{ "study": { "slug": "clinical-trial-sponsor-concentration-2026", "title": "Who runs the clinical trials: academia, not pharma, 2026", "standfirst": "Of the 589,453 studies registered on ClinicalTrials.gov, 71.4% are run by academic and hospital sponsors and only 22.1% by industry — the registry of medical research is led by universities, not pharma. Yet industry runs 41.2% of phased drug-development trials, and 53.8% of all sponsors registered just one study.", "desk": "care-quality", "article_type": "Original Research", "published": "2026-06-17", "issue": 85, "doi": "10.5072/fonteum/clinical-trial-sponsor-concentration-2026", "url": "https://fonteum.com/research/clinical-trial-sponsor-concentration-2026", "methodology_version": "clinicaltrials/v1" }, "data_as_of": "2026-06-14", "datasets": [ { "slug": "clinicaltrials-gov", "name": "ClinicalTrials.gov", "publisher": "NIH — National Library of Medicine", "upstream_url": null } ], "key_findings": [ { "number": "71.4%", "finding": "of the 589,453 studies on ClinicalTrials.gov are run by academic, hospital, and foundation sponsors — the registry's 'Other' class — against 22.1% led by industry and 5.4% by government (NIH, other U.S. federal, and other government combined). The public ledger of medical research is led by universities, not pharma", "dataset": "clinicaltrials-gov" }, { "number": "41.2%", "finding": "of phased interventional trials — the regulated drug-development pipeline, Early Phase 1 through Phase 4 — are run by industry, nearly double its 22.1% share of all studies. The academic share falls from 71.4% to 51.7%. Industry concentrates where the regulatory stakes are highest", "dataset": "clinicaltrials-gov" }, { "number": "26.2%", "finding": "of the registry is run by just 100 sponsors — 0.2% of the 50,756 distinct lead sponsors. The top 1,000 sponsors run 62.7%; the top 10 alone run 6.0%. The registry is steeply concentrated at the head", "dataset": "clinicaltrials-gov" }, { "number": "53.8%", "finding": "of all 50,756 lead sponsors registered exactly one study, and 82.4% registered five or fewer — the median sponsor is a one-time registrant. Of the 100 most prolific sponsors, 79 are academic or hospital institutions, running 73.3% of all top-100 studies", "dataset": "clinicaltrials-gov" }, { "number": "589,453", "finding": "registered studies across 50,756 distinct lead sponsors make up the snapshot, dated 2026-06-14 and pulled from the ClinicalTrials.gov Data API v2; 76.3% interventional, 23.3% observational. Every figure is a count over published records — no investigator, sponsor, or trial is named, ranked, or scored", "dataset": "clinicaltrials-gov" } ], "faqs": [ { "q": "Who runs the most clinical trials — pharma or universities?", "a": "Universities and hospitals. Of the 589,453 studies registered on ClinicalTrials.gov, 71.4% are led by the registry's 'Other' class — academic institutions, hospitals, and foundations — against 22.1% led by industry and 5.4% by government. The popular image of clinical research as a pharma activity is the opposite of what the registry of record shows: by study count it is overwhelmingly an academic and hospital enterprise." }, { "q": "If academia runs most trials, why is industry associated with drug development?", "a": "Because the two run different kinds of trials. Restrict the count to phased interventional trials — the regulated pipeline that tests a drug or biologic in humans, Early Phase 1 through Phase 4 — and industry's share jumps from 22.1% of all studies to 41.2%, while the academic share falls from 71.4% to 51.7%. Industry concentrates in the high-stakes, expensive, regulator-facing pipeline; academic and hospital sponsors run a far