Bio-IT World Conference & Expo Pre-Conference Workshops

Cambridge Healthtech Institute is pleased to offer morning and afternoon pre-conference workshops on Tuesday, October 6, 2020. The workshops are designed to be instructional, interactive and provide in-depth information on a specific topic. They allow for one-on-one interaction and provide a great way to explain more technical aspects that would otherwise not be covered during the main conference tracks that take place Wednesday-Thursday.

Tuesday, October 6, 2020   11:55 - 1:55 PM |

W1: Data Management for Biologics: Registration and Beyond

Detailed Agenda
The research IT systems that are used to support biologics pharma and biotech organizations are maturing to go beyond registration and support assay data collection, analytics and decision support. Additionally, new software providers are bringing forward innovative solutions to address structured data capture and automation. In this workshop we bring together some of the pharma, biotechs, and software providers who will share their approaches to registration and management of biologics data.

Monica Wang, PhD, Principal Technology Lead, Scientific Informatics, Takeda

Sebastian Schlicker, Head, Biologics Business Operations, Genedata AG

In silico Prediction for Biologics Developability and Immunogenicity

Monica Wang, PhD, Principal Technology Lead, Scientific Informatics, Takeda

Biologics drug discovery and development require joint efforts from many scientists with very specific knowledge of Biologics. We are building an integrated Global Biologics Research Informatics Platform to ensure data quality and transparency, improve cross-function collaboration, and enhance data-driven decision-making. This platform will cover many aspects of biologics research from screening, registration, candidate selection, engineering and optimization, with a focus on in silico prediction for developability and immunogenicity. The goal is to accelerate biologics drug design and development with combined in silico prediction and lab experiment data to enable decision-making through real-time data access with integrated systems. This platform will help Discovery Research to improve efficiency and productivity across the lifecycle of biologics innovation.

Digitalizing Biopharma: R&D Innovation through Operational Excellence

Sebastian Schlicker, Head, Biologics Business Operations, Genedata AG

We present a purpose-built E2E workflow platform that supports, both operationally and scientifically, the entire biopharma R&D process. The platform increases overall process efficiency and quality by integrating and automating workflows and identifying the most promising drug candidates to move forward. We show how the platform enables the exploration of new R&D processes, such as the engineering of highly-engineered multi-specific antibodies and novel cell and gene therapies (CARTs, TCRs).

INSTRUCTOR BIOGRAPHIES:

Monica Wang, PhD, Principal Technology Lead, Scientific Informatics, Takeda

Monica currently leads the Biology (including Biologics) Capabilities and Products in Takeda Scientific Informatics. She comes with multidiscipline education with PhD in Biochemistry and MSc in Software Engineering. She has 8+ years of experience in academic research and 15+ years of experience in Research Informatics in the biotechnology and pharmaceutical industries. She is good at strategic planning with proven successful track records of managing complicated global enterprise informatics projects. She has delivered many informatics projects/programs within time and budget for many departments (Global Biologics, Molecular Pathology, Protein Science, Biotherapeutics, Translational Medicine and Legal IP, et al). She is technically and scientifically proficient in Bioinformatics, Cheminformatics, Functional Genomics, and Pharmacogenomics. Her team has designed and implemented many global enterprise informatics solutions to support biologics research, biomarker discovery, translational research and personalized medicine. Her recent focus is concentrated on building a state-of-art Global Biologics Platform to support the global biologics R&D research in Oncology, GI and CNS across Takeda.

Sebastian Schlicker, Head, Biologics Business Operations, Genedata AG

Sebastian Schlicker has more than 15 years of experience in managing pharma R&D IT projects, specializing in the implementation of global enterprise software solutions for large molecule R&D. As the director of Genedata’s Biologics business, Sebastian oversees all major consulting and deployment projects globally. Currently based in Basel, Switzerland, Sebastian previously worked out of the Genedata Boston office, where he helped to build Genedata’s biopharma business in the US. Among his many responsibilities, he led implementation and customization projects for major US biopharma companies. Before joining Genedata, Sebastian worked at Sanofi, where he managed the implementation of new R&D platforms in both small- and large-molecule R&D, covering the complete project life-cycle and resulting in integrated and harmonized enterprise solutions used by scientists around the globe. Sebastian holds a degree in Computer Science and Economics from the University of Applied Sciences in Darmstadt, Germany.

