PAT for Real-time Culture Monitoring and Closed-Loop Process Control
In this three-day, hands-on course, you will gain familiarity with and applied insight into the functionality of control equipment and instrumentation, and how to integrate Process Analytical Technology (PAT) into a model yeast fermentation for more advanced in-line monitoring and process control. Participants will work with traditional sensors, a PAT spectral sensor, and multivariate data analysis (MVDA) software, to model, monitor, and control a microbial process.
This course will give professionals with experience in fermentation an in-depth introduction to process instrumentation and its integration into a distributed control system. Professionals will learn how process information is communicated and used for different engineering controls, including PID control, split-range control, and cascade control within the DeltaV distributed control system. A Raman spectral sensor and Partial Least Squares (PLS) model will be deployed for process monitoring and control to familiarize participants with implementing PAT in an upstream process. Participants will gain hands-on experience with data analytics software to build a data model for monitoring in real-time to enable better control of process parameters such as substrate concentration, and allow tighter control of the culture process. Coming out of this course professionals will have the knowledge of how to deploy a PAT system for an upstream process.
| Dates | Course | Cost | Registration |
|---|---|---|---|
| May 12-13, 2026 | Artificial Intelligence in FDA-Regulated Manufacturing: From Foundations to Implementation | $1,500 | Register |
| May 20–21, 2026 | Hands-On Essentials of Automation for Biomanufacturing | $2,050 | Register |
| May 27–29, 2026 | Preparative Chromatography Column Packing: Lab to Process Scale | $2,500 | Register |
| June 3–4, 2026 | Applied Cleaning Validation Practices: A STERIS Master Class | $2,000 | Register |
| June 9–10, 2026 | Introduction to Biopharmaceutical Lyophilization | $1,975 | Register |
| June 11, 2026 | Essentials of Spray Drying and Powder Analysis | $995 | Register |
| June 16–18, 2026 | Fundamentals of Mammalian Cell Line Development | $3,100 | Register |
| June 23–25, 2026 | Biopharmaceutical Assay Essentials | $3,100 | Register |
| June 23–25, 2026 | Fermentation Engineering | $3,100 | Register |
| June 30–July 2, 2026 | Hands-On Principles of mRNA Technology | $2,500 | Register |
| July 8–10, 2026 | Downstream Biopharmaceutical Processes: Fundamentals and Design | $3,100 | Register |
| July 14–16, 2026 | AAV Quality Attributes: Theory and Practice | $2,975 | Register |
| July 14–17, 2026 | Hands-On cGMP Biomanufacturing Operations | $4,200 | Register |
| July 28–31, 2026 | Hands-On Biomanufacturing of Vectors for Gene Therapy | $4,500 | Register |
| Aug 6, 2026 | Design of Experiments for Biomanufacturing | $500* | Register |
| Sept 29–Oct 1, 2026 | Cell Culture Engineering | $4,200 | Register |
| Oct 13–16, 2026 | Applied Principles and Techniques of Depth Flow Filtration (DFF) and Tangential Flow Filtration (TFF) for BioPharm Purification | $3,995 | Register |
| Nov 10–12, 2026 | PAT for Real-time Culture Monitoring and Closed-Loop Process Control | $2,975 | Register |
| November 12-19 | Microbial Contamination Control in Bioprocessing Operations | $2,975 |
Register by October 26
Attend and you will learn
- To design and set up basic process monitoring, feedback, and control loop systems
- To use commercial MVDA software to model and monitor process parameters in a yeast culture
- To utilize a PAT sensor and PLS modeling for process monitoring and feedback control
Delivery methods
45% Lecture
55% Hands-on lab experience
Course content
30% Fundamentals and concepts
70% Industry applications
22 hours of instruction
Who should attend
This course is intended for scientists and engineers familiar with biomanufacturing processes, and with some experience in fermentation, who are interested in gaining insight into how the control equipment functions and how PAT sensors are employed to monitor a process. This course is appropriate for upstream process engineers, manufacturing scientists, process developers, and integrators who are interested in learning more about using predictions from statistical models to monitor and control a bioreactor process. Participants do not need advanced knowledge of process automation or the use of analytics to build models for this course.