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CPT Pharmacometrics Syst Pharmacol. 2015 Sep;4(9):516-26. doi: 10.1002/psp4.12006. Epub 2015 Aug 22.

Application of a Systems Pharmacology-Based Placebo Population Model to Analyze Long-Term Data of Postmenopausal Osteoporosis.

Author information

1
Department of Medical Informatics, Erasmus Medical Centre Rotterdam, The Netherlands ; Leiden Academic Centre for Drug Research, Division of Pharmacology Leiden, The Netherlands.
2
Merck Sharp & Dohme Corp. Whitehouse Station, New Jersey, USA.
3
Department of Medical Informatics, Erasmus Medical Centre Rotterdam, The Netherlands.
4
Department of Epidemiology, Erasmus Medical Centre Rotterdam, The Netherlands ; Drug Safety Unit, The Health Care Inspectorate The Hague, The Netherlands.
5
Leiden Academic Centre for Drug Research, Division of Pharmacology Leiden, The Netherlands.
6
Leiden Experts on Advanced Pharmacokinetics and Pharmacodynamics (LAP&P) Leiden, The Netherlands.

Abstract

Osteoporosis is a progressive bone disease characterized by decreased bone mass resulting in increased fracture risk. The objective of this investigation was to test whether a recently developed disease systems analysis model for osteoporosis could describe disease progression in a placebo-treated population from the Early Postmenopausal Intervention Cohort (EPIC) study. First, we qualified the model using a subset from the placebo arm of the EPIC study of 222 women who had similar demographic characteristics as the 149 women from the placebo arm of the original population. Second, we applied the model to all 470 women. Bone mineral density (BMD) dynamics were changed to an indirect response model to describe lumbar spine and total hip BMD in this second population. This updated disease systems analysis placebo model describes the dynamics of all biomarkers in the corresponding datasets to a very good approximation; a good description of an individual placebo response will be valuable for evaluating treatments for osteoporosis.

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