 

W2: A Crash Course in AI: 0-60 in Three

Detailed Agenda
Have you ever been curious to apply machine learning to large amounts of data but were not sure of the concepts to use? Have you ever wondered how to get started on AI? Well, you have come to the right place! This workshop will help you learn AI like never before (our instructors guarantee it!). The workshop is a crash course on AI where you will learn the fundamentals and applications of AI/ML in Pharma. Come join us, learn, and network!

Peter V. Henstock, PhD, Machine Learning & AI Lead, Software Engineering & Statistics & Visualization, Pfizer Inc.

INSTRUCTOR BIOGRAPHY:

Peter V. Henstock, PhD, Machine Learning & AI Lead, Software Engineering & Statistics & Visualization, Pfizer Inc.

Peter Henstock is working to transform Pfizer using AI and Machine Learning. He is the Machine Learning and Technical Lead in Pfizer’s Digital group based in Massachusetts. He holds a PhD in Artificial Intelligence from Purdue University and Master’s degrees in Biology, Software Engineering, Statistics, Applied Linguistics, and Image Processing. Before joining Pfizer, Peter worked at MIT Lincoln Laboratory in image processing and computational linguistics. He also teaches graduate level Machine Learning & Data Mining, Image Processing & Computer Vision, and Software Engineering at Harvard University.

 

W3: Data Science Driving Better Informed Decisions

Detailed Agenda
This workshop will highlight how data science is succeeding in helping pharma organizations make data-driven decisions to gain efficiencies and let companies grow their research programs effectively. Attendees will learn how to bridge the worlds of data scientists and bench researchers and see how novel tools and applications can impact their research.

Meghan Raman, Director, IT - Biometrics & Data Sciences, Bristol Myers Squibb Co.

Nigel Greene, PhD, Director & Head Data Science & Artificial Intelligence, Drug Safety & Metabolism, AstraZeneca Pharmaceuticals

Got Data? Got ML? Raise the Bar for Clinical Trial Feasibility!

Meghan Raman, Director, IT - Biometrics & Data Sciences, Bristol Myers Squibb Co.

Lack of consistent process and usage of non-standardized data result in sub-optimal clinical trial feasibility identification and longer study startup timelines. Country and site identification processes for clinical trials are complex and time consuming as they rely on various standalone data sources and disparate datasets. Foundational datasets and a little bit of machine learning capability can provide an innovative Clinical Trial Feasibility solution to improve study startup timelines through efficient site, country selection and recruitment.

Application of Data Science and AI to Improve the Identification and Development of New Drug Candidates

Nigel Greene, PhD, Director & Head Data Science & Artificial Intelligence, Drug Safety & Metabolism, AstraZeneca Pharmaceuticals

Drug discovery and development is a multiparameter optimization problem that requires a fine balance between efficacy, ADME and safety. Although improvements have been made in the attrition rate for drug candidates there is still plenty of room for improvement. There are strong economic drivers to reduce the costs of discovering new medicines particularly with the rising costs of development and the concerns over late stage failure. Data science and artificial intelligence is being seen as a potential way to improve the discovery and development of new drugs as well as reduce the costs and time to bring these to the clinic. This talk will highlight some of the current investments in computational methods and highlight some of the key gaps in realizing these benefits.

INSTRUCTOR BIOGRAPHIES:

Meghan Raman, Director, IT - Biometrics & Data Sciences, Bristol Myers Squibb Co.

Meghan Raman has 20+ years of experience in successfully leading large scale business transformation programs. She has cross industry domain expertise including Life Sciences, Financial, Consulting, Insurance, Telecomm and Resellers. She is experienced in building and leading global, high performance teams. She has also built Analytics frameworks, AI/ML capabilities and Data Platforms to drive scientific prediction, revenue uplift and productivity. Meghan has led process development and implementation activities in Clinical, Regulatory and Pharmacovigilance domains. She has set up Analytics framework and integration efforts between Product Registration, Safety Reporting and Clinical Trial Management. She is currently leading the IT organization for Biometrics & Data Sciences. She is accountable for the roadmap, strategy, platforms including a Clinical Data Repository & Statistical Compute Environment and various digital-AI/ML products across the Drug Development area including cohort selection, biomarker identification, trial design, site feasibility, signal detection etc.

