Project Model and control strategy development to modernize the pharmaceutical tablet manufacturing process Program DUIRI - Discovery Undergraduate Interdisciplinary Research Internship Term Summer 2023 Status Accepted Research Area Pharmaceutical Manufacturing, Process Systems Engineering Description The pandemic, such as COVID-19 crisis, has highlighted the requirement for smart manufacturing in pharmaceuticals. Continuous manufacturing is a highly promising solution given its lower capital cost, smaller footprint, and higher efficiency compared to batch manufacturing. Instead of relying on frequent off-line quality tests of samples from each batch, designing an effective and efficient process with knowledge and optimal control strategies becomes increasingly important. Ultimately, an automated smart system can be built to produce high-quality drug products with minimized errors from human intervention. In a dry granulation tableting line, the powders are transformed into granules before being compressed into tablets. The granulation step can increase the powder flowability by enlarging particle size and improving the powder blend's content uniformity by minimizing segregation. The goals of this project include (1) investigating the impact of granulation on final tablet qualities and building high-fidelity models using first principles and machine learning, and (2) developing soft sensors to predict critical quality attributes such as tensile strength in real time. (3) Implementing model-based process control strategy to control end-to-end pharmaceutical manufacturing processes. All the research works will be conducted in Purdue's newly installed tablet manufacturing pilot plant at the FLEX Lab in Discovery Park. Supervisor Yan-Shu Huang Mentor Yan-Shu Huang Type of work required 1. Operate equipment in the pilot plant to manufacture pharmaceutical oral solid dosage drug product
2. Characterize samples (powder, ribbon, granule, tablet) to understand the relationship between process parameters and product quality
3. Perform data analysis to build a quantitative model to describe the pharmaceutical manufacturing processes Websites Qualifications Basic programming skills (MATLAB or Python) and powder characterization experience would be a plus, but they are not necessary. All students are welcome if they are interested in hands-on experiments and pharmaceutical processes. Credit Hours 0 Weekly Hours 40 (estimated)