SlideShare a Scribd company logo
In the quest of successfully launching a new drug, drug discovery in the preclinical phase, and
drug development in the clinical phase is crucial. Especially in the field of anti cancer drug
screening, researchers have been heavily involved in producing new drugs that bridge the gap
between experimental research and clinical trials (Meng et al., 2019).
Recent advancement in bioprinting, has thus produced several in vitro models such as 2D and
3D models that are widely used in drug screening. 2D models are traditionally used by
researchers to evaluate effectiveness of anti-cancer drugs towards cancer cell lines.
Additionally, it is to understand the molecular pathways of cell proliferation. 2D models are
also grown in either shake flasks or Petri dishes with growth medium as their source of
nutrients (Breslin & O’Driscoll, 2013).
Meanwhile, in this presentation, 3D models are used by researchers to mimic tumour
microenvironment and visualise the structure of cells (Breslin & O’Driscoll, 2013). This
presentation will be reviewing the differences between these two models, the recent preference
of researchers for 3D models, and case study that highlights the new direction for the future 3D
bioprinted models.
INTRODUCTION
COMPARISON OF 2D AND 3D MODELS
2D 3D
3D models mimic in vivo physiology of organisms, such as the
histological architecture and heterogeneity (Jackson and Lu,
2016).
They mimic native matrixes and cell-cell interaction as well
as the interactions with the extracellular matrix (ECM) (Leong
and Ng, 2014).
Researchers prefer 3D models because 2D models are
unnatural while animal models are expensive and brings
about ethical issues (Gurski et al., 2010).
Cancer cells cultured in 3D models reflects the behaviour of
cancer cells in their native, in vivo environment (Gurski et al.,
2010)
An example would be where cancer cells cultured in 3D models
respond to chemotherapeutic treatments similarly to in vivo
cancer cells.
WHY RESEARCHERS ARE USING 3D MODELS
Source: (Bourré, 2018)
Other methods of generating 3D tumour models
Methods of anticancer drug screening from 3D tumour models
•Once the 3D tumour models have been cultured in anticancer drug supplied medium, different analysis
techniques are used to screen for the most efficient drug.
3D bioprinted cancer model to
test anticancer drugs
A new direction in producing 3D bioprinted in vitro metastatic models via
reconstruction of tumor microenvironments
Source:National
Institute of
Biomedical Imaging
and Bioengineering
(NBIB),2019.
A NIBIB-funded research conducted recently
by a team of researchers from University of
Minnesota (UMN), has developed a newly
dynamic and efficient 3D bioprinted tumor
model for anticancer drug screening. The 3D
model was made in a laboratory dish, and
functions in studying the primary site, growth
and spread of cancer tumours in the body.
Thus, tackling the recurring problems in which
previous 2D models, could not replicate the
conditions and outcomes of tumor growth in
the human body. The 3D bioprinting
technology used in this project originated from
UMN lab through Michael McAlpine. Through
this research, 3D printed biochemical
capsules were combined with 3D bioprinted
tumor cells. Through 3D bioprinting
technology, melanoma cancer cells,lung cancer
cells, normal cells, and blood-vessel like
structures, are able to be precisely located in
the laboratory dish based on their individual
functions (Nibib.nih.gov, 2019).
Chemicals that guide cancer cell migration
or the growth of blood vessels, are as well
packed in the cores of hydrogels. They are
also encapsulated within an outer shell made
of gold nanorods. A time controlled release
of the capsules are activated by laser
light, which then creates a chemical
gradient that ultimately guides targeted cell
growth. Thus, these features provides a 4D
control over both space and time. “The
cells and capsules are precisely printed in
biologically relevant sites and the
chemical depots propel movement upon a
triggered release. This is a dynamic 3D
tissue engineering system giving the user
control over the diffusion process at some
later point after the printing process.”
emphasized McAlpine (Nibib.nih.gov, 2019). Figure above shows the schematics of the 3D bioprinted in vitro tumor
model, which demonstrates the integration of tumor cells, the blood-
vessel like structures, and chemical gradients
3D bioprinted cancer model to
test anticancer drugs
A new direction in producing 3D bioprinted in vitro metastatic models via
reconstruction of tumor microenvironments
Source:
Nibib.nih.
gov,
2019).
CONCLUSION
(Zanoni et al., 2019)
(Zanoni et al., 2019)
3D cell culture and anticancer drug testing | Cherry Biotech 2019 Cherry Biotech. viewed 8 May 2019, <https://www.cherrybiotech.com/scientific-
note/organs-on-chip/3d-cell-culture-and-anticancer-drug-testing>.
Bing He, Guomin Chen, Yi Zeng, 2016: Three-dimensional cell culture models for investigating human viruses, Virologica Sinica, 31, 363-379.,
viewed 08 May 2019, <https://www.virosin.org/article/doi/10.1007/s12250-016-3889-z#bpampaloni2007>
Bourré, L., 2018. Facilitating Drug Discovery with 3D In Vitro Oncology Models. [online] Blog.crownbio.com. Available at:
https://blog.crownbio.com/in-vitro-3d-organoids-spheroids-oncology [Accessed 3 May 2019].
Breslin, S & O’Driscoll, L 2013, "Three-dimensional cell culture: the missing link in drug discovery", Drug Discovery Today, vol. 18, no. 5-6, pp.
240-249. viewed 1 May 2019, <https://www.ncbi.nlm.nih.gov/pubmed/23073387>.
Duval, K., Grover, H., Han, L. H., Mou, Y., Pegoraro, A. F., Fredberg, J., & Chen, Z., 2017. “Modeling Physiological Events in 2D vs. 3D Cell
Culture.”, Physiology (Bethesda, Md.), 32(4), 266–277., viewed 08 May 2019,
<https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5545611/?report=classic>
Gurski, L.A., Petrelli, N.J., Jia, X. and Farach-Carson, M.C., 2010. 3D matrices for anti-cancer drug testing and development. Oncology Issues,
25(1), pp.20-25.
Huang, L, Holtzinger, A, Jagan, I, BeGora, M, Lohse, I, Ngai, N, Mutuswamy LB, Crawford, HC, Arrowsmith, C, Kalloger, SE, Renouf, DJ,
Connor, AA, Clearly, S, Schaeffer, DF, Roehrl, M, Tsao MS, Gallinger, S, Keller, G & Muthuswamy, SK 2015, “Ductal pancreatic cancer
modeling and drug screening using human pluripotent stem cell– and patient-derived tumor organoids.” Nature Medicine, vol. 21, no. 11, pp.
1364–1371, viewed 08 May 2019, <https://www.nature.com/articles/nm.3973>
REFERENCES
Ivascu, A & Kubbies, M 2006, “Rapid Generation of Single-Tumor Spheroids for High-Throughput Cell Function and Toxicity Analysis”, SLAS
Discovery, vol. 11, no. 8, pp. 922-932, viewed 08 May 2019, <https://journals.sagepub.com/doi/abs/10.1177/1087057106292763>
Jackson, E.L. and Lu, H., 2016. Three-dimensional models for studying development and disease: moving on from organisms to organs-on-a-
chip and organoids. Integrative Biology, 8(6), pp.672-683.
Jitcy Saji Joseph, Sibusiso Tebogo Malindisa and Monde Ntwasa, 2018, Two Dimensional (2D) and Three Dimensional(3D) Cell Culturing in
Drug Discovering”, Intechopen, viewed 08 May 2019, <https://www.intechopen.com/books/cell-culture/two-dimensional-2d-and-three-
dimensional-3d-cell-culturing-in-drug-discovery>
Kwapiszewska, K, Michalczuk, A, Rybka, M, Kwapiszewski, R & Brzózka, Z 2014, “A microfluidic-based platform for tumour spheroid culture,
monitoring and drug screening”, Lab Chip, vol. 14, pp. 2096-2104, <https://pubs.rsc.org/en/content/articlehtml/2014/lc/c4lc00291a>
Leong, D.T. and Ng, K.W., 2014. Probing the relevance of 3D cancer models in nanomedicine research. Advanced drug delivery reviews, 79,
pp.95-106.
Markovitz-Bishitz, Y, Tauber, Y, Afrimzon, E, Zurgil, N, Sobolev, M, Shafran, Y, Deutsch, A, Howitz, S, Deutsch, M 2010, “A polymer
microstructure array for the formation, culturing, and high throughput drug screening of breast cancer spheroids.” Biomaterials, vol. 31, no. 32,
pp. 8436–8444, viewed 08 May 2019, <https://www.sciencedirect.com/science/article/pii/S0142961210008938>
Marta Kapałczyńska , Tomasz Kolenda, Weronika Przybyła, et al., 2016, “2D and 3D cell cultures – a comparison of different types of cancer cell
cultures”, 14, 4: 910–919, viewed 08 May 2019, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6040128/pdf/AMS-14-28752.pdf>
Mellor, HR, Ferguson, DJ & Callaghan, R 2005, “A model of quiescent tumour microregions for evaluating multicellular resistance to
chemotherapeutic drugs”, British Journal of Cancer, vol. 93, pp. 302-309, viewed 08 May 2019, <https://www.nature.com/articles/6602710>
Nibib.nih.gov. (2019). 3D bioprinted cancer model to test anticancer drugs | National Institute of Biomedical Imaging and
Bioengineering. [online] Available at: https://www.nibib.nih.gov/news-events/newsroom/3d-bioprinted-cancer-model-test-anticancer-
drugs [Accessed 9 May 2019].
Souza, GR, Molina, JR, Raphael, RM, Ozawa, MG, Stark, DJ, Levin, CS, Bronk, LF, Ananta, JS, Mndelin, J, Georgescu, M, Bankson, JA,
Gelovani, JG, Killian, TC, Arap, W & Pasqualini, R 2010, “Three-dimensional tissue culture based on magnetic cell levitation.” Nature
Nanotechnology, vol. 5, no.4, pp. 291–296, viewed 08 May 2019, <https://www.nature.com/articles/nnano.2010.23>
Tung, YC, Hsiao, AY, Allen, SG, Torisawa, Y, Ho, M, & Takayama, S 2011, “High-throughput 3D spheroid culture and drug testing using a 384
hanging drop array.” The Analyst, vol. 136, no. 3, pp. 473–478, viewed 08 May 2019,
<https://pubs.rsc.org/en/content/articlelanding/2011/an/c0an00609b/unauth#!divAbstract>
Zanoni, M., Pignatta, S., Arienti, C., Bonafè, M. and Tesei, A., 2019. Anticancer drug discovery using multicellular tumor spheroid
models. Expert Opinion on Drug Discovery, 14(3), pp.289-301.

