Kochanek, Stanton
(2019)
Data-Driven HTS Strategies for Selection of Drug Combinations and 3D Models for Physiologically Relevant Drug Discovery.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Currently, the approval rate for cancer drugs is dismal, where only ~ 5% of candidates that enter phase I clinical trials become therapies. To address this, it is necessary to improve our preclinical strategies. In particular, the leading clinical observation for patient treatment is that drug combinations more consistently provide better therapeutic outcomes and reduce or delay the emergence of drug resistance as opposed to monotherapy alone. What’s more, models that better recapitulate tumor biology are more likely to be predictive of therapeutic success. Therefore, it was necessary for our laboratory to use data-driven high-throughput / content screening strategies to confirm synergistic drug-drug interactions and optimize cell culture conditions in 3D for drug discovery, to address these preclinical limitations. Specifically, we developed a strategy to confirm and evaluate the synergistic interaction between DCs identified in a pilot screen of 20 drugs performed in pairwise combinations. We were able to both confirm synergism across 4 DCs and develop a mechanism of synergistic action. We also characterized 11 head and neck squamous cell carcinoma cell lines as multicellular tumor spheroids (MCTSs) looking at changes in cellular viability and spheroid diameter over time as well as other microenvironmental characteristics of a solid tumor. Lastly, we applied our MCTSs to screen 19 FDA approved drugs to determine drug sensitivity in both 2D and 3D models. We observed that 2D was consistently more sensitive than 3D and that it was necessary to implement several metrics to adequately evaluate drug effect in 3D.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
5 August 2019 |
| Date Type: |
Publication |
| Defense Date: |
8 July 2019 |
| Approval Date: |
5 August 2019 |
| Submission Date: |
1 August 2019 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
228 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Pharmacy > Pharmaceutical Sciences |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Drug Combinations, Multicellular Tumor Spheroids, High Throughput Screening, High Content Screening |
| Date Deposited: |
05 Aug 2019 13:05 |
| Last Modified: |
05 Aug 2019 13:05 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/37271 |
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