A revenue ranking tells you who is big. A broker, or a sourcing team at an AI data company, needs a different order: which companies generate the records AI buyers want, which of those records the company actually owns, and who inside can say yes. This page maps US pharma and its service ecosystem in that order, then shows a scored preview of US labs, CROs and life-science companies.
Found a target? Qualify it against micro1, Mode and Grepped rules in about 20 seconds.
Search for a list of pharmaceutical companies in the USA and you get the same names in the same order: the largest drug makers by sales, then a long tail sorted alphabetically. That list answers an investor's question, or a job seeker's. It does not answer the question a data broker or a partnership team at an AI data company is asking, which sounds more like this: where is there a large, owned, well-documented record of expert work, and is there someone at that company who can approve licensing a copy of it?
Pharma is an unusually rich place to ask. The industry runs on written procedure. Every batch is recorded step by step. Every deviation is investigated and closed with a documented root cause. Every adverse event report is triaged, coded and assessed, and every question from a physician gets a referenced answer. Regulators require much of this paperwork, so it exists, it is structured, and it goes back years. That is the kind of record AI buyers describe wanting: long, connected histories of how specialists reason and decide.
It is also an unusually hard place to close a deal. A large share of what pharma companies hold is patient data, a trade secret, or content that belongs to a client or a sponsor. Separating the record that might be licensable from the record that never will be is most of the work, and the split changes by segment. So this page goes segment by segment, then record by record, and then lists the questions to put in front of counsel before anyone mentions a buyer.
One industry label covers very different businesses. What a company makes decides which records it keeps. How big it is decides who signs. The fit labels below are our reading for a broker's time, not a buyer's verdict.
A rule of thumb that holds across all five: the further a company sits from the patient and the molecule, the more of its record it owns outright. A CRO's study data belongs to the sponsor, but its SOPs, training program and the way it runs projects are its own. A testing lab's results belong to its clients, but its method validation know-how and its support history are its own. A software vendor to quality teams may own almost everything it holds, apart from customer content. When you sort a prospect list, sort by that distance first and by company size second.
These are the records that come up when sourcing teams describe what they want from regulated industries. Ownership here is the usual pattern, not a rule: each company's contracts decide it.
| Record family | Typical systems | What is inside | Usually owned by | Why AI buyers care |
|---|---|---|---|---|
| Quality systems | Electronic QMS, document control, training management | SOPs, deviations, investigations, corrective and preventive actions, change controls, audit findings, training records | The company, for its own procedures. The client, for product records at a CDMO or CRO | An investigation is written expert reasoning: a problem, the evidence, a conclusion and a fix |
| Regulatory submissions | Regulatory information management, publishing tools, document management | Applications, amendments, annual reports, answers to agency questions, labeling | The sponsor that filed them, even when a consultancy or CRO wrote them | Long technical writing in a strict structure, plus the questions an agency asked and how they were answered |
| Manufacturing batch records | MES, electronic or paper batch records, ERP | Master and executed batch records, in-process checks, equipment logs, line clearance, exceptions | The product owner, for product data. The manufacturer, for its own equipment and methods | Step-by-step procedure with checks and exceptions, a close match for process and agent training |
| Pharmacovigilance | Safety databases, case intake, literature screening | Adverse event cases, narratives, coding, causality assessments, periodic safety reports, signal reviews | The company that holds the marketing authorization. Service providers process cases for it | A repeated expert workflow from intake to assessment. Also full of patient health information |
| Medical information | Medical information systems, contact center tools, content libraries | Questions from physicians, pharmacists and patients, standard response documents, references | The company that markets the product. Vendors often run it under contract | Question and referenced answer pairs written by specialists. Inquiries carry personal and sometimes health data |
| Support | Helpdesk, CRM, customer portals, knowledge bases | Customer and technical support tickets, order issues, instrument and software support, how-to articles | Usually the company itself | Long, specialist conversations about real problems, and usually the easiest family to scope and de-identify |
Brokers new to pharma go straight for the regulated record: submissions, batch records, safety cases. Those are the most impressive and the hardest to license. The record that moves most easily is often the plainest one. A company that sells instruments, reagents, software or testing services to labs has years of support tickets in which specialists explain a failed run, a calibration drift or a validation question to another specialist. Those threads are the company's own, they rarely contain patient data, and they can be scoped by product line and date. In the public labs preview, support tickets and chat transcripts appear as a likely data asset for almost every company in the free preview.
