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Application of Scaling Factors in Simultaneous Modeling of Microarray Data from Diverse Chips

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Abstract

Purpose

Microarrays have been utilized in many biological, physiological and pharmacological studies as a high-throughput genomic technique. Several generations of Affymetrix GeneChip® microarrays are widely used in gene expression studies. However, differences in intensities of signals for different probe sets that represent the same gene on various types of Affymetrix chips make comparison of datasets complicated.

Materials and Methods

A power coefficient scaling factor was applied in the pharmacokinetic/pharmacodynamic (PK/PD) modeling to account for differences in probe set sensitivities (i.e., signal intensities). Microarray data from muscle and liver following methylprednisolone 50 mg/kg i.v. bolus and 0.3 mg/kg/h infusion regimens were taken as an exemplar.

Results

The scaling factor applied to the pharmacodynamic output function was used to solve the problem of intensity differences between probe sets. This approach yielded consistent pharmacodynamic parameters for the applied models.

Conclusions

Modeling of pharmacodynamic/pharmacogenomic (PD/PG) data from diverse chips should be performed with caution due to differential probe set intensities. In such circumstances, a power scaling factor can be applied in the modeling.

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Abbreviations

ADX:

adrenalectomized

BS:

biosignal

CS:

corticosteroids

CV:

coefficient of variation

DR(N):

nucleus drug-receptor complex

GR:

glucocorticoid receptor

GRE:

glucocorticoid response element

MPL:

methylprednisolone

PD:

pharmacodynamics

PG:

pharmacogenomics

PK:

pharmacokinetics

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Acknowledgments

We would like to acknowledge Ms Nancy Pyszczynski for the conduct of animal studies. This work was supported by grants GM24211 and GM67650 from the National Institute of General Medical Sciences, National Institutes of Health, in part by grant R24HD050846 from NICHD National Center for Medical Rehabilitation Research and a research grant from NASA.

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Authors and Affiliations

  1. Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, 565 Hochstetter Hall, Buffalo, New York, 14260, USA

    Zhenling Yao, Baiteng Zhao, Debra C. DuBois,  Richard R. Almon & William J. Jusko

  2. Department of Biological Sciences, State University of New York at Buffalo, Buffalo, New York, USA

    Debra C. DuBois &  Richard R. Almon

  3. Children’s National Medical Center, Washington District of Columbia, USA

    Eric P. Hoffman & Svetlana Ghimbovschi

Authors
  1. Zhenling Yao
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  2. Baiteng Zhao
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  3. Eric P. Hoffman
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  4. Svetlana Ghimbovschi
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  5. Debra C. DuBois
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  6. Richard R. Almon
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  7. William J. Jusko
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Corresponding author

Correspondence to William J. Jusko.

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Yao, Z., Zhao, B., Hoffman, E.P. et al. Application of Scaling Factors in Simultaneous Modeling of Microarray Data from Diverse Chips. Pharm Res 24, 643–649 (2007). https://doi.org/10.1007/s11095-006-9215-y

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  • DOI: https://doi.org/10.1007/s11095-006-9215-y

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