Development, optimization and implementation of a centralized metabolic soft spot assay-Reference-Cited by-同舟云学术

Development, optimization and implementation of a centralized metabolic soft spot assay

Published:2017-04 Issue:7 Volume:9 Page:541-552
ISSN:1757-6180
Container-title:Bioanalysis
language:en
Short-container-title:Bioanalysis

Author:

Paiva Anthony A¹,Klakouski Cheryl²,Li Shu¹,Johnson Benjamin M²,Shu Yue-Zhong³,Josephs Jonathan⁴⁵,Zvyaga Tatyana¹,Zamora Ismael⁶,Shou Wilson Z¹

Affiliation:

1. Bristol-Myers Squibb R & D, SATT, 5 Research Parkway, Wallingford, CT 06492, USA

2. Bristol-Myers Squibb R & D, PCO, 5 Research Parkway, Wallingford, CT 06492, USA

3. Bristol-Myers Squibb R & D, PCO, 3551 Lawrenceville, Princeton, NJ 08648, USA

4. Bristol-Myers Squibb R & D, PCO, 311 Pennington Rocky Hill Road, Pennington, NJ 08534, USA

5. Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA 95134, USA

6. Lead Molecular Design SL, Sant Cugat de Valles, Spain

Abstract

Aim: High clearance is a commonly encountered issue in drug discovery. Here we present a centralized metabolic soft spot identification assay with adequate capacity and turnaround time to support the metabolic optimization needs of an entire discovery organization. Methodology: An integrated quan/qual approach utilizing both an orthogonal sample-pooling methodology and software-assisted structure elucidation was developed to enable the assay. Major metabolic soft spots in liver microsomes (rodent and human) were generated in a batch mode, along with kinetics of parent disappearance and metabolite formation, typically within 1 week of incubation. Results & conclusion: A centralized metabolic soft spot identification assay has been developed and has successfully impacted discovery project teams in mitigating instability and establishing potential structure–metabolism relationships.

Publisher

Future Science Ltd

Subject

Medical Laboratory Technology,Clinical Biochemistry,General Pharmacology, Toxicology and Pharmaceutics,General Medicine,Analytical Chemistry

Link

http://www.future-science.com/doi/pdf/10.4155/bio-2016-0299

Reference16 articles.

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4. Metabolic Soft Spot Identification and Compound Optimization in Early Discovery Phases Using MetaSite and LC-MS/MS Validation

5. Enhanced metabolite identification with MSE and a semi-automated software for structural elucidation

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