larger share of observational and non-phased interventional work." }, { "q": "How concentrated is the clinical-trials registry?", "a": "Steeply, at the top. The 100 most prolific lead sponsors — 0.2% of the 50,756 distinct sponsors — run 26.2% of all registered studies; the top 1,000 run 62.7%, and the top 10 alone run 6.0%. A small number of large research institutions and companies account for a disproportionate share of the registered record." }, { "q": "Is the registry dominated by a few large sponsors, then?", "a": "It is concentrated and fragmented at the same time. While the top 100 sponsors run 26.2% of studies, 53.8% of all 50,756 lead sponsors registered exactly one study, and 82.4% registered five or fewer. The median sponsor is a one-time registrant. The registry is a short head of prolific institutions sitting on top of a very long tail of sponsors that appear once." }, { "q": "Does running many trials mean a sponsor is better or more important?", "a": "No. A sponsor count records who registers research — how many studies an institution has filed — not the quality, size, cost, or scientific importance of that research. A university with hundreds of small investigator-initiated studies and a company with a handful of large multi-site trials are different shapes of the same enterprise. This study counts and groups sponsors; it does not name, rank, or score any one of them, and draws no inference about any investigator or provider." }, { "q": "Are these all American trials?", "a": "No. ClinicalTrials.gov is run by the U.S. National Library of Medicine and is the registry U.S. law requires for federally funded and FDA-regulated research, but its coverage is global — it includes studies sponsored from outside the United States. So 'who runs the trials' here means who runs the studies on this registry worldwide, not a U.S.-only count. The sponsor-class and concentration patterns are computed over the registry as a whole." }, { "q": "Can I reproduce these figures?", "a": "Yes. Every number is a direct count over the public clinical_trials table — the ClinicalTrials.gov Data API v2 registry, snapshot 2026-06-14 — with no modeling. The exact SQL for the sponsor-class mix, the phased-pipeline inversion, the top-N concentration, the one-study tail, and the class composition of the top 100 sponsors is published in the reproducibility block below." } ], "citation": { "apa": "Fonteum Research. (2026, June 17). Who runs the clinical trials: academia, not pharma, 2026. Fonteum Research, Issue 85. https://doi.org/10.5072/fonteum/clinical-trial-sponsor-concentration-2026", "url": "https://fonteum.com/research/clinical-trial-sponsor-concentration-2026" }, "reproducible_sql": "-- WHO RUNS the clinical-trials registry — the composition and concentration of\n-- the sponsors behind every study on ClinicalTrials.gov. Fully reproducible.\n--\n-- Question: of the studies registered on ClinicalTrials.gov, who sponsors them?\n-- What share is run by industry vs academic/hospital vs government sponsors,\n-- how concentrated is the registry among the most prolific sponsors, and how\n-- long is the tail of one-study sponsors? The lead figure: 71.4% of the\n-- 589,453 registered studies are led by academic, hospital, and foundation\n-- sponsors (the \"Other\" class), against 22.1% led by industry. A sponsor count\n-- is a record of who registers research — NOT a quality, fraud, or wrongdoing\n-- signal of any kind, and says nothing about any investigator, sponsor, or\n-- provider.\n--\n-- Source:\n-- public.clinical_trials — ClinicalTrials.gov Data API v2 (the U.S. National\n-- Library of Medicine registry of interventional and observational\n-- studies). 