More Related Content

What's hot

CCRC Clonality Poster
CCRC Clonality PosterCCRC Clonality Poster
CCRC Clonality PosterNathan How
 
Big Data & Immunotherapeutics Symposium Program
Big Data & Immunotherapeutics Symposium ProgramBig Data & Immunotherapeutics Symposium Program
Big Data & Immunotherapeutics Symposium Program
Michael Evtushenko
 
Pluripotent stem cells An in vitro model for nanotoxicity
Pluripotent stem cells An in vitro model for nanotoxicityPluripotent stem cells An in vitro model for nanotoxicity
Pluripotent stem cells An in vitro model for nanotoxicityDr. Harish Handral
 
Precision Oncology - using Genomics, Proteomics and Imaging to inform biology...
Precision Oncology - using Genomics, Proteomics and Imaging to inform biology...Precision Oncology - using Genomics, Proteomics and Imaging to inform biology...
Precision Oncology - using Genomics, Proteomics and Imaging to inform biology...
Warren Kibbe
 
Numerical Prediction of Microbubble Attachment in Biological Flows (2)
Numerical Prediction of Microbubble Attachment in Biological Flows (2)Numerical Prediction of Microbubble Attachment in Biological Flows (2)
Numerical Prediction of Microbubble Attachment in Biological Flows (2)Joshua Gosney
 
