Section 11 – Toxicological Information: The Science Behind the Hazard
Jan ••
#SDS#Section 11#Toxicology#REACH#CLP#SHEQ
Section 11 – Toxicological Information: The Science Behind the Hazard
Understanding what lies beneath the classifications in your SDS
Every Safety Data Sheet tells a story, but few sections go as deep into the science as Section 11 – Toxicological Information.
It is the part that many skip over, filled with technical terms, test results, and biological jargon.
Yet this section is where hazard classification begins.
For SHEQ managers, Section 11 is the bridge between toxicology data and real-world worker safety.
It explains how a substance can harm, how much exposure matters, and which data justify the risk statements that appear in Section 2.
What Section 11 Contains
Section 11 summarises toxicological properties of a substance or mixture, based on scientific testing and available data.
According to REACH Annex II and the CLP Regulation, it must describe, in clear and consistent terms, what happens when a person is exposed through different routes: inhalation, skin contact, ingestion, or eye exposure.
Typical contents include:
Acute toxicity
This describes the harmful effects that occur shortly after a single exposure.
Expressed as LD₅₀ (lethal dose, mg/kg body weight) or LC₅₀ (lethal concentration, mg/L of air).
Tests are historically performed on rats (oral and inhalation) and rabbits (dermal), because their physiology and absorption pathways are well-characterised and standardised under OECD guidelines.
These data are used to assign hazard categories such as “Toxic if swallowed (H301)” or “Harmful if inhaled (H332)”.
Increasingly, QSAR models and bridging data are replacing direct testing, especially for mixtures and structurally similar substances.
Skin corrosion and irritation
Describes whether the substance damages or irritates the skin after contact.
Older studies used rabbits, but these are now largely replaced by in vitro reconstructed human epidermis models (OECD 431, 439).
Results lead to classifications like “Causes severe skin burns (H314)” or “Causes skin irritation (H315)”.
Serious eye damage and irritation
Eye irritation studies historically used rabbits (OECD 405).
Today, non-animal tests such as BCOP (Bovine Corneal Opacity and Permeability) or EpiOcular™ models are widely accepted.
Classifications include “Causes serious eye damage (H318)” or “Causes eye irritation (H319)”.
Respiratory or skin sensitisation
Sensitisers trigger allergic reactions even at very low exposure levels.
The Guinea Pig Maximisation Test and Buehler Test were traditionally used.
These are now largely replaced by in vitro assays (like h-CLAT or DPRA) or Local Lymph Node Assay (LLNA) in mice, which provides quantitative data with fewer animals.
Sensitisers are classified as “May cause an allergic skin reaction (H317)” or “May cause allergy or asthma symptoms if inhaled (H334)”.
Germ cell mutagenicity
Indicates whether a substance can cause DNA or chromosomal mutations.
In vitro assays such as Ames tests (using bacteria) or mammalian cell mutation tests are the first step.
If these show concern, follow-up studies in rodents verify whether mutations occur in bone marrow or germ cells.
Substances with clear genotoxic potential may be labeled “May cause genetic defects (H340)”.
Carcinogenicity
Carcinogenicity testing studies long-term exposure in rats or mice over most of their lifespan.
These species are used because they share similar metabolic pathways with humans and can develop comparable tumor types.
Such studies form the scientific basis for classifications like “May cause cancer (H350)”.
Reproductive toxicity
Evaluates effects on fertility, embryo development, or offspring health.
Studies are carried out in rats or rabbits, covering prenatal and multigenerational effects.
Substances like certain phthalates or lead compounds are classic examples.
Classification outcomes include “May damage fertility or the unborn child (H360)”.
Specific target organ toxicity (STOT)
Describes non-lethal effects on organs after single or repeated exposure.
Animal studies, often in rats or mice, track changes in organ weight, blood chemistry, or tissue pathology.
Data are used for hazard categories like “May cause damage to organs through prolonged exposure (H373)”.
Two key categories are distinguished:
STOT-SE (Single Exposure) for immediate effects such as drowsiness or dizziness.
STOT-RE (Repeated Exposure) for chronic effects like liver or kidney damage.
Aspiration hazard
Relevant mainly for low-viscosity liquids like mineral oils or solvents.
Animal studies in rats help identify whether substances enter the lungs upon swallowing or vomiting.
Results support classification as “May be fatal if swallowed and enters airways (H304)”.
