TY - JOUR
T1 - Current advances and future trends in characterizing poorly water-soluble drugs using spectroscopic, imaging and data analytical techniques
AU - Wu, Jian-Xiong
AU - van der Berg, Franciscus Winfried J
AU - Rantanen, Jukka
AU - Rades, Thomas
AU - Yang, Mingshi
PY - 2014
Y1 - 2014
N2 - A common feature of many new analytical techniques that allows fast and non-destructive analysis of poorly-water-soluble drug is that they generate a large amount of data with a multivariate character within a short time frame, which in turn highlights the need for advanced data analytical methods in extracting information from the complex data set. The current review critically examines how spectroscopy and imaging techniques can be utilized for fast and non-destructive characterization of solid state poorly water-soluble drug formulations. The first part of the present review describes the basics behind many of the currently used methods including Raman, near infrared (NIR), infrared (IR) spectroscopy and X-ray powder diffractometry in characterizing poorly water soluble drugs. Key emphasis was placed on a critical review of the currently used spectral preprocessing methods, and the influence of selected preprocessing on spectral data sets is exemplified. Further the existing uni- and multivariate spectral data analytical methods in analyzing complex spectral data sets are reviewed, covering estimation of spectral peak moments, peak modeling, variations of Principal Component Analysis (PCA), variations of Partial Least Squares (PLS) analysis and Multivariate Curve Resolution (MCR). The second part of the present review discusses hyperspectral imaging, UV imaging, optical microscopy imaging and process imaging methods suitable for characterization of poorly water-soluble solid state drug formulations. Image analytical techniques suitable for analyzing hyperspectral image data set are described. Further, the application of various image analytical techniques leading to the estimation of nucleation and crystal growth rates from polarized light microscopy is described.
AB - A common feature of many new analytical techniques that allows fast and non-destructive analysis of poorly-water-soluble drug is that they generate a large amount of data with a multivariate character within a short time frame, which in turn highlights the need for advanced data analytical methods in extracting information from the complex data set. The current review critically examines how spectroscopy and imaging techniques can be utilized for fast and non-destructive characterization of solid state poorly water-soluble drug formulations. The first part of the present review describes the basics behind many of the currently used methods including Raman, near infrared (NIR), infrared (IR) spectroscopy and X-ray powder diffractometry in characterizing poorly water soluble drugs. Key emphasis was placed on a critical review of the currently used spectral preprocessing methods, and the influence of selected preprocessing on spectral data sets is exemplified. Further the existing uni- and multivariate spectral data analytical methods in analyzing complex spectral data sets are reviewed, covering estimation of spectral peak moments, peak modeling, variations of Principal Component Analysis (PCA), variations of Partial Least Squares (PLS) analysis and Multivariate Curve Resolution (MCR). The second part of the present review discusses hyperspectral imaging, UV imaging, optical microscopy imaging and process imaging methods suitable for characterization of poorly water-soluble solid state drug formulations. Image analytical techniques suitable for analyzing hyperspectral image data set are described. Further, the application of various image analytical techniques leading to the estimation of nucleation and crystal growth rates from polarized light microscopy is described.
U2 - 10.2174/13816128113199990398
DO - 10.2174/13816128113199990398
M3 - Journal article
SN - 1381-6128
VL - 20
SP - 436
EP - 453
JO - Current Pharmaceutical Design
JF - Current Pharmaceutical Design
IS - 3
ER -