Methodology

How We Score Ingredient Safety

Our methodology for the 34,000+ ingredient safety assessments powering theformulator.ai

Every formulation generated on theformulator.ai includes per-ingredient safety scores across six hazard axes. This page explains how those scores are calculated, what data sources feed them, and why we built a proprietary system instead of licensing an existing one.

Why existing safety databases fall short for formulators

The two most widely referenced ingredient safety databases — EWG Skin Deep and SkinSafe — were designed for consumers, not formulators. This creates fundamental problems when R&D teams try to use them as data inputs for formulation decisions.

EWG Skin Deep scores approximately 11,500 ingredients. Its methodology applies a data gap penalty: ingredients with limited safety studies receive elevated hazard scores. For a formulator working with novel or niche raw materials, this means an absence of negative evidence gets treated as evidence of harm. The scoring algorithm is opaque — weights and methodology are not published. Exposure context (whether an ingredient appears in a leave-on serum at 2% or a rinse-off shampoo at 0.5%) is not factored into the score. And the database is consumer-facing, with framing that tends toward alarmism rather than risk-based assessment.

SkinSafe takes a different approach, focusing on allergen and irritant avoidance based on Mayo Clinic data. While clinically grounded for contact dermatitis, it does not cover the full hazard spectrum that regulatory affairs teams need — carcinogenicity, reproductive toxicity, and endocrine disruption are outside its scope.

Neither system provides per-market regulatory status. A formulator developing for both EU and China needs to know that an ingredient permitted in Europe may be prohibited or restricted under NMPA — this cross-market view does not exist in consumer-facing databases. Neither system updates automatically from primary regulatory sources. Neither system adjusts scores based on product type or exposure duration.

We needed a scoring system that:

• Draws from the same primary sources regulatory authorities use
• Treats absence of data honestly — as a data gap, not a hazard signal
• Accounts for exposure context (leave-on vs rinse-off)
• Covers the full hazard spectrum across six independent axes
• Provides per-market regulatory intelligence alongside safety scores
• Updates from primary sources automatically, not via periodic manual review

Six axes of hazard assessment

Each ingredient is scored 0–10 on six independent hazard axes. A composite score is calculated, but all six axis scores are always visible to the formulator — because a single number hides critical information.

Five principles that guide our scoring

1. 1

   No data gap penalty

   If an ingredient has no studies addressing a particular hazard axis, that axis scores 0 — not an elevated score. Absence of evidence is not evidence of harm. This is the single largest methodological difference between our system and EWG Skin Deep, which inflates scores for under-studied ingredients. A novel botanical extract with limited toxicology literature should not receive a higher hazard score than a well-studied petrochemical with confirmed clean safety data.

2. 2

   Exposure context matters

   The same ingredient at the same concentration poses different risks in a leave-on facial serum (hours of skin contact) versus a rinse-off shampoo (30 seconds of contact). Our scoring applies an exposure modifier based on product type. This is standard practice in regulatory toxicology — SCCS and CIR both evaluate safety in the context of exposure — but is absent from consumer-facing databases.

3. 3

   Source hierarchy

   Not all safety data is equal. Peer-reviewed regulatory assessments (ECHA CLP, SCCS opinions, CIR final reports) carry more weight than preliminary findings or supplier-provided data. Our system enforces a clear hierarchy: regulatory authority classifications first, then peer-reviewed clinical data, then curated literature. Scores from higher-tier sources are never downgraded by lower-tier data.

4. 4

   Confidence tiering

   Every safety score carries a confidence level: high (direct ECHA, CIR, or IARC classification), medium (extracted from peer-reviewed literature or CIR group assessments), or low (baseline from COSING registration with no hazard evidence found). Only medium and high confidence scores are displayed to users. Low confidence ingredients show "No hazard data available in our sources" rather than a green score that implies safety has been confirmed.

5. 5

   Conservative on carcinogenicity

   Carcinogenicity is treated asymmetrically. A known carcinogen classified by IARC or NTP cannot have its composite score pulled below a floor by clean scores on other axes. When multiple sources provide different carcinogenicity classifications, the highest (most conservative) score is retained. This reflects the irreversible nature of carcinogenic harm compared to reversible irritation.

Where our data comes from

All extraction pipelines run automatically. Regulatory source pages across 16 markets are monitored daily for changes. When a regulatory authority updates an ingredient classification or restriction, the change is detected via content hashing, logged as a structured event, and propagated to affected safety scores without manual intervention.

Safety scores are only half the picture

An ingredient can score well on all six hazard axes and still be prohibited in your target market. Formaldehyde releasers are a clear example — permitted with concentration limits in some markets, banned outright in others. Safety scoring without market-specific regulatory status is incomplete.

Every ingredient in our system carries per-market regulatory status across 16 markets: EU, US (FDA), China (NMPA IECIC), Japan (MHLW), South Korea (MFDS), India (BIS IS 4707), Canada, Australia (TGA), Brazil (ANVISA), Thailand, Malaysia (NPRA), Singapore (HSA), Indonesia, Vietnam, Philippines, and ASEAN harmonised standards. Status categories include: permitted, restricted (with maximum concentrations, required labelling, and product-type limitations), prohibited, and not listed.

What we deliberately exclude

This methodology is not static. As regulatory authorities update classifications, as new clinical data enters the peer-reviewed literature, and as our automated pipelines expand coverage, scores are refined. We publish this methodology because transparency is a prerequisite for trust — and trust is what separates a tool formulators rely on from one they dismiss.

Last updated: April 2026