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AboutConfirmed Speakers

Speakers

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Daniel Bozinov
Senior Director, Head of ECD Informatics
Genentech

Daniel has expressed a lifelong fascination in the blend of healthcare and computing. Learning how to program when 8-bit CPUs were still fashionable, his love for elegant algorithmic solutions has deeply influenced his way of thinking and appreciation for every single bit (or millisecond) to this very day. However, only in Daniel’s mind this deep love for technology translated into becoming a clinically trained MD with primary focus on human genetics and working experience in both, pediatrics and infectious disease. In a seemingly intentional evasion of having to pick a profession after all, Daniel completed a subsequent Masters program in Computer Science with focus on AI and parallel computing. Later on, Daniel figured it would somehow be a good idea to add another Masters in Cybersecurity to his already chaotic life. Daniel’s professional career includes senior scientist positions at the National Institutes of Health and in academia as well as executive leadership positions in various Silocon Valley startups. As the Head of Informatics & Artificial Intelligence (AI) at Genentech, Daniel currently overseas five distinct teams, i.e. Information Management (IMO), Technology Development (TechDev), Systems Operations (SysOps), Predictive Analytics (gPA), and Artificial Intelligence (AI). Regarding his work style, Daniel is a proud and longstanding Linux desktop user, strong advocate for open source, and absolutely passionate about servant leadership. In his free time he likes to build autonomous robots, develop 3D rendering engines from scratch, or cook "old world" food dishes that he learned from his dad.

Day One

Thursday 13th December 2018

3:40 pm | Panel: Know the Present, Predict the Future

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

Tudor Oprea, MD PhD is Professor of Medicine and Pharmaceutical Sciences, and Chief, Translational Informatics Division, at the Department of Internal Medicine, University of New Mexico School of Medicine in Albuquerque, NM (USA). He is also Guest Professor at the Institute of Medicine, Gothenburg University in Sweden and at the Center for Protein Research, University of Copenhagen, Denmark. Dr. Oprea has co-authored over 200 publications, 8 US patents, and 3 books (as editor). Dr. Oprea is PI for the Illuminating the Druggable Genome Knowledge Management Center, a NIH Common Fund initiative (druggablegenome.net). His computational work led to clinical trials in two types of cancer, most notably for R-ketorolac, which shows promise in ovarian cancer; and G-1, the first G-protein estrogen receptor agonist, currently under therapeutic investigation for melanoma. His most current research is in the development of machine learning and artificial intelligence models for target and drug discovery, by combining numerical and free-text information to model human health.

Day One

Thursday 13th December 2018

11:50 am | Discovery Without Data: Novel Target Selection

8:40 am | Panel: The Good, the Bad and the Ugly

Shruthi Bharadwaj
Scientist
Novartis

Day One

Thursday 13th December 2018

9:20 am | Panel: Big Data, Big Deal?

Day Two

Thursday 13th December 2018

3:00 pm | Panel: Endless Possibilities

2:30 pm | Case Study: AI and Machine Learning Approaches in Clinical Trials

Sándor Szalma
Senior Director - Biomedical Informatics & Global Head of Computational Biology Biomedical Informatics
Takeda

Sándor Szalma is Global Head, Computational Biology in Takeda Pharmaceuticals. He is responsible for computational biology, computational and statistical genetics, machine learning and informatics approaches supporting target discovery and validation/reverse translation and forward translation/biomarker and patient stratification in neuroscience, gastroenterology, rare disease and oncology. He serves as a member of the governance board of Open Targets and leads the Takeda engagement in the Regeneron Whole Exome Sequencing of UK Biobank Consortium. Before joining Takeda, he was head of Translational Informatics and External Innovation, R&D IT in Janssen Research & Development, LLC. Previously, he was member of the industry advisory committee of ELIXIR, member of the board of the Pistoia Alliance, member of the Translational Medicine Advisory Committee of the PhRMA Foundation and led the Data & Knowledge Management Strategic Governance Group of Innovative Medicine Initiative. His past positions included president of MeTa Informatics, general manager of QuantumBio and senior director of Computational Biology and Bioinformatics at Accelrys, Inc. He was co-founder of Acheuron Pharmaceuticals, Inc. He lectured at UCSD Extension and was adjunct professor at Rutgers University in the Computational Biology and Molecular Biophysics program. He is the author of 45 scientific publications and book chapters and two patents. He received his doctoral degree in physical organic chemistry from A. Szent-Györgyi Medical University in Szeged, Hungary.

Day One

Thursday 13th December 2018

9:20 am | Panel: Big Data, Big Deal?

Deirdre Olynick
ATOM, Director - Business Development & Operations
University of Califorina, San Francisco

Dr. Olynick joined ATOM, a consortium for AI driven drug discovery, at its founding in October 2017 as Head of Business Development and Operations. At ATOM,  Dr. Olynick is responsible for creating high value public-private partnerships and understanding the AI, data, and experimental landscape that will drive the future of early drug discovery. In the data space, Dr. Olynick has been working with the ATOM team to enable the AI community with sharable curated and newly generated drug discovery data. Dr. Olynick has an MBA from Wharton and a PhD in Materials Science and Engineering from the University of Illinois at Urbana-Champaign.

Day One

Thursday 13th December 2018

9:20 am | Panel: Big Data, Big Deal?

