Methodologies in Biosimilar Product Development Methodologies in Biosimilar Product Development
Chapman & Hall/CRC Biostatistics Series

Methodologies in Biosimilar Product Development

    • CHF 52.00
    • CHF 52.00

Beschreibung des Verlags

Methodologies for Biosimilar Product Development covers the practical and challenging issues that are commonly encountered during the development, review, and approval of a proposed biosimilar product. These practical and challenging issues include, but are not limited to the mix-up use of interval hypotheses testing (i.e., the use of TOST) and confidence interval approach, a risk/benefit assessment for non-inferiority/similarity margin, PK/PD bridging studies with multiple references, the detection of possible reference product change over time, design and analysis of biosimilar switching studies, the assessment of sensitivity index for assessment of extrapolation across indications without collecting data from those indications not under study, and the feasibility and validation of non-medical switch post-approval.

Key Features:
Reviews withdrawn draft guidance on analytical similarity assessment. Evaluates various methods for analytical similarity evaluation based on FDA’s current guidelines. Provides a general approach for the use of n-of-1 trial design for assessment of interchangeability. Discusses the feasibility and validity of the non-medical switch studies. Provides innovative thinking for detection of possible reference product change over time.
This book embraces innovative thinking of design and analysis for biosimilar studies, which are required for review and approval of biosimilar regulatory submissions.

GENRE
Wissenschaft und Natur
ERSCHIENEN
2021
30. September
SPRACHE
EN
Englisch
UMFANG
392
Seiten
VERLAG
CRC Press
GRÖSSE
11.6
 MB
Mathematical and Statistical Skills in the Biopharmaceutical Industry Mathematical and Statistical Skills in the Biopharmaceutical Industry
2019
Clinical Trial Optimization Using R Clinical Trial Optimization Using R
2017
Advanced Statistical Analytics for Health Data Science with SAS and R Advanced Statistical Analytics for Health Data Science with SAS and R
2025
R for Health Technology Assessment R for Health Technology Assessment
2025
Design and Analysis of Clinical Trials with Time-to-Event Endpoints Design and Analysis of Clinical Trials with Time-to-Event Endpoints
2009
Generalized Linear Models Generalized Linear Models
2000