Central mucoepidermoid carcinoma an up to-date analysis of 147 cases
Central mucoepidermoid carcinoma an up to-date analysis of 147 casesCentral mucoepidermoid carcinoma an up to-date analysis of 147 cases
Central mucoepidermoid carcinoma an up to-date analysis of 147 cases
MNTan1
 
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
IJDKP
 
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
IJDKP
 
Disseminated Breast Cancer Cells Acquire a Highly Malignant and Aggressive Me...
Disseminated Breast Cancer Cells Acquire a Highly Malignant and Aggressive Me...Disseminated Breast Cancer Cells Acquire a Highly Malignant and Aggressive Me...
Disseminated Breast Cancer Cells Acquire a Highly Malignant and Aggressive Me...Carolyn Marsden
 
How is machine learning significant to computational pathology in the pharmac...
How is machine learning significant to computational pathology in the pharmac...How is machine learning significant to computational pathology in the pharmac...
How is machine learning significant to computational pathology in the pharmac...
Pubrica
 
Cancer moonshot and data sharing
Cancer moonshot and data sharingCancer moonshot and data sharing
Cancer moonshot and data sharing
Warren Kibbe
 
Cancer surgery or biopsy collection could influence disease progression
Cancer surgery or biopsy collection could influence disease progressionCancer surgery or biopsy collection could influence disease progression
Cancer surgery or biopsy collection could influence disease progression
undesirabledete79
 
A CLASSIFICATION MODEL ON TUMOR CANCER DISEASE BASED MUTUAL INFORMATION AND F...
A CLASSIFICATION MODEL ON TUMOR CANCER DISEASE BASED MUTUAL INFORMATION AND F...A CLASSIFICATION MODEL ON TUMOR CANCER DISEASE BASED MUTUAL INFORMATION AND F...
A CLASSIFICATION MODEL ON TUMOR CANCER DISEASE BASED MUTUAL INFORMATION AND F...
Kiogyf
 
Effective Cancer Detection Using Soft Computing Technique
Effective Cancer Detection Using Soft Computing TechniqueEffective Cancer Detection Using Soft Computing Technique
Effective Cancer Detection Using Soft Computing Technique
IOSR Journals
 
A Review on Data Mining Techniques for Prediction of Breast Cancer Recurrence
A Review on Data Mining Techniques for Prediction of Breast Cancer RecurrenceA Review on Data Mining Techniques for Prediction of Breast Cancer Recurrence
A Review on Data Mining Techniques for Prediction of Breast Cancer Recurrence
Dr. Amarjeet Singh
 
Senology Newsletter - April 10, 2013
Senology Newsletter - April 10, 2013Senology Newsletter - April 10, 2013
Senology Newsletter - April 10, 2013
Senology.org
 

What's hot (19)

CCRC Clonality Poster
CCRC Clonality PosterCCRC Clonality Poster
CCRC Clonality Poster
 
Big Data & Immunotherapeutics Symposium Program
Big Data & Immunotherapeutics Symposium ProgramBig Data & Immunotherapeutics Symposium Program
Big Data & Immunotherapeutics Symposium Program
 
poster_Xingzhi2
poster_Xingzhi2poster_Xingzhi2
poster_Xingzhi2
 
Pluripotent stem cells An in vitro model for nanotoxicity
Pluripotent stem cells An in vitro model for nanotoxicityPluripotent stem cells An in vitro model for nanotoxicity
Pluripotent stem cells An in vitro model for nanotoxicity
 
Precision Oncology - using Genomics, Proteomics and Imaging to inform biology...
Precision Oncology - using Genomics, Proteomics and Imaging to inform biology...Precision Oncology - using Genomics, Proteomics and Imaging to inform biology...
Precision Oncology - using Genomics, Proteomics and Imaging to inform biology...
 
Numerical Prediction of Microbubble Attachment in Biological Flows (2)
Numerical Prediction of Microbubble Attachment in Biological Flows (2)Numerical Prediction of Microbubble Attachment in Biological Flows (2)
Numerical Prediction of Microbubble Attachment in Biological Flows (2)
 
Central mucoepidermoid carcinoma an up to-date analysis of 147 cases
Central mucoepidermoid carcinoma an up to-date analysis of 147 casesCentral mucoepidermoid carcinoma an up to-date analysis of 147 cases
Central mucoepidermoid carcinoma an up to-date analysis of 147 cases
 
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
 
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
EFFICACY OF NON-NEGATIVE MATRIX FACTORIZATION FOR FEATURE SELECTION IN CANCER...
 
Disseminated Breast Cancer Cells Acquire a Highly Malignant and Aggressive Me...
Disseminated Breast Cancer Cells Acquire a Highly Malignant and Aggressive Me...Disseminated Breast Cancer Cells Acquire a Highly Malignant and Aggressive Me...
Disseminated Breast Cancer Cells Acquire a Highly Malignant and Aggressive Me...
 
How is machine learning significant to computational pathology in the pharmac...
How is machine learning significant to computational pathology in the pharmac...How is machine learning significant to computational pathology in the pharmac...
How is machine learning significant to computational pathology in the pharmac...
 
Cancer moonshot and data sharing
Cancer moonshot and data sharingCancer moonshot and data sharing
Cancer moonshot and data sharing
 
Biomarker-Vol-8
Biomarker-Vol-8Biomarker-Vol-8
Biomarker-Vol-8
 
Cancer surgery or biopsy collection could influence disease progression
Cancer surgery or biopsy collection could influence disease progressionCancer surgery or biopsy collection could influence disease progression
Cancer surgery or biopsy collection could influence disease progression
 
A CLASSIFICATION MODEL ON TUMOR CANCER DISEASE BASED MUTUAL INFORMATION AND F...
A CLASSIFICATION MODEL ON TUMOR CANCER DISEASE BASED MUTUAL INFORMATION AND F...A CLASSIFICATION MODEL ON TUMOR CANCER DISEASE BASED MUTUAL INFORMATION AND F...
A CLASSIFICATION MODEL ON TUMOR CANCER DISEASE BASED MUTUAL INFORMATION AND F...
 
