Journal article
Individualizing drug dosage by using a random intercept linear model
Statistics in medicine, v 26(9), pp 2052-2073
30 Apr 2007
PMID: 16847902
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
An algorithm for drug dosage individualization is proposed. The algorithm assumes a random intercept linear model for the log of trough-plasma-concentration-to-dosage ratio of the drug at steady-state, and aims at determining an optimum dosage for producing a trough steady-state plasma concentration within a target concentration range. The minimum number of algorithm steps necessary to find the optimum dosage is computed. Computations are illustrated for clozapine, an antipsychotic drug used to treat patients with severe schizophrenia.
Metrics
Details
- Title
- Individualizing drug dosage by using a random intercept linear model
- Creators
- Francisco J Diaz - Universidad Nacional de ColombiaTulia E Rivera - Industrial University of SantanderRichard C Josiassen - University of PennsylvaniaJose de Leon - Eastern State Hospital
- Publication Details
- Statistics in medicine, v 26(9), pp 2052-2073
- Publisher
- Wiley
- Grant note
- MH-47162 / NIMH NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychiatry
- Web of Science ID
- WOS:000245479600010
- Scopus ID
- 2-s2.0-34047223028
- Other Identifier
- 991021890008704721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Mathematical & Computational Biology
- Medical Informatics
- Medicine, Research & Experimental
- Public, Environmental & Occupational Health
- Statistics & Probability