(585n) An Integrated Mechanistic Model for Nucleotide Sugar Metabolism and Monoclonal Antibody Glycosylation

Authors: 
Jimenez del Val, I., Imperial College London
Constantinou, A., Imperial College London
Dell, A., Imperial College
Haslam, S., Imperial College
Jedrzejewski, P., Imperial College London
Polizzi, K. M., Imperial College London
Kontoravdi, C., Imperial College London



Pharmaceutical quality by design (QbD) is a framework for the development and approval of manufacturing processes that aims to build quality into drugs at every stage of process development. Implementation of QbD requires identification of the critical attributes that define product quality (CQAs) which, in the case of pharmaceuticals, are the properties that define a drug’s safety and therapeutic efficacy. Implementation of QbD relies on all available knowledge regarding the mechanisms that quantitatively relate manufacturing process inputs with product CQAs. These mechanistic relationships are then used to control the manufacturing process so that product CQAs are maintained and end-product quality is ensured. Within this framework, mathematical models that mechanistically describe drug product quality as a function of process inputs are of paramount importance.

Monoclonal antibodies (mAbs) are one of the leading products of the pharmaceutical industry having had worldwide sales of over $43 billion in 2010. All approved mAbs contain a consensus N-linked glycosylation site on their constant fragments. It has been widely reported that the complex carbohydrates (glycans) bound to these sites directly impact the safety and efficacy of mAbs when administered to patients. This has led to defining N-linked glycosylation as a CQA of mAbs. It has also been reported that many bioprocess conditions (e.g. nutrient availability, dissolved oxygen, pH, temperature, stirring speed and culture medium supplementation) influence the composition and distribution of glycans bound to mAbs. Within the context of QbD, we have defined a mathematical model that mechanistically and quantitatively describes the glycosylation profiles of mAbs as a function of nutrient availability during cell culture.

The mathematical model consists of two elements, the first of which describes cell culture dynamics and has been adapted to include intracellular accumulation of nucleotide sugars (NSDs) as a function of extracellular nutrient availability. The metabolic pathway for nucleotide sugars has been reduced from 32 to 8 reactions, yet the regulatory motifs of the full pathway have been included in “lumped” rate expressions. The second element is a model for N-linked glycosylation, which approximates the Golgi apparatus to a plug-flow reactor and includes NSDs as co-substrates for the glycosylation reactions that occur therein.1 Both elements are linked through mAb specific productivity and intracellular availability of NSDs.

The unknown parameters of the model were estimated with data obtained from murine hybridoma (CRL-1606, ATCC) culture. Typical data (viable cell density, extracellular glucose, glutamine, lactate, ammonia and mAb titre) was collected along with intracellular measurements of nucleotides (ATP, CTP, GTP and UTP) and nucleotide sugars (CMP-Neu5Ac, GDP-Fuc, GDP-Man, UDP-GalNAc, UDP-Glc and UDP-GlcNAc). In addition, the mAb glycan profiles were obtained using MALDI mass spectrometry. With the estimated parameters, the model reproduces the experimental data accurately. Finally, the full model was used to perform simulations of glucose and glutamine depletion. These studies predict accumulation of high-mannose glycans under glutamine starvation, a phenomenon that is consistent with previous observations.2

The final product of this work is a mathematical model that mechanistically and quantitatively describes how extracellular glucose and glutamine availability impact the glycosylation profiles of mAbs by using intracellular NSD availability as the fundamental link between both elements. Mathematical models that mechanistically relate process inputs with product CQAs may prove successful in aiding process development, control and optimisation under the QbD scope.

References:

  1. del Val, I.J., Nagy, J.M. & Kontoravdi, C. A dynamic mathematical model for monoclonal antibody N-linked glycosylation and nucleotide sugar donor transport within a maturing Golgi apparatus. Biotechnol Progr 27, 1730-1743 (2011).
  2. Wong, D.C.F., Wong, K.T.K., Goh, L.T., Heng, C.K. & Yap, M.G.S. Impact of dynamic online fed-batch strategies on metabolism, productivity and N-glycosylation quality in CHO cell cultures. Biotechnol Bioeng 89, 164-177 (2005).
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