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Interface Focus. 2013 Apr 6;3(2):20120071. doi: 10.1098/rsfs.2012.0071.

Systems pharmacology of the nerve growth factor pathway: use of a systems biology model for the identification of key drug targets using sensitivity analysis and the integration of physiology and pharmacology.

Author information

1
Xenologiq Ltd, Unit 7 , Denne Hill Business Park, Canterbury CT4 6HD , UK ; Department of Pharmacokinetics, Dynamics and Metabolism , Pfizer Worldwide R&D , Boston, MA , USA.
2
Department of Pharmacokinetics, Dynamics and Metabolism , Pfizer Worldwide R&D , Boston, MA , USA ; Astellas , 21 Miyukigaoka, Tsukuba, Ibaraki 305-8585 , Japan.
3
Institute for Systems Biology SPb, Leninskie Gory 1/75G, Moscow 119992 , Russia.
4
Department of Pharmacokinetics, Dynamics and Metabolism , Pfizer Worldwide R&D , Boston, MA , USA.
5
Pharmatherapeutics Clinical Pharmacology, Pfizer Neusentis , The Portway Building, Granta Park, Cambridge CB21 6GS , UK ; Neusentis, Pfizer Global Clinical Pharmacology , The Portway Building, Granta Park, Cambridge CB21 6GS , UK.
6
Department of Pharmacokinetics, Dynamics and Metabolism , Pfizer Worldwide R&D , Boston, MA , USA ; Neusentis, Pfizer Global Clinical Pharmacology , The Portway Building, Granta Park, Cambridge CB21 6GS , UK ; Leiden Academic Centre for Drug Research (LACDR) , Leiden RA 2300 , The Netherlands.

Abstract

The nerve growth factor (NGF) pathway is of great interest as a potential source of drug targets, for example in the management of certain types of pain. However, selecting targets from this pathway either by intuition or by non-contextual measures is likely to be challenging. An alternative approach is to construct a mathematical model of the system and via sensitivity analysis rank order the targets in the known pathway, with respect to an endpoint such as the diphosphorylated extracellular signal-regulated kinase concentration in the nucleus. Using the published literature, a model was created and, via sensitivity analysis, it was concluded that, after NGF itself, tropomyosin receptor kinase A (TrkA) was one of the most sensitive druggable targets. This initial model was subsequently used to develop a further model incorporating physiological and pharmacological parameters. This allowed the exploration of the characteristics required for a successful hypothetical TrkA inhibitor. Using these systems models, we were able to identify candidates for the optimal drug targets in the known pathway. These conclusions were consistent with clinical and human genetic data. We also found that incorporating appropriate physiological context was essential to drawing accurate conclusions about important parameters such as the drug dose required to give pathway inhibition. Furthermore, the importance of the concentration of key reactants such as TrkA kinase means that appropriate contextual data are required before clear conclusions can be drawn. Such models could be of great utility in selecting optimal targets and in the clinical evaluation of novel drugs.

KEYWORDS:

nerve growth factor; systems biology; systems pharmacology; tropomyosin receptor kinase A

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