RESUMEN
This paper presents a case study on the first in-line application of AI-based image analysis for real-time pharmaceutical particle size measurement in a continuous milling process. An AI-based imaging system, which utilises a rigid endoscope, was tested for the real-time particle size measurement of solid NaCl powder used as a model API in the range of 200-1000 µm. After creating a dataset containing annotated images of NaCl particles, it was used to train an AI model for detecting particles and measuring their size. The developed system could analyse overlapping particles without dispersing air, thus broadening its applicability. The performance of the system was evaluated by measuring pre-sifted NaCl samples with the imaging tool, after which it was installed into a continuous mill for in-line particle size measurement of a milling process. By analysing â¼100 particles/s, the system was able to accurately measure the particle size of sifted NaCl samples and detect particle size reduction when applied in the milling process. The Dv50 values and PSDs measured real-time with the AI-based system correlated well with the reference laser diffraction measurements (<6% mean absolute difference over the measured samples). The AI-based imaging system shows great potential for in-line particle size analysis, which, in line with the latest pharmaceutical QC trends, can provide valuable information for process development and control.
Asunto(s)
Cloruro de Sodio , Tecnología Farmacéutica , Tecnología Farmacéutica/métodos , Tamaño de la Partícula , Excipientes , Inteligencia ArtificialRESUMEN
The present paper serves as a demonstration how an in-line PAT tool can be used for rapid and efficient process development in a fully continuous powder to granule line consisting of an interconnected twin-screw wet granulator, vibrational fluid bed dryer, and a regranulating mill. A new method was investigated for the periodic in-line particle size measurement of high mass flow materials to obtain real-time particle size data of the regranulated product. The system utilises a vibratory feeder with periodically altered feeding intensity in order to temporarily reduce the mass flow of the material passing in front of the camera. This results in the drastic reduction of particle overlapping in the images, making image analysis a viable tool for the in-line particle size measurement of high mass-flow materials. To evaluate the performance of the imaging system, the effect of several milling settings and the liquid-to-solid ratio was investigated on the product's particle size in the span of a few hours. The particle sizes measured with the in-line system were in accordance with the expected trends as well as with the results of the off-line reference particle size measurements. Based on the results, the in-line imaging system can serve as a PAT tool to obtain valuable real-time information for rapid process development or quality assurance.
Asunto(s)
Química Farmacéutica , Excipientes , Composición de Medicamentos , Tamaño de la Partícula , Polvos , Tecnología FarmacéuticaRESUMEN
The present paper reports the first monitoring and control of ultra-low dose powder feeding using a camera image-based mass flow measurement system. Caffeine was fed via a single-screw microfeeder as a model active pharmaceutical ingredient (API). The mass, mass flow and sizes of the particles were successfully monitored in real-time by the developed videometric system consisting of a high-speed process camera coupled with an image analysis software. The system was also tested in feedback control mode to automatically reach the desired mass flow values by adjusting the feeder speed based on the mass flow measured by the image analysis system. Based on these features, the developed videometric system can serve as a multi-purpose PAT-tool and can provide valuable real-time information about the process which is indispensable for modern continuous pharmaceutical manufacturing.
Asunto(s)
Procesamiento de Imagen Asistido por Computador/métodos , Polvos/química , Tecnología Farmacéutica/métodos , Grabación en Video/métodos , Cafeína/química , Retroalimentación , Programas InformáticosRESUMEN
The present paper reports the first dynamic image analysis-based feedback control of continuous twin-screw wet granulation process. Granulation of the blend of lactose and starch was selected as a model process. The size and size distribution of the obtained particles were successfully monitored by a process camera coupled with an image analysis software developed by the authors. The validation of the developed system showed that the particle size analysis tool can determine the size of the granules with an error of less than 5⯵m. The next step was to implement real-time feedback control of the process by controlling the liquid feeding rate of the pump through a PC, based on the real-time determined particle size results. After the establishment of the feedback control, the system could correct different real-life disturbances, creating a Process Analytically Controlled Technology (PACT), which guarantees the real-time monitoring and controlling of the quality of the granules. In the event of changes or bad tendencies in the particle size, the system can automatically compensate the effect of disturbances, ensuring proper product quality. This kind of quality assurance approach is especially important in the case of continuous pharmaceutical technologies.