Nigel Greene, PhD, Director & Head Data Science & Artificial Intelligence, Drug Safety & Metabolism, AstraZeneca Pharmaceuticals

Nigel Greene leads the Data Science and Artificial Intelligence department in Clinical Pharmacology and Safety Sciences at AstraZeneca and is interested in the application of artificial intelligence methods to understand of mechanisms of drug-induced toxicity and their translation to a clinical patient population. Previously Dr. Greene was a head of the Predictive Compound ADME and Safety group at AstraZeneca. Dr Greene also spent 14 years at Pfizer, Inc. where he started in Drug Safety R&D and later transitioned to the Compound Safety Prediction group in Medicinal Chemistry. In his early career, Dr. Greene worked for Lhasa Ltd. where he pioneered computational toxicology, and for Tripos, Inc. Nigel’s other activities outside of AstraZeneca have included being the Chair of the Board of Trustees for Lhasa Ltd. and he has served on multiple National Research Council committees sponsored by the US Environmental Protection Agency, US Food and Drug Administration, and the National Institutes of Health. Dr. Greene received his BSc and PhD from the University of Leeds in the UK.

Tuesday, October 6, 2020   2:15 - 4:15 PM |

W4: Digital Biomarkers and Wearables in Pharma R&D and Clinical Trials

Detailed Agenda
There is a wealth of data in the form of digital information from sensors we use daily, from smart watches to fitness trackers, and this data has the potential to uncover new insight in the form of digital biomarkers. This workshop will cover the role of digital biomarkers in clinical trials and drug development, as well as technical challenges related to extracting data from sensors such as wearables and developing analytics, from the infrastructure to the algorithms. This workshop will also address the role of digital biomarkers in real-world practice in wellness programs and the pharmacy, and ultimately outline how digital biomarkers can advance personalized medicine.

Danielle Bradnan, MS, Research Associate, Digital Health and Wellness, Lux Research

Graham Jones, PhD, Director, Innovation, Technical Research and Development, Novartis

Ariel Dowling, PhD, Director of Digital Strategy, Data Sciences Institute, Research and Development, Takeda Pharmaceuticals

Digital Biomarkers: Unlocking Opportunities in Healthcare

Danielle Bradnan, MS, Research Associate, Digital Health and Wellness, Lux Research

The hype surrounding digital biomarkers coming out of research institutions today for the early diagnostics of health conditions often overlooks the fact that they enable infrastructural changes in the healthcare industry ranging from decentralized care to better informed decisions about resource allocation. In this talk, we will explore the current landscape of digital biomarkers, and how they can impact different players.

Digital Adherence Drivers: A Tale of Assumptions and Realities

Graham Jones, PhD, Director, Innovation, Technical Research and Development, Novartis

Combination products offer seemingly ideal venues for deployment of digital inspired solutions to address patient engagement and adherence rates. Successful design requires innovation processes where patient-centricity is embedded in the iteration cycles, allowing near term field testing. A rapid innovation cycle approach to such design will be highlighted along with examples of successful deployment in selected indications.

Wearable Devices in Drug Development Clinical Trials: Case Studies

Ariel Dowling, PhD, Director of Digital Strategy, Data Sciences Institute, Research and Development, Takeda Pharmaceuticals

Wearable devices are revolutionizing our understanding of human body performance in daily life. This presentation will provide an overview of the use of wearable devices in drug development clinical trials to quantify patient outcome measures and disease progression. Specific case studies in neurology and oncology will be highlighted to illustrate the benefits and hurdles of implementing this technology. This presentation will also provide a rationale for how wearable device data can be used to achieve regulatory approval for new clinical endpoints.

INSTRUCTOR BIOGRAPHIES:

Danielle Bradnan, MS, Research Associate, Digital Health and Wellness, Lux Research

Dani is a Digital Health and Wellness Research Associate at Lux Research with deep expertise in digital therapeutics, digital biomarkers, and FemTech. Prior to her time at Lux, Dani worked as an Environmental Group Manager for a water treatment company, surveying and developing treatment plans for waterborne pathogen outbreaks in healthcare facilities across the United States. Dani graduated with a Masters Degree in biology from the University of Louisiana at Lafayette.

