-kettering in structural biology/Immunology. He was further trained by Dr. Gunter Blobel at Rockefeller University. With a dream of using a hybrid approach (by combining computation design and experimental validation) to accelerate drug discovery, and to reform current “hit-2-lead” drug discovery scheme, Dr. Fan founded Accutar biotech with the support of Dr. Gunter Blobel. Dr. Fan also hold a joint appointment at SUNY, Downstate medical school as a research assistant professor.

Day Two

Wednesday 28th February, 2018

10.50 | Case Study: Accutar Biotech Employs Artificial Intelligence to Revolutionize Drug Discovery

Robin McEntire
Emerging Technologies Solutions Specialist
Data2Discovery Inc

Robin McEntire has been a leader in the application of advanced technologies for over 20 years. He was a founding member of the Bio-Ontologies Consortium, established in 1998, and co-led that for its first ten years. During his research career, he contributed to multiple AI projects, including work on KQML (the Knowledge Query and Manipulation Language), one of the first agent communication languages, efforts leveraging early knowledge representation systems such as LOOM from SRI, and Natural Language Processing work, contributing to the DARPA-funded Message Understanding Conferences (MUC). In the pharma industry Mr. McEntire has led numerous efforts applying semantic technologies to industry problems. Mr. McEntire has an MSE in Computer Science from the University of Pennsylvania and has multiple publications in the areas of ontologies text analytics and agent communication languages.

Day One

Tuesday 27th February, 2018

10.35 | Case Study: Reinventing Drug Discovery with AI

Hugo Geerts
CSO
In Silico Biosciences

Dr. Hugo Geerts is the Chief Scientific Officer at In Silico Biosciences, where he leads the development and use of the company’s patented quantitative systems pharmacology AI discovery engine. Dr. Geerts holds a bachelor’s degree in theoretical physics, a bachelor’s degree in medicine, and a PhD in biophysics from the University of Antwerp. Previously he worked with the legendary Dr. Paul Janssen at the Janssen Research Foundation for over sixteen years, where he headed Alzheimer’s discovery research and led the successful development of galantamine as an Alzheimer’s drug. Dr. Geerts has more than one hundred peer reviewed publications and is inventor/co-inventor on twelve patents.

Day Two

Wednesday 28th February, 2018

10.00 | Case Study:The In Silico Biosciences Quantitative Systems Pharmacology (QSP) Platform as the Next Step in the Big Data AI Value Chain in CNS

Brandon Allgood
CTO
Numerate

Brandon Allgood is the CTO and cofounder at Numerate, Inc, an AI driven drug discovery company.  At Numerate, he manages the development and application of Numerate's AI platform and is responsible for Numerate’s technological vision. Brandon has also served as Director of Computational Science at Numerate and as a Research Scientist at Pharmix. He received a B.S. in Physics from the University of Washington, Seattle, and a Ph.D. in Computational Physics from the University of California, Santa Cruz. Brandon has authored scientific publications in astrophysics, solid-state physics, and computational biology and has 15 years of experience in AI, mathematical modeling, and large scale cloud and distributed computing. He is a member of the Forbes Technology Council and is a UCSC Foundation Trustee.

Day Two

Wednesday 28th February, 2018

11.50 | Case Study: Harnessing the Power of AI to Improve Translation: From Biology to Discovery and Discovery to Development

Ed Addison
CEO
Cloud Pharmaceuticals

Ed Addison co-founded Cloud Pharmaceuticals in 2009. Addison is a serial entrepreneur who founded three previous ventures, two of which successfully merged with public companies.  He has a unique and strong blend of in-depth business and technical experience in biotechnology and in information technology. Addison holds an MS in Biomedical Engineering from Johns Hopkins University and MBA from Duke University Fuqua School of Business, including a diploma in Duke’s Health Sector Management Program. From 2000-2009, Addison focused on a series of ventures in the pharmaceutical and life sciences space. These included start-ups in the life sciences market, including BioFortis, a LIMS venture in Baltimore, and Inclinix, a CRO in Wilmington, NC, and TeraDisc, the predecessor of Cloud Pharmaceuticals, where he was named "Coastal Entrepreneur of the Year" in 2009.

