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A weekly index of what US pharmacies pay for generic medicines, built by ORTEX from every generic product in the National Average Drug Acquisition Cost survey the Centers for Medicare & Medicaid Services publish: the chained index level, its week-on-week change, the median change across all manufacturers, how many prices rose and fell, and how brand prices moved alongside.

This is the benchmark for generic price deflation. The US generic market typically loses a few percent a year; a flattening or rising index means shortages, exits and supplier consolidation are handing manufacturers pricing back, and that shows here before it reaches company guidance.

The per-manufacturer readings from the same survey are served by the per-instrument drug_prices endpoint, so a company's own median change can be set against this index for the same week.

Available Data Points:

• Period Date: The period the value describes — what the number is about (the valid clock).
• Published At: When the value first became knowable — when the publisher released it (the knowledge clock). Filter on this for anything where look-ahead bias would matter.
• Value: The numeric value, where the series has one.
• Value Text: The textual value, for categorical series such as a trial's status or phase.
• Unit: Unit of the value, e.g. vehicles, percent, USD.
• Value Type: number, percent, currency, count or text.
• Frequency: How often the publisher releases the series.
• Market: The market the reading describes — an ISO-3166 alpha-2 code (DE), a sub-national one (US-CA), a supranational aggregate (EA, EU) or GLOBAL.
• Series Slug: Which series the reading belongs to. Unique within a publisher, not globally.
• Series Name: Human-readable name of the series.
• Source Slug: Publisher/feed identifier, e.g. kba_registrations.
• Source Name: Human-readable name of the publisher or feed.
• Publisher: Who publishes the underlying data.
• Entity Ref: The publisher's own identifier for what the reading is about — a manufacturer name, a securitisation trust, a reactor unit, a country code. Kept so any value can be traced back to the row it was parsed from.

This dataset describes a market, not a company

Every reading here is about a country or a whole market, so there is no ticker in the path and no instrument in the response envelope. That is deliberate: attaching a national print to a listing would be a claim the data does not support. Read it as the context the company-level endpoints are measured against.

Coverage

Weekly from 2025. Every generic product CMS priced in two consecutive weeks counts equally, about 27,000 of them, and products added or withdrawn that week are left out. The index level is chained week to week from 100 at the first week imported, so it is continuous only where every earlier week was imported in order.

Most weeks move by almost nothing. Roughly once a month CMS applies its pharmacy survey and reprices nearly everything, which is where the index actually moves.

What to look for

Read the index level over months, not weeks, and read a week with more increases than decreases as a supply signal. generic_price_change_pct is the geometric-mean move behind the index; generic_median_change_pct is the typical product's move, and the two part company when a few large corrections dominate a survey week.

Two dates on every reading, and the difference is the edge

periodDate is what the number is about. publishedAt is when it first became knowable. The gap between them is the whole point of alternative data — and it is also the trap. A Form 10-D describing July is filed in mid-August, so a backtest that treats the period as the knowledge date reads a document six weeks before it existed.

from_date and to_date filter on periodDate, because that is the axis you plot against. Join on publishedAt when you are joining against returns.

Filtering: one market or all of them

Called with no filters, the endpoint returns every series in the dataset, for every market ORTEX covers it in. Each row names its own market, seriesSlug and sourceSlug, so a single request is enough to chart the whole dataset.

Narrow it with any combination of market (one market), series (one measure) and source (one publisher). Filter values that are each valid but select nothing together return 400 invalidSelection rather than a misleading empty result.

How much history there is

Several of these publishers overwrite their own pages and keep no archive. Where that is so, the series begins on the day ORTEX started capturing it and lengthens from there — nobody, including the publisher, can supply the days before that. Everything ORTEX has ever fetched is archived on capture, so the series only ever grows.

Try it out! You can test the API with the trial key TEST. Simply include it in your request headers; either here, or add the header "Ortex-Api-Key": "TEST" to your http request.

Trial key restrictions: Trial keys may be limited to a specific date range and set of regions. Requests outside the allowed regions or entirely outside the allowed date range are rejected; a date window that partially overlaps the allowed range is trimmed to it, reported in meta.restriction.

Get full access! Get a key at app.ortex.com/apis