Spectroscopy Integration in Bioreactors Enables Robust Model Transfer Across Scales

Why It Matters

This research demonstrates a significant advancement in process analytical technology for biopharmaceutical production. By enabling consistent data acquisition and model development across scales, it reduces the time and cost associated with process development and scale-up, leading to more efficient and reliable manufacturing.

Key Finding

Spectroscopy can be integrated into bioreactors of different sizes to create accurate models that work across scales, improving process development and manufacturing.

Key Findings

• Spectroscopy can be effectively integrated into both miniature and large-scale bioreactors for automated, non-destructive analysis.
• Accurate OPLS models for multiple analytes were developed at both scales.
• Models developed at the miniature scale could be successfully transferred to the large-scale bioreactor, demonstrating continuity in process understanding.
• The 50 L SUB prototype allowed for on-line monitoring without probe sterilization and showed minimal light interference.

Research Evidence

Aim: To evaluate the integration of spectroscopy into miniature and large-scale bioreactors for automated data acquisition and to assess the transferability of developed predictive models across these scales.

Method: Experimental and modelling study

Procedure: A prototype miniature bioreactor system (ambr®15) was equipped with integrated spectroscopy for automated Raman spectra acquisition. A separate prototype 50 L single-use bioreactor bag was also fitted with an integrated spectral window. Orthogonal Partial Least Squares (OPLS) models were developed using data from both systems to predict multiple analytes. Model transferability between scales was investigated.

Context: Biopharmaceutical manufacturing and process development

Design Principle

Data consistency and model transferability across process scales are crucial for efficient biopharmaceutical development and manufacturing.

How to Apply

When designing or optimizing bioprocesses, consider integrating spectroscopic sensors directly into bioreactors at all stages of development to build and transfer robust predictive models.

Limitations

The study focused on specific bioreactor systems and analytes; further validation may be needed for other configurations and compounds. The long-term stability and calibration of integrated spectroscopic probes require ongoing monitoring.

Student Guide (IB Design Technology)

Simple Explanation: By putting sensors directly into small and big bioreactors, scientists can create computer models that predict what's happening in the process. These models work well even when you move from a small test reactor to a big production one, saving time and effort.

Why This Matters: This research shows how technology can make developing and producing biological products more efficient by ensuring that what you learn in the lab can be directly applied to larger production systems.

Critical Thinking: What are the potential challenges in maintaining the calibration and accuracy of integrated spectroscopic probes over extended periods in a dynamic bioreactor environment?

IA-Ready Paragraph: The integration of spectroscopic techniques into bioreactors, as demonstrated by Rowland‐Jones et al. (2020), offers a powerful method for continuous, non-destructive data acquisition. This approach facilitates the development of robust predictive models that can be effectively transferred across different scales of operation, thereby enhancing process understanding and streamlining scale-up from development to manufacturing.

Project Tips

• When designing a system that involves chemical or biological processes, think about how you can collect data continuously and non-destructively.
• Consider how the data you collect at a small scale can be used to predict outcomes at a larger scale.

How to Use in IA

• Reference this study when discussing the importance of data collection and modelling in process optimization, especially when considering scale-up challenges.

Examiner Tips

• Demonstrate an understanding of how data from laboratory-scale experiments can be leveraged for industrial-scale applications through robust modelling.

Independent Variable: ["Scale of bioreactor (miniature vs. large-scale)","Integration of spectroscopy"]

Dependent Variable: ["Accuracy of predictive models (e.g., OPLS models)","Analyte concentration measurements","Model transferability"]

Controlled Variables: ["Type of spectroscopy used (Raman)","Specific analytes being measured","Bioreactor operating conditions (e.g., temperature, agitation)"]

Strengths

• Demonstrates practical integration of advanced technology into existing systems.
• Provides evidence for successful model transferability across scales, a key challenge in process engineering.

Critical Questions

• How does the spectral resolution and signal-to-noise ratio of the integrated spectroscopy affect model accuracy at different scales?
• What are the economic implications of integrating spectroscopy compared to traditional sampling and analysis methods for bioreactors?

Extended Essay Application

• Investigate the feasibility of integrating non-destructive sensing technologies into a custom-designed miniature bioreactor for real-time monitoring of a specific biological process.

Source

Spectroscopy integration to miniature bioreactors and large scale production bioreactors–Increasing current capabilities and model transfer · Biotechnology Progress · 2020 · 10.1002/btpr.3074