Day Two

Wednesday 28th February, 2018

09.30 | Case Study: Pure AI Approach Versus Augmented Intelligence Approach: Augmentation of Data Using AI to Predict Missing Data to Consequently Build Disease Models

Michael Palovich
Senior Director and Senior Fellow; In Silico Unit
GSK

Dr Michael Palovich received a Bachelor of Science degree in chemistry from Allegheny College; a Ph.D. degree in organic chemistry from the University of Pittsburgh under the guidance of Professor Dennis Curran; and did postdoctoral research studies in James Marshall’s group at the University of Virginia as a National Institutes of Health research fellow. Michael has been at GSK for about 20 years; joining SmithKline Beecham in 1997.  He has spent much of his career in the drug discovery part of the organization performing medicinal chemistry and small molecule lead discovery and lead optimization activities across several therapeutic and disease areas.  Some examples include the Cathepsin C inhibitor lead optimization program in which they discovered and advanced into human trails a targeted covalent irreversible inhibitor, and the muscarinic M3 antagonist lead optimization program which resulted in the discovery of the drug umeclidinium which is found in the medicines; Anoro, Incruse and Trelegy. In addition to the discovery roles mentioned above, he was the head of the Neuronal Targets unit and the Neuro Virtual Proof of Concept Discovery Performance Unit (Neuro VPoC DPU). Michael is currently part of the recently formed in silico drug discovery unit at GSK in which he is interested in identifying and using artificial intelligence, in silico, etc techniques to identify novel small molecule therapeutics.

Day One

Tuesday 27th February, 2018

15.15 | Discuss: The Big Pharma Perspective Around Data Partnership with Smaller Pharma Companies, Biotech Companies and Solution Providers

Francis Kendall
Digital Strategy Leader
Roche

Francis has over 25 years experience in the industry working at several major Big Pharma companies (Hoecsht, Sandoz, Nycomed, Roche, Novartis & now Roche) mainly leading and working within Biometrics groups. His first degree is in Applied Statistics, then he went on to be a Chartered Statistician and Chartered manager and also completed his MBA. He has a keen interest in new technology and the democratisation of data. His current role is within the Strategic Innovation group which helps the organisation look at future digital strategies and opportunities such as Machine Learning and Big Data.

Day One

Tuesday 27th February, 2018

14.30 | Discuss: If the Strength of AI Is in Translation How to Make Smart/Strategic Decisions in Early Phases of Drug Discovery Based on the Lessons Learned from Failed Clinical Trials?

09.30 | Case Study: Big Pharma Perspective on the Use of AI & Machine Learning

Ron Alfa
VP, Discovery & Product
Recursion Pharmaceuticals

Dr. Alfa is Vice President, Discovery and Product at Recursion Pharmaceuticals where he manages scientific product development and external alliances across Recursion's AI-enabled discovery platform. Dr. Alfa's scientific contributions prior to Recursion span Neurosciences, Metabolism, and Genetics.

Day One

Tuesday 27th February, 2018

14.30 | Discuss: If the Strength of AI Is in Translation How to Make Smart/Strategic Decisions in Early Phases of Drug Discovery Based on the Lessons Learned from Failed Clinical Trials?

Day Two

Wednesday 28th February, 2018

12.20 | Case Study: Multi-dimensional Drug Discovery with AI-enabled Phenomics

Hugo Ceulemans
Scientific Director Discovery-Data Sciences
Johnson & Johnson

As Scientific Director Discovery Data Sciences, Hugo currently heads a multidisciplinary team that supports drug discovery with machine learning approaches. This team leverages data from various data sources at industrial scale to build models for the prediction of the bioactivity of compounds, and applies these models for compound selection throughout the discovery phases. The same team also formulates analysis methods for biomarker and drug target identification, with an emphasis on single-cell data methods. 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.

