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PopED lite: an optimal design software for preclinical pharmacokinetic and pharmacodynamic studies
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Applied Mathematics and Statistics. (Pharmacometrics Group)ORCID iD: 0000-0002-5881-2023
AstraZeneca R&D. (CVMD iMed DMPK)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics Group)ORCID iD: 0000-0002-2676-5912
AstraZeneca R&D. (CVMD iMed DMPK)
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Optimal experimental design approaches are seldom used in pre-clinical drug discovery. Main reasons for this lack of use are that available software tools require relatively high insight in optimal design theory, and that the design-execution cycle of in vivo experiments is short, making time-consuming optimizations infeasible. We present the publicly available software PopED lite in order to increase the use of optimal design in pre-clinical drug discovery. PopED lite is designed to be simple, fast and intuitive. Simple, to give many users access to basic optimal design calculations. Fast, to fit the 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 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. Key functionality of PopED lite is demonstrated by three case studies from real drug discovery projects. 

Keyword [en]
optimal experimental design, pre-clinical drug discovery, model-based drug discovery
National Category
Pharmaceutical Sciences Computational Mathematics
Research subject
Mathematics with specialization in Applied Mathematics; Pharmaceutical Science
URN: urn:nbn:se:uu:diva-253304OAI: oai:DiVA.org:uu-253304DiVA: diva2:814092
Available from: 2015-05-26 Created: 2015-05-26 Last updated: 2015-05-26Bibliographically approved

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Aoki, YasunoriHooker, Andrew C.
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