Henry Wei Manager   •   about 2 years ago

IDEA/NEED: predicting good clinical trial investigators

EXAMPLE OF A POTENTIAL TRACK 2 ENTRY AREA OF NEED:
Today, most industry clinical trial sponsors do what’s called “site feasibility” analyses, referring to the potential clinical trial sites, largely based on analyzing databases of clinical trial investigators. These are usually databases of investigators who have had their info added to a clinical trial registry (like clinicaltrials.gov, or proprietary sources like Citeline), had their data included in other databases derived from IRB submissions (e.g. WCG and Advarra are two common industry-facing central IRB services who also offer site feasibility services). Some are cross-referenced against large physician datasets, such as the publicly-available NPI dataset maintained by CMS, in a system called NPPES.
https://download.cms.gov/nppes/NPI_Files.html

Although clinicaltrials.gov has some information about trial locations, they often include only the sponsor-level investigator over the whole study, rather than the individual sites' investigators, often called PIs (principal investigators), at every location. https://classic.clinicaltrials.gov/ct2/resouces/download

The FDA also has a database called BMIS that aggregates information from something called Form 1572, a form that each clinical investigator in a trial – particularly industry-sponsored new drug trials – is required to complete.
https://www.fda.gov/drugs/drug-approvals-and-databases/bioresearch-monitoring-information-system-bmis

Conversely, some investigators have been found to violate different regulatory requirements. These are sometimes found in FDA’s 483 Letters, a type of warning letter usually based on inspection findings. Such a warning letter would be a potential indicator of a lower quality investigator or site.
https://www.fda.gov/inspections-compliance-enforcement-and-criminal-investigations/compliance-actions-and-activities/warning-letters

THE PROBLEM: These databases tend to only list investigators who have *already done* clinical trials, especially industry-sponsored trials. Most investigators on industry-sponsored trials are physicians. These individuals may do non-industry, government-funded clinical trials, as well as industry-sponsored trials.

At some point in the past, however, these physicians had not yet done any clinical trials. So a major opportunity is to identify emerging talent i.e. predicting investigators who are likely to go on to be principal investigators for a series of multiple industry-sponsored trials.

An additional twist is that these investigators may move their location or institution over time, and/or certain sites or institutions may be better at producing future investigators for industry-sponsored trials. So not only predicting, but understanding the driving factors such as institution, specialty, experience, or otherwise can be helpful.