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Experimental and Molecular Therapeutics

Abstract 5818: Globally optimizing therapeutic combinations against bortezomib-resistant multiple myeloma using a quantitative parabolic optimization platform

Masturah Rashid, Tan Boon Toh, Lissa Hooi, Aleidy Silva, Yanzhou Zhang, Neerja Karnani, Sudhakar Jha, Chih-Ming Ho, Wee Joo Chng, Dean Ho and Edward Kai-Hua Chow
Masturah Rashid
National University of Singapore (NUS), SINGAPORE, Singapore;
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Tan Boon Toh
National University of Singapore (NUS), SINGAPORE, Singapore;
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Lissa Hooi
National University of Singapore (NUS), SINGAPORE, Singapore;
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Aleidy Silva
University of California, Los Angeles (UCLA), Los Angeles, CA;
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Yanzhou Zhang
National University of Singapore (NUS), SINGAPORE, Singapore;
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Neerja Karnani
Singapore Institute for Clinical Sciences (SICS), A*STAR, SINGAPORE, Singapore.
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Sudhakar Jha
National University of Singapore (NUS), SINGAPORE, Singapore;
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Chih-Ming Ho
University of California, Los Angeles (UCLA), Los Angeles, CA;
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Wee Joo Chng
National University of Singapore (NUS), SINGAPORE, Singapore;
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Dean Ho
University of California, Los Angeles (UCLA), Los Angeles, CA;
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Edward Kai-Hua Chow
National University of Singapore (NUS), SINGAPORE, Singapore;
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DOI: 10.1158/1538-7445.AM2018-5818 Published July 2018
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Proceedings: AACR Annual Meeting 2018; April 14-18, 2018; Chicago, IL

Abstract

Multiple myeloma is an incurable hematological malignancy that relies on drug combinations as first and secondary lines of treatment. The inclusion of proteasome inhibitors, such as bortezomib, into these drug combination regimens has improved median survival. Resistance to bortezomib, however, is a common occurrence that ultimately contributes to treatment failure. Thus, there remains a need to identify improved drug combinations that may serve as later lines of treatment for improved treatment against bortezomib-resistant multiple myeloma. We have developed the quantitative parabolic optimization platform (QPOP) to optimize drug combinations against bortezomib-resistant multiple myeloma. By mapping phenotypic output data to parabolic response surfaces, QPOP is able to deterministically optimize drug combinations as well as drug dosages. By continuously optimizing in multiple systems of interest, from in vitro to in vivo, drug combinations can be globally optimized for greater efficacy in increasingly complex biological systems. While QPOP does not rely on molecular mechanism modeling or prediction, identified optimal drug combinations can reverse DNA hypermethylation and silencing of tumor suppressors that occurs following acquired bortezomib-resistance in multiple myeloma. Furthermore, this drug combination is broadly effective across a range of primary multiple myeloma patient samples. Beyond bortezomib-resistant multiple myeloma, global optimization of drug combinations by QPOP can serve to improve drug combination design across a range of other cancers and diseases through a continuous optimization process across the entire drug development pipeline.

Citation Format: Masturah Rashid, Tan Boon Toh, Lissa Hooi, Aleidy Silva, Yanzhou Zhang, Neerja Karnani, Sudhakar Jha, Chih-Ming Ho, Wee Joo Chng, Dean Ho, Edward Kai-Hua Chow. Globally optimizing therapeutic combinations against bortezomib-resistant multiple myeloma using a quantitative parabolic optimization platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5818.

  • ©2018 American Association for Cancer Research.
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Cancer Research: 78 (13 Supplement)
July 2018
Volume 78, Issue 13 Supplement
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Abstract 5818: Globally optimizing therapeutic combinations against bortezomib-resistant multiple myeloma using a quantitative parabolic optimization platform
Masturah Rashid, Tan Boon Toh, Lissa Hooi, Aleidy Silva, Yanzhou Zhang, Neerja Karnani, Sudhakar Jha, Chih-Ming Ho, Wee Joo Chng, Dean Ho and Edward Kai-Hua Chow
Cancer Res July 1 2018 (78) (13 Supplement) 5818; DOI: 10.1158/1538-7445.AM2018-5818

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Abstract 5818: Globally optimizing therapeutic combinations against bortezomib-resistant multiple myeloma using a quantitative parabolic optimization platform
Masturah Rashid, Tan Boon Toh, Lissa Hooi, Aleidy Silva, Yanzhou Zhang, Neerja Karnani, Sudhakar Jha, Chih-Ming Ho, Wee Joo Chng, Dean Ho and Edward Kai-Hua Chow
Cancer Res July 1 2018 (78) (13 Supplement) 5818; DOI: 10.1158/1538-7445.AM2018-5818
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