589,453 registered studies across 50,756 distinct lead\n-- sponsors; snapshot 2026-06-14. Public, read-only. License:\n-- ClinicalTrials.gov Terms & Conditions (NLM public data).\n-- methodology_version = 'clinicaltrials/v1'.\n--\n-- Universe: this study reads the published registry AS A WHOLE — every row is a\n-- study NLM lists on ClinicalTrials.gov as of the 2026-06-14 snapshot. The\n-- registry is global in coverage: it includes trials sponsored from outside\n-- the United States as well as U.S.-based research.\n--\n-- Counting note: 589,453 distinct NCT IDs, one row each; no row is duplicated.\n-- \"Sponsor\" = lead_sponsor_name; sponsor \"class\" = lead_sponsor_class as the\n-- registry codes it (OTHER = academic / hospital / foundation; INDUSTRY;\n-- NIH; FED = other U.S. federal; OTHER_GOV; NETWORK; INDIV; etc.). No\n-- individual investigator, sponsor, or provider is named, ranked, or scored\n-- in the published study.\n\n-- ============================================================================\n-- (1) Universe reconciliation — the registry at a glance.\n-- ============================================================================\nSELECT\n count(*) AS studies,\n count(DISTINCT nct_id) AS distinct_nct,\n count(DISTINCT lead_sponsor_name) AS sponsors,\n count(*) FILTER (WHERE study_type = 'INTERVENTIONAL') AS interventional,\n count(*) FILTER (WHERE study_type = 'OBSERVATIONAL') AS observational,\n max(ingested_at)::date AS snapshot\nFROM public.clinical_trials;\n-- studies 589,453 · distinct_nct 589,453 · sponsors 50,756\n-- interventional 449,800 (76.3%) · observational 137,624 (23.3%) · snapshot 2026-06-14\n\n-- ============================================================================\n-- (2) HEADLINE: who runs the registry — share of all 589,453 studies by lead\n-- sponsor class. Academic / hospital / foundation sponsors (OTHER) run\n-- 71.4%; industry runs 22.1%; the three government classes combined\n-- (NIH + FED + OTHER_GOV) run 5.4%. The registry is led by universities and\n-- hospitals, not pharma.\n-- ============================================================================\nSELECT\n coalesce(lead_sponsor_class, '(uncoded)') AS sponsor_class,\n count(*) AS studies,\n round(100.0 * count(*) / 589453, 1) AS pct_of_registry\nFROM public.clinical_trials\nGROUP BY sponsor_class\nORDER BY studies DESC;\n-- OTHER 420,647 · 71.4% INDUSTRY 130,207 · 22.1%\n-- OTHER_GOV 15,564 · 2.6% NIH 11,536 · 2.0%\n-- NETWORK 4,966 · 0.8% FED 4,890 · 0.8%\n-- (uncoded) 975 · 0.2% INDIV 566 · 0.1%\n-- UNKNOWN 99 · ~0% AMBIG 3 · ~0%\n-- government combined (NIH + FED + OTHER_GOV) = 31,990 = 5.4%\n\n-- ============================================================================\n-- (3) THE INVERSION: who runs the regulated drug-development pipeline. Restrict\n-- to PHASED interventional trials (Early Phase 1 .. Phase 4) — the trials\n-- that test a drug or biologic in humans. Industry's share JUMPS from 22.1%\n-- of all studies to 41.2% of phased trials; the OTHER class falls from\n-- 71.4% to 51.7%. Industry concentrates where the regulatory stakes are.\n-- ============================================================================\nSELECT\n coalesce(lead_sponsor_class, '(uncoded)') AS sponsor_class,\n count(*) AS phased_trials,\n round(100.0 * count(*) / sum(count(*)) OVER (), 1) AS pct_of_phased\nFROM public.clinical_trials\nWHERE study_type = 'INTERVENTIONAL'\n AND phase IN ('EARLY_PHASE1','PHASE1','PHASE1/PHASE2','PHASE2',\n 'PHASE2/PHASE3','PHASE3','PHASE4')\nGROUP BY sponsor_class\nORDER BY phased_trials DESC;\n-- OTHER 113,926 · 51.7% INDUSTRY 90,723 · 41.2%\n-- NIH 7,049 · 3.2% OTHER_GOV 3,983 · 1.8%\n-- NETWORK 2,722 · 1.2% FED 1,412 · 0.6%\n-- total phased interventional = 220,186\n\n-- ============================================================================\n-- (4) CONCENTRATION at the top — share of the registry run by the N most\n-- prolific lead sponsors. The top 100 sponsors (0.2% of the 50,756) run\n-- 26.2% of all studies; the top 1,000 run 62.7%. \"Top N\" is a concentration\n-- metric over the sponsor count distribution; no individual sponsor is\n-- named.