Bowen Liu
Candidate, Pande Group
Stanford University

Day One

Thursday 13th December 2018

3:40 pm | Panel: Know the Present, Predict the Future

Liling Warren
Associate Director, Lead Translational Statistics
Teva Pharmaceuticals

Liling Warren is Head of Translational Medicine Statistics at Teva Pharmaceuticals. She is responsible for building and applying computational biology, statistical genetics, biomarker analytics to support drug discovery and development projects at Teva. She served as a member of the scientific committee in GRC (Genomic Research Consortium) to evaluate and assess drug discovery and drug repurposing opportunities using Real World Data (RWD)-based GWAS and PheWAS studies. Before joining Teva, she was Director of Statistics at Roivant, Head of US biostatistics at Acclarogen and led many statistical genetics projects at GSK. She received her Ph.D. in Bioinformatics and MS in Statistics from North Carolina State University.

Day Two

Thursday 13th December 2018

9:40 am | Case Study: Biomarker Identification

Marcin Grotthuss
Computational Biologist
The Broad Institute of MIT & Harvard

Senior Computational Scientist with 18 years of experiences in developing sophisticated, analytical, bioinformatics algorithms, pipelines, and portals as well as applying them to understand complex biological data. Credo: the properly conducted analysis of combined clinical, molecular and genomic data can be easily translated into clinical applications to increase a success rate of drug developments and to provide personalized medicine solution to patients.

Day One

Thursday 13th December 2018

3:40 pm | Panel: Know the Present, Predict the Future

12:30 pm | Protein Prediction for Small Molecules and Assays

Lina Nilsson
Senior Director - Data Science Product
Recursion Pharmaceuticals

" I turn complexity into clarity. I lead interdisciplinary teams of data scientists, biologists, software engineers, and computational chemists that turn large quantities (petabytes!) of complex data into actionable insights in drug discovery and healthcare. Central to this challenge is developing and deploying machine learning algorithms that 1) accurately answer the *right* questions, 2) are integrated smoothly at scale, and 3) provide analysis that can be easily understood through intuitive user interfaces. My people-first philosophy: Building long-term strategy and implementing quarterly tactics is hard, and I am obsessed with how to get groups to embrace ideation, mutual respect and vigorous debate, while still driving to clear and timely decisions that scale our business. What motivates me: My career thread has been working with groups that push the limits of new science and emerging tech. I am excited by the human impact that new tools can have as long as we embrace approaches that truly are nuanced, balanced and thoughtful. Beyond the office: I write about women in tech, startup best practices and open science and have been published in the NY Times, Washington Post and Science. I am also a regular speaker on AI in biopharma. And as a final surprise twist, I lead biyearly commercial backpacking trips in Alaska! "

Day One

Thursday 13th December 2018

8:40 am | Panel: The Good, the Bad and the Ugly

Huanyu Zhou
Senior Director and Head Translational and Non-clinical Statistics
Teva Pharmaceuticals

Huanyu Zhou is Senior Director, Head of Translational and Non-clinical Statistics in Teva Pharmaceutical Industries. His team is responsible for 1) statistical genetics/genomics, computational biology, and bioinformatics on target discovery/validation, biomarker identification and patient stratification; 2) pre-clinical and non-clinical statistics in cell-line development, biologics process development, bioassays, animal studies, anti-drug antibody detection, Chemistry, Manufacturing and Controls, and biosimilar and generics development; 3) applying machine learning and artificial intelligence approaches in support of various R&D activities such as patient stratification, cell-line and biologics process development, and clinical trial monitoring. Before joining Teva, he worked at Pfizer and Merck leading translational and genomic analytical activities. He received his doctoral degree in population genetics from Harvard School of Public health.

Day One

Thursday 13th December 2018

12:10 pm | Case Study: Cell Line Development and Bioreactor Prediction

Birgit Schoeberl
Global Head of Modeling, Simulation & Pharmacokinetics Sciences
Novartis

" Biotech/Pharma Executive with more than 15 years experience in R&D. As a bioengineer by training I am passionate about applying computational approaches (machine learning/AI as well as Systems Biology/Systems Pharmacology) to drug discovery and development. Currently, I serve a Global Head of Modeling and Simulation, PK Sciences at Novartis. Before joining Novartis, I served as interim Senior Vice President, Scientific Value, at GNS Healthcare. I focussed on how causal machine learning can drive strategic decision making in drug development. Prior, I established the use of Systems Biology (quantitative Biology combined with mathematical modeling and simulation) at Merrimack Pharmaceuticals where I held assignments of increasing responsibility from 2003 to 2017. As Head of Discovery and Early Development, I was responsible for all target identification and Ph1/2 clinical development activities. I received my Diplom Ingenieur (M. Sc.) in Chemical Engineering from the Technical University in Karlsruhe, Germany, and her Ph.D. in Biological Engineering from the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg. She was a post-doctoral fellow in the laboratories of Douglas Lauffenburger and Peter Sorger in the Biological Engineering Department at MIT. "

Day One

Thursday 13th December 2018

8:40 am | Panel: The Good, the Bad and the Ugly

Day Two

Thursday 13th December 2018

10:00 am | Case Study: In Vivo and In Vitro Model Selection

Andrew Weber
Research Director
ATOM Consortium

Andrew Weber is a Research Director with the ATOM Consortium, a public-private consortium developing accelerated workflows for the discovery of small molecule cancer therapeutics. His current research focus areas are on generative networks for optimization of chemical structure in high performance compute workflows, predictive pharmacokinetics, and drug induced liver injury. Andrew has over 10 years of drug discovery and development experience at GlaxoSmithKline, deploying computational modelling techniques applied to pharmacokinetics (including physiologically based pharmacokinetics), pharmacodynamics, transnational medicine, systems toxicology, route of delivery, and manufacturing throughput and cost of goods. Andrew has a M.S. in Chemical Engineering from Villanova University and a B.S. in Chemical Engineering from Bucknell University.