Biomarker Testing Gaps and How HCP Media Can Help Close Them

For a targeted therapy, the patient who never gets tested is invisible to the brand. They do not show up as a lost prescription or a competitive switch. They just never enter the market. Published studies in non-small cell lung cancer and several other tumor types have reported that a meaningful share of eligible patients do not receive recommended biomarker testing before first-line treatment, though the size of the gap varies by study, setting, and year. Check the current literature for your indication rather than borrowing a figure from another one.

This article is part of the series on diagnostic data in precision medicine launches.

Why eligible patients go untested

The gap is rarely one thing. The usual leaks, roughly in the order a sample moves:

1. Test not ordered. The physician does not order, assumes someone else will, or does not know the marker is now actionable.
2. Test too narrow. A single-gene test is ordered when a panel or comprehensive profiling would cover more actionable markers, including yours.
3. Tissue problems. The biopsy sample is too small or used up by earlier tests.
4. Turnaround. Results arrive after the physician feels pressure to start treatment.
5. Result not seen. The report lands somewhere the treating physician does not routinely check.
6. Coverage and cost. Uncertainty about reimbursement delays or prevents ordering.

Media can do something about the first, second, fourth, and fifth. It can do much less about tissue handling or reimbursement, which need field, medical, and market access work.

Diagnose the gap before you plan media

Diagnostic data shows where the gap is. HCP-level testing data, joined to your target list, can separate high-opportunity physicians who test well from those who do not, and can show test type mix by account. That is the input for tiering HCPs by testing behavior. Before acting on it, check coverage: an account with an in-house lab that the data does not see will look like a gap when it is not. See how to judge the accuracy of diagnostic data.

HCP education that actually changes testing

Testing education is usually unbranded disease education and goes through MLR like everything else. A few principles from the media side:

• Be specific about the action. "Test all eligible patients at diagnosis with a panel that includes [marker]" is more useful than "know your biomarkers."
• Address the timing objection. Physicians start treatment early when they worry about delay. Messaging on turnaround and on what to do while waiting speaks to the real concern.
• Point to guidelines rather than making the brand the authority.
• Keep the branded and unbranded tracks separate in creative, landing pages, and placement, and follow your regulatory team's rules on how they connect.

Pathology and lab audiences

Pathologists and lab professionals decide a lot of what happens to a sample: reflex testing, tissue triage, which tests run first. They are rarely on a prescriber target list because they do not prescribe. For a biomarker-gated brand, they belong in a separate audience with separate messaging focused on testing workflow, not treatment.

Build this audience by specialty and taxonomy, which is messier than it sounds; handling HCP specialty ambiguity covers the issues. Expect small reach. Pathology lists are short, and endemic channels may reach them better than broad programmatic. Keep frequency sensible; reach expectations by specialty size helps set targets.

Some teams also reach oncology care coordinators (often nurses) and tumor board staff. These roles often lack NPIs or have taxonomy codes that do not reflect their function, so plan them through account-level or field-led programs.

Measuring testing uplift

If the goal is more testing, measure testing. The design:

1. Define the eligible HCP population and the testing metric (tests per period, or share of tests that are panels).
2. Randomly hold out a share of HCPs from the education campaign before it starts.
3. Check pre-period balance on testing rate, specialty, setting, and lab coverage.
4. Run the campaign for a defined window that accounts for data latency.
5. Compare the change in testing between exposed and holdout groups.

Illustrative example (hypothetical): exposed HCPs average 4.0 tests per quarter before the campaign and 4.6 after; holdout HCPs move from 4.0 to 4.2. The estimated uplift is 0.6 minus 0.2, or 0.4 tests per HCP per quarter, a 10 percent increase on the 4.0 baseline. Whether that is meaningful depends on the size of the list and the positivity rate for your marker. Holdout test design for pharma media covers sizing and pitfalls.

Practical takeaway

Before writing any testing education creative, pull the five gap types in the table above for your top accounts and label each account with its main one. Then assign media only to accounts where the main gap is ordering, test choice, turnaround, or result visibility, and route the rest to field and medical.

Editorial note. Analysis and frameworks are the author's own and do not represent Acxiom or any current or former employer, client, or named platform. Examples labeled hypothetical or illustrative are not results from real campaigns. Nothing here is legal, regulatory, or medical advice.