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

Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances i...

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Published inFrontiers in physiology Vol. 12; p. 637999
Main Authors Azer, Karim, Kaddi, Chanchala D, Barrett, Jeffrey S, Bai, Jane P F, McQuade, Sean T, Merrill, Nathaniel J, Piccoli, Benedetto, Neves-Zaph, Susana, Marchetti, Luca, Lombardo, Rosario, Parolo, Silvia, Immanuel, Selva Rupa Christinal, Baliga, Nitin S
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 25.03.2021
Subjects
bioinformatics
computational biology
data science
Physiology
QSP modeling
systems biology
systems pharmacology
computational biology
systems biology
data science
bioinformatics
drug development
systems pharmacology
QSP modeling
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Abstract Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. In this paper, we will review milestones in the evolution of mathematical biology and pharmacology models, highlight some of the gaps and challenges in developing and applying systems pharmacology models, and provide a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.
AbstractList Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. In this paper, we will review milestones in the evolution of mathematical biology and pharmacology models, highlight some of the gaps and challenges in developing and applying systems pharmacology models, and provide a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.
Author Baliga, Nitin S
Parolo, Silvia
Lombardo, Rosario
Marchetti, Luca
Immanuel, Selva Rupa Christinal
Neves-Zaph, Susana
Piccoli, Benedetto
McQuade, Sean T
Azer, Karim
Barrett, Jeffrey S
Merrill, Nathaniel J
Kaddi, Chanchala D
Bai, Jane P F
AuthorAffiliation 1 Quantitative Sciences, Bill and Melinda Gates Medical Research Institute , Cambridge, MA , United States
6 Translational Disease Modeling, Data and Data Science, Sanofi , Bridgewater, NJ , United States
2 Critical Path Institute , Tucson, AZ , United States
5 Department of Mathematical Sciences and Center for Computational and Integrative Biology, Rutgers University , Camden, NJ , United States
3 Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration , Silver Spring, MD , United States
7 Fondazione the Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI) , Rovereto , Italy
4 Center for Computational and Integrative Biology, Rutgers University , Camden, NJ , United States
8 Institute for Systems Biology , Seattle, WA , United States
AuthorAffiliation_xml – name: 4 Center for Computational and Integrative Biology, Rutgers University , Camden, NJ , United States
– name: 5 Department of Mathematical Sciences and Center for Computational and Integrative Biology, Rutgers University , Camden, NJ , United States
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– name: 6 Translational Disease Modeling, Data and Data Science, Sanofi , Bridgewater, NJ , United States
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– name: 7 Fondazione the Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI) , Rovereto , Italy
– name: 1 Quantitative Sciences, Bill and Melinda Gates Medical Research Institute , Cambridge, MA , United States
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  organization: Quantitative Sciences, Bill and Melinda Gates Medical Research Institute, Cambridge, MA, United States
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  surname: Piccoli
  fullname: Piccoli, Benedetto
  organization: Department of Mathematical Sciences and Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, United States
– sequence: 8
  givenname: Susana
  surname: Neves-Zaph
  fullname: Neves-Zaph, Susana
  organization: Translational Disease Modeling, Data and Data Science, Sanofi, Bridgewater, NJ, United States
– sequence: 9
  givenname: Luca
  surname: Marchetti
  fullname: Marchetti, Luca
  organization: Fondazione the Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy
– sequence: 10
  givenname: Rosario
  surname: Lombardo
  fullname: Lombardo, Rosario
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  givenname: Selva Rupa Christinal
  surname: Immanuel
  fullname: Immanuel, Selva Rupa Christinal
  organization: Institute for Systems Biology, Seattle, WA, United States
– sequence: 13
  givenname: Nitin S
  surname: Baliga
  fullname: Baliga, Nitin S
  organization: Institute for Systems Biology, Seattle, WA, United States
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Copyright Copyright © 2021 Azer, Kaddi, Barrett, Bai, McQuade, Merrill, Piccoli, Neves-Zaph, Marchetti, Lombardo, Parolo, Immanuel and Baliga.
Copyright © 2021 Azer, Kaddi, Barrett, Bai, McQuade, Merrill, Piccoli, Neves-Zaph, Marchetti, Lombardo, Parolo, Immanuel and Baliga. 2021 Azer, Kaddi, Barrett, Bai, McQuade, Merrill, Piccoli, Neves-Zaph, Marchetti, Lombardo, Parolo, Immanuel and Baliga
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Keywords computational biology
systems biology
data science
bioinformatics
drug development
systems pharmacology
QSP modeling
Language English
License Copyright © 2021 Azer, Kaddi, Barrett, Bai, McQuade, Merrill, Piccoli, Neves-Zaph, Marchetti, Lombardo, Parolo, Immanuel and Baliga.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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Edited by: Yoram Vodovotz, University of Pittsburgh, United States
This article was submitted to Systems Biology, a section of the journal Frontiers in Physiology
Reviewed by: Hugo Geerts, In Silico Biosciences, United States; Tarek A. Leil, Bristol Myers Squibb, United States; Ioannis P. Androulakis, Rutgers, The State University of New Jersey, United States
Nathaniel J. Merril, Pacific Northwest National Laboratory, Computational Biology Group, Richland, WA, United States
Present address: Chanchala D. Kaddi,Translational Disease Modeling, Data and Data Science, Sanofi, Cambridge, MA, United States
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computational biology
data science
Physiology
QSP modeling
systems biology
systems pharmacology
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Title History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications
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