Target Selection: The Universal Challenge

A never-ending challenge for companies that develop IVDs, LDTs, and RUO products is identifying the most marketable biomarkers, both to guide sales and marketing strategies for existing products, and to guide investment in the development of new products.

Biomarkers being used in clinical trials provide some of the best opportunities for identifying marketable products. Clinical trials utilize biomarkers that are typically growing in

research use, and which also have the highest potential to provide utility in diagnostic, prognostic, or companion diagnostic applications. Clinical trials also consume a lot of tests themselves, and so are good sales opportunities in their own rights.

Most people I know at life science companies who are tasked with identifying biomarkers for sales and marketing and product development opportunities utilize clinical trial records to some extent, due to the easy access provided by ClinicalTrials.gov. But maximizing the complete dataset is challenging.

Clinical Trials Provide a Vast, But Challenging Landscape of Information

One of the biggest challenges is that you have to already have an idea of what you are looking for at CT.gov. Biomarkers are not indexed, so building lists by filtering biomarkers for relevant criteria isn’t possible.

If you know the target you are interested in, you can find trials that are using it. But if you want to take an unbiased approach to target selection, and identify opportunities based on increase in use for example, that isn’t possible. There’s also no ability to compare clinical trial data with other sources that can inform a biomarker’s potential, such as publication rates, test approvals, and drug label inclusions.

And of course there’s no ability to look at trends related to specific biomarkers and to conduct other quantitative analyses, so even if you know what you are looking for, any analysis is going to take place in a spreadsheet with a (hopefully complete) download from CT.gov.

There are services that provide better looks into trial data (TrialTrove, Cortellis Clinical Trial Intelligence), but they don’t go deep by identifying the specific biomarkers being used in each trial, and by linking them to other types of information that describe their clinical use (inclusion in an IVD for example).

Current State of the Art: BiomarkerBase

We have held back from talking too specifically in this blog about what our knowledge base, BiomarkerBase, currently contains and what is under development, because we want the focus in this blog to be on analyses and news that really add value for biomarker stakeholders.

For the topic at-hand it seems timely to share a bit more, however, because we are now at a point with the database where we can significantly increase a user’s ability to maintain strategic awareness of the complete clinical biomarker landscape.

BiomarkerBase includes every biomarker in an FDA-cleared or approved test; every biomarker in the label of an FDA-approved drug; and thousands of biomarkers being used in recent late-stage clinical trials. All of these biomarkers were gathered manually, using record-by-record review of thousands of FDA and NIH documents. The result is a core collection of the most well-validated biomarkers in use today, which is the set of biomarkers for which any biomarker stakeholder should want complete strategic awareness.

This core collection of biomarkers, especially those in clinical trials (the bulk), is being used to guide the completion of an automated data gathering tool. The goal of this tool is to pull into BiomarkerBase every biomarker that has ever been disclosed in a clinical trial, and the results of the biomarker’s use, wherever posted.

We are also going to be adding biomarkers in lab-developed tests, biomarkers in CE-marked tests, and comprehensive information about commercial aspects of biomarker use, such as partnering and licensing arrangements. All of this information will also soon be filterable and viewable based any number of criteria, making it very easy to create highly refined lists of biomarker opportunities for very specific needs.

If you are interested in having beta access to our data and analytical tools as they are developing, please contact me directly to join our early access group.