Monday, October 24, 11:40 - 12:40 PDT
James H. Clark Professor in the School of Engineering
Department of Chemical Engineering and Department of Bioengineering
Dr. Swartz obtained his BS in chemical engineering from South Dakota School of Mines and Technology. After working two years for Union Oil Co. of California, he earned his M.S. in chemical engineering and D.Sc. in biochemical engineering at MIT. Following a scientific exchange visit to the U.S.S.R. and an initial research position at Eli Lilly and Co., he joined Genentech in 1981, where he served in both scientific and managerial positions related to protein pharmaceutical development for nearly 18 years.
In 1998, he moved to Stanford University as Professor of Chemical Engineering focusing on cell-free biology. In 1999, he was elected to the National Academy of Engineering, and, in 2003, he helped create Stanford’s new Department of Bioengineering. He was named the Leland T. Edwards Professor in the School of Engineering in 2006 and the James H. Clark Professor in 2009. He is a founder of Sutro Biopharma, Inc., now a public company dedicated to developing cell-free protein pharmaceuticals. Sutro currently has four products in clinical testing with several others in development. Sutro spun off Vaxcyte, a public company using cell-free approaches to develop glycoconjugate vaccines. He also co-founded GreenLight Biosciences, a publicly traded cell-free metabolic engineering company now focusing on low-cost nucleic acid production.
Prof. Swartz’s research seeks to reproduce and direct complex metabolism in a cell-free environment with a broad application focus ranging from the targeted delivery of therapeutics and vaccines to economically attractive and carbon-negative production of commodity biochemicals.
This talk is offered to illustrate the versatility and effectiveness of cell-free biotechnologies for producing medicines as well as commodity chemicals. We build upon a foundation that provides unprecedented control over metabolism. For health-related applications, we are targeting a totally new class of biotherapeutic: one that effectively directs its efficacious load toward a specific cell type. This requires a highly engineered nanoparticle with unprecedented functional capabilities for: a) stability during production, storage, and administration while still releasing its load after entry into the targeted cell, b) accepting a variety of loads of up to several hundred smaller molecules in each nanoparticle and retaining the load until cell entry, and c) either avoiding (for therapeutics) or specifically targeting (for vaccines) immune system cells. Of course, the nanoparticles must also not be contaminated by other proteins or metabolites, must be produced by a reliable production process, and must be highly consistent within a batch and from batch to batch.
For therapeutic and vaccine delivery applications, we have developed a novel production process for a highly mutated form of the Hepatitis B core protein virus-like particle (VLP). I will describe the mutations as well as several innovative process features required for protein production and purification as well as VLP assembly and loading. Early animal data will also be presented.
For the economical and carbon negative production of commodity chemicals, we are using the production of succinic acid as our model. The process must deliver high glucose to succinate conversion efficiency and very high productivity. It must also do so while using membrane associated enzymatic complexes. Additional innovative features are needed to further reduce manufacturing costs. Three of the four carbons in succinate will derive from glucose with the fourth coming from CO2. Since our conversion efficiency target requires additional electrons, these will come from hydrogen. Cell-free approaches makes this all feasible and also provide unprecedented opportunities for precise control and additional cost reductions.
Tuesday, October 25, 11:40 - 12:40 PDT
Biao Huang, FCIC
University of Alberta
Biao Huang received his Ph.D. degree in Process Control from the University of Alberta, Canada, in 1997. He has an MSc degree (1986) and a BSc degree (1983) in Automatic Control from the Beijing University of Aeronautics and Astronautics. He joined the University of Alberta in 1997 as an Assistant Professor in the Department of Chemical and Materials Engineering and is currently a Full Professor. He held the positions of NSERC Senior Industrial Research Chair in Control of Oil Sands Processes and AITF Industry Chair in Process Control. He is an IEEE Fellow, Fellow of the Canadian Academy of Engineering, and Fellow of the Chemical Institute of Canada. He is a recipient of awards including Alexander von Humboldt Research Fellowship from Germany, Best Paper Award from IFAC Journal of Process Control, APEGA Summit Award in Research Excellence, AsTech Outstanding Achievement in Science & Engineering Award and CSChE’s Bantrel Award in Design and Industrial Practice, D.G. Fisher Award, and Syncrude Canada Innovation Award. His research interests include process control, data analytics, and machine learning. He is currently the Editor-in-Chief for IFAC Journal Control Engineering Practice.
