Innovative Research for a Sustainable Future www.epa.gov/research knudsen.thomas@epa.gov l 919-541-9776 hunter.sid@epa.gov l 919-541-3490 Framework for Predictive Developmental Toxicity of Chemicals Regulated under TSCA Thomas B. Knudsen1 and E. Sidney Hunter2 U.S. Environmental Protection Agency, Office of Research and Development 1NCCT and 2NHEERL Mining ToxCast to define sensitive pathways Summary OBJECTIVE: build a framework for pre-prioritizing chemicals for developmental toxicity (DevTox) for potential application to chemicals regulated under TSCA (amended 2016). INPUTS: ToxCast data including new information on chemical effects in zebrafish embryos and in diverse mammalian embryonic stem cell lines (hESC, mESC). OUTPUT: generalized workflow to sort compounds by their predicted potential for DevTox and in silico modeling of quantitative cellular, tissue and phenotypic responses. Evaluating model performance • Assigning chemicals under amended TSCA to low and high priority comes with uncertainties in complexity of predicting toxicity during pregnancy. • A DevTox predictive framework will implement data from in vitro assays assessing embryonic cell growth and differentiation. • The framework will operationalize a defined interpretation protocol for computational synthesis and integration DevTox decision tree. • Multiscale modeling and simulation will provide tools and approaches to virtually reconstruct and analyze complexity and quantitative prediction. OBSERVATIONS: • ZFISH platforms were more sensitive but less specific than mESC or hESC platforms. • Model performance improves against more stringent in vivo criteria for DevTox. • Overall accuracy approaches 62% (ZFISH), 72% (mESC), and 84% (hESC). • The hESC model also predicts the critical concentration for human dosimetry. DEFINITIONS: (a) LEL, lowest effect level (mg/kg/day) in ToxRefDB prenatal developmental toxicity study: dLEL (fetal endpoint) and mLEL (maternal endpoint) in the same ToxRefDB study for ‘n’ compounds; (b) evidence for DevTox: ‘CLEAR’ (dLEL< 200, dLEL<mLEL); ‘SOME’ (dLEL< 200, dLEL> mLEL); ‘EQUIVOCAL’ (dLEL> 200 but <1000); and ‘NO’ (dLEL>1000) in rat and/or rabbit study; (c) TP (true positive), FP (false positive), FN (false negative), TN (true negative); SENS, sensitivity [TP/(TP+FN)]; SPEC, specificity [TN/(TN+FP)]; ACC, accuracy [(TP+FN)/(TP+FP+FN+TN)]. Anatomical development Overview Computational synthesis and integration This poster does not represent EPA Policy i) assess qualitative performance of the predictive model; ii) set an exposure-based prediction of teratogenicity; iii) characterize sensitive response pathways; and iv) virtually reconstruct quantitative phenotypic response. Chemicals ranked by enumerated response Toxicity Prioritization index (ToxPi): • chart maps 753 ToxCast chemicals tested across 6 in vitro platforms; • slices indicate response (1) or no response (0) for each platform: blue - zebrafish platforms (2) yellow - ToxCast pathways (multiple) red - hESC (pluripotent H9 cells) green - mESC (differentiating J1 cells). Pyridaben (strong evidence) Captan (moderate evidence) Hexaconazole (weak evidence) 2,4-Dichlorophenoxy- acetic acid (false negative) Specific aims examples Human palatal closure (left) simulated in a virtual embryo (right). Running the simulation with ToxCast data for ‘Captan’ predicts a tipping point at 4 µM. Captan (+) EGF (-) TGF-beta Human HTTK model predicts exposure of a pregnant woman to Captan at 2.39 mg/kg/day would achieve a steady state of 4 µM in fetal plasma. example