Controller design for effective glycosylation control in mAbs

Monoclonal antibodies (mAbs), a class of commercially viable biotherapeutics, undergo post-translational modifications when expressed in mammalian cell lines, resulting in structural and pharmacological changes in the protein. One such post translational modification is N-linked glycosylation, where the non-template driven enzymatic attachment of different sugar moieties (glycans) to the mAb can alter the product quality of the mAb, compromising the efficacy and safety of the drug product. While significant research effort has been devoted to developing techniques for characterizing and monitoring the glycosylation pattern in mAbs, a robust technique for controlling the glycan distribution and ensuring consistent glycosylation does not currently exist. In this work, we present a framework for designing and implementing controllers for effective control of glycosylation in mAbs. The two-step procedure requires first performing output controllability analysis [1, 2] to identify specific inputs that can be manipulated to control particular glycan species (outputs) along with a quantitative relationship between inputs and outputs. Next, this structural information is used to design appropriate proportional integral (PI) controllers. The effectiveness of the controller design technique to track a specified glycan distribution trajectory has been evaluated via simulation for two cases of practical importance: (a) where glycosyltransferase enzyme concentrations are used as manipulated variables (inputs) to control glycan distribution (output) and the input output relationship is represented by a dynamic glycosylation model [3]; and (b) where amino acids are used as manipulated variables (inputs) but the quantitative relationship between the inputs and the outputs is established experimentally. In each case, we design appropriate controllers and then test the controller performance under nominal conditions (i.e., when the process model accurately represents the process in question) and under more realistic model-plant mismatch conditions. The results indicate how effective glycosylation control is possible with appropriate controller design using our proposed technique

ADVANCED CONTROL OF GLYCOSYLATION AND TITER IN FED-BATCH MONOCLONAL ANTIBODY PRODUCTION

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Controlling the Glycosylation Profile in mAbs Using Time-Dependent Media Supplementation

In order to meet desired drug product quality targets, the glycosylation profile of biotherapeutics such as monoclonal antibodies (mAbs) must be maintained consistently during manufacturing. Achieving consistent glycan distribution profiles requires identifying factors that influence glycosylation, and manipulating them appropriately via well-designed control strategies. Now, the cell culture media supplement, MnCl2, is known to alter the glycosylation profile in mAbs generally, but its effect, particularly when introduced at different stages during cell growth, has yet to be investigated and quantified. In this study, we evaluate the effect of time-dependent addition of MnCl2 on the glycan profile quantitatively, using factorial design experiments. Our results show that MnCl2 addition during the lag and exponential phases affects the glycan profile significantly more than stationary phase supplementation does. Also, using a novel computational technique, we identify various combinations of glycan species that are affected by this dynamic media supplementation scheme, and quantify the effects mathematically. Our experiments demonstrate the importance of taking into consideration the time of addition of these trace supplements, not just their concentrations, and our computational analysis provides insight into what supplements to add, when, and how much, in order to induce desired changes

Preprocessing of Raman Lidar Signal Over a High Altitude Station in India: Practical Considerations

Lidar can provide the range-resolved information about the vertical profiles of optical properties of aerosol content and clouds present in the atmosphere. However, before obtaining the information from received lidar signal we ought to use a few pre-processing techniques such as range-correction, temporal and spatial averaging, dead time correction of the photon counts (PC) signal, correction due to overlap effect, Simulation of molecular Rayleigh signal and gluing analog & PC signals. In this work, we have discussed some of the initial pre-processing techniques ought to be performed before lidar inversion

Lidar Overlap Function Determination Using the Raman Lidar Signals

The determination of vertical distribution of optical properties of clouds and aerosols using the lidar system is affected by the incomplete overlap between the field of view of transmitter i.e. laser beam & the receiver in the near‐field range. Thus, the study of vertical profiles of aerosol optical properties in the lower atmosphere is erroneous without the correction of lidar overlap function. Here we have analysed the effect of overlap using a simple technique proposed by Ansmann and Wandinger to determine overlap function. We have determined the overlap factor for 5 different days of June 2016 and then calculated the mean overlap profile and determined the relative deviation of each day with respect to mean overlap factor. Results reveal that the complete overlap was achieved beyond 300 meters

Lidar Overlap Function Determination Using the Raman Lidar Signals

The determination of vertical distribution of optical properties of clouds and aerosols using the lidar system is affected by the incomplete overlap between the field of view of transmitter i.e. laser beam & the receiver in the near‐field range. Thus, the study of vertical profiles of aerosol optical properties in the lower atmosphere is erroneous without the correction of lidar overlap function. Here we have analysed the effect of overlap using a simple technique proposed by Ansmann and Wandinger to determine overlap function. We have determined the overlap factor for 5 different days of June 2016 and then calculated the mean overlap profile and determined the relative deviation of each day with respect to mean overlap factor. Results reveal that the complete overlap was achieved beyond 300 meters

Preprocessing of Raman Lidar Signal Over a High Altitude Station in India: Practical Considerations

Lidar can provide the range-resolved information about the vertical profiles of optical properties of aerosol content and clouds present in the atmosphere. However, before obtaining the information from received lidar signal we ought to use a few pre-processing techniques such as range-correction, temporal and spatial averaging, dead time correction of the photon counts (PC) signal, correction due to overlap effect, Simulation of molecular Rayleigh signal and gluing analog & PC signals. In this work, we have discussed some of the initial pre-processing techniques ought to be performed before lidar inversion

Controllability analysis of protein glycosylation in CHO cells.

To function as intended in vivo, a majority of biopharmaceuticals require specific glycan distributions. However, achieving a precise glycan distribution during manufacturing can be challenging because glycosylation is a non-template driven cellular process, with the potential for significant uncontrolled variability in glycan distributions. As important as the glycan distribution is to the end-use performance of biopharmaceuticals, to date, no strategy exists for controlling glycosylation on-line. However, before expending the significant amount of effort and expense required to develop and implement on-line control strategies to address the problem of glycosylation heterogeneity, it is imperative to assess first the extent to which the very complex process of glycosylation is controllable, thereby establishing what is theoretically achievable prior to any experimental attempts. In this work, we present a novel methodology for assessing the output controllability of glycosylation, a prototypical example of an extremely high-dimensional and very non-linear system. We first discuss a method for obtaining the process gain matrix for glycosylation that involves performing model simulations and data analysis systematically and judiciously according to a statistical design of experiments (DOE) scheme and then employing Analysis of Variance (ANOVA) to determine the elements of process gain matrix from the resulting simulation data. We then discuss how to use the resulting high-dimensional gain matrix to assess controllability. The utility of this method is demonstrated with a practical example where we assess the controllability of various classes of glycans and of specific glycoforms that are typically found in recombinant biologics produced with Chinese Hamster Ovary (CHO) cells. In addition to providing useful insight into the extent to which on-line glycosylation control is achievable in actual manufacturing processes, the results also have important implications for genetically engineering cell lines design for enhanced glycosylation controllability

Singular values, <i>σ_i</i>, obtained from singular value decomposition of the glycan class process gain matrices for three operating ranges.

<p>Output modes associated with singular values, <i>σ_i</i>><i>σ_*</i> = 1, are considered controllable.</p