School of Engineering, University of Warwick, Coventry, CV4 7AL, UK.
Innovative Medicines and Early Development, AstraZeneca, Cambridge, UK.
J Pharmacokinet Pharmacodyn. 2018 Feb;45(1):79-90. doi: 10.1007/s10928-018-9569-x. Epub 2018 Feb 2.
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.
结构可识别性是实验设计阶段经常被忽视但又是必不可少的前提条件。将结构可识别性分析应用于骨髓抑制模型，以证明其考虑的重要性。结果表明，在某些假设下，这些模型是结构可识别的，因此可以真正分离药物和系统特定参数。进一步通过对文献的荟萃分析表明，由于这一点，文献中报告的“Friberg”或“Uppsala”模型的系统参数估计值是一致的。
