Accelerating throughput of analytics with one-click data analysis
July 14-18, 2019
The downstream process development for antibody-based biopharmaceuticals has been applying a platform approach based around Protein A affinity chromatography for many years. Process development can be performed at laboratory scale, but with the adoption of microscale techniques and automation, process development throughput can be enhanced. Being able to do more with less material enables the downstream process development to start with small scale bioreactor-derived feedstreams and can therefore start earlier in the development timeline. For example, 96-well microplates allow multiple binding and elution conditions to be evaluated for a mixed-mode chromatography step in a less than 2% of the time it would take to screen these same conditions, with a similar saving in feed material requirements. The benefit of being able to perform many chromatography experiments is however bottlenecked by the ability to obtain meaningful analytical data from the large number of samples taken and the analytical method used. The Host Cell Protein ELISA assay has a limited throughput and requires two software packages for analysis. A 93% increase in efficiency was achieved by using a MATLAB™ app to automate this analysis. The further optimization and process understanding performed as the clinical development progresses can also exploit the benefits of the automated microscale techniques. Moving from 96-well plates to 600μL microscale columns allows the chromatography experiments to be transformed into a format that provides a more representative separation to that achieved at more conventional laboratory scales. However, to obtain useful comparative information that translates to larger scale requires the UV absorbance data to be converted into a chromatogram. Although scientifically straight forward, this process requires the transfer of large amounts of data into a plot-able format. Manual copying of data across formats is not ideal, but apps created in MATLAB™ that can be deployed on any PC are able to rapidly transfer the data from defined analytical formats to generate recognisable chromatograms. The use of Design of Experiment methodologies should work well with the automated parallel operations of the microscale format, however, converting the experimental design into a suitable automation script to perform the different experiments can be challenging. Using apps for this purpose allows processes to be more consistent and provides a saving in time and reducing the number of repeats due to automation errors.
Razwan Hanif, "Accelerating throughput of analytics with one-click data analysis" in "Biochemical and Molecular Engineering XXI", Christina Chan, Michigan State University, USA Mattheos Koffas, RPI, USA Steffen Schaffer, Evonik Industries, Germany Rashmi Kshirsagar, Biogen, USA Eds, ECI Symposium Series, (2019). https://dc.engconfintl.org/biochem_xxi/29