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What US pharmacies pay for generic medicines, week by week, grouped by the company that makes them, from the National Average Drug Acquisition Cost survey the Centers for Medicare & Medicaid Services run across retail pharmacies: the median move in a manufacturer's generic prices against the week before, how many of its prices rose and how many fell, and how many of its products were priced.

Generic price deflation is the number that drives guidance cuts at Teva, Viatris, Sandoz and the Indian exporters, and here it is per manufacturer, weekly, from the buyer's side of the counter rather than the seller's. A manufacturer whose median keeps falling faster than the market index is losing pricing power on its portfolio months before it says so; a week with more increases than decreases is a shortage, or a supplier leaving a molecule.

The all-manufacturer index the same survey produces is served by the market-level drug_prices endpoint, so a company's reading can be set against the market's 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.

Coverage

About 30,000 products a week, some 27,000 of them generics, from 2025. A manufacturer is identified by the labeler code at the front of its products' national drug codes, which often belongs to a US subsidiary rather than the listed parent, so one group can appear under several labelers; repackagers are never mapped. Products added or withdrawn that week are left out of the change.

Most weeks only a handful of rates change. Roughly once a month CMS applies its pharmacy survey and reprices almost everything, so most weekly readings sit at zero with one large week a month. The price of each individual product is kept in ORTEX's raw archive rather than served here.

What to look for

Watch the survey weeks, and read several of them together: one week can be dominated by a few injectable price corrections. Compare a manufacturer's median change with the market index for the same week rather than with zero, since the whole market drifts down in most months.

generic_ndcs_priced is the denominator for the increase and decrease counts, and it moves when a labeler launches or withdraws products, not only when prices do.

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.

Raw readings here; comparable ones next door

This endpoint serves the publisher's numbers. Raw values are frequently not comparable — receivables of $10.9bn against $4.9bn say nothing without each book's size, and a 5.3% charge-off rate means something different on a subprime book than a prime one. The Alt Data signals endpoint serves the same series as percentiles and z-scores against a stated comparison set, which is the form a screen or a backtest wants.

Why a company you expect may be missing

Three reasons, and none of them is a bug:

• The dataset is a window, not a census: Several of these publishers release a rolling window rather than a complete history.
• The filer is not the listed company: Registers name a marque, a charter or a trust. ORTEX maps those to the listed parent where the link is defensible and leaves them unmapped where it is not — a wrong mapping silently attributes another company's data to your ticker.
• The population is genuinely narrow: Not every listed company appears in every register, and no amount of mapping changes that.

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