Additional information and human experience
Includes case studies, occupational health surveillance data, or clinical findings.
Sometimes it summarises neurotoxicity or endocrine effects that are not yet formally classified but are under scientific review.
Each of these toxicological endpoints links directly to the hazard statements you find in Section 2, making Section 11 the scientific backbone of the SDS.
Why Animal Testing Is Still Referenced
Although the EU actively promotes non-animal testing under REACH and OECD guidelines, much of the historical toxicological evidence comes from animal studies.
These data remain essential because:
They form the scientific baseline for current classifications.
They are required when alternative methods are not yet validated for certain complex endpoints (like carcinogenicity or developmental toxicity).
They allow read-across between similar substances, reducing new testing needs.
However, modern toxicology increasingly relies on alternative, human-relevant approaches.
Modern Alternatives to Animal Testing
Toxicology is changing rapidly.
While most of the data in existing Safety Data Sheets still come from historical animal studies, today’s REACH and OECD strategies encourage non-animal scientific methods.
1. In vitro models using human cells or reconstructed tissues
“In vitro” means “in glass.” These tests are performed in cell cultures or engineered tissue models.
They use human-derived cells or reconstructed skin and eye tissues, such as EpiDerm™ or EpiOcular™, to mimic how chemicals interact with human biology.
Tests measure cell viability, membrane damage, or enzyme activity, offering more direct insight into human responses.
They are now standard for skin corrosion, irritation, and eye irritation, and are increasingly applied to genotoxicity and endocrine screening.
These models improve scientific relevance and allow faster, reproducible results without involving animals.
QSAR models are computational algorithms predicting toxicity from molecular structure.
They work on the principle that substances with similar structures show similar effects.
Using extensive datasets of known results, they estimate acute toxicity, mutagenicity, or bioaccumulation potential.
Under REACH, validated QSAR predictions can replace experimental data if documented according to OECD QSAR validation principles.
ECHA’s QSAR Toolbox is a leading platform supporting this approach, making it easier for companies to fill data gaps ethically and efficiently.
3. In silico databases and read-across frameworks
“In silico” refers to computer-based methods, including read-across and large toxicological databases.
Read-across allows using data from one substance to predict another that is structurally similar.
ECHA’s Read-Across Assessment Framework (RAAF) ensures these predictions are scientifically robust.
Databases like the ECHA REACH database, OECD eChemPortal, and IUCLID store high-quality toxicological data for reference.
Together, these tools reduce testing needs and strengthen the evidence base for chemical safety assessments.
Why Section 11 Matters
All the hazard statements and classification codes in Section 2 (Hazard Identification) are built from the data presented in Section 11.
Without the toxicological evidence here, there is no scientific basis for labeling a product as harmful, toxic, or sensitising.
It also supports:
Exposure control decisions in Section 8, by identifying critical effects and relevant exposure routes.
First aid guidance in Section 4, which depends on understanding the mechanism of toxicity.
Ecological risk assessments in Section 12, where human toxicity parallels environmental concern.
For occupational health teams, Section 11 provides the background to understand why certain DNELs or OELs exist and how health effects can be prevented through proper control measures.
Where the Data Come From
Toxicological data in Section 11 are drawn from:
Animal studies (OECD guideline tests)
In vitro assays (cell or tissue models)
Human case reports or epidemiological studies
Read-across data from similar substances
QSAR and in silico predictions
These data are submitted to ECHA’s REACH dossiers by manufacturers and importers.
SDS authors summarise this evidence to provide a readable version for end users, focusing on results that justify classification.
Because new data constantly emerge, outdated SDSs might miss critical findings such as reclassification as carcinogenic, new endocrine effects, or revised toxicity thresholds.
The NextSDS Perspective
At NextSDS, we go beyond the surface of Section 11.
Our platform extracts toxicological data and classification triggers directly from SDSs, linking them with REACH dossiers and ECHA updates.
This allows companies to:
Verify if Section 11 reflects the latest test results and hazard classes.
Identify when a substance has new toxicological evidence pending SDS update.
Connect human health data to exposure scenarios and DNEL calculations.
Toxicology is complex, but keeping it transparent is what turns compliance into protection.
Section 11 is where chemistry meets biology.
It translates molecules into human effects, and data into prevention.
For SHEQ professionals, understanding what lies here means not just knowing what a product is, but what it does.
See how NextSDS can help you keep your toxicological information accurate and connected to the latest REACH data. Learn more.
