U.S. Environmental Protection Agency Office of Research and Development CELL AGENT-BASED MODEL (ABM): multicellular and signaling dynamics were modeled in CompuCell3D (www.compucell3d.org/); the small working prototype simulated mouse hindlimb-bud development between Theiler stages 16-19 (~42h) in ~55,000 Monte Carlo Steps (MCS). ABM Gradients for FGFs, SHH, BMPS,GREM1, Retinoic acid (RA) and (RAD gradient: RA with aldrin and dieldrin). We mined the ToxCast high-throughput screening (HTS) database [1] for in vitro chemical-bioactivity profiles that significantly correlated with skeletal defects in ToxRefDB for prenatal developmental toxicity studies [2]. 734 of 1060 chemicals had in vivo developmental toxicity data; 44 of them (4-5%) produced limb defects. In addition, we identified 132 ToxCast chemicals not in ToxRefDB that according to published articles produced limb defects. We hypothesized that significant in vitro – in vivo correlations would reveal meaningful mechanistic relationships for predictive modeling of limb/paw defects. Introduction References Workflow for Data-mining DISCLAIMER: this work does not reflect EPA policy Conclusion and Future Directions Computational Toxicology and Computational Modeling of Limb Development using ToxCastTM High-Throughput Screening Data Ahir1 BK, Spencer2 RM, Baker3 NC, Judson, RS4 and Knudsen4 TB U.S. Environmental Protection Agency, Office of Research and Development 1 University of Illinois College of Medicine at Chicago, IL, USA, 2Applied Research Associations, Inc., 3Leidos, 4National Center for Computational Toxicology, Research Triangle Park, NC, USA Bhavesh Ahir l bhavesh.med@gmail.com l 312-989-6683 Hits to assay targets are based on if an AC50 (50% effect on the assay readout) was recorded (active) or not (inactive); the list was filtered for those assays with at least 3 true positive calls (p ≤0.05, TP ≥3). Assays were grouped by biological function; endpoint categories indicate limb or paw defects. Retinoic acid receptor (RAR) assays emerged as the top correlated target and were disrupted by 23 ToxCast chemicals. Vitamin A (retinol) and its biologically active derivatives (e.g. retinoic acid) are essential for embryonic development [4]. Endpoint Class Limb-bud Outgrowth Control Network ToxPi Ranking of in vitro Bioactivity Assay (Univariate Features) Chemicals with effects on limb/paw development were ranked by ToxCast bioactivity profile. Highlighted are aldrin, dieldrin, endrin, all-trans retinoic acid, and retinol. Retinoic acid (RA) signaling play an essential role in limb-bud outgrowth and patterning as a ligand for nuclear RA receptors (α, β, or γ) [4]. Aldrin and dieldrin (the major metabolite of aldrin) bind to RARs (α, β and γ) [5], and can activate these RARs. This is consistent with interference with RA- signaling. Chemical Disruption in the Agent-Based model (ABM) How might local effects predicted by HTS data propagate through the pivotal GREM1 cell lineage in silico to predict, therefore, a key event? We selected aldrin and dieldrin as known limb defect teratogens [5]. Our signature prediction suggest these two compounds are very potent (e.g. Dieldrin (concentration at 50% of maximum activity values (AC50) AC50 = 1.679 µM on RARγ, and 0.770 µM on RARα) and Aldrin (AC50 = 0.911 µM on RARγ, and 1000 μM on RARα) to RARs and activate the RARs assay (see ToxPi Results)). The agonistic activity of these two compounds activate endogenous RA levels, and excessive RA levels, downregulate GREM1 expression. Electronic knock down of GREM1 expression subsequently affects other important signaling networks (e.g. BMPs, FGFs and SHH), and the resultant outcome or ‘cybermorphs’ predict limb defects. The current results support the use of ABM as a predictive model for disruptive embryonic limb development, potentially leading to defects. The ABM correctly predicted that aldrin and dieldrin disrupt embryonic limb development [6] and predicts down-regulation of GR