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Activity Number:
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185
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Type:
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Contributed
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Date/Time:
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Tuesday, August 13, 2002 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section*
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| Abstract - #300560 |
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Title:
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A Functional Linear Model For Comparing Two Pharmacokinetics Profiles
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Author(s):
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Jason Liao*+
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Affiliation(s):
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Merck Research Laboratories
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Address:
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WP37C-305, 770 Sumneytown Pike, West Point, Pennsylvania, 19486,
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Keywords:
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Profile ; Functional linear model ; Error-in-variable ; Kernel estimate ; Mean squared error (MSE)
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Abstract:
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In a traditional pharmacokinetics (PK) study, compartmental models or non-compartmental models are often used to make indirect inferences on some PK parameters such as area under the plasma concentration curve (AUC), maximum plasma concentration ($C_{max}$), time to maximum plasma concentration ($T_{max}$) and half-life. The assumptions about compartmental models are sometimes not attainable or very difficult to validate. The indirect inferences on some PK parameters are sometimes not good enough. In this paper, a functional linear model is proposed to compare PK profiles directly instead of the PK parameters. The model does not make any parametric assumptions about compartments. The model undertaken is general and allows the number of observations as well as the administration and measuring time to be different for experiment unit. The usefulness of the proposed model is demonstrated by a real data set from a PK study.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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