2013 Garvan PhD_brochure
2013 Garvan PhD_brochure2013 Garvan PhD_brochure
2013 Garvan PhD_brochure
 
Effective Cancer Detection Using Soft Computing Technique
Effective Cancer Detection Using Soft Computing TechniqueEffective Cancer Detection Using Soft Computing Technique
Effective Cancer Detection Using Soft Computing Technique
 
A Review on Data Mining Techniques for Prediction of Breast Cancer Recurrence
A Review on Data Mining Techniques for Prediction of Breast Cancer RecurrenceA Review on Data Mining Techniques for Prediction of Breast Cancer Recurrence
A Review on Data Mining Techniques for Prediction of Breast Cancer Recurrence
 
Senology Newsletter - April 10, 2013
Senology Newsletter - April 10, 2013Senology Newsletter - April 10, 2013
Senology Newsletter - April 10, 2013
 

Similar to Potentials of 3D models in anticancer drug screening

SCT60103 Group 4 Assignment
SCT60103 Group 4 AssignmentSCT60103 Group 4 Assignment
SCT60103 Group 4 Assignment
Sheryn Yeo
 
The potential of using 3D in vitro models for drug efficiency testing compare...
The potential of using 3D in vitro models for drug efficiency testing compare...The potential of using 3D in vitro models for drug efficiency testing compare...
The potential of using 3D in vitro models for drug efficiency testing compare...
Josiah Sim
 
Group 6 - GTC
Group 6 - GTCGroup 6 - GTC
Group 6 - GTC
Thiiban Thuraiv
 
Group 6 - GTC
Group 6 - GTCGroup 6 - GTC
Group 6 - GTC
Thiiban Thuraiv
 
Group 6 - GTC
Group 6 - GTCGroup 6 - GTC
Group 6 - GTC
Thiiban Thuraiv
 
Genes and Tissue Culture Technology Assignment (G6)
Genes and Tissue Culture Technology Assignment (G6)Genes and Tissue Culture Technology Assignment (G6)
Genes and Tissue Culture Technology Assignment (G6)
Rohini Krishnan
 
Gene and Tissue Culture ppt Group 4
Gene and Tissue Culture ppt Group 4Gene and Tissue Culture ppt Group 4
Gene and Tissue Culture ppt Group 4
Ken Lee
 
Application of Microarray Technology and softcomputing in cancer Biology
Application of Microarray Technology and softcomputing in cancer BiologyApplication of Microarray Technology and softcomputing in cancer Biology
Application of Microarray Technology and softcomputing in cancer Biology
CSCJournals
 
Gene & Tissue Culture: Presentation (Group 4)
Gene & Tissue Culture: Presentation (Group 4)Gene & Tissue Culture: Presentation (Group 4)
Gene & Tissue Culture: Presentation (Group 4)
Su Shen Lim
 
Majumder_B_et_al_Nature_Communications_2015
Majumder_B_et_al_Nature_Communications_2015Majumder_B_et_al_Nature_Communications_2015
Majumder_B_et_al_Nature_Communications_2015Michelle Stevens
 
Dr Adeola Henry_Colorectal cancer book chapter 2014
Dr Adeola Henry_Colorectal cancer book chapter 2014Dr Adeola Henry_Colorectal cancer book chapter 2014
Dr Adeola Henry_Colorectal cancer book chapter 2014
adeolahenry
 
7IJMPD-28-Cancer.pdf-Cancer: A review IJMPD
7IJMPD-28-Cancer.pdf-Cancer: A review IJMPD7IJMPD-28-Cancer.pdf-Cancer: A review IJMPD
7IJMPD-28-Cancer.pdf-Cancer: A review IJMPD
PriyankaKilaniya
 
Top downloaded article in academia 2020 - International Journal of Computatio...
Top downloaded article in academia 2020 - International Journal of Computatio...Top downloaded article in academia 2020 - International Journal of Computatio...
Top downloaded article in academia 2020 - International Journal of Computatio...
ijcsity
 
Revolutionizing Cancer Research Immunohistochemistry and Digital Slide Scanne...
Revolutionizing Cancer Research Immunohistochemistry and Digital Slide Scanne...Revolutionizing Cancer Research Immunohistochemistry and Digital Slide Scanne...
Revolutionizing Cancer Research Immunohistochemistry and Digital Slide Scanne...
ihc-prs
 
PREDICTION OF BREAST CANCER USING DATA MINING TECHNIQUES
PREDICTION OF BREAST CANCER USING DATA MINING TECHNIQUESPREDICTION OF BREAST CANCER USING DATA MINING TECHNIQUES
PREDICTION OF BREAST CANCER USING DATA MINING TECHNIQUES
IAEME Publication
 
Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...
Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...
Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...
CSCJournals
 
JournalofCancerEpidemiologyandTreatment3
JournalofCancerEpidemiologyandTreatment3JournalofCancerEpidemiologyandTreatment3
JournalofCancerEpidemiologyandTreatment3Christian Schmidt
 
ciclo autonomico-short paper - Witfor 2016 paper_42
ciclo autonomico-short paper - Witfor 2016 paper_42ciclo autonomico-short paper - Witfor 2016 paper_42
ciclo autonomico-short paper - Witfor 2016 paper_42
.. ..
 
A Comprehensive Evaluation of Machine Learning Approaches for Breast Cancer C...
A Comprehensive Evaluation of Machine Learning Approaches for Breast Cancer C...A Comprehensive Evaluation of Machine Learning Approaches for Breast Cancer C...
A Comprehensive Evaluation of Machine Learning Approaches for Breast Cancer C...
IRJET Journal
 

Similar to Potentials of 3D models in anticancer drug screening (20)

SCT60103 Group 4 Assignment
SCT60103 Group 4 AssignmentSCT60103 Group 4 Assignment
SCT60103 Group 4 Assignment
 
The potential of using 3D in vitro models for drug efficiency testing compare...
The potential of using 3D in vitro models for drug efficiency testing compare...The potential of using 3D in vitro models for drug efficiency testing compare...
The potential of using 3D in vitro models for drug efficiency testing compare...
 