Day One

Tuesday 27th February, 2018

15.15 | Discuss: The Big Pharma Perspective Around Data Partnership with Smaller Pharma Companies, Biotech Companies and Solution Providers

Day Two

Wednesday 28th February, 2018

09.00 | Case Study: Massive Scale Machine Learning for Integrative Compound Activity Prediction

Sang Ok Song
COO
Standigm

As the co-founder and COO of Standigm, Sang Ok Song, PhD is focusing on conceptual design, application and validation of AI models at the interface of AI and biology in order to enhance and accelerate drug discovery. Prior to Standigm, Sang Ok was leading a variety of computational biology activities including bioinformatics and PKPD modeling for antibody drug development at the biotherapeutics lab of the Samsung Advanced Institute of Technology. Sang Ok has an extensive research experience in mathematical and computational modeling and analysis of chemical, biological systems with leading institutions and organizations, including Cornell University, University of Pittsburgh Medical center. He received a PhD in Chemical engineering from Seoul National University, applying machine learning to chemical process monitoring.

Day One

Tuesday 27th February, 2018

13.15 | Case Study: How Drugs or Patients Can Be Represented to Infer Therapeutic Insights

Leonardo Rodrigues
Associate Director, Advanced Analytics
BERG

Leonardo Rodrigues, Ph.D. is the Associate Director of Advanced Analytics at BERG. With more than 15 years of experience in data analysis and R&D, Dr. Rodrigues is a reference in applying AI and advanced analytical methods to extract actionable insights from clinical and biological data. At BERG, he leads the research and analysis of disruptive projects, as well as the development and deployment of innovative analytics technologies and IT platforms. Dr. Rodrigues holds a Ph.D. in Biochemistry and concluded his postdoctoral studies at the Whitehead Institute-MIT, where he applied statistics, bioinformatics, and molecular/cell biology in the study of cancer stem cells and metastasis initiation.

Day One

Tuesday 27th February, 2018

10.00 | Discuss: Evolution of Machine Learning Approaches into Deep Learning Approaches for Drug Discovery: Unlocking the Potential While Avoiding the Hype

09.00 | Case Study: Deploying an AI-driven Drug Discovery Platform

Tudor Oprea
Professor-Medicine & Chief of Translational Informatics & Internal Medicine
University of New Mexico

Tudor Oprea, MD PhD, is a scientist with three decades of experience in biomedical research. His interests include drug discovery, data sciences and machine learning, with application to knowledge management in human health research. Dr. Oprea’s contribution have led to clinical trials in two types of cancer, most notably ketorolac (Toradol™), which shows promise in an open label clinical trial for ovarian cancer. To date, he has co-authored over 170 publication and 8 US patents. He serves as PI for a multi-annual, multi-million dollar NIH project, “Illuminating the Druggable Genome Knowledge Management Center”. Dr. Oprea is also a Guest Professor at Gothenburg University, Sweden.  Visit http://targetcentral.ws and http://datascience.unm.edu for more details.

Day One

Tuesday 27th February, 2018

10.00 | Discuss: Evolution of Machine Learning Approaches into Deep Learning Approaches for Drug Discovery: Unlocking the Potential While Avoiding the Hype

Day Two

Wednesday 28th February, 2018

14.20 | Case Study: Accurate Data and Domain Expertise: Key Ingredients of AI-driven Target and Drug Discovery

Guido Lanza
CEO
Numerate

Guido Lanza is the President and CEO of Numerate. Formerly, Guido was the co-founder and Chief Technical Officer of Pharmix, where he served on the company’s Board of Directors for five years and was named one of Business Week’s “Tech’s Best Young Entrepreneurs under-30” in 2006. Prior to Pharmix, Guido was a research scientist with Professor Koza of Stanford University with whom he developed applications of genetic programming in the area of bioinformatics and computational biology. Guido is the author of 10 scientific publications and inventor of 4 issued patents. He received a B.A. in Molecular and Cell Biology and Integrative Biology from the University of California, Berkeley and an M.Sc. in Bioinformatics from the University of Manchester (UK).

Day One

Tuesday 27th February, 2018

15.15 | Discuss: The Big Pharma Perspective Around Data Partnership with Smaller Pharma Companies, Biotech Companies and Solution Providers

Carolina Garcia Rizo
CBO
Just Biotherapeutics

Carolina is the Chief Business Officer of Just Biotherapeutics and is responsible for corporate strategy, business development, finance and business operations. Carolina brings more than 15 years of strategy, business development, commercial and operational experience within the biopharmaceutical and medical device industries. Carolina joins Just from Thermo Fisher Scientific, where she most recently was Global Managing Director, Business Development. In this role, she was responsible for developing strategic partnerships across the pharmaceutical and healthcare industries for the commercialization of oncology-based diagnostics and companion diagnostics.

