The hereby described invention discloses a method to operate an in situ analytical tool in bioreactors using a computer supported physics-based model.
The invention deals with the technological area of a continuous biopharmaceutical process.
The pharmaceutical industry's quality approach is focused on improving and increasing productivity in the manufacture of biochemical compounds. This requires the use of complex bioprocesses with real-time monitoring integrated within the production line. In-line analysis can enable the process automation, thus optimizing it by a significant saving of time and materials. Currently, there is a wide range of sensors and off-line technologies on the market capable of monitoring essential variables in a cell culture, like biomass, radius, nutrient quantity, metabolic indicators etc, as well as critical parameters of a bioprocess, but few of them are converted into in-situ sensors.
The conversion of analytical tools towards in situ sensors is therefore a current exploratory trend, aiming at improving the quality of their measurements. Moreover, thanks to these optimized sensors, called Process Analytical Tools (PAT), the conditions of continuous or discontinuous cell cultures could be adjusted in real time thanks to physical measurements converted through models to quantitative and qualitative information. This adaptation to in-line sensors has a lot of benefits: no cleaning steps, less system downtime, no cleanroom requirement, and reduced costs.
Another tendency is the conversion from multi-use (MU) to single-use (SU) sensors which provide similar advantages, especially the missing necessity of cleaning steps. Unfortunately SU sensors have a major difficulty about their calibration which cannot be performed prior to the system installation.
These process sensors and analytical tools require therefore specific and complex calibration models based on a large amount of data to handle those difficulties.
Summarized there are four major problem statements regarding the mentioned known state of the art:
The task of this patent application is therefore to find a method to use an analytical tool in bioreactors which can overcome the known limitations of the prior art.
This task has been solved by a method to analyze biomasses in a bioreactor via a computer with a system software, the bioreactor having at least one sensor to measure the biomasses and which has a data connection to the computer managed by a data interface provided by the system software, wherein the system software provides a data conversion model to analyze real time raw data about permittivity measured by and transmitted from the at least one sensor to the computer to calculate specific cell parameters of cells in the biomasses. The purpose of the invention is the transformation of the sensor, in this case a capacitance probe, integrating the dielectric spectroscopy into a true biomass probe providing qualitative and quantitative information on cell parameters, like radius and viable cell density. Important is further that the probe works in real time to provide the raw data, with a reduced effort of calibration, and for either multi-use or single-use probe variations. This approach solves the four described problems one by one:
The physics-based model is usable from the very first use of the probe and does not require any machine learning and/or model building as parameters and coefficients of the model, because this data are either coming from the probe measurements, are extrapolated from offline measurements or leveraged from the literature. The physics-based model also does not require a large amount of data nor prior calibration-based on older cell culture runs as it is based on equations describing cells as “dielectric” objects. It is able to use real-time physical values taken from the probe.
The physics-based model is sensor independent and factory calibration-free. The model can therefore self-calibrate with the used sensor. Parameters to be extracted from the equations are coming from cells considered as dielectric objects, and thus the model can be transferred from one multi-use probe to another MU one, or a single-use probe.
The physics-based model is cell line independent while the cells have the shape modelized in the model. Indeed, as cells are considered as dielectric object, thus their biochemical specificities are not a root cause of interference in the model.
The cell membrane capacitance Cm and the internal conductivity σi are calculated from an offline analysis and allow the regular adjustment of the model while giving qualitative information of the cell.
Preferred further developments of the process include, for example, but are not limited to that:
Another solution to this task is an automated system for analyzing biomasses comprising a bioreactor with at least one sensor to measure the biomasses, a computer being connected to the at least one sensors and a system software performed on the computer with a data interface managing the connection to the at least one sensor and providing a data conversion model, being arranged to perform the previously described method.
Preferred further developments of the automated system include, for example, but are not limited to that:
The method and the automated system 1 including the software 5 according to the invention and functionally advantageous developments of those are described in more detail below with reference to the associated drawings using at least one preferred exemplary embodiment. In the drawings, elements that correspond to one another are provided with the same reference numerals.
The drawings show:
The data model 8 is preferably a phenomenological Cole-Cole model 8 which convert real time raw data of permittivity into viable cell density (VCD) and average cell culture radius (R) indications. Based itself on the Debye equation (Debye, 1929), the Cole-Cole equation reproduce the shape of the β-dispersion by expressing the permittivity (ε) as a function of frequency (f) and can be written as follows:
The dielectric parameters Δε, fc, and α are calculated by the INCYTE internal software (ArcAir, Hamilton) from raw permittivity data each time a scan is executed.
The Cole-Cole parameters can be linked to quantitative information of the cells, like the average culture cell radius R by using the following equations:
Finally the viable cell density VCD is calculated starting from the assumption that the cells in the culture are spherical, thus the single cell volume V can be written as:
The software 5 which provides and applies the Cole-Cole model 8 also comprises a raw data conversion module. In its graphical user interface (GUI) 4, the user 7 can choose the type of modeling he wants to use for the calculations. Preferably the MATLAB software (The MathWorks Inc) is used as software 5, but any other suitable software can also be used. In this example MATLAB version 9.9.0.1570001 from 2020 was used.
Using that model 8 in an algorithm, r and VCD values were calculated every minutes. Two daily samples were taken to obtain average offline values of cell radius and VCD. They were interpolated with a smoothing spline. The values calculated by the model 8 were compared to the spline and the Standard Error Prediction (SEP) was calculated, as follow:
The computer software 5 is preferably integrated on an platform to monitor radius and VCD during cultivation. Using this GUI 4, the user is requested to enter theoretical values for Cm and σi as well as files containing raw permittivity values. It is also possible, depending on the chosen model 8, to add a file containing the values determined offline with the Nova analyzer. The raw permittivity data could also be provided in an alternative option by the biomass sensor 6 in real-time.
The calculated radius and VCD values will be compared to offline measurements made with an automated cell culture analyzer. By doing so the validity of the Cole-Cole model 8 applied to cells in culture is tested.
The specific software module is preferably implemented in the system software in between the smart dielectric spectroscopy probe and the software interface and enables the real time raw data processing with the embedded model 8.
The following method steps show a preferred example to use the model 8 with the best accuracy:
As conclusion, it can be comprehended that the adjusted model 8 can be used either on MU or SU probes 6 without any additional calibration step on the SU sensor as usually required on typical process control sensors, like pH, dissolved oxygen, while not losing the calibration-free feature of the invention. The scalability to characterize and monitor cell cultures from small to large bioreactor is obvious as the model 8 is cell line independent and uses cells as dielectric objects. Improving the accuracy of the model 8 is done with a data driven approach combined with the physics-based model 8 giving a hybrid model.
Number | Date | Country | Kind |
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21306688.9 | Dec 2021 | EP | regional |
Filing Document | Filing Date | Country | Kind |
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PCT/EP2022/084079 | 12/1/2022 | WO |