Avid Bioservices Inc (CDMO)

[biopharm]

Biomarkers, PS Targeting hedge funds to John Springs Stafford to Sard Verbinnen

Sometimes ....one can't control everything but ask oneself this, those that spend time on a company that likely is positioning itself for paradigm shifts across Big Pharma as we now know it....either want PS Targeting to advance or they will lose out in other ways and want it delayed as long as possible

Sard Verbinnen was brought on board for a reason

John Springs Stafford was brought on board for reasons as well

Nothing happens for no reason and Biomarkers are here for good

The following from the FDA and how quickly things change once scientifically proven Biomarkers rise up and lead the way that some in Big Pharma will not like

Data used to establish the relationship between a biomarker and an outcome of interest, to
support biomarker qualification, can come from a variety of sources including the following:

Randomized controlled trial Single-arm/historical control trial Cohort study
Case-control study (including nested) Cross-sectional study
Case series or case reports Registry information Meta-analysis
Contains Nonbinding Recommendations

- Randomized controlled trial
- Single-arm/historical control trial - - Cohort study
- Case-control study (including nested)
- Cross-sectional study
- Case series or case reports
- Registry information
- Meta-analysis

The strongest level of evidence to support the association of a biomarker with an outcome of interest comes from prospective studies that are specifically designed and powered to assess the association. In many settings, however, data from studies conducted for other purposes are used to support biomarker qualification. Ultimately, the COU, with its associated potential benefits and risks, determines what types of data may be acceptable to support qualification; clinical trial
data is not critical for all COUs. Regardless of the data sources proposed to support the biomarkerâ??s COU, biomarker developers should consider the potential methodological limitations that could lead to overestimation of any actual associations, including lack of proper control for bias, confounding, and multiplicity, and address these limitations in their analysis plan. Verification of the results with an independent data source increases the credibility of the results.