Cambridge Healthtech Institute’s 2nd Annual

Digital Biomanufacturing

Embracing Digital Transformation in Bioprocessing

August 14-15, 2019


Industry 4.0, internet of things, big data, AI … these are words that we are seeing and hearing around us, enabling exciting developments such as autonomous cars, smart factories and connected cities. This wave of transformation is coming to the biopharm industry, promising to revolutionize the way we approach biologics development to manufacturing.

At CHI’s inaugural Manufacturing 4.0 last year, we introduced the concept of disruptive technologies driving manufacturing changes. This year, we have renamed the conference to Digital Biomanufacturing to reflect our focus on digital implementation, from digital labs to smart factories, from operations to supply chain transformation, and to discuss the tools and technologies enabling this digital transformation – AI, big data, IoT, data mining, predictive analytics, modeling, automation and robotics.

Preliminary Agenda

THE DIGITAL REVOLUTION

Machine Learning in Bioprocess Development: From Current State to the Future

Moritz von Stosch, PhD, Senior Manager, Process Systems Biology and Engineering, Centre of Excellence, GSK

Innovation in Biologics Manufacturing: Moving Towards Personalized Medicines

Antonio Moreira, PhD, Vice Provost, Academic Affairs, UMBC

Applying Industry 4.0 Concepts to Biologics Manufacturing

Richard D. Braatz, PhD, Gilliland Professor, Chemical Engineering, MIT

TRANSFORMING PROCESSES, FACILITIES AND WORKFLOWS

Robotic Automation and Digital Transformation to Enable High Throughput Process Development of Novel Biologics from Clone to Clinic

John Lin, Systems Engineering, Five Prime Therapeutics, Inc.

Digital Transformation and Smart Biomanufacturing Facilities: Case Study from Boehringer Ingelheim (tentative title)

Samet Yildirim, Technology Innovation Manager, Global Technology Management, Boehringer-Ingelheim

Digitization of Raw Material Data and the Application of Data Analytics to Better Understand and Control Variation

Patrick Gammel, PhD, Executive Director, Amgen

Bioprocess Research of Tomorrow: Automated Workflows, Model-based Analytics and Data-driven Decisions

Tobias Grosskopf, PhD, Scientist, Roche Diagnostics

PROCESS MODELING

Product Attribute Forecast - Adaptive Model Selection Using Real-Time Machine Learning (tentative title)

Cenk Undey, PhD, Executive Director, Amgen

Biopharmaceutical Process Models in the Digital Age - How to Make Value Out of Data

MIchael Sokolov, PhD, COO, DataHow, and Lecturer, ETH Zurich

Biopharmaceutical Process Model Evolution – Enabling Process Knowledge Continuum from an Advanced Process Control Perspective

Saly Romero-Torres, PhD, Senior Manager, Advanced Data Analytics, Biogen


* The program is subject to change without notice, due to unforeseen reason.