Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach.

Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach. Talanta. 2018 Jul 01;184:260-265 Authors: Le LMM, Kégl B, Gramfort A, Marini C, Nguyen D, Cherti M, Tfaili S, Tfayli A, Baillet-Guffroy A, Prognon P, Chaminade P, Caudron E Abstract The use of monoclonal antibodies (mAbs) constitutes one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. These antibodies are prescribed by the physician and prepared by hospital pharmacists. An analytical control enables the quality of the preparations to be ensured. The aim of this study was to explore the development of a rapid analytical method for quality control. The method used four mAbs (Infliximab, Bevacizumab, Rituximab and Ramucirumab) at various concentrations and was based on recording Raman data and coupling them to a traditional chemometric and machine learning approach for data analysis. Compared to conventional linear approach, prediction errors are reduced with a data-driven approach using statistical machine learning methods. In the latter, preprocessing and predictive models are jointly optimized. An additional original aspect of the work involved on submitting the problem to a collaborative data challenge platform called Rapid Analytics and Model Prototyping (RAMP). This allowed using solutions from about 300...
Source: Talanta - Category: Chemistry Authors: Tags: Talanta Source Type: research