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Literature DB >> 29396780

Structural identifiability for mathematical pharmacology: models of myelosuppression.

Neil D Evans¹, S Y Amy Cheung², James W T Yates³.

Abstract

Structural identifiability is an often overlooked, but essential, prerequisite to the experiment design stage. The application of structural identifiability analysis to models of myelosuppression is used to demonstrate the importance of its considerations. It is shown that, under certain assumptions, these models are structurally identifiable and so drug and system specific parameters can truly be separated. Further it is shown via a meta-analysis of the literature that because of this the reported system parameter estimates for the "Friberg" or "Uppsala" model are consistent in the literature.

Entities: Disease

Keywords: Mathematical pharmacology; Myelosuppression; Structural identifiability; System parameters

Mesh：

Substances：

Year: 2018 PMID： 29396780 DOI： 10.1007/s10928-018-9569-x

Source DB: PubMed Journal: J Pharmacokinet Pharmacodyn ISSN： 1567-567X Impact factor: 2.745

23 in total

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Authors: Lena E Friberg; Anja Henningsson; Hugo Maas; Laurent Nguyen; Mats O Karlsson
Journal: J Clin Oncol Date: 2002-12-15 Impact factor: 44.544

2. Deterministic identifiability of population pharmacokinetic and pharmacokinetic-pharmacodynamic models.

Authors: Vijay K Siripuram; Daniel F B Wright; Murray L Barclay; Stephen B Duffull
Journal: J Pharmacokinet Pharmacodyn Date: 2017-06-13 Impact factor: 2.745

3. Mechanism-based models for topotecan-induced neutropenia.

Authors: Frédéric Léger; Walter J Loos; Roland Bugat; Ron H J Mathijssen; Marine Goffinet; Jaap Verweij; Alex Sparreboom; Etienne Chatelut
Journal: Clin Pharmacol Ther Date: 2004-12 Impact factor: 6.875

4. The input-output relationship approach to structural identifiability analysis.

Authors: Daniel J Bearup; Neil D Evans; Michael J Chappell
Journal: Comput Methods Programs Biomed Date: 2012-12-08 Impact factor: 5.428

5. The design and analysis of parallel experiments to produce structurally identifiable models.

Authors: S Y Amy Cheung; James W T Yates; Leon Aarons
Journal: J Pharmacokinet Pharmacodyn Date: 2013-01-09 Impact factor: 2.745

6. Semimechanistic cell-cycle type-based pharmacokinetic/pharmacodynamic model of chemotherapy-induced neutropenic effects of diflomotecan under different dosing schedules.

Authors: Víctor Mangas-Sanjuan; Núria Buil-Bruna; María J Garrido; Elena Soto; Iñaki F Trocóniz
Journal: J Pharmacol Exp Ther Date: 2015-05-06 Impact factor: 4.030

7. Factors for hematopoietic toxicity of carboplatin: refining the targeting of carboplatin systemic exposure.

Authors: Antonin Schmitt; Laurence Gladieff; Céline M Laffont; Alexandre Evrard; Jean-Christophe Boyer; Amélie Lansiaux; Christine Bobin-Dubigeon; Marie-Christine Etienne-Grimaldi; Michèle Boisdron-Celle; Mireille Mousseau; Frédéric Pinguet; Anne Floquet; Eliane M Billaud; Catherine Durdux; Chantal Le Guellec; Julien Mazières; Thierry Lafont; Florent Ollivier; Didier Concordet; Etienne Chatelut
Journal: J Clin Oncol Date: 2010-09-20 Impact factor: 44.544

8. A population pharmacokinetic/pharmacodynamic model of thrombocytopenia characterizing the effect of trastuzumab emtansine (T-DM1) on platelet counts in patients with HER2-positive metastatic breast cancer.

Authors: Brendan C Bender; Franziska Schaedeli-Stark; Reinhold Koch; Amita Joshi; Yu-Waye Chu; Hope Rugo; Ian E Krop; Sandhya Girish; Lena E Friberg; Manish Gupta
Journal: Cancer Chemother Pharmacol Date: 2012-08-12 Impact factor: 3.333

9. Good Practices in Model-Informed Drug Discovery and Development: Practice, Application, and Documentation.

Authors: S F Marshall; R Burghaus; V Cosson; S Y A Cheung; M Chenel; O DellaPasqua; N Frey; B Hamrén; L Harnisch; F Ivanow; T Kerbusch; J Lippert; P A Milligan; S Rohou; A Staab; J L Steimer; C Tornøe; S A G Visser
Journal: CPT Pharmacometrics Syst Pharmacol Date: 2016-03-14

10. A review of mixed-effects models of tumor growth and effects of anticancer drug treatment used in population analysis.

Authors: B Ribba; N H Holford; P Magni; I Trocóniz; I Gueorguieva; P Girard; C Sarr; M Elishmereni; C Kloft; L E Friberg
Journal: CPT Pharmacometrics Syst Pharmacol Date: 2014-05-07

4 in total

4. Analysis of cellular kinetic models suggest that physiologically based model parameters may be inherently, practically unidentifiable.

Authors: Liam V Brown; Mark C Coles; Mark McConnell; Alexander V Ratushny; Eamonn A Gaffney
Journal: J Pharmacokinet Pharmacodyn Date: 2022-08-06 Impact factor: 2.410