Group 6 - GTC
Group 6 - GTCGroup 6 - GTC
Group 6 - GTC
 
Group 6 - GTC
Group 6 - GTCGroup 6 - GTC
Group 6 - GTC
 
Group 6 - GTC
Group 6 - GTCGroup 6 - GTC
Group 6 - GTC
 
Genes and Tissue Culture Technology Assignment (G6)
Genes and Tissue Culture Technology Assignment (G6)Genes and Tissue Culture Technology Assignment (G6)
Genes and Tissue Culture Technology Assignment (G6)
 
Gene and Tissue Culture ppt Group 4
Gene and Tissue Culture ppt Group 4Gene and Tissue Culture ppt Group 4
Gene and Tissue Culture ppt Group 4
 
Application of Microarray Technology and softcomputing in cancer Biology
Application of Microarray Technology and softcomputing in cancer BiologyApplication of Microarray Technology and softcomputing in cancer Biology
Application of Microarray Technology and softcomputing in cancer Biology
 
Gene & Tissue Culture: Presentation (Group 4)
Gene & Tissue Culture: Presentation (Group 4)Gene & Tissue Culture: Presentation (Group 4)
Gene & Tissue Culture: Presentation (Group 4)
 
Majumder_B_et_al_Nature_Communications_2015
Majumder_B_et_al_Nature_Communications_2015Majumder_B_et_al_Nature_Communications_2015
Majumder_B_et_al_Nature_Communications_2015
 
Dr Adeola Henry_Colorectal cancer book chapter 2014
Dr Adeola Henry_Colorectal cancer book chapter 2014Dr Adeola Henry_Colorectal cancer book chapter 2014
Dr Adeola Henry_Colorectal cancer book chapter 2014
 
7IJMPD-28-Cancer.pdf-Cancer: A review IJMPD
7IJMPD-28-Cancer.pdf-Cancer: A review IJMPD7IJMPD-28-Cancer.pdf-Cancer: A review IJMPD
7IJMPD-28-Cancer.pdf-Cancer: A review IJMPD
 
s12935-014-0115-7
s12935-014-0115-7s12935-014-0115-7
s12935-014-0115-7
 
Top downloaded article in academia 2020 - International Journal of Computatio...
Top downloaded article in academia 2020 - International Journal of Computatio...Top downloaded article in academia 2020 - International Journal of Computatio...
Top downloaded article in academia 2020 - International Journal of Computatio...
 
Revolutionizing Cancer Research Immunohistochemistry and Digital Slide Scanne...
Revolutionizing Cancer Research Immunohistochemistry and Digital Slide Scanne...Revolutionizing Cancer Research Immunohistochemistry and Digital Slide Scanne...
Revolutionizing Cancer Research Immunohistochemistry and Digital Slide Scanne...
 
PREDICTION OF BREAST CANCER USING DATA MINING TECHNIQUES
PREDICTION OF BREAST CANCER USING DATA MINING TECHNIQUESPREDICTION OF BREAST CANCER USING DATA MINING TECHNIQUES
PREDICTION OF BREAST CANCER USING DATA MINING TECHNIQUES
 
Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...
Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...
Toward Integrated Clinical and Gene Expression Profiles for Breast Cancer Pro...
 
JournalofCancerEpidemiologyandTreatment3
JournalofCancerEpidemiologyandTreatment3JournalofCancerEpidemiologyandTreatment3
JournalofCancerEpidemiologyandTreatment3
 
ciclo autonomico-short paper - Witfor 2016 paper_42
ciclo autonomico-short paper - Witfor 2016 paper_42ciclo autonomico-short paper - Witfor 2016 paper_42
ciclo autonomico-short paper - Witfor 2016 paper_42
 
A Comprehensive Evaluation of Machine Learning Approaches for Breast Cancer C...
A Comprehensive Evaluation of Machine Learning Approaches for Breast Cancer C...A Comprehensive Evaluation of Machine Learning Approaches for Breast Cancer C...
A Comprehensive Evaluation of Machine Learning Approaches for Breast Cancer C...
 

Recently uploaded

20240520 Planning a Circuit Simulator in JavaScript.pptx
20240520 Planning a Circuit Simulator in JavaScript.pptx20240520 Planning a Circuit Simulator in JavaScript.pptx
20240520 Planning a Circuit Simulator in JavaScript.pptx
Sharon Liu
 
Leaf Initiation, Growth and Differentiation.pdf
Leaf Initiation, Growth and Differentiation.pdfLeaf Initiation, Growth and Differentiation.pdf
Leaf Initiation, Growth and Differentiation.pdf
RenuJangid3
 
Nucleic Acid-its structural and functional complexity.
Nucleic Acid-its structural and functional complexity.Nucleic Acid-its structural and functional complexity.
Nucleic Acid-its structural and functional complexity.
Nistarini College, Purulia (W.B) India
 
bordetella pertussis.................................ppt
bordetella pertussis.................................pptbordetella pertussis.................................ppt
bordetella pertussis.................................ppt
kejapriya1
 
原版制作(carleton毕业证书)卡尔顿大学毕业证硕士文凭原版一模一样
原版制作(carleton毕业证书)卡尔顿大学毕业证硕士文凭原版一模一样原版制作(carleton毕业证书)卡尔顿大学毕业证硕士文凭原版一模一样
原版制作(carleton毕业证书)卡尔顿大学毕业证硕士文凭原版一模一样
yqqaatn0
 
