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Clinical Trials Principal Investigator Data: Linking Studies and Researchers

Clinical trials principal investigator data can help researchers and healthcare data engineers understand which people and organizations are associated with a study. The information is not always represented in one simple “researcher” field, however.

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Clinical trials principal investigator data can help researchers and healthcare data engineers understand which people and organizations are associated with a study. The information is not always represented in one simple “researcher” field, however. ClinicalTrials.gov separates overall study officials, sponsors, responsible parties, site facilities, and contacts.

That distinction matters when you want to link trials to researchers, interpret a ClinicalTrials.gov investigator record, or design a principal investigator matching workflow. This guide explains how the NCT identifier anchors a study record, how study roles differ, and why name and affiliation matching requires cautious entity resolution.

Table of contents

What ClinicalTrials.gov study records contain

ClinicalTrials.gov is a U.S.-based public registry containing structured information about clinical studies. A record can include a study title, sponsor, status, design, intervention, eligibility criteria, locations, contacts, and officials.

The example record is:

  • NCT identifier: NCT05266235
  • Brief title: “Clinical Validation of the Withings ECG Monitor for the Detection of Atrial Fibrillation”
  • Organization: Withings
  • Study type: Interventional
  • Overall status: Completed
  • Start date: 2022-04-14
  • Completion date: 2022-07-28
  • Actual enrollment: 274

The record concerns validation of the Withings WBS08 device for identifying atrial fibrillation and sinus rhythm. Its listed locations include sites in Belgium and France. Although ClinicalTrials.gov is a U.S.-based registry, an individual study may include locations outside the United States.

The study’s design fields include phase NA, allocation NA, and masking NONE. QOPE’s Clinical Trials dataset includes fields such as study status, phase, allocation, masking, and sponsor. QOPE brings selected public healthcare datasets into a more accessible environment. Users should consult the original public source when official verification is required. QOPE’s available public healthcare data is listed on the databases page.

How the NCT identifier anchors clinical trial data

The NCT identifier is the central reference for an individual ClinicalTrials.gov study record. In this example, NCT05266235 identifies the study and connects its title, sponsor, status, design, officials, locations, and other record modules.

For data integration:

  1. Read the NCT identifier as the study-level key.
  2. Attach study attributes to that identifier.
  3. Treat officials, contacts, locations, and sponsors as related roles or entities.
  4. Preserve the relationship between each extracted person or organization and the originating study record.

The NCT identifier anchors the study record; it does not identify a person. A researcher may appear in one or more study records, and the same individual may be represented with differences in punctuation, credentials, spelling, or affiliation. The study key should therefore remain separate from any person-level matching key created during downstream analysis.

Overall officials, sponsors, and site contacts represent different roles

ClinicalTrials.gov records distinguish officials responsible for the overall study from contacts associated with a study or location.

The overallOfficials record in this example contains:

  • Name: Nicolas Lellouche, MD
  • Affiliation: Henri Mondor University Hospital
  • Role: PRINCIPAL_INVESTIGATOR

The record also includes a locations list. These entries identify facilities and places, including Cliniques Universitaires de Bruxelles - Hôpital Erasme in Brussels, Henri Mondor University Hospital in Créteil, Poitiers University Hospital in Poitiers, and George Pompidou European Hospital in Paris.

An overall official and a site contact should not be treated as interchangeable. An overall official is associated with the study as a whole, while a site contact relates to contact information for a study or location when that information is provided. The sponsor and responsible party represent additional study-responsibility concepts.

In this record, responsibleParty has type SPONSOR, and the lead sponsor is Withings. That differs from the overallOfficials entry naming Nicolas Lellouche, MD as principal investigator. Keeping sponsor, responsible-party, site, contact, and investigator fields separate prevents them from being collapsed into one generic “owner” or “researcher” concept.

Why name and affiliation matching requires cautious entity resolution

Linking trials to researchers is an entity-resolution problem, not a simple text join.

A person’s name may appear with or without a professional suffix. For example, Nicolas Lellouche, MD contains both a name and credential. Another record might format the same text differently, such as changing punctuation or omitting MD. Affiliations can also vary through abbreviations, translated names, former names, or different administrative forms.

A careful data model should preserve source values before normalization. Useful separate fields include:

  • Study NCT identifier
  • Official name
  • Official role
  • Official affiliation
  • Site facility
  • Site city, region, and country
  • Sponsor name
  • Responsible-party type

Normalization can support candidate matching, but a name match does not prove person identity. Two people can share a name, and one person can have multiple affiliations. A matching process should retain uncertainty, document its rules, and avoid treating a probable match as a verified identity without additional evidence.

Affiliation matching also requires care. In this example, Henri Mondor University Hospital appears both as the overall official’s affiliation and as a listed facility. That shared text is useful context, but it does not prove that the official worked at every study location or served as the contact for that site.

Worked example: reading one ClinicalTrials.gov investigator record

Start with the study key:

NCT05266235

That value anchors the ClinicalTrials.gov record for the Withings ECG Monitor validation study. Next, read the overall official as a structured object:

name: Nicolas Lellouche, MD
affiliation: Henri Mondor University Hospital
role: PRINCIPAL_INVESTIGATOR

The record supports these conclusions:

  • ClinicalTrials.gov lists Nicolas Lellouche, MD as an overall official.
  • The listed role is principal investigator.
  • The recorded affiliation is Henri Mondor University Hospital.
  • The association belongs to study NCT05266235.

The record does not establish that:

  • this person was the contact for every study location;
  • the person was employed by the institution throughout the study period;
  • another record with a similar name refers to the same individual;
  • a separate person identifier is present in the fields shown here.

Henri Mondor University Hospital is listed in Créteil, France, while other facilities are listed in Brussels, Poitiers, and Paris. The record therefore supports a distinction between the overall official’s affiliation and the study’s participating locations. It does not justify assigning the overall official to each location.

An engineering pipeline could represent the study-to-official relationship as:

study_nct_id: NCT05266235
official_name: Nicolas Lellouche, MD
official_role: PRINCIPAL_INVESTIGATOR
official_affiliation: Henri Mondor University Hospital

Site records should remain separate, with their own facility and geographic fields. This preserves what the source states instead of inferring additional person-to-site relationships.

Practical modeling for principal investigator matching

A useful schema should distinguish study-level, person-level, organization-level, and site-level concepts.

Retain the original NCT identifier and source fields. Store the official’s name, affiliation, and role independently rather than combining them into one display string. Keep sponsor and responsible-party fields separate from officials. Model locations as repeated site records because one study can list multiple facilities.

For matching, normalize cautiously:

  • Remove formatting differences without discarding the original value.
  • Treat credentials such as MD as separate attributes where possible.
  • Compare affiliations using reviewed organization mappings rather than exact string equality alone.
  • Use the NCT identifier to preserve the study relationship.
  • Record match confidence or review status when creating researcher links.

This approach supports analysis while keeping derived links distinguishable from registry-provided fields.

Limitations to keep in view

ClinicalTrials.gov records are structured public information, not a universal authority on every researcher’s identity, employment history, or site responsibilities. Field presence and detail can vary by record. Before relying on a study for official verification, check the current ClinicalTrials.gov record and its field definitions.

QOPE’s approved Clinical Trials fields include study status, phase, allocation, masking, and sponsor. Do not assume that investigator identifiers are exposed unless they are explicitly listed as available fields.

Explore clinical trial data in QOPE

QOPE is not affiliated with CMS, the FDA, or any government agency. QOPE organizes selected public healthcare data and does not replace official sources.

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