Vakili Hossein, Kolakovic Ruzica, Genina Natalja, Marmion Mathieu, Salo Harri, Ihalainen Petri, Peltonen Jouko, Sandler Niklas
Pharmaceutical Sciences Laboratory, Department of Biosciences, Åbo Akademi University, Tykistökatu 6A, 20520 Turku, Finland.
Pharmaceutical Sciences Laboratory, Department of Biosciences, Åbo Akademi University, Tykistökatu 6A, 20520 Turku, Finland.
Int J Pharm. 2015 Apr 10;483(1-2):244-9. doi: 10.1016/j.ijpharm.2014.12.034. Epub 2014 Dec 16.
The aim of the study was to investigate applicability of near infra-red (NIR) hyperspectral imaging technique in quality control of printed personalised dosage forms. Inkjet printing technology was utilized to fabricate escalating doses of an active pharmaceutical ingredient (API). A solution containing anhydrous theophylline as the model drug was developed as a printable formulation. Single units solid dosage forms (SDFs) were prepared by jetting the solution onto 1 cm × 1 cm areas on carrier substrate with multiple printing passes. It was found that the number of printing passes was in excellent correlation (R(2)=0.9994) with the amount of the dispensed drug (μg cm(-2)) based on the UV calibration plot. The API dose escalation was approximately 7.5 μg cm(-2) for each printing pass concluding that inkjet printing technology can optimally provide solutions to accurate deposition of active substances with a potential for personalized dosing. Principal component analysis (PCA) was carried out in order to visualize the trends in the hyperspectral data. Subsequently, a quantitative partial least squares (PLS) regression model was created. NIR hyperspectral imaging proved (R(2)=0.9767) to be a reliable, rapid and non-destructive method to optimize quality control of these planar printed dosage forms.
本研究的目的是探讨近红外（NIR）高光谱成像技术在印刷个性化剂型质量控制中的适用性。利用喷墨印刷技术制备活性药物成分（API）剂量递增的产品。开发了一种含有无水茶碱作为模型药物的溶液作为可印刷制剂。通过将溶液多次喷射到载体基质上1 cm×1 cm的区域来制备单单元固体剂型（SDF）。基于紫外校准图发现，印刷次数与所分配药物的量（μg cm⁻²）具有极好的相关性（R² = 0.9994）。每次印刷过程中API剂量递增约7.5 μg cm⁻²，这表明喷墨印刷技术能够为活性物质的精确沉积提供最佳解决方案，具有实现个性化给药的潜力。进行主成分分析（PCA）以可视化高光谱数据中的趋势。随后，创建了定量偏最小二乘（PLS）回归模型。近红外高光谱成像被证明（R² = 0.9767）是一种可靠、快速且无损的方法，可用于优化这些平面印刷剂型的质量控制。