Unveiling the Energy Potential of Marshmallow Deposits.pdf
Unveiling the Energy Potential of Marshmallow Deposits.pdfUnveiling the Energy Potential of Marshmallow Deposits.pdf
Unveiling the Energy Potential of Marshmallow Deposits.pdf
Erdal Coalmaker
 
NuGOweek 2024 Ghent programme overview flyer
NuGOweek 2024 Ghent programme overview flyerNuGOweek 2024 Ghent programme overview flyer
NuGOweek 2024 Ghent programme overview flyer
pablovgd
 
Topic: SICKLE CELL DISEASE IN CHILDREN-3.pdf
Topic: SICKLE CELL DISEASE IN CHILDREN-3.pdfTopic: SICKLE CELL DISEASE IN CHILDREN-3.pdf
Topic: SICKLE CELL DISEASE IN CHILDREN-3.pdf
TinyAnderson
 
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
University of Maribor
 
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptx
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptx
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptx
RASHMI M G
 
Nucleophilic Addition of carbonyl compounds.pptx
Nucleophilic Addition of carbonyl  compounds.pptxNucleophilic Addition of carbonyl  compounds.pptx
Nucleophilic Addition of carbonyl compounds.pptx
SSR02
 
DMARDs Pharmacolgy Pharm D 5th Semester.pdf
DMARDs Pharmacolgy Pharm D 5th Semester.pdfDMARDs Pharmacolgy Pharm D 5th Semester.pdf
DMARDs Pharmacolgy Pharm D 5th Semester.pdf
fafyfskhan251kmf
 
THEMATIC APPERCEPTION TEST(TAT) cognitive abilities, creativity, and critic...
THEMATIC  APPERCEPTION  TEST(TAT) cognitive abilities, creativity, and critic...THEMATIC  APPERCEPTION  TEST(TAT) cognitive abilities, creativity, and critic...
THEMATIC APPERCEPTION TEST(TAT) cognitive abilities, creativity, and critic...
Abdul Wali Khan University Mardan,kP,Pakistan
 
如何办理(uvic毕业证书)维多利亚大学毕业证本科学位证书原版一模一样
如何办理(uvic毕业证书)维多利亚大学毕业证本科学位证书原版一模一样如何办理(uvic毕业证书)维多利亚大学毕业证本科学位证书原版一模一样
如何办理(uvic毕业证书)维多利亚大学毕业证本科学位证书原版一模一样
yqqaatn0
 
ESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptxESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptx
PRIYANKA PATEL
 
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Sérgio Sacani
 
Deep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless ReproducibilityDeep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless Reproducibility
University of Rennes, INSA Rennes, Inria/IRISA, CNRS
 
SAR of Medicinal Chemistry 1st by dk.pdf
SAR of Medicinal Chemistry 1st by dk.pdfSAR of Medicinal Chemistry 1st by dk.pdf
SAR of Medicinal Chemistry 1st by dk.pdf
KrushnaDarade1
 
What is greenhouse gasses and how many gasses are there to affect the Earth.
What is greenhouse gasses and how many gasses are there to affect the Earth.What is greenhouse gasses and how many gasses are there to affect the Earth.
What is greenhouse gasses and how many gasses are there to affect the Earth.
moosaasad1975
 
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
University of Maribor
 

Recently uploaded (20)

20240520 Planning a Circuit Simulator in JavaScript.pptx
20240520 Planning a Circuit Simulator in JavaScript.pptx20240520 Planning a Circuit Simulator in JavaScript.pptx
20240520 Planning a Circuit Simulator in JavaScript.pptx
 
Leaf Initiation, Growth and Differentiation.pdf
Leaf Initiation, Growth and Differentiation.pdfLeaf Initiation, Growth and Differentiation.pdf
Leaf Initiation, Growth and Differentiation.pdf
 
Nucleic Acid-its structural and functional complexity.
Nucleic Acid-its structural and functional complexity.Nucleic Acid-its structural and functional complexity.
Nucleic Acid-its structural and functional complexity.
 
bordetella pertussis.................................ppt
bordetella pertussis.................................pptbordetella pertussis.................................ppt
bordetella pertussis.................................ppt
 
原版制作(carleton毕业证书)卡尔顿大学毕业证硕士文凭原版一模一样
原版制作(carleton毕业证书)卡尔顿大学毕业证硕士文凭原版一模一样原版制作(carleton毕业证书)卡尔顿大学毕业证硕士文凭原版一模一样
原版制作(carleton毕业证书)卡尔顿大学毕业证硕士文凭原版一模一样
 
Unveiling the Energy Potential of Marshmallow Deposits.pdf
Unveiling the Energy Potential of Marshmallow Deposits.pdfUnveiling the Energy Potential of Marshmallow Deposits.pdf
Unveiling the Energy Potential of Marshmallow Deposits.pdf
 
NuGOweek 2024 Ghent programme overview flyer
NuGOweek 2024 Ghent programme overview flyerNuGOweek 2024 Ghent programme overview flyer
NuGOweek 2024 Ghent programme overview flyer
 
Topic: SICKLE CELL DISEASE IN CHILDREN-3.pdf
Topic: SICKLE CELL DISEASE IN CHILDREN-3.pdfTopic: SICKLE CELL DISEASE IN CHILDREN-3.pdf
Topic: SICKLE CELL DISEASE IN CHILDREN-3.pdf
 
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
 
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptx
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptx
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptx
 
Nucleophilic Addition of carbonyl compounds.pptx
Nucleophilic Addition of carbonyl  compounds.pptxNucleophilic Addition of carbonyl  compounds.pptx
Nucleophilic Addition of carbonyl compounds.pptx
 
DMARDs Pharmacolgy Pharm D 5th Semester.pdf
DMARDs Pharmacolgy Pharm D 5th Semester.pdfDMARDs Pharmacolgy Pharm D 5th Semester.pdf
DMARDs Pharmacolgy Pharm D 5th Semester.pdf
 
THEMATIC APPERCEPTION TEST(TAT) cognitive abilities, creativity, and critic...
THEMATIC  APPERCEPTION  TEST(TAT) cognitive abilities, creativity, and critic...THEMATIC  APPERCEPTION  TEST(TAT) cognitive abilities, creativity, and critic...
THEMATIC APPERCEPTION TEST(TAT) cognitive abilities, creativity, and critic...
 
