Abstract
BackgroundScience-based recombinant bioprocess designs as well as the design of statistical experimental plans for process optimization (Design of Experiments, DoE) demand information on physiological bioprocess boundaries, such as the onset of acetate production, adaptation times, mixed feed metabolic capabilities or induced state maximum metabolic rates as at the desired cultivation temperature. Dynamic methods provide experimental alternatives to determine this information in a fast and efficient way. Information on maximum metabolic capabilities as a function of temperature is needed in case a reduced cultivation temperature is desirable (e.g. to avoid inclusion body formation) and an appropriate feeding profile is to be designed.ResultsHere, we present a novel dynamic method for the determination of the specific growth rate as a function of temperature for induced recombinant bacterial bioprocesses. The method is based on the control of the residual substrate concentration at non-limiting conditions with dynamic changes in cultivation temperature. The presented method was automated in respect to information extraction and closed loop control by means of in-line Fourier Transformation Infrared Spectroscopy (FTIR) residual substrate measurements and on-line first principle rate-based soft-sensors. Maximum induced state metabolic capabilities as a function of temperature were successfully extracted for a recombinant E. coli C41 fed-batch bioprocess without the need for sampling in a time frame of 20 hours.ConclusionsThe presented method was concluded to allow the fast and automated extraction of maximum metabolic capabilities (specific growth rate) as a function of temperature. This complements the dynamic toolset necessary for science-based recombinant bacterial bioprocess design and DoE design.
Highlights
Science-based recombinant bioprocess designs as well as the design of statistical experimental plans for process optimization (Design of Experiments, DoE) demand information on physiological bioprocess boundaries, such as the onset of acetate production, adaptation times, mixed feed metabolic capabilities or induced state maximum metabolic rates as at the desired cultivation temperature
The basic toolset for quality by design (QbD) driven process development as discussed by several recent contributions [4,5,6,7,8,9,10] and covered in recent text books [4,11] includes following elements: 1) Risk assessment approaches for the identification of possible Critical process parameter (CPP) and Critical quality attribute (CQA)
The applicability of the method is demonstrated on a recombinant E. coli C41 bioprocess
Summary
Science-based recombinant bioprocess designs as well as the design of statistical experimental plans for process optimization (Design of Experiments, DoE) demand information on physiological bioprocess boundaries, such as the onset of acetate production, adaptation times, mixed feed metabolic capabilities or induced state maximum metabolic rates as at the desired cultivation temperature. Information on maximum metabolic capabilities as a function of temperature is needed in case a reduced cultivation temperature is desirable (e.g. to avoid inclusion body formation) and an appropriate feeding profile is to be designed. Fuelled by regulatory initiatives [3] as well as the emerging focus on biosimilars (follow-on biologics), novel strategies for the science and risk based development of efficient pharmaceutical bioprocesses are needed. Bioprocess development aims at the identification and quantification of the interactions of process parameters with productivity and product quality related attributes, The basic toolset for QbD driven process development as discussed by several recent contributions [4,5,6,7,8,9,10] and covered in recent text books [4,11] includes following elements: 1) Risk assessment approaches for the identification of possible CPPs and CQAs
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