Yin‐Chao Tseng
Papers
1
Total Citations
9
H-Index
1
About
Yin‐Chao Tseng is a researcher at the forefront of pharmaceutical process analytical technology (PAT) and continuous manufacturing. His work focuses on integrating advanced machine learning with ultrasonic and spectroscopic methods to enable real-time quality assessment and release testing of solid dosage forms. Tseng’s key contributions include developing predictive models that link ultrasonic sensor data to critical quality attributes like tablet hardness, porosity, and dissolution, thereby supporting the shift from batch to continuous production. His most-cited paper, "Machine learning modeling for ultrasonic quality attribute assessment of pharmaceutical tablets for continuous manufacturing and real-time release testing" (2024, 9 citations), demonstrates how ensemble and deep learning approaches can accurately predict tablet properties from non-destructive measurements. This work addresses a major industry challenge: ensuring product quality without slowing down high-speed manufacturing lines. Tseng’s research has practical implications for reducing waste, improving patient safety, and accelerating regulatory approval of continuous processes. By bridging materials science, chemometrics, and artificial intelligence, he is helping to define the next generation of smart pharmaceutical manufacturing.
Research Focus
Key Achievements
Top Papers
- 1