title: PopED lite: An optimal design software for preclinical pharmacokinetic and pharmacodynamic studies.
abstract: OBJECTIVE
  Optimal experimental design approaches are seldom used in preclinical drug discovery. The objective is to develop an optimal design software tool specifically designed for preclinical applications in order to increase the efficiency of drug discovery in vivo studies.
  
  
  METHODS
  Several realistic experimental design case studies were collected and many preclinical experimental teams were consulted to determine the design goal of the software tool. The tool obtains an optimized experimental design by solving a constrained optimization problem, where each experimental design is evaluated using some function of the Fisher Information Matrix. The software was implemented in C++ using the Qt framework to assure a responsive user-software interaction through a rich graphical user interface, and at the same time, achieving the desired computational speed. In addition, a discrete global optimization algorithm was developed and implemented.
  
  
  RESULTS
  The software design goals were simplicity, speed and intuition. Based on these design goals, we have developed the publicly available software PopED lite (http://www.bluetree.me/PopED_lite). Optimization computation was on average, over 14 test problems, 30 times faster in PopED lite compared to an already existing optimal design software tool. PopED lite is now used in real drug discovery projects and a few of these case studies are presented in this paper.
  
  
  CONCLUSIONS
  PopED lite is designed to be simple, fast and intuitive. Simple, to give many users access to basic optimal design calculations. Fast, to fit a short design-execution cycle and allow interactive experimental design (test one design, discuss proposed design, test another design, etc). Intuitive, so that the input to and output from the software tool can easily be understood by users without knowledge of the theory of optimal design. In this way, PopED lite is highly useful in practice and complements existing tools.
authors.affiliation: Pharmacometrics Research Group, Dept. Pharmaceutical Biosciences, Uppsala University, Box 591, SE-751 24 Uppsala, Sweden. Electronic address: yaoki@uwaterloo.ca.
authors.forename: Yasunori
authors.initials: Y
authors.lastname: Aoki
authors.affiliation: Cardiovascular and Metabolic Diseases, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Pepparedsleden 1, Mölndal 431 83, Sweden.
authors.forename: Monika
authors.initials: M
authors.lastname: Sundqvist
authors.affiliation: Pharmacometrics Research Group, Dept. Pharmaceutical Biosciences, Uppsala University, Box 591, SE-751 24 Uppsala, Sweden.
authors.forename: Andrew C
authors.initials: AC
authors.lastname: Hooker
authors.affiliation: Cardiovascular and Metabolic Diseases, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Pepparedsleden 1, Mölndal 431 83, Sweden.
authors.forename: Peter
authors.initials: P
authors.lastname: Gennemark
mesh_terms: D055808:Drug Discovery; D010600:Pharmacology; D012984:Software
keywords: Model-based drug discovery; Optimal experimental design; preclinical drug discovery