Roadmap.
Current coverage of the database, and the conditions, methods, and data releases planned for future versions.
- Six conditions: endometriosis, PMDD, PCOS, adenomyosis, vulvodynia, menopause
- Five evidence pipelines running across four research arms
- 281 signals, each scored against a published five-dimension rubric
- Run the two-rater validation study and publish the agreement score
- Add disproportionality statistics (PRR / ROR) to the adverse-event arm
- Make every citation reproduce the count it claims; finish source de-duplication
- Publish an open CSV / JSON data export with a citable DOI
- Extend to further under-researched women's health conditions
- Add complementary pipelines once the existing ones are solid
- Deepen coverage of the conditions already in scope
What Whel is, and who it is for
Whel is a research instrument: an evidence database rather than a consumer health tool or a drug-discovery algorithm. It does not tell anyone what to take, and it does not invent new compounds or predict new drug targets. What it does is build something the field currently lacks: a structured, scored, searchable evidence base for drug-repurposing signals across under-researched women's health conditions.
It gathers evidence that already exists, scattered across published literature, clinical-trial registries, adverse-event databases, genetic-target platforms, and patient communities, then grades each signal against a published rubric and makes it citable. It is closer to a small evidence lab than a website. That makes Whel useful across the research community, where different readers use it differently.
Researchers
Scored, sourced repurposing hypotheses worth taking into a formal study.
Clinician-researchers
The state of the evidence for a condition: every signal and source, at a glance.
Graduate students
An open, fundable research question in a field with unclaimed ground.
Journalists & advocates
Traceable, scored evidence to ground reporting and advocacy, not anecdote.
Institutions & funders
Where the evidence is thinnest, and where new attention would go furthest.
Why these six conditions
The six conditions Whel covers were not chosen at random, and they are not the whole picture. They were selected against three explicit criteria, and those same criteria determine how the project grows.
Shared biology
The six conditions converge on the same handful of systems: estrogen signaling, chronic inflammation, metabolic regulation, and pain processing. That biological overlap is what makes cross-condition reasoning valid: a signal in one condition can be informative about the others.
Documented neglect
Each condition carries a measurable evidence gap: long diagnostic delays, few or no treatments that address the underlying disease rather than the symptoms, and thin research funding. Whel is most useful exactly where the published literature is thinnest.
A focus on women
Whel exists to address the structural under-study of women's hormonal and reproductive health, a field that, until the NIH Revitalization Act of 1993, did not even require women in clinical research. That focus is deliberate and permanent. Every condition Whel adds will be a women's health condition.
The six conditions, mapped
Each condition is tagged with the biological systems it shares with the others, the overlap that makes cross-condition reasoning valid.
| Condition | Shared pathways | The gap |
|---|---|---|
| Endometriosis | EstrogenInflammationPain | Affects up to 10% of women of reproductive age; 7 to 10 year average diagnostic delay; no disease-modifying drug. |
| PMDD | EstrogenMoodPain | Clinically severe and cyclical; still treated mainly with imprecisely prescribed SSRIs. |
| PCOS | MetabolicEstrogenInflammation | The most common endocrine disorder in women of reproductive age; chronically under-represented in research. |
| Adenomyosis | EstrogenInflammationPain | Long under-recognized; historically confirmable only after hysterectomy. |
| Vulvodynia | PainInflammation | A chronic pain condition; among the least-studied of the six. |
| Menopause | EstrogenMetabolic | A transition every woman who lives long enough experiences; widely acknowledged to be poorly managed. |
The database is designed to grow beyond its current six conditions.
The selection criteria are explicit and repeatable, so the condition set can expand as the project's capacity grows. The section below outlines the conditions that meet those criteria and are under consideration for future versions.
Where the framework goes next
Because the selection rule is explicit, extending it is straightforward. Any women's health condition that shares biology with the existing six, carries a documented research gap, and has enough of an evidence base to surface signals is a candidate. The conditions below illustrate where the framework points. They are not yet covered, and the final list remains a research and editorial decision. The scope itself will not change: Whel stays within women's hormonal and reproductive health.
Interstitial cystitis / bladder pain syndrome
A chronic pelvic pain condition that frequently co-occurs with endometriosis, predominantly affects women, and carries long diagnostic delays.
PainInflammationUterine fibroids
Extremely common and estrogen-driven, yet undertreated relative to prevalence; shares hormonal biology directly with adenomyosis and endometriosis.
EstrogenInflammationPrimary ovarian insufficiency
Hormonal and metabolic; extends the existing menopause arm to women who reach that transition far earlier than expected.
EstrogenMetabolicPerinatal mood conditions
A hormonally driven transition with severe consequences and a thin, only recently growing treatment literature.
EstrogenMoodLipedema
A metabolic and inflammatory condition that affects women almost exclusively and is routinely misdiagnosed; among the most neglected in the field.
MetabolicInflammationIllustrative only; these conditions are not yet in the database.
Strengthening the evidence engine
The most valuable near-term work is to make the existing engine more rigorous before adding new data sources. The priorities below come directly from Whel's own methods document and from the project's first independent review. New conditions are worth little if the evidence behind each signal is not as solid as it can be.
| Source / method | Role | Status |
|---|---|---|
| PubMed | Published literature | ● Live |
| ClinicalTrials.gov | Trial registry | ● Live |
| FDA AEMS (openFDA) | Adverse-event data | ● Live |
| Open Targets | Genetic-target & pathway data | ● Live |
| Reddit communities | Patient-reported signal | ● Live |
| EudraVigilance | European adverse-event data; populate or formally retire | ● Under review |
| SIDER | Drug side-effect reference; populate or formally retire | ● Under review |
| Disproportionality statistics (PRR / ROR) | Method upgrade to the adverse-event arm | ● Planned |
| Two-rater validation study | Reliability measurement (Cohen's kappa) | ● Planned |
| Open data export | CSV / JSON under CC BY 4.0, with a Zenodo DOI | ● Planned |
| DrugBank | Drug-target & indication data | ● Planned |
Disproportionality statistics
Pharmacovigilance has a standard way of separating a real adverse-event signal from background reporting noise: the proportional reporting ratio and reporting odds ratio. Adding even a basic PRR / ROR calculation to the adverse-event arm, using data Whel already holds, is the single biggest credibility upgrade available to the project.
The validation study
Whel's central claim is that it can grade evidence. The methods document already designs the test: a stratified sample of signals, re-scored blind by two independent human raters, with agreement reported as Cohen's kappa. Running it, and publishing the result whatever it turns out to be, converts every confidence tier from model output into a measured claim.
Open data
A CSV / JSON export under a CC BY 4.0 license, deposited with a DOI, makes Whel citable. A tool other researchers can cite enters the research record; one they cannot remains only a website.
A living page
This roadmap is a dated document, and it will change. Whel is released as dated snapshots rather than a live feed, and its priorities are shaped by feedback from researchers, clinicians, and the patient communities whose reported experience the database draws on, about which gaps matter most. If you work in one of these fields, that feedback is welcome.