Raw records are the start, not the whole value. Practitioners say evaluations are worth about 10 times raw data, and full environments reach six to eight figures. Pharma workflows translate well into both. A deviation investigation, a safety case or a medical information response has a clear input, a documented expert process and an output a reviewer can check. For a data company, that means a pharma services firm may be worth more as a partner whose specialists help build and grade tasks than as a one-time seller of an archive. For a broker, it means the introduction is worth framing around the company's expertise, not only its files.
None of this is legal advice. These are the questions to put to the company's own lawyer, and to yours, before anyone drafts a manifest. If the honest answer to any of them is "we do not know", the record stays out of scope.
The buyer programs that pay referral fees publish who they want. Their published rules point at mid-size companies, which is where much of the pharma service ecosystem sits.
Buyer facts as published, checked 7 October 2026: micro1 "$100K-$2M+ for approved data packages", Mode "$100K-$5M", Grepped "$20K-$5M". These are published ranges, not offers. The trade-off is real: a mid-size service company has less data than a global drug maker, and some of what it holds belongs to clients. Smaller, owned and decidable usually beats larger, shared and stuck.
The first five rows of the free preview, as shown on 8 October 2026; the rows below them are masked on the preview. The free preview is on the labs and CROs preview. The whole list can be bought once for $249, or kept always current through the API on the Pro and Scale plans.
| # | Company website | Score | Status | Online since | Likely data assets |
|---|---|---|---|---|---|
| 1 | promega.com | 78 B | Active | 1993 | SupportKnowledge baseCustomer accountsOrders |
| 2 | ul.com | 75 B | Active | 1994 | SupportKnowledge baseCRMForum |
| 3 | schrodinger.com | 73 B | Active | 1996 | SupportKnowledge baseCustomer accountsOrders |
| 4 | quidel.com | 67 B | Active | 1994 | SupportKnowledge baseCustomer accountsRecruiting |
| 5 | gene.com | 65 B | Active | 1987 | SupportKnowledge baseCustomer accountsRecruiting |
Notice what the preview does not do: it does not sort these companies into the five segments above. A domain and a category do not tell you whether a company is a manufacturer, a service provider, a software vendor or a supplier to labs, and we will not guess on a public page. That sorting is your first job as a broker, and it takes a few minutes per company on its own website. The preview's value is the order: it puts the companies that likely hold the most of what AI buyers want at the top, with their history and status beside them.
Look also at the dates. Most of the top ten have been online since the 1980s or 1990s. Long, continuous history is one of the nine factor groups in the score, and it lines up with what Mode publishes: several years of records. A company that has run a support desk for two decades has a deeper archive than one that opened last year, even if both look similar today.
Every Data Asset Score gives a company a score from 0 to 100, a grade, the data it likely holds, its history and an activity status. The nine factor groups are history, scale, knowledge assets, operational systems, customer systems, organization, industry value, expertise and activity status.
The company looks like it is trading normally. Next step: qualify it against published buyer rules, then work out who signs.
Pharma services consolidate often. If a lab or CRO was bought, the parent may now control the systems and the data policy. Find out who owns the records before you pitch anyone.
The domain no longer presents an operating company. Treat it as history, not a target, unless you can establish who controls whatever records survive.
The site could not be reached when it was checked. Check again later before drawing any conclusion about the company.
A working order for a broker or a data company's sourcing team, using only company-level information.
On Pro, page through the US labs, CROs and life-science list in the API, 100 companies per call, best first. On Scale, take the whole segment as one CSV file. Without a plan, buy the list once as a CSV snapshot for $249.
Set a minimum score, keep companies marked active, and set aside anything winding down or acquired until you know who controls it now.
Open each company's site and tag its segment. Push service providers, labs, software and instrument companies up; push anyone whose record is mostly patient data down.
Run each survivor through check your company. It reads public pages and compares team size, location, history and systems with micro1, Mode and Grepped rules, with quotes, in about 20 seconds.
Only with consent from someone who can speak for the company, and only through each program's own referral process. Read data referral programs for the published terms.
