About Workshop
Smart biomanufacturing is at the intersection of biotechnology and artificial intelligence, promising transformative improvements in product yield, process efficiency, and quality control. This workshop delves into how AI and automation reshape modern bioreactor operations—through real-time monitoring, automated control, and adaptive responses. Participants will be introduced to cutting-edge AI tools like TensorFlow, Azure ML, and MATLAB for predictive modeling and analytics.
Through hands-on demonstrations, expert-led discussions, and real-world case studies, participants will gain practical knowledge of designing and simulating AI-controlled bioproduction systems. From GMP compliance to predictive maintenance and adaptive process control, this workshop prepares the next generation of biotechnologists and bioengineers for the smart factories of the future.
Aim
To equip participants with knowledge and practical insights into AI-driven biomanufacturing processes. The workshop will demonstrate how smart automation, AI/ML, and real-time monitoring revolutionize bioproduction. Attendees will learn to design intelligent systems that optimize yield, detect faults, and ensure compliance. Emphasis will be placed on practical tools and industry use cases.
What Participants Will Learn
- Understand smart biomanufacturing principles and AI applications
- Learn real-time bioreactor monitoring and control
- Apply ML for predictive maintenance and process optimization
- Gain exposure to AI tools like TensorFlow, MATLAB, Azure ML
- Simulate an end-to-end AI-controlled bioproduction system
Structure
Day 1 – AI-Powered Bioprocess Control Systems
- Real-Time Monitoring and Control in Smart Bioreactors
- Introduction to AI in bioprocessing
- Bioreactor sensors, data acquisition, and feedback loops
- Case study: Adaptive control via AI algorithms (MATLAB/Simulink simulation)
Day 2 – Machine Learning in Biomanufacturing
- Predictive Maintenance and Fault Detection using ML
- ML techniques: Supervised & unsupervised models in bioprocesses
- Predictive models for yield, quality, and failure prevention
- Hands-on with Python or TensorFlow for ML-based fault prediction
Day 3 – AI-Driven Analytics and GMP Compliance
- Compliance, Analytics, and Simulation of AI-Based Systems
- GMP standards and AI alignment
- AI dashboards for process traceability and regulatory audits
- Final simulation: AI-controlled workflow from culture to yield optimization
Important Dates
Registration Ends
7:00 PM
Workshop Dates
2025-07-30
8:00 PM
8:00 PM
What You Will Gain
Outcomes
- Build a simulated AI-controlled bioproduction workflow
- Analyze and improve yield through ML
- Apply AI for compliance and audit readiness
- Use industry tools for automation and control
- Gain competence in AI analytics for process insights
Who Should Attend
- Undergraduate/postgraduate degree in Biotechnology, Genetics, Biomedical Engineering, Bioinformatics, or related life sciences.
- Researchers and professionals in genomics, oncology, molecular biology.
- Individuals interested in CRISPR, cancer research, or translational genomics.