Making cell and gene therapies currently requires scientists to repeatedly pull samples from bioreactors and run them through separate machines, a manual process that risks contaminating or losing the very cells being grown. This labour-intensive approach creates two problems: it introduces variability between batches, and it generates data too slowly for scientists to make timely decisions about the cell culture. The existing bioreactor platform, MFX, already integrates one sensor for counting cells and checking their viability without invasive sampling. But critical information about cell surface markers and metabolic byproducts like glucose and lactate still requires separate benchtop flow cytometers and metabolite analysers. The researchers aim to integrate these analytical tools directly into the bioreactor, creating a single system that monitors cell phenotype and metabolism in real time. If successful, this would eliminate manual sampling, reduce batch-to-batch variability, and speed up process development for cell and gene therapies. The impact would be felt in manufacturing efficiency rather than in patients’ daily lives directly—fewer failed batches and lower production costs could ultimately make advanced therapies more accessible, but the immediate advance is in streamlining a complex industrial process.
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Cell and Gene Therapies (CGTs) are revolutionising treatments for degenerative diseases (e.g. Chimeric Antigen Receptor (CAR) T-cell therapies). However, manufacturing these treatments requires significant improvements in repeatability and reproducibility to achieve optimal efficiency. There are two principal issues: (1) the need for scalable cell culture vessels (i.e. bioreactors) that translate process development (R&D) to GMP manufacturing; and (2) bioreactors are already present in the market but data-enabled ones yet to be truly established. This means leveraging process analytical technologies (PATs) that automatically feedback data to the cell culture process to allow the skilled user (i.e. scientist) to make rapid, informed and data-supported key decisions. The main challenge with existing bioreactor systems is that they rely on separate process analytics platforms outside of the bioreactor; therefore: necessitating greater labour-intensity from manual sampling of the bioreactor into another benchtop instrument for data read-out. While sampling volumes are in the microlitre-range, consistent invasive sampling accumulates cell culture volume loss incurring high capital usage for different equipment for various types of data acquisition greater labour-intensity, i.e. the use of multiple equipment, which increases operational costs (lab footprint, maintenance & overhead) having batch-to-batch variability in cell culture due to complex and often invasive sampling protocols that increase risk for cell loss providing the risk of obtaining extraneous data. The lack of relevant automation to generate real-time cell culture data risks missing out on key Critical Quality Attributes (CQAs) needed for process decision-making. The lack of in-line PATs contribute to the limited understanding of the entire cell culture bioprocess, including variability in process control; thereby slowing down CGT development times. Whilst some competitor bioreactors offer some degree of in-line PATs, key data are still processed in separate benchtop instruments; thereby not providing enough value-add particularly in streamlining data acquisition processes. With support from the original FLF, MFX has developed a scalable bioreactor platform for CGT process development with one already-integrated crucial PAT, i.e. digital cell count & viability, which eliminates the need for invasive manual sampling of small cell concentrations. However, there is more to PATs than just cell count. Cell phenotype markers are essential and are often obtained from separate benchtop flow cytometers that have complex, time-consuming preparation protocols. Metabolites (glucose, lactate) are equally vital and are often acquired from benchtop metabolite analysers. Both analytics platforms require regular invasive sampling of small volumes that contribute to sample loss. Our objective is then to integrate other relevant PATs (e.g. flow cytometer, metabolite analyser) in-line of the cell culture bioprocess, enhancing to the existing features of the MFX bioreactor platform; thereby allowing monitoring of key process steps in real-time. The implementation of robust & validated PATs informed by process development has the potential to improve cost-effectiveness in CGT development.
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