BACKGROUND: With the advent of targeted therapies, biomarkers provide a 
promising means of individualizing therapy through an integrated approach to 
prediction using the genetic makeup of the disease and the genotype of the 
patient. Biomarker validation has therefore become a central topic of discussion 
in the field of medicine, primarily due to the changing landscape of therapies 
for treatment of a disease and these therapies purported mechanism(s) of action.
PURPOSE: In this report, we discuss the merits and limitations of some of the 
clinical trial designs for predictive biomarker validation using examples from 
ongoing or completed clinical trials.
METHODS: The designs are broadly classified as retrospective (i.e., using data 
from previously well-conducted randomized controlled trials (RCT)) versus 
prospective (enrichment or targeted, unselected or all-comers, hybrid, and 
adaptive analysis). We discuss some of these designs in the context of real 
trials.
RESULTS: Well-designed retrospective analysis of prospective RCT can bring 
forward effective treatments to marker defined subgroup of patients in a timely 
manner. An example is the KRAS gene status in colorectal cancer - the benefit 
from cetuximab and panitumumab was demonstrated to be restricted to patients 
with wild type status based on prospectively specified analyses using data from 
previously conducted RCTs. Prospective enrichment designs are appropriate when 
compelling preliminary evidence suggests that not all patients will benefit from 
the study treatment under consideration; however, this may sometimes leave 
questions unanswered. An example is the established benefit of trastuzumab as 
adjuvant therapy for breast cancer; a clear definition of HER2-positivity and 
the assay reproducibility have, however, remained unanswered. An all-comers 
design is optimal where preliminary evidence regarding treatment benefit and 
assay reproducibility is uncertain (e.g., EGFR expression and tyrosine kinase 
inhibitors in lung cancer), or to identify the most effective therapy from a 
panel of regimens (e.g., chemotherapy options in breast cancer).
LIMITATIONS: The designs discussed here rest on the assumption that the 
technical feasibility, assay performance metrics, and the logistics of specimen 
collection are well established and that initial results demonstrate promise 
with regard to the predictive ability of the marker(s).
CONCLUSIONS: The choice of a clinical trial design is driven by a combination of 
scientific, clinical, statistical, and ethical considerations. There is no one 
size fits all solution to predictive biomarker validation.