Longevity Clinical Trial Monitor (Catalyst Calendar)

A catalyst calendar for longevity biotech: which trials produce data, and when. 638 trials across 9 longevity topics · 108 industry-sponsored · 29 sponsored by a listed company you can trade · 65 with a primary completion date in the next 180 days, 33 within 90 days.

The core question this answers: which longevity studies read out in the next 90 days — and who owns the upside? Every trial carries its primaryCompletionDate (the date the primary endpoint is measured, i.e. when data exists), its sponsor type (industry / academic / government), and — where the sponsor is a listed company — its stock ticker.

Built on the official ClinicalTrials.gov API v2 — no scraping, no AI-generated summaries, no scoring or "hype vs. real science" judgment calls. Every field comes straight from the registered trial record; what this Actor adds is structure: sponsor-name normalization (so "Acme Inc.", "Acme, Inc" and "ACME" roll up as one company), sponsor classification, ticker mapping, and change detection across runs.

Works as a tool for AI agents as well as for humans: the Actor is exposed over Apify's MCP server, so an agent can call it with structured filters and get typed JSON back. See Use as an MCP tool.

Live demo

Open the viewer →

This viewer is the free preview of the full unfiltered feed. Paying runs go further — see Query filters below for the topic/status/phase/sponsor/change filters available on every run.

Prefer raw data over a UI? These two URLs always point at the latest run's full, unfiltered output — no need to look up a run ID:

• Full feed (JSON) — every trial in the dataset, incl. its full change history
• Digest (JSON) — per-topic stats + trials that changed in the last 30 days

What you get

Each dataset item is one clinical trial matching one of the tracked longevity topics:

Field	Description
nctId, nctUrl	Trial identity + link to the source record on ClinicalTrials.gov
title, conditions	What the trial is studying and which conditions it targets
sponsor, sponsorKey	Normalized sponsor/company name (legal-suffix and casing variants collapsed into one group)
sponsorType, sponsorClass	industry / academic / government / other, plus ClinicalTrials.gov's own raw class it was derived from
ticker, tickerCompany, listingStatus	Stock ticker if the sponsor is publicly listed (ticker), or why not (privat, non-commercial, unmapped)
status, phases	Current recruitment status and trial phase(s)
topics, topicKeys	Which tracked longevity topic(s) this trial matches
startDate, primaryCompletionDate, lastUpdateDate	Trial timeline as registered. primaryCompletionDate is the catalyst date — when the primary endpoint is measured
firstSeenAt	When this Actor first recorded the trial
changes	Detected status/phase/date changes since first seen — each entry has field, fromValue, toValue, detectedAt. This accumulates the longer the Actor runs; it is a bonus, not the headline

Tracked topics

Nine longevity themes, each a curated ClinicalTrials.gov query. Anything whose bare term is also a mainstream indication (metformin → diabetes, GLP-1 → obesity, plasma exchange → neurology) carries an explicit aging qualifier, so the feed stays a longevity feed rather than a general-medicine dump.

Topic key	Covers	Trials
nad_nmn	NMN, nicotinamide mononucleotide/riboside	166
klotho	Klotho	127
glp1_aging	Semaglutide/tirzepatide/GLP-1 × aging, frailty, sarcopenia	93
metformin	Metformin × aging/longevity/frailty (incl. TAME)	73
senolytics	Senolytics, senescent cells	68
gene_therapy	Gene therapy × aging, klotho, follistatin	58
rapamycin	Rapamycin/sirolimus × aging, longevity, frailty	56
plasma_exchange	Plasmapheresis / therapeutic plasma exchange × aging	14
reprogramming	Partial/cellular reprogramming, Yamanaka factors, OSKM	9

Sponsor coverage

	Trials
Industry-sponsored	108
— mapped to a stock ticker (ticker)	29
— confirmed privately held (privat)	50
— not yet researched (unmapped)	29
Academic — university, hospital, individual investigator	494
Government — NIH, federal, other government agency	34
Other	2

Tickers currently mapped: ABBV, ADVM, FDMT, RGNX, OXB.L, CDXC, JNJ, PFE, NVS, SNY, NESN.SW, 4536.T.

The mapping is deliberately narrow — only sponsors that actually appear in this feed, each verified against a primary source. A listingStatus of unmapped means "a company we haven't researched yet", not "no ticker exists"; privat means we checked and there is no tradeable security.

Query filters (Actor input)

The dataset is filterable per run — you don't have to take the full feed. Every field below shows up as a real form in the Apify Console (Actor → Input tab) when you configure a run:

• completionWithinDays — the catalyst calendar. Only trials whose primary completion date falls between today and N days from now. Prefilled with 180; set it to 90 for the near-term readout list, or clear it for everything
• topics — restrict to one or more of the nine topic keys above
• sponsorTypes — industry, academic, government, other
• listingStatus — ticker, privat, non-commercial, unmapped
• tickerSymbols — restrict to specific listed sponsors, e.g. ABBV, OXB.L
• status — restrict to specific trial statuses, e.g. RECRUITING, COMPLETED, TERMINATED (ClinicalTrials.gov's own vocabulary)
• phases — restrict to specific trial phases, e.g. PHASE1, PHASE2, PHASE3
• dateFrom / dateTo — restrict to a trial start-date range
• sponsorKeyword — substring match on the sponsor/company name
• conditionKeyword — substring match on the trial's listed medical conditions
• keyword — substring match on title + conditions
• onlyWithChanges — only return trials with at least one recorded change since first seen
• changesWithinDays — only return trials with a change detected within the last N days — the fastest way to see "what moved recently" across all tracked trials

Leave any filter empty/unset to not restrict on it.

What it costs

$0.003 per trial returned, plus a $0.01 Actor start. Measured on actual runs:

Run	Trials	Cost
Prefilled input (primary completion within 180 days)	65	$0.24
Readouts in the next 90 days	33	$0.14
Full feed, no filters	638	$1.95

Why not just query ClinicalTrials.gov yourself?

The API is free and public. What sits between it and this dataset:

1. Curated longevity queries. A bare metformin search returns thousands of diabetes trials; a bare gene therapy search returns oncology. The nine topic queries above are tuned so the feed stays a longevity feed — that tuning is the product, and it's maintained here.
2. Sponsor identity. ClinicalTrials.gov gives you a free-text sponsor string. It does not roll up spelling variants, does not reliably tell you whether a sponsor is a company or a hospital (its OTHER class lumps both together), and never gives you a stock ticker. All three are added here.
3. A catalyst date you can filter on. primaryCompletionDate is registered as YYYY-MM or YYYY-MM-DD depending on the trial, which makes naive date filtering silently drop rows. completionWithinDays handles both shapes.

Use as an MCP tool

Callable from any MCP client (Claude, Cursor, an agent framework) via Apify's MCP server:

{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": ["-y", "@apify/actors-mcp-server", "--actors", "northlab/bio-finance-trial-monitor"],
      "env": { "APIFY_TOKEN": "<your token>" }
    }
  }
}

The input schema is the tool signature. "Which listed companies have longevity trials reading out this quarter?" becomes one call with completionWithinDays: 90, listingStatus: ["ticker"].

Who this is for

Longevity/biotech investors, analysts and researchers who want to know what data is coming and from whom — without manually re-checking ClinicalTrials.gov. And AI agents doing that job on their behalf.

Data source & update frequency

ClinicalTrials.gov, the official U.S. National Library of Medicine registry of clinical trials worldwide — freely accessible, no scraping involved. The Actor runs on a schedule and accumulates trial history over time; a change is only recorded once this Actor has observed a trial at least twice, so change data becomes richer the longer the Actor has been running.