---
license: cc-by-nc-4.0
pretty_name: SuppDB — Supplements & Nootropics Dataset (Free Sample)
tags:
- health
- chemistry
- supplements
- nootropics
- nih-dsld
- pubchem
- recommender-systems
size_categories:
- 1K<n<10K
---

# 💊 SuppDB — Supplements & Nootropics Dataset (Free Sample)

A **free sample** of SuppDB: a structured dataset of real supplement & nootropic products built **exclusively from the public [NIH Dietary Supplement Label Database (DSLD)](https://dsld.od.nih.gov/)** — every active ingredient normalized to **milligrams**, proprietary blends flagged where the dose is undisclosed, and compounds enriched with **NIH PubChem** chemical identity. Think *INCIDecoder for supplements*: one row per active ingredient, with dose, form, safety reference, and molecular identity.

**This sample contains 2,249 ingredient records across 300 real products from 218 brands.**

The **full dataset covers 17,000+ products, 2,000+ brands, 115,000+ active-ingredient records, and 40,000+ proprietary-blend flags** (SQLite · CSV · JSON).

## Get the Full Dataset

* 🔗 **Official Portal:** [suppdb.net](https://supplements-nootropics-suppdb.pages.dev) — full snapshot $99 one-time
* 🏆 **Kaggle:** [SuppDB Supplements Sample](https://www.kaggle.com/datasets/ahtiticheamine/suppdb-supplements-sample)
* 💊 **Interactive Explorer:** [Dataset Sample Explorers Space — SuppDB tab](https://huggingface.co/spaces/Ichlibitiche/dataset-sample-explorers)

## Key Columns

| Column | Description |
| :--- | :--- |
| `brand`, `product_name`, `upc_barcode`, `form_type` | Product identity as printed on the label |
| `ingredient`, `ingredient_form`, `ingredient_category` | Active ingredient per row |
| `amount_per_serving_mg` | Dose normalized to mg (`mcg`, `g`, substance-specific `IU` handled correctly) |
| `is_proprietary_blend` | `1` where the dose is hidden in a proprietary blend (`amount = 0`) — transparency, not omission |
| `recommended_daily_mg`, `upper_safety_limit_mg` | NIH DRI reference intakes; NULL where no official value exists |
| `pubchem_cid`, `molecular_formula`, `molecular_weight`, `canonical_smiles`, `inchikey` | PubChem chemistry — InChIKey canonicalizes the same molecule across label names |
| `dsld_label_id`, `source_url` | Exact NIH DSLD label page — every record re-verifiable |

## Quick Start

```python
import pandas as pd

df = pd.read_csv("hf://datasets/Ichlibitiche/suppdb-supplements-sample/suppdb_sample.csv")
print(len(df), "ingredient records,", df["product_id"].nunique(), "products,", df["brand"].nunique(), "brands")
hidden = df[df["is_proprietary_blend"] == 1]
print(len(hidden), "ingredients with doses hidden in proprietary blends")
```

## Use Cases

- AI health co-pilots & supplement recommendation apps (structured dose + chemistry data)
- Ingredient/dose comparison and proprietary-blend transparency tools
- ML / RAG corpora over supplement labels
- Formulation, market, and assortment research across brands and ingredient categories

## License

Sample data: **CC BY-NC 4.0** — attribution, non-commercial. Full dataset commercially licensed at [suppdb.net](https://supplements-nootropics-suppdb.pages.dev); underlying facts are public-domain U.S. Government data (NIH DSLD + PubChem) — the license covers SuppDB's curated, normalized compilation. **Not medical advice** — always verify against the current physical label. Contact: `suppdb.doorframe589@simplelogin.com`.