SELECTING BETTER GENERIC DRUGS

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SELECTING BETTER GENERIC DRUGS

フォーマット:
雑誌論文
Kyushu Univ. Production 九州大学成果文献
責任表示:
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)

全て表示
本文言語:
英語
出版情報:
Bulletin of informatics and cybernetics. 46, pp. 53-70, 2014-12. 統計科学研究会
バージョン:
Publisher
概要:
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. 続きを見る
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