\n-- ============================================================================\nWITH s AS (\n SELECT count(*) AS c FROM public.clinical_trials GROUP BY lead_sponsor_name\n),\nr AS (SELECT c, row_number() OVER (ORDER BY c DESC) AS rn FROM s)\nSELECT\n count(*) AS sponsors,\n sum(c) AS studies,\n sum(c) FILTER (WHERE rn <= 10) AS top10_studies,\n round(100.0 * sum(c) FILTER (WHERE rn <= 10) / sum(c), 1) AS top10_pct,\n sum(c) FILTER (WHERE rn <= 50) AS top50_studies,\n round(100.0 * sum(c) FILTER (WHERE rn <= 50) / sum(c), 1) AS top50_pct,\n sum(c) FILTER (WHERE rn <= 100) AS top100_studies,\n round(100.0 * sum(c) FILTER (WHERE rn <= 100) / sum(c), 1) AS top100_pct,\n sum(c) FILTER (WHERE rn <= 1000) AS top1000_studies,\n round(100.0 * sum(c) FILTER (WHERE rn <= 1000) / sum(c), 1) AS top1000_pct\nFROM r;\n-- sponsors 50,756 · studies 589,453\n-- top10 35,523 (6.0%) · top50 104,569 (17.7%)\n-- top100 154,542 (26.2%) · top1000 369,564 (62.7%)\n\n-- ============================================================================\n-- (5) FRAGMENTATION at the bottom — the long tail. 53.8% of all lead sponsors\n-- registered exactly one study; 82.4% registered five or fewer. The median\n-- sponsor is a one-time registrant. Concentration at the top and a vast\n-- thin tail are two faces of the same distribution.\n-- ============================================================================\nWITH s AS (\n SELECT count(*) AS c FROM public.clinical_trials GROUP BY lead_sponsor_name\n)\nSELECT\n count(*) AS sponsors,\n count(*) FILTER (WHERE c = 1) AS one_study,\n round(100.0 * count(*) FILTER (WHERE c = 1) / count(*), 1) AS one_study_pct,\n count(*) FILTER (WHERE c <= 5) AS five_or_fewer,\n round(100.0 * count(*) FILTER (WHERE c <= 5) / count(*), 1) AS five_or_fewer_pct\nFROM s;\n-- sponsors 50,756 · one_study 27,328 (53.8%) · five_or_fewer 41,799 (82.4%)\n\n-- ============================================================================\n-- (6) WHO is at the top — the CLASS composition of the 100 most prolific\n-- sponsors (aggregate; no sponsor named). 79 of the 100 are academic /\n-- hospital / foundation sponsors, and they account for 73.3% of all\n-- top-100 studies. The concentration at the head of the registry is\n-- academic, not industrial.\n-- ============================================================================\nWITH s AS (\n SELECT lead_sponsor_class, count(*) AS c\n FROM public.clinical_trials GROUP BY lead_sponsor_name, lead_sponsor_class\n),\nr AS (SELECT lead_sponsor_class, c, row_number() OVER (ORDER BY c DESC) AS rn FROM s)\nSELECT\n coalesce(lead_sponsor_class, '(uncoded)') AS sponsor_class,\n count(*) AS sponsors_in_top100,\n sum(c) AS their_studies,\n round(100.0 * sum(c) / 154542, 1) AS pct_of_top100\nFROM r\nWHERE rn <= 100\nGROUP BY sponsor_class\nORDER BY their_studies DESC;\n-- OTHER 79 · 113,214 · 73.3% INDUSTRY 16 · 31,517 · 20.4%\n-- NIH 3 · 7,111 · 4.6% FED 1 · 1,725 · 1.1%\n-- (uncoded) 1 · 975 · 0.6%", "license": "U.S. Government Works (federal sources; 17 U.S.C. §105)", "generated_by": "Fonteum — https://fonteum.com", "notes": "Aggregate, source-traced figures frozen to the snapshot above. Reproduce by running reproducible_sql against the cited federal dataset; no per-entity records are included." }