如何办理(uvic毕业证书)维多利亚大学毕业证本科学位证书原版一模一样
如何办理(uvic毕业证书)维多利亚大学毕业证本科学位证书原版一模一样如何办理(uvic毕业证书)维多利亚大学毕业证本科学位证书原版一模一样
如何办理(uvic毕业证书)维多利亚大学毕业证本科学位证书原版一模一样
 
ESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptxESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptx
 
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...
 
Deep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless ReproducibilityDeep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless Reproducibility
 
SAR of Medicinal Chemistry 1st by dk.pdf
SAR of Medicinal Chemistry 1st by dk.pdfSAR of Medicinal Chemistry 1st by dk.pdf
SAR of Medicinal Chemistry 1st by dk.pdf
 
What is greenhouse gasses and how many gasses are there to affect the Earth.
What is greenhouse gasses and how many gasses are there to affect the Earth.What is greenhouse gasses and how many gasses are there to affect the Earth.
What is greenhouse gasses and how many gasses are there to affect the Earth.
 
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
 

Potentials of 3D models in anticancer drug screening

  • 1.
  • 2. In the quest of successfully launching a new drug, drug discovery in the preclinical phase, and drug development in the clinical phase is crucial. Especially in the field of anti cancer drug screening, researchers have been heavily involved in producing new drugs that bridge the gap between experimental research and clinical trials (Meng et al., 2019). Recent advancement in bioprinting, has thus produced several in vitro models such as 2D and 3D models that are widely used in drug screening. 2D models are traditionally used by researchers to evaluate effectiveness of anti-cancer drugs towards cancer cell lines. Additionally, it is to understand the molecular pathways of cell proliferation. 2D models are also grown in either shake flasks or Petri dishes with growth medium as their source of nutrients (Breslin & O’Driscoll, 2013). Meanwhile, in this presentation, 3D models are used by researchers to mimic tumour microenvironment and visualise the structure of cells (Breslin & O’Driscoll, 2013). This presentation will be reviewing the differences between these two models, the recent preference of researchers for 3D models, and case study that highlights the new direction for the future 3D bioprinted models. INTRODUCTION
  • 3. COMPARISON OF 2D AND 3D MODELS 2D 3D
  • 4. 3D models mimic in vivo physiology of organisms, such as the histological architecture and heterogeneity (Jackson and Lu, 2016). They mimic native matrixes and cell-cell interaction as well as the interactions with the extracellular matrix (ECM) (Leong and Ng, 2014). Researchers prefer 3D models because 2D models are unnatural while animal models are expensive and brings about ethical issues (Gurski et al., 2010). Cancer cells cultured in 3D models reflects the behaviour of cancer cells in their native, in vivo environment (Gurski et al., 2010) An example would be where cancer cells cultured in 3D models respond to chemotherapeutic treatments similarly to in vivo cancer cells. WHY RESEARCHERS ARE USING 3D MODELS Source: (Bourré, 2018)
  • 5.
  • 6. Other methods of generating 3D tumour models Methods of anticancer drug screening from 3D tumour models •Once the 3D tumour models have been cultured in anticancer drug supplied medium, different analysis techniques are used to screen for the most efficient drug.
  • 7. 3D bioprinted cancer model to test anticancer drugs A new direction in producing 3D bioprinted in vitro metastatic models via reconstruction of tumor microenvironments Source:National Institute of Biomedical Imaging and Bioengineering (NBIB),2019. A NIBIB-funded research conducted recently by a team of researchers from University of Minnesota (UMN), has developed a newly dynamic and efficient 3D bioprinted tumor model for anticancer drug screening. The 3D model was made in a laboratory dish, and functions in studying the primary site, growth and spread of cancer tumours in the body. Thus, tackling the recurring problems in which previous 2D models, could not replicate the conditions and outcomes of tumor growth in the human body. The 3D bioprinting technology used in this project originated from UMN lab through Michael McAlpine. Through this research, 3D printed biochemical capsules were combined with 3D bioprinted tumor cells. Through 3D bioprinting technology, melanoma cancer cells,lung cancer cells, normal cells, and blood-vessel like structures, are able to be precisely located in the laboratory dish based on their individual functions (Nibib.nih.gov, 2019).
  • 8. Chemicals that guide cancer cell migration or the growth of blood vessels, are as well packed in the cores of hydrogels. They are also encapsulated within an outer shell made of gold nanorods. A time controlled release of the capsules are activated by laser light, which then creates a chemical gradient that ultimately guides targeted cell growth. Thus, these features provides a 4D control over both space and time. “The cells and capsules are precisely printed in biologically relevant sites and the chemical depots propel movement upon a triggered release. This is a dynamic 3D tissue engineering system giving the user control over the diffusion process at some later point after the printing process.” emphasized McAlpine (Nibib.nih.gov, 2019). Figure above shows the schematics of the 3D bioprinted in vitro tumor model, which demonstrates the integration of tumor cells, the blood- vessel like structures, and chemical gradients 3D bioprinted cancer model to test anticancer drugs A new direction in producing 3D bioprinted in vitro metastatic models via reconstruction of tumor microenvironments Source: Nibib.nih. gov, 2019).