# Pro plan: first page of the segment, companies scoring 50 or more curl -H "X-API-Key: YOUR_KEY" \ "https://www.selldatatoai.com/api/v1/companies?segment=labs-cro&min_score=50&limit=100&offset=0" { "segment": "labs-cro", "min_score": 50, "offset": 0, "count": (companies on this page, up to 100), "companies": [ { "domain": "example-bioanalytical.com", "data_asset_score": 63, "grade": "C", "status": "active", "industry": { "group": "Life sciences, pharma and labs" }, "history": { "first_seen_year": 2004, "years_online": 22 }, "likely_data_assets": [ { "type": "knowledge_base", "confidence": "high" }, { "type": "research_records", "confidence": "medium" } ] } (more companies on this page, best first) ] }
Last checked: 8 October 2026. Payment by PayPal or card. The plans below keep the list always current; if you need it once, the one-time purchase is set out under the plans. Your API key appears in your dashboard after payment, not by email. Full details on pricing.
US labs, CROs and life-sciences list: $249 one-time, on sale from 1,000 verified companies
Referral fees in this market are published and large. micro1 publishes "earn $50,000" per referred company with "no cap", paid after onboarding plus a minimum revenue threshold. Mode publishes "$50K per referral". Grepped publishes "Refer for another $10K". All as published, checked 7 October 2026.
The terms matter as much as the amounts. micro1's terms give it sole discretion over every referred company, allow clawbacks, forbid sharing payouts with the company you refer, and forbid presenting yourself as micro1's partner. Read each program's terms before your first introduction, not after your first close.
Pharma adds its own layer. A company that runs regulated systems will ask hard questions early, and a broker who cannot answer them loses the room. Arrive knowing which segment the company is in, which of the six record families it likely holds, which of those are off limits, and which buyer program's published rules it meets. That is what the checklist covers, and none of it needs anything beyond company-level information.
One more point of conduct. You never handle the data. The company signs with the buyer, scopes the records with the buyer, and gets paid by the buyer. Your job ends at a qualified, consented introduction. For the roles in this market, read what is an AI data broker.
No. This page maps the segments of US pharma and the records each one keeps, for people who find data partners. The company list closest to pharma is our US labs, CROs and life-science companies list, one of 20 US sector lists we sell, and a free preview of it is public. Any pharmaceutical company outside that list can be scored one at a time in the demo or through the API.
Often mid-size service companies rather than the largest drug makers: CROs, testing and bioanalytical labs, CDMOs, regulatory and quality consultancies, and software and instrument suppliers to labs. They tend to own their procedures, training and support history outright, they sit inside the team sizes buyer programs publish, and a founder or COO can usually decide.
Treat it as out of scope until the company’s own counsel says otherwise. Trial participant data, adverse event cases and patient inquiries are covered by consent forms, contracts and health privacy law, and much trial data belongs to the sponsor rather than the company holding it. This page lists the questions to ask; it is general information, not legal advice.
Big pharma holds the deepest records but has the longest path to a yes: central data governance, internal AI programs, global privacy teams and a payout that is small next to its budgets. When a company that size licenses data, it can talk to AI labs directly and has little need for an introduction.
Pro ($299 a month) keeps the US labs, CROs and life-science list, and the other 19 sector lists, always current through the API: JSON, up to 100 companies per call, with paging, plus 25,000 lookups a month. Scale ($799 a month) adds the one-file bulk CSV export, 100,000 lookups and new segments on request. Without a plan, the list can be bought once for $249 as a CSV snapshot with no updates. Payment is by PayPal or card; on a plan, the API key appears in your dashboard after payment.
Whether the company looks active, winding down or acquired, parked, or unreachable. In pharma services, where companies are often bought and merged, it tells you early whether the decision may now sit with a parent company, before you spend time on an introduction.
No. The score is an estimate from public signals of how much data AI buyers want a company is likely to hold. It is not a valuation, not an offer and not a sign that the company wants to sell. Use it to decide which companies to look at first, then qualify each one.
No. Everything we provide is company level: the domain, the score, the grade, the data the company likely holds, its history and its activity status. We do not provide names, emails or phone numbers.
See the top of the scored labs and CROs list for free, score any pharma company in the demo, and qualify a target against published buyer rules before you spend an hour on it. When you want the whole list, buy it once for $249 or keep it current on Pro.