Modelling of bioprocess non-linear fluorescence data for at-line prediction of etanercept based on artificial neural networks optimized by response surface methodology-Reference-Cited by-同舟云学术

Modelling of bioprocess non-linear fluorescence data for at-line prediction of etanercept based on artificial neural networks optimized by response surface methodology

Published:2020-04 Issue: Volume:210 Page:120664
ISSN:0039-9140
Container-title:Talanta
language:en
Short-container-title:Talanta

Author:

Chiappini Fabricio A.,Teglia Carla M.,Forno Ángela G.,Goicoechea Héctor C.

Funder

PLS

CONICET

ANPCyT

Publisher

Elsevier BV

Subject

Analytical Chemistry

Reference32 articles.

1. Manufacturing history of etanercept (Enbrel(®)): consistency of product quality through major process revisions;Hassett;mAbs,2018

2. Multivariate PAT solutions for biopharmaceutical cultivation: current progress and limitations;Mercier;Trends Biotechnol.,2014

3. Multivariate data analysis as a PAT tool for early bioprocess development data;Mercier;J. Biotechnol.,2013

4. A.P. Teixeira, R. Oliveira, P.M. Alves, M.J.T. Carrondo, Advances in On-Line Monitoring and Control of Mammalian Cell Cultures: Supporting the PAT Initiative.

5. A Review of Spectroscopic Methods and Their Applicability for High-Throughput Characterization of Mammalian Cell Cultures in Automated Cell Culture Systems;Musmann,2016

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Antibody glycan quality predicted from CHO cell culture media markers and machine learning;Computational and Structural Biotechnology Journal;2024-12

2. Applications of machine learning in antibody discovery, process development, manufacturing and formulation: Current trends, challenges, and opportunities;Computers & Chemical Engineering;2024-03

3. Two sides of the same coin: Kernel partial least-squares (KPLS) for linear and non-linear multivariate calibration. A tutorial;Talanta Open;2023-08

4. Artificial intelligence and machine learning applications in biopharmaceutical manufacturing;Trends in Biotechnology;2023-04

5. State-of-the-Art Review of Artificial Neural Networks to Predict, Characterize and Optimize Pharmaceutical Formulation;Pharmaceutics;2022-01-13