Multiple forces, including lessons from COVID-19, are driving biopharma R&D toward faster development cycles and more decentralized R&D activities across geographies and contract research and development organizations. These two shifts seem
to be at polar odds with one another. Decentralized R&D means more difficult communication and possibly more opportunity for error and delay. On the other hand, faster cycles could bring more intensive communication and data needs and more
localization for efficiency and reliability. Where can innovations in team structure, skillsets, process technology, and digital technology help address these needs?
- Learn about the challenges that are reshaping biopharmaceutical development to be faster and more distributed
- Learn about innovations in scientific workflows, digitization, and process technology
- Learn how industry thought leaders are addressing the challenges of this changing R&D landscape
Heads of R&D, Heads of Digital Innovation, Laboratory Managers, Heads of R&D IT, Head of Data Analytics
Timothy Gardner, PhD
Timothy Gardner, Riffyn’s Founder and CEO, is a scientist who pioneered the field of synthetic biology. He was previously Vice President of R&D at Amyris, where he led the engineering of yeast strain and process technology for bio-manufacturing of renewable chemicals. Tim has been recognized for his pioneering work by Scientific American, the New Scientist, Nature, Technology Review, and the New York Times. He also serves as an advisor to the European Union Scientific Committees, Imperial College London, and the Boston University Engineering Alumni Advisory Board. He holds a Bachelors in Mechanical Engineering from Princeton University and a PhD in Biomedical Engineering from Boston University.
Delivering Products to Market 2x Faster with Blueprints for Science
Biopharmaceutical products are the result of methodical development, iterative improvement, and scale-up of technologies — all of which depend on good data. Industry momentum to digitize the core of R&D has been accelerating – with a focus on more integrated, more accessible, and more useable data by their employees (citizen data scientists). We discuss the value of a process-centric approach to R&D data — using "blueprints" of lab processes. This approach lends itself to the needs of distributed fast-evolving organizations with modular / interacting data ecosystems. It helps to accelerate development and smooth technology transfer across sites and to manufacturing.
Head, Biotech Data Science & Digitization, Bayer
Oliver Hesse is Head of Biotech Data Science & Digitalization at Bayer – Product Supply in Berkeley, CA. He started his career in small biotech, building up and running high-throughput screening systems for large molecules that generated large amounts of data and incorporated automated decision making. Since 2008, he is at Bayer and since 2011, at the Berkeley site. There he has been developing and implementing strategies and directed projects with respect to lab automation, lab informatics, and data sciences for the global biological development organization and since March, he is in his new role where his focus is on the application of data science and digital technologies to gain better process understanding and the seamless digital integration from process development to commercial manufacturing.
Digital Continuum – From Development to Manufacturing
Development of production processes and manufacturing in the biopharmaceutical industry become more distributed. We will discuss approaches to a so called digital continuum that allows for seamless flow of process information. This digital continuum is even more relevant in times where a technical transfer maybe not be possible through in person presence, as seen during the current pandemic. Several key topics and concepts that have been demonstrated at Bayer will be presented.
Vice President, R & D Business Technology, Janssen Pharmaceuticals
Strategic, visionary leader with an established track record of building and leading multidisciplinary, global Informatics and IS/IT teams, driving change and simplification, and delivering value through innovation. She has over 20 years of experience in the biotechnology and pharmaceutical industry working in both Discovery and Development leading projects, managing complex portfolios, driving change programs, identifying opportunities for strategic initiatives, and translating scientific and medical questions into innovative solutions. Anastasia’s areas of particular strength include: strategy development and implementation; translational medicine; biomedical and health informatics; evidence-based decision making; scientific and competitive intelligence; and "Big Data" exploitation.
Digital Transformation in Pharmaceutical R&D
The Pharmaceutical industry has been on a digital transformation journey for a number of years prompted, and at the same time facilitated, by the increased availability of new technologies to generate, manage, and effectively utilize more the ever-increasing volume and speed of data being generated and necessitated, at least in part, by the increase in externalization and collaborations across the industry, academia, and other research organizations. While progressing at different pace across the value chain from discovery through development, manufacturing and commercialization, the current pandemic has increased the urgency and people’s comfort level with adopting new technology, and thereby the pace of transformation, at every stage of the process. This brief talk will share some examples of digital transformation in Pharmaceutical R&D, including a couple of highlights of how the pandemic has acted as a catalyst.
Riffyn was founded in 2014 with the belief, borne of decades of experience, that there was a better way to approach scientific workflows and data. The approach was deceptively simple – make the processes of R&D tangible, transparent, and accessible
to the scientists who operate them. With improved transparency comes better data, better decisions, better science, and a better world. Riffyn Nexus is the world’s first Process Data System – a cloud-based data system that uses R&D
and manufacturing processes as the organizing principle for its data storage, analysis, and user interface.