Programs

Overview

A program is one drug in one indication at one company, as the company publishes it in its pipeline. Each program carries a normalized phase, a modality, the molecular target and mechanism when disclosed, the clinical trials linked to it, and the page it was read from. Questions this dataset answers:

Which companies have an oral GLP-1 agonist in development for obesity?
Which KRAS G12C inhibitors are in Phase 3, and in which indications?
What else is being developed that looks like this program?
What is Eli Lilly’s full Phase 3 pipeline?

Coverage

Programs	Companies	Normalized phases	Normalized modalities
27,000+	6,500+	9	19

Counts are from September 2026. Get current counts, and program counts per phase and modality, from GET /v1/stats. Partial fields are listed in Coverage and sources.

Key fields

Field	Description
`id`	Pav program id. Stable across updates; a phase change updates the program, it does not create a new one.
`company_id`, `company`, `short_name`	Owning company: Pav id, display name, slug.
`drug`	Drug or asset name as the company publishes it.
`indication`	Indication as the company publishes it.
`phase` / `phase_norm`	Phase as published, and the normalized phase (`Preclinical`, `Phase 1`, `Phase 1/2`, `Phase 2`, `Phase 2/3`, `Phase 3`, `Filed`, `Registration`, `Approved`).
`modality` / `modality_norm`	Modality as published, and the normalized modality (`small_molecule`, `antibody`, `adc`, `cell_therapy`, …).
`target`, `mechanism_of_action`	Molecular target and mechanism, when disclosed.
`partners`	Partner companies named with the program.
`clinical_trials[]`	Linked ClinicalTrials.gov studies (`nct_id`, phase, status, sponsor).
`indication_terms[]`, `target_terms[]`	Indication mapped to MONDO terms and target mapped to NCIT terms, when available.
`source_url`, `source_checked_at`	The company page the program was read from, and when Pav last read it.

Full schema: List and search pipeline programs.

Endpoints

Endpoint	Use
`GET /v1/programs`	Search (`q`) or filter programs.
`GET /v1/programs/{program_id}`	One program with its trials and ontology terms.
`GET /v1/programs/{program_id}/similar-programs`	Programs most similar to a given program.
`GET /v1/programs/autocomplete`	Search-as-you-type suggestions for a search box.
`GET /v1/companies/{company_id}/programs`	One company’s programs.

Filters

All filters are optional, repeatable, and combine with AND. Repeating a filter matches any of its values.

Parameter	Matches	Example
`q`	Relevance-ranked search that matches meaning as well as exact words.	`oral GLP-1 obesity`
`phase`	Normalized phase label, exactly as in `phase_norm`.	`Phase 3`
`modality`	Modality token (as in `modality_norm`) or its display label. Unknown values return `422`.	`adc`, `Small molecule`
`target`	Target, case-insensitive exact match.	`KRAS`
`indication`	Indication, case-insensitive exact match.	`Obesity`
`drug`	Drug name, case-insensitive exact match.	`Tirzepatide`
`company`	Company display name.	`Eli Lilly`
`short_name`, `company_id`	Company slug or Pav id.	`eli_lilly`, `218`
`sort`, `direction`	Listing order (not with `q`): `company`, `drug`, `indication`, `target`, `phase`, `modality`, `source_checked_at`.	`sort=phase&direction=desc`
`include_total`	Exact match count on filter-only listings.	`true`
`limit`, `offset`	Page size (1–5000, default 50) and offset.	`limit=100`

phase takes the label shown in phase_norm (Phase 3), not a token such as phase_3. A value that matches nothing returns an empty data array, not an error.

Search programs by mechanism and phase

q finds programs by meaning, not only by exact words. Add filters to narrow the ranked results.

curl -G https://api.pav.bio/v1/programs \
  -H "Authorization: Bearer $PAV_API_KEY" \
  --data-urlencode "q=KRAS G12C inhibitor" \
  --data-urlencode "phase=Phase 3" \
  --data-urlencode "limit=3"

import os
import requests

resp = requests.get(
    "https://api.pav.bio/v1/programs",
    headers={"Authorization": f"Bearer {os.environ['PAV_API_KEY']}"},
    params={"q": "KRAS G12C inhibitor", "phase": "Phase 3", "limit": 3},
)
resp.raise_for_status()
for p in resp.json()["data"]:
    print(p["company"], "|", p["drug"], "|", p.get("indication", ""), "|", p.get("target"))

const params = new URLSearchParams({ q: "KRAS G12C inhibitor", phase: "Phase 3", limit: "3" });
const resp = await fetch(`https://api.pav.bio/v1/programs?${params}`, {
  headers: { Authorization: `Bearer ${process.env.PAV_API_KEY}` },
});
const { data } = await resp.json();
for (const p of data) console.log(p.company, "|", p.drug, "|", p.indication, "|", p.target);

Example response (trimmed)

{
  "data": [
    {
      "id": 3407,
      "company_id": 313,
      "company": "Merck",
      "drug": "calderasib",
      "indication": "Colorectal cancer",
      "phase_norm": "Phase 3",
      "modality_norm": "small_molecule",
      "target": "KRAS G12C"
    },
    {
      "id": 3408,
      "company_id": 313,
      "company": "Merck",
      "drug": "calderasib",
      "indication": "Non-small cell lung cancer",
      "phase_norm": "Phase 3",
      "modality_norm": "small_molecule",
      "target": "KRAS G12C"
    }
  ],
  "pagination": { "limit": 3, "offset": 0 }
}

