SELECTING BETTER GENERIC DRUGS

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SELECTING BETTER GENERIC DRUGS

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Article
Kyushu Univ. Production Kyushu Univ. Production
Responsibility:
Hayakawa, Masanobu(Graduate School of Medicine, Kurume University)
早川, 正信(久留米大学大学院医学研究科)
Yanagawa, Takashi(Biostatistics Center Kurume University)

柳川, 堯(久留米大学バイオ統計センター)
Jiang, Ying(Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health)
姜, 英(産業医科大学産業生態科学研究所)
Sakurai, Rieko(Graduate School of Medicine, Kurume University)
櫻井, 利恵子(久留米大学大学院医学研究科)

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Language:
English
Publication info:
Bulletin of informatics and cybernetics. 46, pp. 53-70, 2014-12. Research Association of Statistical Sciences
Version:
Publisher
Abstract:
Often, more than twenty generic (GE) drugs are developed for one brand name (B-N) drug. Each GE drug has passed the trial of bio-equivalence to the B-N drug, and its characteristics (which are generally expressed by AUC, Cmax, and Tmax, or one of its subsets) are close to the values for the B-N drug in each trial. However, trial-to-trial variation in the AUC, Cmax, and Tmax values is substantial. A model is developed in this paper to extract the distance between the characteristics of the GE and B-N drugs by adjusting for trial-to-trial variation. A method is proposed in this paper to use this distance for selecting better GE drugs from the list of candidates. Read more
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