Graham Jones, PhD, Director, Innovation, Technical Research and Development, Novartis

Following his PhD at Imperial College London, Graham was a NATO fellow at Harvard University where he worked with Nobel Laureate E. J. Corey. His independent academic career spanned 25 years and generated >$100 million external funding and 160 peer reviewed publications in the fields of drug discovery, drug delivery, process technology, regulatory science and medical devices. He held a number of leadership roles in the academy including pro-vice chancellor, vice provost and institute director, most recently Professor of Medicine and Director of Translational Research at the Tufts Clinical and Translational Science Institute (CTSI) in Boston MA. In 2018 Graham was recruited by Novartis as Director of Innovation. Graham has been a regular consultant to the pharmaceutical and biotechnology industry and was an advisor to the FDA in the development of the biosimilars approval pathway. He has also been instrumental in establishing and advising a large number of technology-based startup companies who have subsequently raised >$4B in venture funding. Graham sits on several advisory and editorial boards and has been the recipient of numerous awards for scientific and technology development. He was awarded the DSc in 2006 for contributions to medicinal chemistry.

Ariel Dowling, PhD, Director of Digital Strategy, Data Sciences Institute, Research and Development, Takeda Pharmaceuticals

Ariel V. Dowling, PhD is a Director of Digital Strategy within the Data Sciences Institute at Takeda Pharmaceuticals. In this role, Ariel oversees the strategy, assessment, and deployment of digital devices in clinical studies and related activities across the organization. She advises clinical teams on the selection of digital devices, conducts due diligence on vendors, develops digital sensor implementation protocols and risk mitigation strategies, and assists with data analysis plans for device data. Prior to joining Takeda, she was a Senior Clinical Data Scientist at Biogen Inc where she oversaw the analysis of data from wearable sensors deployed in drug development clinical trials for Parkinson’s Disease. Prior to Biogen, Ariel was the algorithm team lead at MC10 Inc, where she oversaw the development and implementation of algorithms across the full product line and managed all aspects of algorithm testing that lead to a successful FDA submission. She has also worked as a senior research scientist at BioSensics LLC, where she designed algorithms to analyze digital device data from Huntington’s disease patients, stroke patients, and wheelchair users. Ariel holds an MS and PhD in Mechanical Engineering from Stanford University and a BE in Mechanical Engineering from Dartmouth College.

 

W5: AI-Celerating R&D: Foundational Approaches to How Emerging Technologies Can Create Value

Detailed Agenda
The potential of emerging technologies like Artificial Intelligence, Robotic Process Automation, Quantum Computing, Blockchain/Distributed Ledger Technology, Internet of Things and more to fundamentally change business models and the way business is conducted cannot be understated. In an overtly buzzword crazy session (buzzword bingo cards will be provided), we’ll work through real practical ways to define, derive, and deliver value from emergent technologies.

Brian Martin, Head of AI, R&D Information Research, Research Fellow, AbbVie

INSTRUCTOR BIOGRAPHY:

Brian Martin, Head of AI, R&D Information Research, Research Fellow, AbbVie

Brian joined AbbVie in October of 2018 as the head of the newly formed RAIDERS team within Research & Development’s Information Research division, focused on accelerating, scaling, and amplifying the work of AbbVie’s R&D community using Artificial Intelligence technologies like machine learning, deep learning, and cognitive computing. Brian came to AbbVie after spending five years in technology consulting across many industries, and over a decade of additional experience before that working in trading and financial markets technology. During his consulting time, Brian architected the United States’ Common Securitization Platform and was a founding member of Publicis.Sapient’s AI practice. While his primary focus is AI technologies, his interests are much broader, and he has presented at multiple conferences on topics including optical networking, quantum computing, blockchain, cognitive architecture, and other emerging technology concepts that are all part of digital transformation. Brian holds a BS degree in Computer and Cognitive Science from Alma College and a MS in Computer Science from the University of Chicago. He is actively involved with technology incubator programs at Mundelein and Lake Forest High Schools, the Creative Destruction Lab at the University of Toronto’s Rotman School, and is a member of the Education Committee for District 115’s Board of Education.

