Generation and analysis of 3D cell culture models for drug discovery

Successful preclinical drug testing relies in part on data generated using in vitro cell culture models that recapitulate the structure and function of tumours and other tissues in vivo. The growing evidence that 3D cell models can more accurately predict the efficacy of drug responses compared to t...

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Published in	European journal of pharmaceutical sciences Vol. 163; p. 105876
Main Authors	Belfiore, Lisa, Aghaei, Behnaz, Law, Andrew M.K., Dobrowolski, Jeremy C., Raftery, Lyndon J., Tjandra, Angie D., Yee, Christine, Piloni, Alberto, Volkerling, Alexander, Ferris, Cameron J., Engel, Martin
Format	Journal Article
Language	English
Published	Netherlands Elsevier B.V 01.08.2021
Subjects	3D cell culture Bioprinting Drug screening Drug screening Bioprinting 3D cell culture drug screening bioprinting
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Abstract	Successful preclinical drug testing relies in part on data generated using in vitro cell culture models that recapitulate the structure and function of tumours and other tissues in vivo. The growing evidence that 3D cell models can more accurately predict the efficacy of drug responses compared to traditionally utilised 2D cell culture systems has led to continuous scientific and technological advances that enable better physiologically representative in vitro modelling of in vivo tissues. This review will provide an overview of the utility of current 3D cell models from a drug screening perspective and explore the future of 3D cell models for drug discovery applications. 3D cell models for drug screening. Cells cultured in 3D better represent in vivo tumours by recapitulating tumour architecture and the presence of extracellular matrix (ECM), which affects drug response. [Display omitted]
AbstractList	Successful preclinical drug testing relies in part on data generated using in vitro cell culture models that recapitulate the structure and function of tumours and other tissues in vivo. The growing evidence that 3D cell models can more accurately predict the efficacy of drug responses compared to traditionally utilised 2D cell culture systems has led to continuous scientific and technological advances that enable better physiologically representative in vitro modelling of in vivo tissues. This review will provide an overview of the utility of current 3D cell models from a drug screening perspective and explore the future of 3D cell models for drug discovery applications. Successful preclinical drug testing relies in part on data generated using in vitro cell culture models that recapitulate the structure and function of tumours and other tissues in vivo. The growing evidence that 3D cell models can more accurately predict the efficacy of drug responses compared to traditionally utilised 2D cell culture systems has led to continuous scientific and technological advances that enable better physiologically representative in vitro modelling of in vivo tissues. This review will provide an overview of the utility of current 3D cell models from a drug screening perspective and explore the future of 3D cell models for drug discovery applications. 3D cell models for drug screening. Cells cultured in 3D better represent in vivo tumours by recapitulating tumour architecture and the presence of extracellular matrix (ECM), which affects drug response. [Display omitted]
ArticleNumber	105876
Author	Law, Andrew M.K. Raftery, Lyndon J. Dobrowolski, Jeremy C. Volkerling, Alexander Belfiore, Lisa Yee, Christine Aghaei, Behnaz Engel, Martin Tjandra, Angie D. Piloni, Alberto Ferris, Cameron J.
Author_xml	– sequence: 1 givenname: Lisa orcidid: 0000-0003-1554-7319 surname: Belfiore fullname: Belfiore, Lisa email: lisa.belfiore@inventia.life organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 2 givenname: Behnaz surname: Aghaei fullname: Aghaei, Behnaz organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 3 givenname: Andrew M.K. orcidid: 0000-0002-7492-114X surname: Law fullname: Law, Andrew M.K. organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 4 givenname: Jeremy C. orcidid: 0000-0001-9538-1421 surname: Dobrowolski fullname: Dobrowolski, Jeremy C. organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 5 givenname: Lyndon J. surname: Raftery fullname: Raftery, Lyndon J. organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 6 givenname: Angie D. orcidid: 0000-0002-7161-4603 surname: Tjandra fullname: Tjandra, Angie D. organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 7 givenname: Christine surname: Yee fullname: Yee, Christine organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 8 givenname: Alberto surname: Piloni fullname: Piloni, Alberto organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 9 givenname: Alexander surname: Volkerling fullname: Volkerling, Alexander organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 10 givenname: Cameron J. orcidid: 0000-0002-0441-7116 surname: Ferris fullname: Ferris, Cameron J. organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia – sequence: 11 givenname: Martin orcidid: 0000-0001-7602-1340 surname: Engel fullname: Engel, Martin organization: Inventia Life Science Pty Ltd, Sydney, New South Wales, 2015, Australia
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