Bioprocess monitoring applications of an innovative ATR-FTIR spectroscopy platform

Tools

Christie, Loren and Rutherford, Samantha and Palmer, David S. and Baker, Matthew J. and Butler, Holly J. (2024) Bioprocess monitoring applications of an innovative ATR-FTIR spectroscopy platform. Frontiers in Bioengineering and Biotechnology, 12. 1349473. ISSN 2296-4185 (https://doi.org/10.3389/fbioe.2024.1349473)

[thumbnail of Christie-etal-FBB-2024-Bioprocess-monitoring-applications-of-an-innovative-ATR-FTIR-spectroscopy]
Preview
 Text. Filename: Christie-etal-FBB-2024-Bioprocess-monitoring-applications-of-an-innovative-ATR-FTIR-spectroscopy.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (2MB)| Preview

Abstract

Pharmaceutical manufacturing is reliant upon bioprocessing approaches to generate the range of therapeutic products that are available today. The high cost of production, susceptibility to process failure, and requirement to achieve consistent, high-quality product means that process monitoring is paramount during manufacturing. Process analytic technologies (PAT) are key to ensuring high quality product is produced at all stages of development. Spectroscopy-based technologies are well suited as PAT approaches as they are non-destructive and require minimum sample preparation. This study explored the use of a novel attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy platform, which utilises disposable internal reflection elements (IREs), as a method of upstream bioprocess monitoring. The platform was used to characterise organism health and to quantify cellular metabolites in growth media using quantification models to predict glucose and lactic acid levels both singularly and combined. Separation of the healthy and nutrient deficient cells within PC space was clearly apparent, indicating this technique could be used to characterise these classes. For the metabolite quantification, the binary models yielded R2 values of 0.969 for glucose, 0.976 for lactic acid. When quantifying the metabolites in tandem using a multi-output partial least squares model, the corresponding R2 value was 0.980. This initial study highlights the suitability of the platform for bioprocess monitoring and paves the way for future in-line developments.

ORCID iDs

Christie, Loren, Rutherford, Samantha, Palmer, David S. ORCID logoORCID: https://orcid.org/0000-0003-4356-9144, Baker, Matthew J. and Butler, Holly J.;
CORE (COnnecting REpositories)