The best biomarker strategy isn't always the most sophisticated one.

When your biomarker is present in 90%+ of patients, should you still develop a companion diagnostic?

The answer isn't as obvious as you'd think.

Take KRAS mutations in pancreatic cancer (95% prevalence), TP53 in ovarian cancer (96%), or APC in colorectal cancer (80-90%).

These mutations are practically universal—so why test at all?

Here's the problem most teams miss:

Even gold-standard assays have false negative rates of 5-10%. When your "negative" population is tiny, false negatives can represent a huge chunk of patients who'd actually benefit from treatment.

If 5% of PDAC patients are truly KRAS wild-type, but your assay has a 5% false negative rate, you're potentially excluding as many false negatives as true negatives from therapy.

The operational reality makes it worse:
→ Some patients can't get adequate biopsies
→ Others can't afford the test
→ Tissue may be insufficient for analysis
→ Turnaround time delays treatment

Suddenly, your 95% prevalence biomarker is excluding 15-20% of patients who could benefit.

The strategic question becomes: Does the modest enrichment justify the access barriers you're creating?

Sometimes the answer is still yes—regulatory agencies love precision.

But smart teams are exploring alternatives: lower-cost screening approaches, tissue-agnostic strategies, or simply treating the broad population when prevalence is this high.

📌 The best biomarker strategy isn't always the most sophisticated one.

Is your team weighing biological precision against real-world access?