Day One

Tuesday 27th February, 2018

14.30 | Discuss: If the Strength of AI Is in Translation How to Make Smart/Strategic Decisions in Early Phases of Drug Discovery Based on the Lessons Learned from Failed Clinical Trials?

Gregory Bell
VP, Global Therapeutic Area Head, Immunology, Infectious Disease and Ophthalmology, PD Safety Science
Genentech

Gregory Bell, M.D. earned his medical degree from Cornell University Medical College and completed his training in Internal Medicine and Rheumatology at Brown University and the University of California, San Francisco (UCSF), respectively.   In 1996 Dr. Bell joined Merck & Co., Inc and, in 1999, became the National Arthritis Medical Director. While at Merck, Dr. Bell contributed to several products that received regulatory approval including Vioxx®, Etoricoxib®  and Cancidas®.  Dr. Bell later joined Abgenix, Inc. and became Vice President of Clinical Development, Biometrics and Clinical Operations with responsibilities across all clinical programs including Vectibix® before joining KAI Pharmaceuticals in 2005.  Dr. Bell was Senior Vice President, Development and Chief Medical Officer at KAI Pharmaceuticals and was responsible for all aspects of development of KAI’s portfolio including Parsabiv®. Dr. Bell is currently Vice President, Safety Risk Management at Genentech and is an assistant professor of Clinical Medicine at UCSF.

Day Two

Wednesday 28th February, 2018

14.50 | Case Study: Machine Learning for Safety Risk Models in Development

Enrico Ferrero
Scientific Leader-Computational Biologist
GSK

After completing a BSc in Biotechnology and a MSc in Molecular Biotechnology at the University of Torino, Enrico started his PhD in Genetics and Systems Biology at the University of Cambridge. Here, he applied experimental and computational genomics approaches to study the role and the functional interactions of Sox transcription factors during the central nervous system development of the fruit fly. At GSK, Enrico works as a data scientist in the Computational Biology group within Target Sciences. He works across the Respiratory and Immuno-Inflammation therapeutic areas focusing on the application of data mining, machine learning and other computational biology approaches to the areas of epigenomics, regulatory genomics and transcriptomics.

Day One

Tuesday 27th February, 2018

14.30 | Discuss: If the Strength of AI Is in Translation How to Make Smart/Strategic Decisions in Early Phases of Drug Discovery Based on the Lessons Learned from Failed Clinical Trials?

12.45 | Case Study: Predicting Novel Drug Targets Using Machine Learning and the Open Targets Data

08.50 | Chair’s Opening Remarks

Natalija Jovanovic
Head Digital Catalyst
Sanofi

Natalija Jovanovic specializes in leveraging digital solutions in heavily-regulated industries. As Head Digital Catalyst at Sanofi, she designs and delivers initiatives as part of Sanofi’s digital strategy, and catalyzes new digital approaches and ways of working. Natalija joined Sanofi from AIG, where she was Head of Business Solutions for Property and Special Risks, and Brown Brothers Harriman (global custody bank) where she was VP of Innovation. Natalija built management skills at McKinsey, and holds a PhD in Electrical Engineering from MIT.

Day One

Tuesday 27th February, 2018

15.15 | Discuss: The Big Pharma Perspective Around Data Partnership with Smaller Pharma Companies, Biotech Companies and Solution Providers

Day Two

Wednesday 28th February, 2018

08.50 | Chair’s Opening Remarks

Asim Siddiqui
CTO
NuMedii

Dr. Siddiqui has over 20 years of experience in bioinformatics and software engineering. Prior to joining NuMedii as Chief Technology Officer, he served as Vice President of Product Development at Natera where he built Natera’s product management and program management functions. Dr. Siddiqui drove improvements to Natera’s NIPT diagnostic including its cloud strategy and cell free cancer program. Prior to that, he served as the Director of Bioinformatics at Life Technologies where he was awarded the Life Technology Inventor Award for his work on NGS bioinformatics. He spent several years at the BC Cancer Agency as Bioinformatics Group Leader involved in large scale genomic projects and leading standards creation. He is an an author and co-author on over 30 peer-reviewed publications. He holds a doctorate in Bioinformatics from Oxford University and a bachelor’s degree in Physics from Cambridge University.

