Vakili Hossein, Wickström Henrika, Desai Diti, Preis Maren, Sandler Niklas
Pharmaceutical Sciences Laboratory, Åbo Akademi University, Tykistökatu 6A, FI-20540, Turku, Finland.
Pharmaceutical Sciences Laboratory, Åbo Akademi University, Tykistökatu 6A, FI-20540, Turku, Finland.
Int J Pharm. 2017 May 30;524(1-2):414-423. doi: 10.1016/j.ijpharm.2017.04.014. Epub 2017 Apr 7.
Quality control tools to assess the quality of printable orodispersible formulations are yet to be defined. Four different orodispersible dosage forms containing two poorly soluble drugs, levothyroxine and prednisolone, were produced on two different edible substrates by piezoelectric inkjet printing. Square shaped units of 4cm were printed in different resolutions to achieve an escalating drug dose by highly accurate and uniform displacement of droplets in picoliter range from the printhead onto the substrates. In addition, the stability of drug inks in a course of 24h as well as the mechanical properties and disintegration behavior of the printed units were examined. A compact handheld near-infrared (NIR) spectral device in the range of 1550-1950nm was used for quantitative estimation of the drug amount in printed formulations. The spectral data was treated with mean centering, Savitzky-Golay filtering and a third derivative approach. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) regression were applied to build predictive models for quality control of the printed dosage forms. The accurate tuning of the dose in each formulation was confirmed by UV spectrophotometry for prednisolone (0.43-1.95mg with R=0.999) and high performance liquid chromatography for levothyroxine (0.15-0.86mg with R=0.997). It was verified that the models were capable of clustering and predicting the drug dose in the formulations with both Q and RY values between 0.94-0.99.
用于评估可打印口腔崩解制剂质量的质量控制工具尚未明确。通过压电喷墨打印在两种不同的可食用基质上制备了四种不同的口腔崩解剂型,其中包含两种难溶性药物,即左甲状腺素和泼尼松龙。打印了边长为4厘米的方形单元,采用不同的分辨率,通过将皮升范围内的液滴从打印头高精度且均匀地转移到基质上,实现药物剂量的递增。此外,还研究了药物墨水在24小时内的稳定性以及打印单元的机械性能和崩解行为。使用了一台紧凑型手持式近红外(NIR)光谱仪,其波长范围为1550 - 1950nm,用于定量估计打印制剂中的药物含量。光谱数据经过均值中心化、Savitzky - Golay滤波和三阶导数处理。应用主成分分析(PCA)和正交偏最小二乘法(OPLS)回归来建立打印剂型质量控制的预测模型。通过紫外分光光度法对泼尼松龙(0.43 - 1.95mg,R = 0.999)和高效液相色谱法对左甲状腺素(0.15 - 0.86mg,R = 0.997),确认了每种制剂中剂量的精确调整。验证了这些模型能够对制剂中的药物剂量进行聚类和预测,Q值和RY值均在0.94 - 0.99之间。