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Harnessing human microphysiology systems as key experimental models for quantitative systems pharmacology

  • D. Lansing Taylor
  • , Albert Gough
  • , Mark E. Schurdak
  • , Lawrence Vernetti
  • , Chakra S. Chennubhotla
  • , Daniel Lefever
  • , Fen Pei
  • , James R. Faeder
  • , Timothy R. Lezon
  • , Andrew M. Stern
  • , Ivet Bahar
  • University of Pittsburgh

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

21 Scopus citations

Abstract

Two technologies that have emerged in the last decade offer a new paradigm for modern pharmacology, as well as drug discovery and development. Quantitative systems pharmacology (QSP) is a complementary approach to traditional, target-centric pharmacology and drug discovery and is based on an iterative application of computational and systems biology methods with multiscale experimental methods, both of which include models of ADME-Tox and disease. QSP has emerged as a new approach due to the low efficiency of success in developing therapeutics based on the existing target-centric paradigm. Likewise, human microphysiology systems (MPS) are experimental models complementary to existing animal models and are based on the use of human primary cells, adult stem cells, and/or induced pluripotent stem cells (iPSCs) to mimic human tissues and organ functions/structures involved in disease and ADME-Tox. Human MPS experimental models have been developed to address the relatively low concordance of human disease and ADME-Tox with engineered, experimental animal models of disease. The integration of the QSP paradigm with the use of human MPS has the potential to enhance the process of drug discovery and development.

Original languageEnglish
Title of host publicationHandbook of Experimental Pharmacology
PublisherSpringer
Pages327-367
Number of pages41
DOIs
StatePublished - 2019

Publication series

NameHandbook of Experimental Pharmacology
Volume260
ISSN (Print)0171-2004
ISSN (Electronic)1865-0325

Keywords

  • Computational models of ADME-Tox
  • Computational models of disease
  • DILI
  • Drug development
  • Drug discovery
  • Drug repurposing
  • Induced pluripotent stem cells
  • Microphysiology systems
  • Omics analyses
  • PBPK
  • Personalized medicine
  • Quantitative systems pharmacology
  • Toxicology

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