L22 Human Risk Assessment PDF

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TolerableBliss

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Vrije Universiteit Amsterdam

2024

Timo Hamers

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Human toxicology Risk assessment Environmental toxicology Health risk

Summary

This document discusses human risk assessment, including the comparison of toxic risks and the calculation of disability-adjusted life years (DALYs). It covers topics such as the Paracelsus paradigm, the relationship between risk, hazard, and exposure, and the REACH requirements for human toxicity data. The document also explores compounds with and without threshold values, such as acrylamide, and provides an overview of the risk assessment of various factors.

Full Transcript

6/19/2024 L22 Human Risk Assessment Timo Hamers 1 Set-up  What is risk?  Comparison of risks by toxic compounds to other risk factors  How can critical exposures be determined? Compounds...

6/19/2024 L22 Human Risk Assessment Timo Hamers 1 Set-up  What is risk?  Comparison of risks by toxic compounds to other risk factors  How can critical exposures be determined? Compounds with and without a threshold value  Case-study Dioxins 2 1 2 6/19/2024 Paracelsus paradigm Paracelsus (1493-1541): „All Ding' sind Gift und nichts ohn' Gift; allein die Dosis macht, dass ein Ding kein Gift ist.“ 3 3 Risk = Hazard x Exposure 4 2 4 6/19/2024 Risk Assessment: part of Risk Management 5 5 Comparison of toxic risk to other risk factors  Toxic compounds versus overweight, traffic participation, etc  Express risks in terms of lost life years  Disability Adjusted Life Years (DALY) (for handicaps adjusted life years) 6 3 6 6/19/2024 Disability Adjusted Life Years (DALY)  DALY = YLL + YLD Years of Life Lost (YLL): years lost due to premature death Years Lost to Disability (YLD): years lived with disease  with YLL = n x standard life expectation in year of death YLD = n x handicap weight x duration disease till recovery or death  Example 1: Obese man gets diabetes type II at age of 27 and dies at age of 67 Life expectation: 75 years; diabetes has weight 0.2 DALY = 1x8 + 1x0.2x40 = 16 years  Example 2: 3000 people die in NL 10 years premature due to diabetes type II 1100000 people suffer from diabetes type II, with weight 0.2 Annual DALY loss in NL for diabetes = 3000x10 + 1100000x0.2 = 250000 years!!! (numbers are approximates) 7 7 Acrylamide  Industrial application Raw material for polyacrylamide Application in water treatment, oil drilling, sewage repair, PAGE, ….  Side product formed during heating of food “Cooking toxicants” Especially in starch-rich products at 180 ºC or higher 8 4 8 6/19/2024 Acrylamide Dearfield et al., 1995 9 9 Acrylamide  Carcinogenic compound  100 persons die per year On average 5 years lost of expected lifetime On average 2 years ill (50% disabled) DALY = 100 x 5 + 100 x 0.5 x 2 = 600 years 10 5 10 6/19/2024 “Ons eten gemeten” - RIVM 11 11 “Ons eten gemeten” - RIVM  DALY per year Smoking: 350 000 Unhealthy food: 300 000 – 400 000 Food infections: 1000 – 4000 Toxic compounds < 1000 Traffic accidents: 69 000 12 6 12 6/19/2024 DALY for different risk factors in The Netherlands Subject YLL YLD Scale YLL or YLD Asbestos A # ? unknown or uncertain Pesticides in water 0 ? # Data available, but not as Soil quality incl groundwater A/B ? YLD Drones/RPAS ? ? 