# title
Real-time monitoring of selective laser sintering 3D printing process for lamivudine content quantification in the printlets: a modern solution to a modern problem.

# abstract
Quality control of drug products is an essential step in pharmaceutical manufacturing. It is often time-consuming and requires expensive equipment. Process analytical technology tools are typically integrated into the manufacturing process to monitor quality, thereby reducing time and costs. This study described the incorporation of a NIR probe into the selective laser sintering process to monitor the content uniformity in real-time. Selective laser sintering technology enables the easy manufacturing of personalized medication, making it a suitable candidate for deployment at point-of-care settings, such as pharmacies and hospitals. Printlets containing lamivudine were printed using selective laser sintering. During printing, the installed NIR probe was used to collect the NIR spectra of each printed layer without interfering during the printing process. Real-time NIR data was used to predict the lamivudine content in each layer using a chemometric model. Predicted real-time results were compared with dissolution, assay, and an off-line chemometric model to confirm the accuracy of the real-time prediction. The real-time model predicted 101.5% lamivudine in the printlets, while the off-line method's prediction was 98%. Both methods' predictions were proven to be accurate when compared with the assay of the printlets, which yielded a 99.8% accuracy. In conclusion, by incorporating a NIR probe during printing as a quality control tool is possible at the point-of-care.

# authors[].organizations[].label
Texas A&M University Naresh K. Vashisht College of Medicine

# authors[].organizations[].label
Center for Microencapsulation and Drug Delivery

# authors[].organizations[].label
Texas A&M Engineering Experiment Station (TEES)

# authors[].organizations[].label
Institute for Engineering Education and Innovation

# authorList[]
Kayalar, C., Pansare, S., Gonzales, J. L., Kuttolamadom, M., Rahman, Z., & Khan, M. A.