ZeroPM prioritization workshop presentation Physiologically Based Kinetic Modelling (PBK) using QIVIVE to predict the toxicokinetic profiles of triazines and triazoles via oral route of administration

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036756. Grouping Concepts in toxicokinetics : Assess the bioavailability of PM compounds using PBK modelling Abishek Laxmanan Ravi Shankar1,*, Jenny Irwan1, Max Spänig1, Maxim Carlier2, Timo Hamers2, Nicole Zümbulte3, Todd Gouin4, Pawel Barenczewski5, Tanja Hansen1, Sylvia E. Escher1 ZeroPM; Prioritization Workshop; UBA, Dessau, Germany, 19th -20th September 2024 9/17/2024 1 Contents Compound selection PBK Modelling and Proof of Concept Read Across Approach (RAX) Risk Assessment based on internal concentrations Presented by: Abishek Laxmanan Ravi Shankar 9/17/2024 2 Persistent – Mobile Compounds Presented by: Abishek Laxmanan Ravi Shankar For the persistent and mobile [9] substances, three classes of compounds were selected, namely: Persistent an Mobile compounds Per class -data rich compounds -in vivo animal studies with repeated oral exposure and ADME Triazines –9 compounds selected PFOS PFOA •Selection Strategy Triazoles Triazines Per-and polyfluoroalkyl substances (PFAS) Cyromazine Atrazine N N N OCl OH N H NN Triadimenol 1,2,4 -triazole NH N NH N Cl N NH N N N NH2 NH2 Triazoles –16 compounds selected PFAS –11 compounds selected 9/17/2024 3 Application of PBK models in QIVIVE process IVIVE based PBPK Modelling for PM compounds In vitro biokinetic PBK Model Plasma concentration curve External concentration 0 EC10 EC50 x x x x x x x Response Dose Presented by: Abishek Laxmanan Ravi Shankar 9/17/2024 4 Build Physiologically Based Kinetic (PBK) models 5 Physiological parameters Substance-specific ADME parameters Exposure scenario *Heart, Brain, Muscle, Skin, Bone, Adipose, Rest Arterial blood Spleen Heart Feces GIT Liver Kidneys Brain IV Muscle Skin Adipose Bone Rest Venous blood Urine Pulmonary Bronchial Qin Qout *<a href="https://www.freevector.com/group-of-people-vector--28523">FreeVector.com</a> Generic PBK model - compound specific data from New Approach Methods (NAMs) *Proof that the PBK model provides reliable predictions Presented by: Abishek Laxmanan Ravi Shankar 9/17/2024 5 B P Blood : plasma ratio CaCo2 Assay Measuring premeability across the intestinal cells in cm/s Apical side Basolateral side Measuring intrinsic hepatic clearance in PHH in µg/min/106cells Time dependent CLint Fraction unbound Bound fraction Unbound fraction Protein Output of rat PBK model is compared to the rat in vivo oral data Sensitivity and Uncertainity analysis Build generic PBK Model and Assess performance Presented by: Abishek Laxmanan Ravi Shankar 9/17/2024 6 Data type Clint PHH = 3.62 [µl/min/millio ncells] In Vivo Data In vitro / In vivo C_max [µg/ml] 5.91 4.63 1.27 T_max [h] 7.11 1.53 4.64 AUC [µg/mL * h] 154.5 112.36 1.37 Proof of concept •Rat Model Tebuconazole Presented by: Abishek Laxmanan Ravi Shankar 9/17/2024 7 Sensitivity Analysis 10/29/2025 •Tebuconazole –Rat PBK Model Order of the highest sensitive parameters •Fraction Unbound > Solubility > Apparent permeability > Intrinsic hepatic clearance µ Intrinsic hepatic clearance Apparent permeability Maximum Solubility Fraction Unbound 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.5 0.6 0.7 0.8 0.9 11.1 1.2 1.3 1.4 Tebuconazole Morris Plot σ Uncertainity Analysis Presented by: Abishek