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Fifty-Eight Years and Counting: High-Impact Publishing in Computational Pharmaceutical Sciences and Mechanism-Based Modeling

  • Gregory E. Amidon
  • , Bradley D. Anderson
  • , Joseph P. Balthasar
  • , Christel A.S. Bergstrom
  • , Shiew Mei Huang
  • , Gerald Kasting
  • , Filippos Kesisoglou
  • , Johannes G. Khinast
  • , Donald E. Mager
  • , Christopher J. Roberts
  • , Lian Yu
  • University of Michigan, Ann Arbor
  • University of Kentucky
  • Uppsala University
  • United States Food and Drug Administration
  • University of Cincinnati
  • Merck
  • Graz University of Technology
  • University of Delaware
  • University of Wisconsin-Madison

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

With this issue of the Journal of Pharmaceutical Sciences, we celebrate the nearly 6 decades of contributions to mechanistic-based modeling and computational pharmaceutical sciences. Along with its predecessor, The Journal of the American Pharmaceutical Association: Scientific Edition first published in 1911, JPharmSci has been a leader in the advancement of pharmaceutical sciences beginning with its inaugural edition in 1961. As one of the first scientific journals focusing on pharmaceutical sciences, JPharmSci has established a reputation for publishing high-quality research articles using computational methods and mechanism-based modeling. The journal's publication record is remarkable. With over 15,000 articles, 3000 notes, and more than 650 reviews from industry, academia, and regulatory agencies around the world, JPharmSci has truly been the leader in advancing pharmaceutical sciences.

Original languageEnglish
Pages (from-to)2-7
Number of pages6
JournalJournal of Pharmaceutical Sciences
Volume108
Issue number1
DOIs
StatePublished - Jan 2019

Keywords

  • absorption, distribution, metabolism, and excretion (ADME)
  • biophysical model(s)
  • in silico modeling
  • in vitro model(s)
  • mathematical model(s)
  • mechanistic modeling
  • molecular modeling
  • pharmacokinetic-pharmacodynamic (PKPD) modeling
  • physiologically based pharmacokinetic (PBPK) modeling

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