The Diffusion Index
The Adoption Index
Eight precision medicine technologies, each placed on the Rogers adoption curve every year from the moment it appears in the literature. The placement is quantitative — derived from two signals in PubMed publication data — but calibrated against what we know to be true in the field.
Think of it as a Rogers-inspired scholarly diffusion and maturity proxy: it reads how a technology matures through the research literature and helps identify which are moving toward broader adoption. It is not a direct measure of market size or a forecast of commercial demand — scholarly diffusion leads real-world adoption, and the two can diverge.
Signal 1 — Growth momentum
The composite of 1-, 3-, and 5-year growth in annual paper count. Accelerating from a small base means a field is still pre-chasm; decelerating-but-positive means the majority is adopting; growth at or below the ambient rate of science (~4%/yr) means the field has matured into standard practice. This is a concurrent indicator — it tracks adoption as it happens.
Signal 2 — Novelty premium
The share of papers landing in the most competitive journals, normalized to each technology’s own peak. It is highest when only elite labs are publishing (Innovators) and collapses as the technique becomes routine. This is a leadingindicator — it falls years before the growth rate does, which is precisely what makes the gap between the two signals so informative.
Phase over time
Each row is a technology; each column a year. The color is the adoption phase that year.
| Technology | ’06 | ’07 | ’08 | ’09 | ’10 | ’11 | ’12 | ’13 | ’14 | ’15 | ’16 | ’17 | ’18 | ’19 | ’20 | ’21 | ’22 | ’23 | ’24 | ’25 | ’26 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| NGS | |||||||||||||||||||||
| scRNA-seq | |||||||||||||||||||||
| Spatial Tx | |||||||||||||||||||||
| Long-read | |||||||||||||||||||||
| Spatial Proteo | |||||||||||||||||||||
| cfDNA | |||||||||||||||||||||
| Multi-omics | |||||||||||||||||||||
| Hi-Plex M-O |
“Late Majority” and “Laggards” are Rogers’ terms for a saturated, standard-infrastructure stage — the remaining non-adopters in a now-ubiquitous technology, not a declining or failing one. NGS sits here precisely because it has become routine.
Faded cells = 2026 (partial year, annualized — provisional). Click any cell for detail.
Late Majority triggers when annual publication growth falls below 16% (≈4× the ambient growth rate of the scientific literature) for 2 of the last 3 years; Laggards below 4%. The chasm (Early → Early Majority) crosses when the top-journal novelty premium collapses below 30% of its peak, or when a field exceeds 750 papers/year.
Where each technology sits today
“Laggards” is the Rogers-curve term for the final, saturated phase. For an established platform like NGS, read it as mature / saturated — ubiquitous and past its novelty premium, not declining in importance.
The compression is visible
NGS crossed the chasm in a single year (2008–2009) — arriving into pent-up demand with an obvious application, it skipped the “is this useful?” exploration that took single-cell RNA-seq five years and spatial proteomics six. But every discovery platform eventually walks the same path: Innovators, a brief premium, then a long Early/Late Majority plateau. The window to capture the novelty premium is shorter with each generation.
The aggregate hides the frontier
A single phase per technology is a weighted average across many sub-applications. cfDNA reads Late Majority overall — but that blends a near-mature therapy-selection use, an Early-Majority MRD market, and a still-Innovator multi-cancer early-detection frontier. The aggregate phase tells you where the center of mass is, not where the opportunity is. Read it accordingly.
Methodology. The index combines two quantitative signals from PubMed — publication-growth momentum and a journal-tier novelty premium — but its phase boundaries were calibrated against expert ground truth: the thresholds were tuned until the framework reproduced where domain specialists know these eight technologies actually sit, then held fixed across all of them. This quant-plus-qual calibration is deliberate. A purely mechanical index mislabels a field as mature the moment its novelty premium fades — which happens years before adoption actually peaks. Pairing the leading signal (premium) with the concurrent one (growth) corrects that.
Phase is assigned by a forward-only state machine (a technology never de-diffuses). Early phases are gated by absolute volume — a field too small to have escaped its pioneers is Innovators by definition, regardless of journal-mix noise. The chasm crosses when the novelty premium falls below 30% of its de-noised peak, or when a field exceeds 750 papers/year (a mass-adoption override that handles clinical and methodology technologies whose premium never fully collapses). Late Majority and Laggards trigger on growth deceleration over a 2-of-3-year window, robust to single-year distortions like the 2020–21 COVID surge. The index measures scholarly diffusion; it lags real-world lab adoption by 1–2 years and under-weights clinical and industrial use. Data through mid-2026.