Boundaries
What this is, and firmly
What this is, and firmly
what it is not.
Throughline works exclusively on records that already exist, about care that has already been delivered. That single sentence draws most of the boundary.
| Dimension | What we do | What we do not do |
|---|---|---|
| Input | Records already collected in the course of care: notes, encounters, medications, procedures | No biological samples, no assays, no laboratory work of any kind |
| Time direction | Retrospective. What was documented and what followed | No prediction of whether an individual patient will respond to a therapy |
| Scientific claim | Signal and association, surfaced with its evidence, for qualified people to interpret | No causal claim, no biomarker discovery, no target identification, no mechanism |
| Regulatory posture | Analytics under the customer's own governance and data-use terms | Not a medical device, not FDA-cleared, not a diagnostic, not clinically validated |
| Clinical role | Input to review by clinicians, researchers, and medical affairs professionals | Never a treatment recommendation, and never a substitute for clinical judgment |
| Manufacturer output | De-identified, population-level, under the customer's terms | No patient-level data, no re-identifiable output, no assumption of anyone's pharmacovigilance obligation |
Stated plainly, because the distinction is easy to blur
- We are not a life-sciences discovery company. We do not do proteomics, genomics, or any wet-lab science, and we never will
- We do not predict which patient will respond to a drug. Companies that do that work from laboratory measurements we do not generate and would not attempt to
- Our contribution is engineering: the governed, auditable data layer between records and analysis. It sits underneath scientific work; it is not scientific work
- Throughline is in development. There is no published result and no validation study yet
Complement, not competitor
We are the layer under the science, not the source of it.
Organizations doing genuine discovery science (generating novel measurements in a lab and building models on them) need a records layer that is HIPAA-boundaried, auditable, and citable, and they generally would rather not build one. That is the work we do. Different question, different input, different part of the value chain.