Modern industries are awash with a large amount of data. Extraction of information and knowledge discovery from data, especially the data from day-by-day routine operating processes, for process design, control and optimization, is interesting but also very challenging. Data analytics has played an important role in traditional process automation and control. On the other hand, modern machine learning techniques, particularly supervised/unsupervised learning and reinforcement learning techniques, have significantly progressed, attracting great interest from engineering communities. Their roles become even more evident in the autonomous process systems engineering era. An autonomous process system would at least include smart components, autonomous control systems, and fault tolerance capacity while possessing self-learning ability. This presentation will report some of our progress in these directions through data analytics and machine learning approaches. They include virtual sensors, image processing and computer vision systems, autonomous tuning, control and fault tolerance, and experiment and industrial applications, along with explaining the roles that data analytics and machine learning have played.
Wednesday, October 26, 11:40 - 12:40 PDT
Michael R. Hoffmann
The John S. and Sherry Chen Professor Environmental Science and Engineering California Institute of Technology Pasadena, California
Prof. Hoffmann received a BA in chemistry from Northwestern University and a PhD degree from Brown University in 1973. After graduate school, he was appointed as a NIEHS-NIH post-doctoral fellow at the California Institute of Technology. From 1975 to 1980, he was an assistant and associate professor of environmental engineering at the University of Minnesota. In 1980, he moved back to Caltech as a professor. According to Google Scholar, Prof. Hoffmann has more than 72,800 citations with an H-Index of 119. He has also been recognized by the Web of Science as one of the most highly cited researchers in engineering.
Prof. Hoffmann was awarded an Alexander von Humboldt Prize in 1991, the E. Gordon Young Creative Advances Award of Chemical Society of Canada in 1995, the American Chemical Society Award for Creative Advances in 2001, the Jack E. McKee Medal presented by the Water Environment Federation for providing solutions for groundwater remediation in 2003, the A. R. Gordon Distinguished Lecturer in Chemistry at the University of Toronto also in 2003, and a second von Humboldt Prize in 2005. Prof. Hoffmann is a Member of the U.S. National Academy of Engineering. In 2012, Prof. Hoffmann received a Gates Foundation Prize for his group’s work on solar-powered electrochemical treatment of human waste as applied to sanitation in the developing world. In the same year, he was also recognized as a Distinguished Visiting Fellow of the British Royal Academy of Engineering, and as a Global Vision Scholar by Tsinghua University Beijing. Prof. Hoffmann is an Honorary Professor at the Beijing University of Chemical Technology, the Beijing University of Science and Technology, the Beijing University of Aeronautics and Astronautics (Bei-Hang University), and the Beijing Forestry University. In 2017, he was elected as foreign member of the Chinese Academy of Engineering and designated as a Lifetime Honorary Professor of Tsinghua University in 2018. In 2021, Prof. Hoffmann received the China Friendship Award in recognition to his contributions to science and technology in China.
With support from the Bill and Melinda Gates Foundation, the Hoffmann research group has developed, tested, and implemented coupled biochemical and electrochemical reactor systems that are designed for the onsite treatment of wastewater at its source. The treated wastewater is recycled as toilet flushing water without discharge to the environment. Enteric organism disinfection is achieved for bacteria, protozoa, helminths, and viruses via reactive chlorine evolution (CER) due to the oxidation of chloride coupled with the cathodic reduction of water to form hydrogen (HER). With the use proton exchange membranes, the generated hydrogen can be directly used in a hydrogen fuel cell to recharge Li-ion storage batteries. The fundamental aspects of semiconductor electrochemistry for the in situ production of reactive chlorine species, hydroxyl radical, ozone, and hydrogen peroxide will be presented. Alternative electrochemical reactor designs and anode materials will be introduced. Water treatment applications of electro-Fenton chemistry and electro-peroxone reactions to produce hydroxyl radical have also been implemented for use in greywater treatment. Applications of the various electrochemical reactor configurations are being tested in advanced prototypes and commercial systems that are located in underserved areas of the world lacking modern urban infrastructure. Our Caltech/EcoSan and Caltech/ERAM onsite and wastewater treatment systems can be operated without an external source of electricity or a source of running water. In the system shown below, the collected PV-power is stored in lithium ion battery packs in order to be able to operate the coupled biochemical and electrochemical reactor systems for 24 hours per day.
The Caltech/Eco-San (Yixing, China) PV-powered public toilet located in Beijing (left-hand panel) with a built-in coupled biological and electrochemical wastewater treatment system (middle-panel); the Caltech-ERAM public toilet and compact treatment system developed by Caltech/ERAM collaboration in India employs the same the treatment scheme (right-hand panel). Wastewater is treated to near drinking water standards for recycling back for use as toilet flushing water.