Filter and count

Without q, the endpoint lists programs matching the filters. Pass include_total=true for the exact count. Repeat phase to match several phases.

curl -G https://api.pav.bio/v1/programs \
  -H "Authorization: Bearer $PAV_API_KEY" \
  --data-urlencode "indication=Obesity" \
  --data-urlencode "phase=Phase 2" \
  --data-urlencode "phase=Phase 3" \
  --data-urlencode "include_total=true" \
  --data-urlencode "limit=3"

import os
import requests

resp = requests.get(
    "https://api.pav.bio/v1/programs",
    headers={"Authorization": f"Bearer {os.environ['PAV_API_KEY']}"},
    params={
        "indication": "Obesity",
        "phase": ["Phase 2", "Phase 3"],
        "include_total": "true",
        "limit": 3,
    },
)
resp.raise_for_status()
body = resp.json()
print("total:", body["pagination"]["total"])
for p in body["data"]:
    print(p["company"], "|", p["drug"], "|", p["phase_norm"])

const params = new URLSearchParams([
  ["indication", "Obesity"],
  ["phase", "Phase 2"],
  ["phase", "Phase 3"],
  ["include_total", "true"],
  ["limit", "3"],
]);
const resp = await fetch(`https://api.pav.bio/v1/programs?${params}`, {
  headers: { Authorization: `Bearer ${process.env.PAV_API_KEY}` },
});
const body = await resp.json();
console.log("total:", body.pagination.total);
for (const p of body.data) console.log(p.company, "|", p.drug, "|", p.phase_norm);

Example response (trimmed)

{
  "data": [
    { "id": 24517, "company": "Actelion", "drug": "Canagliflozin", "indication": "Obesity", "phase_norm": "Phase 2" },
    { "id": 24695, "company": "Actelion", "drug": "JNJ-64565111", "indication": "Obesity", "phase_norm": "Phase 2" },
    { "id": 24387, "company": "Actelion", "drug": "R256918", "indication": "Obesity", "phase_norm": "Phase 2" }
  ],
  "pagination": { "limit": 3, "offset": 0, "total": 77 }
}

indication is an exact match on the published indication text. For broader recall across phrasings (“Metabolic (Obesity)”, “Obesity / Metabolic Disease”), use q instead.

Find similar programs

Given a program id, return the programs most similar to it, ranked by similarity. Useful for finding competitors and analogues.

curl https://api.pav.bio/v1/programs/1833/similar-programs \
  -H "Authorization: Bearer $PAV_API_KEY"

import os
import requests

resp = requests.get(
    "https://api.pav.bio/v1/programs/1833/similar-programs",
    headers={"Authorization": f"Bearer {os.environ['PAV_API_KEY']}"},
)
resp.raise_for_status()
for p in resp.json()["data"]:
    print(p["company"], "|", p["drug"], "|", p.get("indication", ""))

const resp = await fetch("https://api.pav.bio/v1/programs/1833/similar-programs", {
  headers: { Authorization: `Bearer ${process.env.PAV_API_KEY}` },
});
const { data } = await resp.json();
for (const p of data) console.log(p.company, "|", p.drug, "|", p.indication);

Example response (trimmed)

{
  "program_id": 1833,
  "data": [
    { "id": 1834, "company": "Eli Lilly", "drug": "Tirzepatide", "indication": "Morbidity and Mortality in Obesity", "phase_norm": "Approved" },
    { "id": 1835, "company": "Eli Lilly", "drug": "Tirzepatide", "indication": "Type 1 Diabetes", "phase_norm": "Phase 3" },
    { "id": 1832, "company": "Eli Lilly", "drug": "Tirzepatide", "indication": "Higher Doses", "phase_norm": "Phase 2" }
  ]
}

Get one program

GET /v1/programs/{program_id} returns the full record, including linked trials and ontology terms.

Example response (trimmed): GET /v1/programs/1833

{
  "id": 1833,
  "company_id": 218,
  "company": "Eli Lilly",
  "drug": "Tirzepatide",
  "indication": "Metabolic Dysfunction-Associated Steatotic Liver Disease",
  "phase": "Phase 3",
  "phase_norm": "Phase 3",
  "modality_norm": "peptide",
  "mechanism_of_action": "GIP/GLP-1 receptor agonist",
  "clinical_trials": [
    {
      "nct_id": "NCT07165028",
      "nct_url": "https://clinicaltrials.gov/study/NCT07165028",
      "nct_phase": "PHASE3",
      "nct_sponsor": "Eli Lilly and Company",
      "nct_status": "RECRUITING"
    }
  ],
  "indication_terms": [
    { "ontology": "MONDO", "term_id": "MONDO:0013209", "term_label": "metabolic dysfunction-associated steatotic liver disease" }
  ],
  "target_terms": [
    { "ontology": "NCIT", "term_id": "NCIT:C191844", "term_label": "Glucagon-Like Peptide 1 Receptor" }
  ],
  "source_url": "https://www.lilly.com/science/research-development/pipeline"
}

Get started

Datasets

Working with the API

Integrations

Guides

Overview

Coverage

Key fields

Endpoints

Filters

Search programs by mechanism and phase

Filter and count

Find similar programs

Get one program

​Overview

​Coverage

​Key fields

​Endpoints

​Filters

​Search programs by mechanism and phase

​Filter and count

​Find similar programs

​Get one program

​Related

Overview

Coverage

Key fields

Endpoints

Filters

Search programs by mechanism and phase

Filter and count

Find similar programs

Get one program

Related