Abstract

Monoclonal antibodies (mAbs) are currently the highest-selling products of the biopharmaceutical industry, having had global sales of over $45 billion in 2012 [1]. All commercially-available mAbs contain a consensus N-linked glycosylation site on each of the Cγ2 domains of their constant fragment (Fc). The monosaccharide composition and distribution of these N-linked carbohydrates (glycans) has been widely reported to directly impact the safety and efficacy of mAbs when administered to patients. Many studies have also shown that manufacturing bioprocess conditions (e.g. nutrient availability, metabolite accumulation, dissolved oxygen, pH, temperature and stirring speed) directly influence the composition and distribution of N-linked glycans bound to mAbs and other recombinant proteins. Given this tight interconnection between manufacturing process conditions, product quality and ensuing safety and therapeutic efficacy, mAbs and their glycosylation present a clear opportunity where process development can be guided by quality by design (QbD) principles. QbD is a conceptual framework that aims to build quality into drug products at every stage of process development. Specifically, implementation of QbD to pharmaceutical process development requires identifying critical quality attributes (CQAs) that define the drug's safety and therapeutic efficacy. QbD then uses all available information on the mechanisms that quantitatively relate process inputs with product quality to control the manufacturing process so that product CQAs are maintained and end-product quality is ensured. Within the QbD context, composition and distribution of the glycans present on the Fc of mAbs is defined as a CQA, and thus, the processes employed in their manufacture must be controlled so that their glycan distribution ensures the required safety and efficacy profiles. Under this perspective, we have defined a mathematical model that mechanistically and quantitatively describes mAb Fc glycosylation as a function of nutrient availability during cell culture. Such a model aims to be used for bioprocess design, control and optimisation, thus facilitating the manufacture of mAbs with built-in glycosylation-associated quality under the QbD scope.

Highlights

  • Monoclonal antibodies are currently the highestselling products of the biopharmaceutical industry, having had global sales of over $45 billion in 2012 [1]

  • Materials and methods The mathematical model consists of three distinct modular elements which have been connected to achieve a mechanistic description of Monoclonal antibodies (mAbs) glycosylation as a function of nutrient availability

  • This, along with data on cell culture dynamics and mAb Fc glycosylation were used to estimate the unknown parameters of the model as described previously

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Summary

Introduction

Monoclonal antibodies (mAbs) are currently the highestselling products of the biopharmaceutical industry, having had global sales of over $45 billion in 2012 [1]. Many studies have shown that manufacturing bioprocess conditions (e.g. nutrient availability, metabolite accumulation, dissolved oxygen, pH, temperature and stirring speed) directly influence the composition and distribution of N-linked glycans bound to mAbs and other recombinant proteins. Given this tight interconnection between manufacturing process conditions, product quality and ensuing safety and therapeutic efficacy, mAbs and their glycosylation present a clear opportunity where process development can be guided by quality by design (QbD) principles. Implementation of QbD to pharmaceutical process development requires identifying critical quality attributes (CQAs) that define the drug’s safety and therapeutic efficacy.

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