Research

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Synthetic Biology underpins advances in the bioeconomy

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{Papathanasiou:2020:10.1016/j.coche.2019.11.010,
author = {Papathanasiou, MM and Kontoravdi, C},
doi = {10.1016/j.coche.2019.11.010},
journal = {Current Opinion in Chemical Engineering},
pages = {81--88},
title = {Engineering challenges in therapeutic protein product and process design},
url = {http://dx.doi.org/10.1016/j.coche.2019.11.010},
volume = {27},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Biologics represent the fastest growing sector of the pharmaceutical industry, yet their manufacture lags significantly behind that of small molecule drugs. This paper discusses the main product-related and process-related challenges during the development and production of therapeutic proteins, with particular focus on product heterogeneity and process monitoring and analytics. Emphasis is placed on novel contributions from the field of computational research that aim to enable the application of model-based process control strategies or are working towards the development of a digital twin of bioprocesses. Lastly, we review promising developments in the paradigm shift from batch to continuous processing.
AU  - Papathanasiou,MM
AU  - Kontoravdi,C
DO  - 10.1016/j.coche.2019.11.010
EP  - 88
PY  - 2020///
SN  - 2211-3398
SP  - 81
TI  - Engineering challenges in therapeutic protein product and process design
T2  - Current Opinion in Chemical Engineering
UR  - http://dx.doi.org/10.1016/j.coche.2019.11.010
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000544589400011&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.sciencedirect.com/science/article/pii/S2211339819300644
UR  - http://hdl.handle.net/10044/1/92674
VL  - 27
ER  -
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