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Your search keyword '"Kaddi, Chanchala D."' showing total 5 results
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5 results on '"Kaddi, Chanchala D."'

1. History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications

Author

Azer, Karim, primary, Kaddi, Chanchala D., additional, Barrett, Jeffrey S., additional, Bai, Jane P. F., additional, McQuade, Sean T., additional, Merrill, Nathaniel J., additional, Piccoli, Benedetto, additional, Neves-Zaph, Susana, additional, Marchetti, Luca, additional, Lombardo, Rosario, additional, Parolo, Silvia, additional, Immanuel, Selva Rupa Christinal, additional, and Baliga, Nitin S., additional

Published
2021
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2. A Quantitative Systems Pharmacology Model of Gaucher Disease Type 1 Provides Mechanistic Insight Into the Response to Substrate Reduction Therapy With Eliglustat

Author

Abrams, Ruth, primary, Kaddi, Chanchala D., additional, Tao, Mengdi, additional, Leiser, Randolph J., additional, Simoni, Giulia, additional, Reali, Federico, additional, Tolsma, John, additional, Jasper, Paul, additional, Rijn, Zachary, additional, Li, Jing, additional, Niesner, Bradley, additional, Barrett, Jeffrey S., additional, Marchetti, Luca, additional, Peterschmitt, M. Judith, additional, Azer, Karim, additional, and Neves‐Zaph, Susana, additional

Published
2020
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3. Quantitative Systems Pharmacology Modeling of Acid Sphingomyelinase Deficiency and the Enzyme Replacement Therapy Olipudase Alfa Is an Innovative Tool for Linking Pathophysiology and Pharmacology

Author

Kaddi, Chanchala D., primary, Niesner, Bradley, additional, Baek, Rena, additional, Jasper, Paul, additional, Pappas, John, additional, Tolsma, John, additional, Li, Jing, additional, van Rijn, Zachary, additional, Tao, Mengdi, additional, Ortemann‐Renon, Catherine, additional, Easton, Rachael, additional, Tan, Sharon, additional, Puga, Ana Cristina, additional, Schuchman, Edward H., additional, Barrett, Jeffrey S., additional, and Azer, Karim, additional

Published
2018
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5. –Omic and Electronic Health Record Big Data Analytics for Precision Medicine.

Author

Wu, Po-Yen, Cheng, Chih-Wen, Kaddi, Chanchala D., Venugopalan, Janani, Hoffman, Ryan, and Wang, May D.

Subjects
ELECTRONIC health records, INDIVIDUALIZED medicine, DATA mining, TEXT mining, WEB analytics
Abstract

Objective: Rapid advances of high-throughput technologies and wide adoption of electronic health records (EHRs) have led to fast accumulation of –omic and EHR data. These voluminous complex data contain abundant information for precision medicine, and big data analytics can extract such knowledge to improve the quality of healthcare. Methods: In this paper, we present –omic and EHR data characteristics, associated challenges, and data analytics including data preprocessing, mining, and modeling. Results: To demonstrate how big data analytics enables precision medicine, we provide two case studies, including identifying disease biomarkers from multi-omic data and incorporating –omic information into EHR. Conclusion: Big data analytics is able to address –omic and EHR data challenges for paradigm shift toward precision medicine. Significance: Big data analytics makes sense of –omic and EHR data to improve healthcare outcome. It has long lasting societal impact. [ABSTRACT FROM AUTHOR]

Published
2017
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