Indexing Human Advancement
Frontier drugs are reshaping human outcomes at every scale -- an individual reversing metabolic disease, a population gaining years of healthspan, a healthcare system bending its cost curve. The evidence is accumulating in real time. But no system is measuring it.
Advancement is the asset
A compound that moves a clinical endpoint, shifts population health outcomes, or unlocks a new therapeutic category is not just a molecule. It is evidence of human progress. That evidence has real value -- at the micro level, it changes what an individual can do with their body. At the macro level, it reshapes how societies allocate resources, how insurers price risk, and how economies absorb the cost of disease.
But the current system cannot match the pace of this progress. Clinical trials take years to publish. Regulatory approvals lag adoption by a decade. Social discourse moves faster than institutions can process it. The result is a landscape where the most consequential compounds are legible only in fragments -- a trial recruiting here, a subreddit noticing there, a search curve bending somewhere else.
The evidence of advancement exists. It is scattered across ClinicalTrials.gov, PubMed, arXiv, Reddit, Google, FDA databases, and fragmented pharmacy and equity data. No single system synthesizes it. No instrument measures it. We built one.
A composite measure of real-world compound traction
The Advancement Index is our answer. It aggregates six independent signal dimensions into a single, continuously updated score for each compound we track. The index does not predict outcomes. It measures observable momentum -- what is actually gaining traction right now across the systems that matter.
We currently track 95+ compounds across 11 categories, from GLP-1 receptor agonists to bioregulator peptides. The index updates in real time as new data arrives from each source.
Six independent vectors, one score
We aggregate raw engagement and activity data from public and institutional sources. Each metric is log-transformed to stabilize variance across power-law distributions, then normalized to a 0-100 scale before weighting.
| Source | What we measure |
|---|---|
| Post volume, engagement, sentiment, subreddit spread across 56 monitored communities | |
| Google Trends | Search interest, momentum, rising related queries |
| OpenAlex + PubMed + arXiv | Published papers, preprints, recency, citation velocity |
| ClinicalTrials.gov | Registered trials, actively recruiting, phase progression |
| FDA / openFDA | Approval status, label count, brand names |
| Market data | Stock price momentum, trading volume for companies with compound exposure |
How the score is constructed
The index is built in three layers. The first combines raw signals using predefined weights. The second applies exponential moving average smoothing with a 12-hour half-life to filter transient noise. The third layer uses a Bayesian rating system that encodes longer-term structural knowledge about each compound's trajectory.
EMAt = EMAt-1 + α × (Rawt - EMAt-1)
Final Score = 0.7 × EMA + 0.3 × Bayesian μ
Research velocity carries the highest weight because clinical and academic evidence is the least gameable signal. Social and search data capture early-stage interest before institutional awareness catches up. Regulatory status anchors the score in observable, binary milestones. Market signal is weighted lowest -- it follows, rather than leads, genuine advancement.
Encoding compound history as a prior
Raw scores are noisy. A single viral Reddit post can move a compound's social signal by 40 points in a day. The Bayesian layer solves this by modeling each compound as a probability distribution -- a mean estimate of its advancement level and a confidence interval around it.
New compounds start with high uncertainty. As data accumulates over days and weeks, the model tightens its estimate. A compound that scores consistently high earns a stable prior that resists transient drops. A compound riding a single spike will see its Bayesian score remain conservative until sustained evidence confirms the trend.
What the labels mean
Each compound receives a human-readable signal label based on its current score and momentum. These are not predictions -- they describe the current state of observable traction.
| Label | Criteria |
|---|---|
| Surging | Score above 75 with accelerating momentum above 10% |
| Rising | Score above 60, or above 45 with strong momentum above 15% |
| Stable | Score above 35 with sustained, consistent interest |
| Cooling | Score above 20 but declining |
| Dormant | Below 20 with minimal current activity |
The index grows itself
We do not maintain a fixed list. The system continuously scans social and research sources for new compound mentions, validates them against academic databases, and adds them to the index automatically. The catalog started with 73 seed compounds. It now tracks over 95, and that number increases as real-world interest surfaces new candidates.
From measurement to infrastructure
The Advancement Index answers a narrow question: which compounds are genuinely advancing right now? But the evidence it synthesizes has implications beyond scoring. The same signals that tell you a compound is surging -- trial activity, regulatory milestones, real-world adoption -- are the foundation for compliance systems, risk models, and routing infrastructure.
We are building toward regulatory-compliant systems for the frontier drug landscape. The index is the first layer. What comes next is shaped by what the data demands.
We publish our methodology because transparency is a prerequisite. If the score cannot be explained, it cannot be trusted. And if it cannot be trusted, it has no value as infrastructure.
Not medical advice. Not investment advice. The Advancement Index is provided for informational and research purposes only. Signal data reflects observable public activity and does not constitute a recommendation to buy, sell, or use any compound.