Day One

Tuesday 27th February, 2018

10.00 | Discuss: Evolution of Machine Learning Approaches into Deep Learning Approaches for Drug Discovery: Unlocking the Potential While Avoiding the Hype

Day Two

Wednesday 28th February, 2018

15.50 | Case Study: The Application of AI & Machine Learning in Multi-target Drug Discovery: Polypharmacology

Randal Ketchem
VP, Molecular Design
Just Biotherapeutics

Dr. Randal Ketchem received his Ph.D. in Molecular Biophysics from The Florida State University, focusing on experimental protein structure determination, resulting in the first membrane-bound protein structure solved by Solid State NMR. As part of this effort he developed computational methods for the structure calculation and refinement of membrane-bound proteins. Randy continued his training in structural biology in a postdoctoral fellowship at The Scripps Research Institute where he expanded his experimental and computational efforts into solution-based protein structure. Randy then joined Immunex in 1997 to apply his expertise in protein structure modeling and analysis to efforts in the development of biologic-based therapeutics.

Day One

Tuesday 27th February, 2018

12.15 | Case Study: Improving Bio-therapeutic Development Through AI Technologies

Gerald A. Higgins
Research Professor, Computational Medicine and Bioinformatics
University of Michigan Medical School

Dr. Gerald A. Higgins is Research Professor of Computational Medicine and Bioinformatics at the University of Michigan Medical School. His background includes chief of molecular neurobiology at the NIH, VP of R&D of Laerdal Medical Corporation, CIO of MedStar Health Hospital network, several start-up companies (e.g., SimQuest, Medscape), and VP of pharmacogenomic science at Assurex (now Myriad Genetics). His research combines expertise in pharmacogenomics, psychiatry, and computational analysis to understand human brain networks involved in psychotropic drug response.  His work using artificial intelligence emphasizes pharmacology expertise combined with development of UX (user interface) design to enhance understanding by experimental biologists.

Day One

Tuesday 27th February, 2018

08.50 | Chair’s Opening Remarks

Day Two

Wednesday 28th February, 2018

16.20 | Case Study: Deep Learning in Pharmacogenomics: From Drug Discovery to Patient Stratification

Ben Allen
Senior Computational Research Scientist
e-Therapeutics

Ben ALLEN, PhD is currently a Senior Research Scientist at e-Therapeutics working application of AI/Machine learning to chemical data and developing novel chemoinformatics tools for application to network pharmacology. In the past he was a Research Scientist at Muscagen Ltd, a now deceased small biotech focusing on GPCR modelling.

Day One

Tuesday 27th February, 2018

11.45 | Case Study: Preparation of Chemical Data Sets for Machine Learning Analysis

Day Two

Wednesday 28th February, 2018

10.20 | Case Study: Discovery of New Chemical Entities Using Network-driven Drug Discovery Augmented by AI

Rafael Depetris
Principal Scientist I
Kadmon Therapeutics

Rafael obtained his Ph.D. from NYU in 2008 working with Stevan Hubbard in the field of X-Ray crystallography, specifically focusing on the structural analysis of proteins that interact with the insulin receptor. His post-graduate work was done at Weill Cornell Medical College where he focused in the structural analysis of the HIV-1 Envelope proteins as well as of the HIV-1 neutralizing antibodies. Rafael went on to assume a position of a Senior Scientist at Pfizer CTI in New York, where he initiated his work focused on modeling of targets and therapeutic antibody candidates. He was also commanding the efforts for the humanization of the lead antibody candidates based on the modeling analyses.

Day Two

Wednesday 28th February, 2018

12.50 | Case Study: The Role of Structural Analysis in the Improvement of AI Methods Used in Drug Design