DISCLAIMER: The tools, as they currently stand, are provided for research and informational purposes only. The underlying models, assumptions, data sources, and methodologies are experimental and might have not yet been peer-reviewed or independently validated. Outputs may be incomplete, uncertain, or inaccurate and should be interpreted with caution. The tools do not provide regulatory, medical, legal, toxicological, or professional risk assessment advice. For the time being, it must not be used as a substitute for expert judgment, regulatory review, or established risk-assessment frameworks, nor relied upon for decision-making related to human health, environmental protection, occupational safety, product registration, compliance, or policy.
Use of these tools for unlawful, harmful, misleading, or unethical purposes—including but not limited to regulatory circumvention, misrepresentation of risk, or inappropriate application to real-world pesticide use decisions—is strictly prohibited. The tool is provided “as is,” without warranties of any kind, express or implied, including but not limited to accuracy, fitness for a particular purpose, or non-infringement.

Results - Tier 1

Summary

Aim of Tier 1

The goal was to use available data and biomonitoring data on over 200 pesticides from the SPRINT survey 2021 to perform in silico modelling to:

  • Identify the Top 20 pesticides of concern.
  • Select the Top 10 to be studied in lab (in vitro) in Tier 2.

A systematic procedure to prioritise the Top 10 pesticides of concern for in vitro toxicology testing has been developed (see graph below).

Methods of Tier 1

A step-by-step procedure was followed to rank and prioritize pesticides:

Step A – Occurrence (banned or not, how often they were found in the environment…)

Step B – Hazard Assessment (data from EFSA and biomonitoring, weighted Hazard Quotient…)

Step C – Final Selection (Synthesis)

Results of Tier 1

A final list of Top 10 pesticides was selected for in vitro testing in Tier 2.

Aims

Tier 1 aimed to use available data and in silico modelling to assess the top 20 pesticides of concern and prioritize the Top 10 pesticides of concern to be studied via in vitro models and physiologically- based kinetic (PBK) modeling (Tier 2).

Methodology

A systematic procedure to prioritise the Top 10 pesticides of concern for in vitro toxicology testing has been developed (see graph below).

Results

The SPRINT standard mixture (in yellow) and the top ten ranking pesticides for in vitro studies were identified and ranked, with the number referring to the rank by occurrence, wHQ and N as the number of samples in the current SPRINT CSS database:

Rank

pesticidea

Group

F+N

wHQ

C

wHQ

Water solubility
(mg/L at 25°C)

Log Po/wb

1

Lambda-Chalothrin

Insecticide

2.5E-03

6.1E-04

None

6.8

2

Cypermethrin (N=100)

Insecticide

8.6E-04

2.7E-04

0.01

6.6

3

Deltamethrin (N=55)

Insecticide

3.3E-04

2.6E-04

<0.002

6.2

4

Tebuconazole (N=99)

Fungicide

2.4E-04

1.1E-04

36

3.1

5

Glyphosate (N=74)

Herbicide

1.3E-04

3.1E-05

12000

-3.4

6

Acetamiprid (M) (N=22)

Insecticide

9.8E-05

5.8E-06

4250

0.60

7

Cyprodinil (N=19)

Fungicide

3.2E-05

4.2E-05

13.9

3.59

8

Piperonyl butoxide (N=37)

Pesticide synergism

2.6E-05

1.8E-05

14.3

4.75

9

Fluopyram (N=26)

Fungicide

2.2E-05

1.3E-06

16

3.3

10

Imazalil (N=10)

Fungicide

1.09E-05

2.7E-05

14

4.6

F + N = farmers + neighbours; C = consumers;

a Folpet was removed from rank 4 because the metabolite used for occurrence is not specific for this chemical;

b British Crop Protection Council C, ed; e-Pesticide Manual. 15th ed., ver. 5.1, Alton, UK;