0 No Electromagnetic fields A ? A 0-10 Noise B/C E B 10-100 Endocrine disrupting compounds ? ? C 100-1000 Nuclear plants 0 0 D 1000-10000 Ionizing radiation C/D C E >10000 Air quality E E Microplastics ? ? Nanomaterials ? ? New biotechnology ? ? Olivine ? ? External safety (transport of chemicals) 0 0 Shale gas ? ? Chemical substances A/B D UV radiation D D Air traffic A # Water traffic B # Rail traffic B # RIVM, 2017. Road traffic D E Water quality C C Een scan van de veiligheid en kwaliteit Water safety 0 0 van onze leefomgeving Self-conducting cars ? ? 13 13 Set-up  What is risk?  Comparison of risks by toxic compounds to other risk factors  How can critical exposures be determined? Compounds with and without a threshold value  Case-study Dioxins 14 7 14 6/19/2024 Risk assessment of compounds 15 15 Risk = Hazard x Exposure  Hazard Intrinsic character of the compound Qualitative (Hazard identification) > E.g. this compound causes infertility Quantitative (Hazard characterization) > E.g. NOAEL, LOAEL, …  Exposure Quantitative measure for the presence of hazard Exposure assessment > E.g. dose (mg per kg bodyweight per day)  (Vulnerability)  Risk Probability that a negative effect will occur (risk characterization) 16 8 16 6/19/2024 Compounds with a threshold value 110 Criticism to NOEC/LOEC: 100 Equal to test concentration 90 Sensitive for # replicates Sensitive for variation in response 80 Depends on statistical test chosen 70 No confidence interval Most data points ignored Response Respons 60 NOEC often gives ~20% effect Poor testing – High NOEC!!! 50 40 30 Safe 20 Unsafe 10 0 0.001 0.01 0.1 1 10 NOAEL LOAEL Dosis of Dose Concentratie 17 17 Dose-response curve: backward use 110 To derive a critical effect dose (CED) 100 or benchmark dose (BMD) 90 at a critical effect size (CES) 80 70 Respons 60 50 40 30 Safe Unsafe 20 CES= 10 0 0.001 0.01 0.1 1 10 CED BMD Dosis of Concentratie 18 9 18 6/19/2024 BMDL CED BMDL BMD BMD  CES: Critical effect size 95% CI  CED: Critical effect dose  BMD: Benchmark dose  CI: confidence interval  BMDL: benchmark dose lower confidence bound 19 19 Terms used in risk assessment  NOAEL: No Observable Adverse Effect Level  LOAEL: Lowest Observable Adverse Effect Level  TDI: Tolerable Daily Intake  CES: Critical effect size  BMDL: benchmark dose lower confidence boun  UF: Uncertainty factor 20 10 20 6/19/2024 Tolerable daily intake (TDI)  TDI = NOAEL/UF or BMDL/UF  UF = uncertainty factors 1. Interspecies: from test animal to human > Rat, mouse, dog, guinea pig, … is not a human being! 2. Intraspecies: from average person to most sensitive person > Infants, elderly, pregnant women 3. Shortcomings within the dataset > E.g. From “unsafe” to safe values: LOAEL to NOAEL > E.g. From acute to chronic toxicity 21 21 Risk assessment of compounds in general Lowest observed adverse effect level (LOAEL) in test animals :2-10 No observed adverse effect level (NOAEL) in test animals :10 Safe dose (NOAEL) in average human :10 Safe dose for sensitive humans So: safe dose is 200-1000x lower than the lowest dose having negative effects in test animals 22 11 22 6/19/2024 Mutagenic compounds have no threshold value 23 23 Compounds without a threshold value: single hit 24 12 24 6/19/2024 Compounds without a threshold value: single hit 25 25 Compounds without a threshold value: single hit No threshold value!!! Maximum Permissible Risk Maximum Permissible Risk Level (MPRL) No uncertainty factors! TDI 26 13 26 6/19/2024 REACH requirements for human toxicity data  >1 t/yr Irritation and corrosion, sensitation, mutagenicity in vitro (bacteria), acute toxicity  >10 t/yr Mutagenicity in vitro (mammalian), acute toxicity (more route of exposure), repeated dose (28d), reproduction, toxicokinetics  >100 t/yr Mutagenicity in vivo (somatic and germ cells), subchronic (90d), developmental toxicity, two-generation study  >1000 t/yr Carcinogenicity study 27 27 Set-up  What is risk?  