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Research

Biological systems - including the simplest cells - exhibit a broad range of functions to thrive in their environment. Research in the Imperial College Centre for Synthetic Biology is focused on the possibility of engineering the underlying biochemical processes to solve many of the challenges facing society, from healthcare to sustainable energy. In particular, we model, analyse, design and build biological and biochemical systems in living cells and/or in cell extracts, both exploring and enhancing the engineering potential of biology.

As part of our research we develop novel methods to accelerate the celebrated Design-Build-Test-Learn synthetic biology cycle. As such research in the Centre for Synthetic Biology highly multi- and interdisciplinary covering computational modelling and machine learning approaches; automated platform development and genetic circuit engineering ; multi-cellular and multi-organismal interactions, including gene drive and genome engineering; metabolic engineering; in vitro/cell-free synthetic biology; engineered phages and directed evolution; and biomimetics, biomaterials and biological engineering.

Publications

Citation

BibTex format

@article{Kontoravdi:2018:10.1016/j.coche.2018.08.007,
author = {Kontoravdi, K and Jimenez, Del Val I},
doi = {10.1016/j.coche.2018.08.007},
journal = {Current Opinion in Chemical Engineering},
pages = {89--97},
title = {Computational tools for predicting and controlling the glycosylation of biopharmaceuticals},
url = {http://dx.doi.org/10.1016/j.coche.2018.08.007},
volume = {22},
year = {2018}
}

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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Glycosylation is a critical quality attribute of biopharmaceuticals because it is a major source of structural variability that influences the in vivo safety and therapeutic efficacy of these products. Manufacturing process conditions are known to influence the monosaccharide composition and relative abundance of the complex carbohydrates bound to therapeutic proteins. Multiple computational tools have been developed to describe these process/product quality relationships in order to control and optimise the glycosylation of biopharmaceuticals. This review will provide a summary highlighting the strengths and weaknesses of each modelling strategy in their application towards cellular glycoengineering or bioprocess design and control. To conclude, potential unified glycosylation modelling approaches for biopharmaceutical quality assurance are proposed.
AU  - Kontoravdi,K
AU  - Jimenez,Del Val I
DO  - 10.1016/j.coche.2018.08.007
EP  - 97
PY  - 2018///
SN  - 2211-3398
SP  - 89
TI  - Computational tools for predicting and controlling the glycosylation of biopharmaceuticals
T2  - Current Opinion in Chemical Engineering
UR  - http://dx.doi.org/10.1016/j.coche.2018.08.007
UR  - http://hdl.handle.net/10044/1/63978
VL  - 22
ER  -

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