
Perspectives on statistical strategies for the regulatory biomarker qualification process
Author(s) -
Suzanne Hendrix,
Robin Mogg,
Sue Jane Wang,
Aloka Chakravarty,
Klaus Romero,
Samuel P. Dickson,
JohnMichael Sauer,
Lisa M. McShane
Publication year - 2021
Publication title -
biomarkers in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.652
H-Index - 44
eISSN - 1752-0371
pISSN - 1752-0363
DOI - 10.2217/bmm-2020-0523
Subject(s) - biomarker , context (archaeology) , process (computing) , parallels , risk analysis (engineering) , medicine , management science , data science , computer science , engineering , operations management , paleontology , biochemistry , chemistry , biology , operating system
Qualification of a biomarker for use in a medical product development program requires a statistical strategy that aligns available evidence with the proposed context of use (COU), identifies any data gaps to be filled and plans any additional research required to support the qualification. Accumulating, interpreting and analyzing available data is outlined, step-by-step, illustrated by a qualified enrichment biomarker example and a safety biomarker in the process of qualification. The detailed steps aid requestors seeking qualification of biomarkers, allowing them to organize the available evidence and identify potential gaps. This provides a statistical perspective for assessing evidence that parallels clinical considerations and is intended to guide the overall evaluation of evidentiary criteria to support a specific biomarker COU.