Laxmanan Ravi Shankar 8 10/29/2025 Data type C_max µg/ml T_max hAUC µg/mL * h Fu (ZeroPM)1.61 1.53 8.49 Fu (CompTox)1.12 1.39 4.72 In vivo data[4] 1.151 3.06 4.41 In vitro / In vivo ratio (ZeroPM) 1.19 1.46 1.92 In vitro / In vivo ratio (CompTox) 0.76 0.45 0.85 AUC, C_max, T_max is within the factor of 2 for both of the cases, thus validating the model Input concentration to rat: 3 mg/kg Also true for Triazines? Rat Model Cyromazine Presented by: Abishek Laxmanan Ravi Shankar 9 Reference 1 Fisher C et al ., VIVD:Virtual in vitro distribution model for the mechanistic prediction of intracellular concentrations of chemicals in in vitro toxicity assays. Toxicol in vitro.2019 Aug;58:42-50.doi:10.1016/j.tiv.2018.12.017.Epub 2018 Dec 29.PMID:30599189 2Maísa Daniela Habenschus (2019)et al., In vitro enantioselective study of the toxicokinetic effects of chiral fungicide tebuconazole in human liver microsomes, Ecotoxicology and Environmental Safety, Vol 181,pages 96 –105, https://doi.org/10.1016/j.ecoenv.2019.05.071 3Mansouri, Ket al., OPERA: A free and open source QSAR tool for predicting physicochemical properties and environmental fate endpoints.Presented at American Chemical Society Spring 2018,New Orleans, LA, March 18 -22,2018. 4ADMET Property Prediction |Machine Learning |AI-driven Drug Design (simulations-plus.com) 5EFSA Draft Assessment Report (DAR) –public version.Initial risk assessment provided by the rapporteur Member State Denmark for the existing active substance –Tebuconazole (Vol 3, annex B, part 2/A, B.6 Nov 2007) 6Williams AJ Wambaugh JF, Richard AM et al., The CompTox Chemistry Dashboard: a community data resource for environmental chemistry. J Cheminform.2017 Nov 28;9(1):61.doi:10.1186/s13321-017-0247-6 7Predict Molecular Properties |Percepta Software |ACD/Labs (acdlabs.com) 8 L. I. Mas, V. C. Aparicio, E. De Gerónimo and J. L. Costa, Pesticides in water sources used for human consumption in the semiarid region of Argentina, SN Applied Sciences, 2020, 2. 9 8. H. Zhu and K. Kannan, Occurrence and distribution of melamine and its derivatives in surface water, drinking water, precipitation, wastewater, and swimming pool water, Environ Pollut,2020,258,113743. 10 R. Paseiro-Cerrato, J. DeVries and T. H. Begley, Evaluation of Short-Term and Long-Term Migration Testing from Can Coatings into Food Simulants:Epoxy and Acrylic-Phenolic Coatings, JAgric Food Chem, 2017,65,2594-260. 11 NORMAN Database System (norman-network.com) Norman database system for ground and surface water concentrations Presented by: Abishek Laxmanan Ravi Shankar 9/17/2024 17 Acknowledgement Sincere thanks to all the ZeroPM project partners and WP6 team for providing with the data and their support throughout this process Jenny Irwan1, Max Spänig1, Anke Londenberg1, Maxim Carlier2, Timo Hamers2, Nicole Zümbulte3, Todd Gouin4, Patrik Lundquist5, Pawel Barenczewski5, Tanja Hansen1, Sylvia E. Escher1 1) Fraunhofer Institute for Toxicology and Experimental Medicine (ITEM), Hannover, Germany; 2) Vrije Universiteit Amsterdam, Netherlands 3) DVGW-Technologiezentrum Wasser, Karlsruhe, Germany; 4) TG Environmental Research, United Kingdom; 5) Department of Pharmacy, Drug delivery, Uppsala University, Sweden 9/17/2024 18 WP6 team Dr. Timo Hamers Prof.Dr. Majorie van Duursen Maxim Carlier Dr. Sylvia Escher Dr. Todd Gouin Dept. Environment & Health Dr. Nicole Zumbulte Abishek Laxmanan Ravi Shankar Jenny Irwan 9/17/2024 19