Following our Trilogy on Alignment in Digital Health
In our trilogy on alignment, we argued that misalignment slows innovation. But what does that actually cost?
The evidence is increasingly measurable.
In tissue agnostic oncology indications, the mean delay between drug approval and corresponding companion diagnostic approval was 707 days, affecting eight of nine approvals studied (Jørgensen, 2025[i]). Without the corresponding diagnostic, identifying the patients for whom a therapy is intended becomes more difficult.
Next, we see that the problem continues into deployment. For example, in the PD-L1 landscape, fragmented co-development produced four approved assays across incompatible platforms and scoring systems. Only three of the top 20 U.S. oncology laboratories offered all four (Oliner et al., 2025[ii]). A biomarker-guided therapy is only as accessible as the testing available to the patient.
Good news: there is evidence that earlier alignment can change these timelines. FDA[iii] reported that the FDA-CMS Parallel Review[iv] allows regulatory and reimbursement evidence to be considered concurrently. Coverage decisions followed FDA approval by under two months for Cologuard® and approximately 3.5 months for FoundationOne® CDx, compared with a 17 month median approval to coverage interval reported for novel medical products generally (Roginiel et al., 2018[v]).
These are individual examples. However, they illustrate how differences in timing, evidence requirements, and decision frameworks can contribute to downstream delays. They demonstrate what concurrent evidence development and review can make possible. However, despite 97 formal requests through December 2024, only two products had completed Parallel Review as of the time we accessed the FDA website, which indicated the information was current as of June 2026.
Reimbursement creates another constraint. Whole slide imaging Category III CPT codes were introduced in 2023 to track adoption ahead of national payment. More than three years later, the original codes remain temporary, while new add on codes have been added.
While these examples arise at different points in the lifecycle, they suggest a common pattern. Regulatory review, coverage, implementation, and evidence generation are frequently optimized within individual domains but not across domains. As a result, delays and inefficiencies can emerge even when each stakeholder is operating effectively within its own decision framework.
Above examples demonstrate that the cost of misalignment can be observed and measured. If those costs are measurable, the next step is to have the alignment itself be designed, evaluated, and improved with the same rigor.
This is what Evidence Architecture describes: evidence generated across the lifecycle, structured to support the decisions required to move innovation from development to patient access.
Misalignment has a measurable cost. How long are we prepared to continue paying that cost, which is not only financial.
[i] Jørgensen JT. An analysis of FDA drug approvals for oncological hematological malignancies in relation to companion diagnostics. Front Oncol. 2025
[ii] Oliner K.S., et al. Challenges to Innovation Arising from Current Companion Diagnostic Regulations and Suggestions for Improvements. Clinical Cancer Research. 2025
[iii] Accessed August 16, 2026
[iv] Accessed August 16, 2026
[v] Roginiel AC, Dhruva SS, Ross JS. Evidence supporting FDA approval and CMS national coverage determinations for novel medical products, 2005 through 2016: A cross-sectional study. Medicine. 2018