Literature DB >> 8576844

Convergence of direct and indirect pharmacodynamic response models.

W J Jusko1, H C Ko, W F Ebling.   

Abstract

Mesh:

Year:  1995        PMID: 8576844     DOI: 10.1007/bf02353781

Source DB:  PubMed          Journal:  J Pharmacokinet Biopharm        ISSN: 0090-466X


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  6 in total

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2.  A general conceptual model for non-steady state pharmacokinetic/pharmacodynamic data.

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3.  Comparison of four basic models of indirect pharmacodynamic responses.

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4.  Physiologic indirect response models characterize diverse types of pharmacodynamic effects.

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5.  Inhibition of rat splenocyte proliferation with methylprednisolone: in vivo effect of liposomal formulation.

Authors:  E V Mishina; W J Jusko
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6.  Understanding pharmacokinetics and pharmacodynamics through computer stimulation: I. The comparative clinical profiles of fentanyl and alfentanil.

Authors:  W F Ebling; E N Lee; D R Stanski
Journal:  Anesthesiology       Date:  1990-04       Impact factor: 7.892

  6 in total
  27 in total

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Review 3.  Bringing Model-Based Prediction to Oncology Clinical Practice: A Review of Pharmacometrics Principles and Applications.

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4.  Collapsing mechanistic models: an application to dose selection for proof of concept of a selective irreversible antagonist.

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5.  Characterization of the dose-dependent time of peak effect in indirect response models.

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Journal:  J Pharmacokinet Biopharm       Date:  1998-04

Review 6.  Expanding clinical applications of population pharmacodynamic modelling.

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Journal:  Br J Clin Pharmacol       Date:  1998-10       Impact factor: 4.335

7.  The time of maximum effect for model selection in pharmacokinetic-pharmacodynamic analysis applied to frusemide.

Authors:  M Wakelkamp; G Alván; G Paintaud
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Review 8.  Characteristics of indirect pharmacodynamic models and applications to clinical drug responses.

Authors:  A Sharma; W J Jusko
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9.  Translational pharmacokinetic-pharmacodynamic modeling from nonclinical to clinical development: a case study of anticancer drug, crizotinib.

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Journal:  AAPS J       Date:  2012-12-19       Impact factor: 4.009

10.  Stochastic modeling of systems mapping in pharmacogenomics.

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