 

W6: Dealing with Instrument Data at Scale: Challenges and Solutions

Detailed Agenda
Instruments including cryo-EM systems, light sheet microscopes, gene sequencers, and X-ray beam lines play a critical role in biomedical research, where discovery is driven by analysis of increasingly large datasets. Managing the data generated by these instruments is complicated and time-consuming, presenting challenges for both the facilities who operate the instruments and the researchers who use them. Instrument facilities want data off their machines as quickly as possible, and require management tools that can scale to many users with very large datasets; they also need automation capabilities to offload routine data management tasks, saving time and money. And researchers just want their data as quickly as possible, so they can get to the job of analyzing the data, sharing it with collaborators, and publishing it to communities and data repositories. The common need is end-to-end solutions that streamline data management throughout the research data lifecycle. In this workshop, we will demonstrate a fast and reliable way to address these challenges via Globus.

Rachana Ananthakrishnan, Executive Director, Globus, University of Chicago

Michael A. Cianfrocco, PhD, Assistant Professor, Department of Biological Chemistry and Research Assistant Professor, Life Sciences Institute, University of Michigan

Brigitte E. Raumann, Product Manager, Globus, University of Chicago

Dealing with Instrument Data at Scale: Challenges and Solutions

Rachana Ananthakrishnan, Executive Director, Globus, University of Chicago

Talk Title to be Announced

Michael A. Cianfrocco, PhD, Assistant Professor, Department of Biological Chemistry and Research Assistant Professor, Life Sciences Institute, University of Michigan

Dealing with Instrument Data at Scale: Challenges and Solutions

Brigitte E. Raumann, Product Manager, Globus, University of Chicago

INSTRUCTOR BIOGRAPHIES:

Rachana Ananthakrishnan, Executive Director, Globus, University of Chicago

Rachana Ananthakrishnan is Executive Director & Head of Products at the University of Chicago, and has a Joint Staff Appointment at Argonne National Laboratory. In her role at the university, she leads Globus (www.globus.org) department, which delivers research data management services and platform to national and international research institutions. She also serves on the WestGrid Board of Directors, and is a member of the InCommon Community Assurance and Trust Board. Her work is focused on research and education field, and she has worked on security and data management solutions on various projects including Earth System Grid (ESG), Biomedical Informatics Research Network (BIRN) and Extreme Science and Engineering Discovery Environment (XSEDE). Prior to that she worked on the Globus Toolkit engineering team and customer engagement teams, leading the efforts in web services and security technologies. Rachana received her MS in Computer Science at Indiana University, Bloomington.

Michael A. Cianfrocco, PhD, Assistant Professor, Department of Biological Chemistry and Research Assistant Professor, Life Sciences Institute, University of Michigan

Michael Cianfrocco grew up in a small town in upstate New York and went to undergraduate at Providence College in Providence, Rhode Island, where he majored in biochemistry. After that, he did his Ph.D. in biophysics in the lab of Eva Nogales at the University of California, Berkeley, focusing on single particle cryo-electron microscopy of human transcription factor complexes. Following his graduate work, he pursued postdoctoral research jointly in the labs of Samara Reck-Peterson and Andres Leschziner at University of California, San Diego. During this time, he helped pioneer the use of cloud computing tools for cryo-EM while also discover a novel mode of dynein regulation by its binding partner Lis1. In his own lab, Michael is passionate about exploring cell biology through the lens of microtubule motor protein transport, and how he can use computational tools to streamline and enhance the power of cryo-EM to determine new and exciting structures.

Brigitte E. Raumann, Product Manager, Globus, University of Chicago

Brigitte Raumann is a Product Manager at Globus and led the effort to enable Globus support for management of protected research data, including PHI and CUI. As the Globus Privacy Officer, she continues to oversee the Globus compliance program and incident investigations. Brigitte has focused her career on providing researchers with the software tools and data they require to advance discovery. Her decades of experience span sectors as diverse as biotech, publishing, patent law, and academic clinical research. Brigitte Raumann earned her B.A. from the University of California, Berkeley and her Ph.D. in biochemistry from the Massachusetts Institute of Technology.






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