For data and research buyers such as biotech, pharma, CRO, academic, DeSci, payer, and other teams evaluating governed real-world evidence or data access.
Can the inputs support useful analysis?
The data-quality page explains the inputs before a buyer evaluates governance. It separates contextual wearable trends, protocol logs, and lab anchors so the RWE story does not feel like an unsupported black box.
Wearable context
Wearable windows provide physiological context around labs and protocol events. They are treated as contextual signals, not standalone clinical conclusions.
- Sleep and recovery windows
- Resting heart-rate context
- Autonomic trend summaries
Protocol logs
User-recorded protocols give analysts the timing and intervention context needed to interpret longitudinal changes.
- Compound or blend naming
- Route and timing context
- Phenotype and symptom notes
Lab anchors
Lab panels anchor the evidence loop with discrete biomarker values that can be reviewed against wearable and protocol context.
- Cardiometabolic markers
- Endocrine and organ-function markers
- Inflammatory and hematology markers
Quality review comes before data access.
Partner evaluation should inspect coverage, freshness, missingness, consent scope, and de-identification requirements before any dataset is scoped. This page describes the input model; it does not claim clinical validation or production readiness.
Next, review access governance.
Once the buyer understands the inputs, the next question is how consent, de-identification review, DUA scope, and partner access boundaries work.