Comparison of risks by toxic compounds to other risk factors  How can critical exposures be determined? Compounds with and without a threshold value  Case-study Dioxins 28 14 28 6/19/2024 O Cl Cl TDI estimation for dioxin Cl O Cl  Not based on DOSE (pg per kg bw per day)  Instead based on BODY BURDEN (ng per kg bw)  Assuming steady state in a one compartment model 29 29 First order toxicokinetics in a one-compartment model a kQ Q Q: ng per kg dQ a: ng per kg per day  a – kQ k: per day dt 30 15 30 6/19/2024 Steady state conditions (dQ/dt = 0) Equilibrium body burden= a/k Initial slope = a dQ  a – kQ dt a Qt  (1- e-kt ) k 31 31 After exposure: exponential decay Halflife time (t½): dQ Time to excrete half of  – kQ the body burden dt Qt  0.5  Q0  Q0  ekt½ Qt  Q0  ekt 0.5  ekt½ kt½  ln(0.5) ln2 ln2 t½  k 32 16 32 6/19/2024 O Cl Cl TDI estimation for dioxin Cl O Cl  Steady state: Qeq = a/k a = k*Qeq = (ln2/t½)* Qeq = f*I absorption (a) = fraction (f) of intake (I) I = a/f = ((ln2/t½)* Qeq)/f Qeq  Assumptions: t½ = 7.5 years = 7.5*365 = 2738 d f=50%=0.5  Imin = ((0.693/2738)*28) / 0.5 = 0.014 ng per kg per day  Imax = ((0.693/(2738)*73)/0.5 = 0.037 ng per kg per day 33 33 O Cl Cl TDI estimation for dioxin Cl O Cl  LOAEL reproduction and development (rat and monkey): 28-73 ng per kg bw  Corresponding intake in humans: 14-37 pg per kg per day  Uncertainty factors interspecies: 1 (based on BODY BURDEN) intraspecies: 5 shortcomings dataset: 2  Total uncertainty factor: 1 x 5 x 2 = 10  TDI is 1-4 pg per kg per day 34 17 34 6/19/2024 Risk communication: Processed and red meat Lancet, 26 October 2015 Processed meat: carcinogenic to humans (Group 1) based on sufficient evidence in humans that the consumption of processed meat causes colorectal cancer Red meat: probably carcinogenic to humans (Group 2A) based on limited evidence that the consumption of red meat causes cancer in humans and strong mechanistic evidence supporting a carcinogenic effect https://www.youtube.com/watch?v=RXRQNlxN5KY 35 35 Learning goals - After this lecture you  Understand the importance of Paracelsus paradigm in risk assessment  Understand the DALY approach to compare different types of risk  Understand how critical body burdens can be calculated into critical dose levels  Are able to make simple risk calculations: see WG04  Understand more complex risk calculations  Realize that risk assessment depends on the number, type and quality of assumptions and data fundamental choices made 36 18 36 6/19/2024 Please contact me if you want…  To do a literature study in the field of Human & Environmental Toxicology  To do an internship in the field of Human & Environmental Toxicology (see next slide)  To provide feedback on the digital text book of the course  [email protected] 37 37 Topics for internships/literature theses  Optimization of FITC-T4 purification and characterization using LC- MS/MS approaches Maria Margalef – [email protected]  Quantifying microplastics of the future in human matrix with pyrolysis- GC-MS Kas Houthuijs – [email protected]  Transformation products elucidation and identification using LC- MS/MS Ingrida Bagdonaite – [email protected]  Discrepancies in data found in databases and fundamental chemical identification concepts (Literature thesis) Ingrida Bagdonaite – [email protected]  Developing analytical methods for fluoropolymers in consumer products and environmental matrices (pyrolysis, GC-MS, F-NMR) Ike van der Veen – [email protected] 38 19 38

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