Some thoughts on the QR method for analytical similarity evaluation.

Son, Sungtaek; Oh, Minkyung; Choo, Minjoo; Chow, Shein-Chung; Lee, Sang Joon

Son, Sungtaek; Oh, Minkyung; Choo, Minjoo; Chow, Shein-Chung; Lee, Sang Joon.

Affiliation

Son S; Clinical Development Division, Celltrion, Inc, Incheon, Republic of Korea.
Oh M; Clinical Development Division, Celltrion, Inc, Incheon, Republic of Korea.
Choo M; Clinical Development Division, Celltrion, Inc, Incheon, Republic of Korea.
Chow SC; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
Lee SJ; Clinical Development Division, Celltrion, Inc, Incheon, Republic of Korea.

J Biopharm Stat ; 30(3): 521-536, 2020 05 03.

Article in En | MEDLINE | ID: mdl-32089068

Subject(s)

Biosimilar Pharmaceuticals/standards; Computer Simulation/statistics & numerical data; Computer Simulation/standards; Drug Approval/statistics & numerical data; United States Food and Drug Administration/statistics & numerical data; United States Food and Drug Administration/standards; Biosimilar Pharmaceuticals/therapeutic use; Drug Approval/methods; Humans; Monte Carlo Method; United States

Key words

Comparative analytical assessment; false positive rate; mQR Method; quality control; reference product change

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: United States Food and Drug Administration / Computer Simulation / Drug Approval / Biosimilar Pharmaceuticals Type of study: Clinical_trials / Guideline / Health_economic_evaluation / Prognostic_studies Limits: Humans Country/Region as subject: America do norte Language: En Journal: J Biopharm Stat Journal subject: FARMACOLOGIA Year: 2020 Type: Article

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