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bequette@rpi.edu
- https://orcid.org/0000-0002-6472-1902
About
B. Wayne Bequette is a Professor of Chemical and Biological Engineering and the Technology Manager for the Northern Regional Center of the Clean Energy Smart Manufacturing Innovation Institute (CESMII) at Rensselaer Polytechnic Institute. His research efforts are focused on the modeling and control of biomedical and chemical process systems. Professor Bequette is the author of over 125 refereed journal publications and two textbooks published by Prentice Hall – (i) Process Control: Modeling, Design and Simulation, 2nd ed. (2024), and (ii) Process Dynamics: Modeling, Analysis and Simulation (1998).
He serves as Board Secretary for the American Automatic Control Council and is a Trustee of the Computer Aids for Chemical Engineering (CACHE) Corporation. Dr. Bequette is a founding member of the Editorial Board of the Journal of Diabetes Science and Technology, and serves on the Editorial Board of Industrial & Engineering Chemistry Research. He is a Fellow of IEEE, AIChE and the American Institute of Medical and Biological Engineers, and was inducted into the Arkansas Academy of Chemical Engineers. He is an avid bicyclist (commuting to campus in upstate NY throughout the entire year) and pole-vaulter (Master’s level competition refers more to age than skill level).
1980 B.S. Ch.E. University of Arkansas, Fayetteville
1985 M.S.E. University of Texas, Austin
1986 Ph.D. University of Texas, Austin
Research
Cell and gene therapies, particularly based on CAR-T, have given hope to many cancer patients whose other lines of treatment have failed. Unfortunately, limited manufacturing capability has resulted in many patients dying while on a waitlist. Similarly, since clinical trial treatments are personalized, it is difficult to treat many patients simultaneously, resulting in longer than desired clinical trials. Therapeutic production often takes over 4 weeks, so a product failure means that a patient may need to wait another month for treatment, often putting them at risk for disease progression. The labor-intensive manufacturing process has led to costs that are roughly $500,000 per treatment.
The major objective of our effort is to develop advanced automated analytics and decision-making techniques to reduce clinical trial and treatment time and increase the number of patients that can be treated simultaneously. A systems approach is taken, since patient prior treatments and current state of health, initial cell quality, lymphodepletion and possible bridging therapy before infusion, and supply chain management, all impact treatment success. The microbiota is important since patients who have taken broad-spectrum antibiotics before receiving CAR-T cell therapy have less microbiome diversity and poorer treatment outcomes. Post-infusion patient monitoring using wearables can enable a safer and more rapid transition to out-patient status.
We stress that “manufacturing” is more than the multiple steps from aphaeresis to infusion, but includes detailed information about the patient, prior and on-going treatments, cell phenotype, etc. A major challenge is reducing T-cell "exhaustion" and several solutions have been proposed. Different bioreactors for T-cell expansion can lead to different T-cell differentiation states and thus reduced exhaustion and better efficacy. Our initial focus is on the approved FDA CAR-T therapies for hematological cancers because there are patient outcome results available, but we also discuss on-going efforts to treat solid tumors.
Deep learning and AI applications in healthcare, Deep learning and AI applications in smart manufacturing , Diabetes technology, Process systems automation and control, Human-in-the-Loop, Safety
Teaching
Teaches courses in process systems engineering. Courses are taught using a flipped-classroom format, where students review reading material and watch brief screencasts, then take a brief online quiz before attending class; this assures that the students have some general background on the material being covered in the “studio classroom,” which enables further discussion and problem-solving sessions involving analytical and numerical solutions.
Chemical Process Dynamics and Control, Model Predictive Control, Chemical Process Design, Introduction to Computational Chemical Engineering, Chemical Reactor Design
Recognition
Fellow, Institute of Electrical and Electronics Engineers (IEEE), 2016
Fellow, American Institute of Medical and Biological Engineering (AIMBE), 2014
Fellow, American Institute of Chemical Engineers (AIChE), 2008
Rensselaer School of Engineering Research Excellence Award, 2008
Arkansas Academy of Chemical Engineers (AAChE), 2007
https://www.aiche.org/chenected/2024/10/cell-therapies-conference-speaker-b-wayne-bequette-on-life-saving-benefits-cell-and-gene
Publications
The following is a selection of recent publications in Scopus. B Wayne Bequette has 194 indexed publications in the subjects of Engineering, Chemical Engineering, Medicine.