  • 9. CONCLUSION (Zanoni et al., 2019) (Zanoni et al., 2019)
  • 10. 3D cell culture and anticancer drug testing | Cherry Biotech 2019 Cherry Biotech. viewed 8 May 2019, <https://www.cherrybiotech.com/scientific- note/organs-on-chip/3d-cell-culture-and-anticancer-drug-testing>. Bing He, Guomin Chen, Yi Zeng, 2016: Three-dimensional cell culture models for investigating human viruses, Virologica Sinica, 31, 363-379., viewed 08 May 2019, <https://www.virosin.org/article/doi/10.1007/s12250-016-3889-z#bpampaloni2007> Bourré, L., 2018. Facilitating Drug Discovery with 3D In Vitro Oncology Models. [online] Blog.crownbio.com. Available at: https://blog.crownbio.com/in-vitro-3d-organoids-spheroids-oncology [Accessed 3 May 2019]. Breslin, S & O’Driscoll, L 2013, "Three-dimensional cell culture: the missing link in drug discovery", Drug Discovery Today, vol. 18, no. 5-6, pp. 240-249. viewed 1 May 2019, <https://www.ncbi.nlm.nih.gov/pubmed/23073387>. Duval, K., Grover, H., Han, L. H., Mou, Y., Pegoraro, A. F., Fredberg, J., & Chen, Z., 2017. “Modeling Physiological Events in 2D vs. 3D Cell Culture.”, Physiology (Bethesda, Md.), 32(4), 266–277., viewed 08 May 2019, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5545611/?report=classic> Gurski, L.A., Petrelli, N.J., Jia, X. and Farach-Carson, M.C., 2010. 3D matrices for anti-cancer drug testing and development. Oncology Issues, 25(1), pp.20-25. Huang, L, Holtzinger, A, Jagan, I, BeGora, M, Lohse, I, Ngai, N, Mutuswamy LB, Crawford, HC, Arrowsmith, C, Kalloger, SE, Renouf, DJ, Connor, AA, Clearly, S, Schaeffer, DF, Roehrl, M, Tsao MS, Gallinger, S, Keller, G & Muthuswamy, SK 2015, “Ductal pancreatic cancer modeling and drug screening using human pluripotent stem cell– and patient-derived tumor organoids.” Nature Medicine, vol. 21, no. 11, pp. 1364–1371, viewed 08 May 2019, <https://www.nature.com/articles/nm.3973> REFERENCES
  • 11. Ivascu, A & Kubbies, M 2006, “Rapid Generation of Single-Tumor Spheroids for High-Throughput Cell Function and Toxicity Analysis”, SLAS Discovery, vol. 11, no. 8, pp. 922-932, viewed 08 May 2019, <https://journals.sagepub.com/doi/abs/10.1177/1087057106292763> Jackson, E.L. and Lu, H., 2016. Three-dimensional models for studying development and disease: moving on from organisms to organs-on-a- chip and organoids. Integrative Biology, 8(6), pp.672-683. Jitcy Saji Joseph, Sibusiso Tebogo Malindisa and Monde Ntwasa, 2018, Two Dimensional (2D) and Three Dimensional(3D) Cell Culturing in Drug Discovering”, Intechopen, viewed 08 May 2019, <https://www.intechopen.com/books/cell-culture/two-dimensional-2d-and-three- dimensional-3d-cell-culturing-in-drug-discovery> Kwapiszewska, K, Michalczuk, A, Rybka, M, Kwapiszewski, R & Brzózka, Z 2014, “A microfluidic-based platform for tumour spheroid culture, monitoring and drug screening”, Lab Chip, vol. 14, pp. 2096-2104, <https://pubs.rsc.org/en/content/articlehtml/2014/lc/c4lc00291a> Leong, D.T. and Ng, K.W., 2014. Probing the relevance of 3D cancer models in nanomedicine research. Advanced drug delivery reviews, 79, pp.95-106. Markovitz-Bishitz, Y, Tauber, Y, Afrimzon, E, Zurgil, N, Sobolev, M, Shafran, Y, Deutsch, A, Howitz, S, Deutsch, M 2010, “A polymer microstructure array for the formation, culturing, and high throughput drug screening of breast cancer spheroids.” Biomaterials, vol. 31, no. 32, pp. 8436–8444, viewed 08 May 2019, <https://www.sciencedirect.com/science/article/pii/S0142961210008938> Marta Kapałczyńska , Tomasz Kolenda, Weronika Przybyła, et al., 2016, “2D and 3D cell cultures – a comparison of different types of cancer cell cultures”, 14, 4: 910–919, viewed 08 May 2019, <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6040128/pdf/AMS-14-28752.pdf> Mellor, HR, Ferguson, DJ & Callaghan, R 2005, “A model of quiescent tumour microregions for evaluating multicellular resistance to chemotherapeutic drugs”, British Journal of Cancer, vol. 93, pp. 302-309, viewed 08 May 2019, <https://www.nature.com/articles/6602710>
  • 12. Nibib.nih.gov. (2019). 3D bioprinted cancer model to test anticancer drugs | National Institute of Biomedical Imaging and Bioengineering. [online] Available at: https://www.nibib.nih.gov/news-events/newsroom/3d-bioprinted-cancer-model-test-anticancer- drugs [Accessed 9 May 2019]. Souza, GR, Molina, JR, Raphael, RM, Ozawa, MG, Stark, DJ, Levin, CS, Bronk, LF, Ananta, JS, Mndelin, J, Georgescu, M, Bankson, JA, Gelovani, JG, Killian, TC, Arap, W & Pasqualini, R 2010, “Three-dimensional tissue culture based on magnetic cell levitation.” Nature Nanotechnology, vol. 5, no.4, pp. 291–296, viewed 08 May 2019, <https://www.nature.com/articles/nnano.2010.23> Tung, YC, Hsiao, AY, Allen, SG, Torisawa, Y, Ho, M, & Takayama, S 2011, “High-throughput 3D spheroid culture and drug testing using a 384 hanging drop array.” The Analyst, vol. 136, no. 3, pp. 473–478, viewed 08 May 2019, <https://pubs.rsc.org/en/content/articlelanding/2011/an/c0an00609b/unauth#!divAbstract> Zanoni, M., Pignatta, S., Arienti, C., Bonafè, M. and Tesei, A., 2019. Anticancer drug discovery using multicellular tumor spheroid models. Expert Opinion on Drug Discovery, 14(3), pp.289-301.