Application of near infrared spectroscopy in monitoring the moisture content in freeze-drying process of human coagulation factor VIII

Fei Wang,Can Li,Pei Wang,Lei Nie,Wei Jiang,Hengchang Zang,Lian Li,Hui Zhang

doi:10.1142/s1793545815500340

Abstract

As an important process analysis tool, near infrared spectroscopy (NIRS) has been widely used in process monitoring. In the present work, the feasibility of NIRS for monitoring the moisture content of human coagulation factor VIII (FVIII) in freeze-drying process was investigated. A partial least squares regression (PLS-R) model for moisture content determination was built with 88 samples. Different pre-processing methods were explored, and the best method found was standard normal variate (SNV) transformation combined with 1st derivation with Savitzky–Golay (SG) 15 point smoothing. Then, four different variable selection methods, including uninformative variable elimination (UVE), interval partial least squares regression (iPLS), competitive adaptive reweighted sampling (CARS) and manual method, were compared for eliminating irrelevant variables, and iPLS was chosen as the best variable selection method. The correlation coefficient (R), correlation coefficient of calibration set (R cal ), correlation coefficient of validation set (R val ), root mean square errors of cross-validation (RMSECV) and root mean square errors of prediction (RMSEP) of PLS model were 0.9284, 0.9463, 0.8890, 0.4986% and 0.4514%, respectively. The results showed that the model for moisture content determination has a wide range, good linearity, accuracy and precision. The developed approach was demonstrated to be a potential for monitoring the moisture content of FVIII in freeze-drying process.

Highlights

Human coagulation factor VIII (FVIII), whose relative molecular mass (Mr) is about 300 kD, is synthesized by the liver cells as a plasma protein
This paper presented a new method to monitor the moisture content of FVIII using Near infrared spectroscopy (NIRS)
After preprocessing of standard normal variate (SNV) and 1st derivative with SG smoothing as well as the variable selection using interval partial least squares regression (iPLS) method, the optimized PLS model wasnally established for the residual moisture content determination

Summary

Introduction

Human coagulation factor VIII (FVIII), whose relative molecular mass (Mr) is about 300 kD, is synthesized by the liver cells as a plasma protein. Two chains form a metal ion-dependent heterodimer by noncovalent binding.[1,2,3] As an important coagulation factor in intrinswoic coagulation pathway, FVIII is defective and decient in hemophilia A patients. It has been reported that one of the most important parameters a®ecting the freeze-drying products was moisture content. High-level and zero-level residual moisture can compromise the stability of product and lead to a loss of biological activity.[10,11] Currently, due to the impossibility of sampling and moisture content determination during manufacturing process, the condition and time of freeze-drying is determined by experience to get qualied products whose moisture content meets the quality requirement. Only a few samples are selected to measure the moisture content, and the analysis results might not represent the quality of the entire batch. Near infrared spectroscopy (NIRS) might be an ideal choice for this aim

Methods

Results

Conclusion