This dataset consists of data from in vitro developmental neurotoxicity new approach methodologies (DNT-NAMs). Assays include evaluations of proliferation, apoptosis, viability, neurite outgrowth, synaptogenesis and network formation. A variety of cell models are utilized depending on the assay, and each assay may have multiple endpoints. Data have been collected and evaluated using the ToxCast PipeLine (tcpl). This dataset is associated with the following publication: Carstens, K., A. Carpenter, M. Martin, J. Harrill, T. Shafer, and K. Friedman. Integrating Data From In Vitro New Approach Methodologies for Developmental Neurotoxicity. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 187(1): 62-79, (2022).

This file contains the data on apoptosis, neurite outgrowth, synaptogenesis and proliferation. This dataset is associated with the following publication: Harrill, J., T. Freudenrich, K. Wallace, K. Ball, T. Shafer, and W. Mundy. Testing for developmental neurotoxicity using a battery of in vitro assays for key cellular events in neurodevelopment. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 354(1): 24-39, (2018).

This file contains the data on apoptosis, neurite outgrowth, synaptogenesis and proliferation. This dataset is associated with the following publication: Harrill, J., T. Freudenrich, K. Wallace, K. Ball, T. Shafer, and W. Mundy. Testing for developmental neurotoxicity using a battery of in vitro assays for key cellular events in neurodevelopment. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 354(1): 24-39, (2018).

Dataset for article ‘Optimization of Human Neural Progenitor Cells for an Imaging-Based High-Throughput Phenotypic Profiling Assay for Developmental Neurotoxicity Screening’ published 02/16/2022 in Neurotoxicology, a section of the journal Frontiers in Toxicology, part of the Special Research Topic: Methods and Protocols in Neurotoxicology. The zip data file contains 10 files; a 'Data for hNP1 Methods Paper' Word document, 7 Figure files in Excel, and 2 Table files in Excel. This dataset is associated with the following publication: Culbreth, M., J. Nyffeler, C. Willis, and J. Harrill. Optimization of Human Neural Progenitor Cells for an Imaging-Based High-Throughput Phenotypic Profiling Assay for Developmental Neurotoxicity Screening (Frontiers in Toxicology). Frontiers in Toxicology. Frontiers, Lausanne, SWITZERLAND, 3: 803987, (2021).

Dataset for article ‘Optimization of Human Neural Progenitor Cells for an Imaging-Based High-Throughput Phenotypic Profiling Assay for Developmental Neurotoxicity Screening’ published 02/16/2022 in Neurotoxicology, a section of the journal Frontiers in Toxicology, part of the Special Research Topic: Methods and Protocols in Neurotoxicology. The zip data file contains 10 files; a 'Data for hNP1 Methods Paper' Word document, 7 Figure files in Excel, and 2 Table files in Excel. This dataset is associated with the following publication: Culbreth, M., J. Nyffeler, C. Willis, and J. Harrill. Optimization of Human Neural Progenitor Cells for an Imaging-Based High-Throughput Phenotypic Profiling Assay for Developmental Neurotoxicity Screening (Frontiers in Toxicology). Frontiers in Toxicology. Frontiers, Lausanne, SWITZERLAND, 3: 803987, (2021).

Table of contents Table S1 DNT inventory List of sources and associated data collected for the development of the Bayesian hierarchical model. Table S2 Data collection It contains the compiled raw data. Table S3 Final dataset It contains data after curation agreed to be included in the Bayesian hierarchical model. Table S4 List of encoders Machine readable format used to encode the data. Table S5 Machine readable The final dataset translated into a machine readable file using the encoders listed above. Table S6 Results for DNT Based on the cut-offs derived from the results themselves, three classes of DNT are proposed (low, medium and high predicted probability). Results are summarised accordingly. This dataset is associated with the following publication: Spinu, N., M. Cronin, J. Lao, A. Bal-Price, I. Campia, S. Enoch, J. Madden, L. Lagares, M. Novic, D. Pamies, S. Scholz, D. Villeneuve, and A. Worth. Probabilistic modelling of developmental neurotoxicity based on a simplified adverse outcome pathway network. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 21: 100206, (2022).

The US EPA Toxicity Forecasting (ToxCast) project has involved the generation of large amount of high throughput in vitro data (Over 4000 chemicals tested in between 100 and 700 assays). This data is generated in a consistent manner, and includes a wide variety of chemicals including industrial and consumer products, food additives, pesticides, and drugs. These chemicals were not chosen because they were expected to be active, resulting in a database containing a balance of positive and negative data points. As such this data is useful for computational model construction. This in vitro data has been used at the EPA and elsewhere in modelling approaches, including computational modelling for specific target binding as biological descriptors for toxicity prediction, and pharmacokinetic modelling of human dose responses. All analyses in the generation of the burst flag hit-call matrix and extraction of chemicals for the targets in this study (AR and GR) were performed using R v3.1.2. This dataset is associated with the following publication: Allen, T.E., M.D. Nelms, S.W. Edwards, J.M. Goodman, S. Gutsell, and P.J. Russell. In Silico Guidance for In Vitro Androgen and Glucocorticoid Receptor ToxCast Assays. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 54(12): 7461-7470, (2020).

A database of embryo-fetal developmental toxicity (EFDT) studies of 379 pharmaceutical compounds in rat and rabbit. This dataset is not publicly accessible because: this paper uses EPA public data to build new datasets and analysis by non-EPA authors. It can be accessed through the following means: EPA data is publicly accessible. Format: N/A. This dataset is associated with the following publication: Theunissen, P., S. Beken, B. Beyer, W. Breslin, G.D. Cappon, C. Chen, G. Chmielewski, L. De Schaepdrijver, B. Enright, J. Foreman, W. Harrouk, K. Hew, A. Hoberman, J. Hui, T. Knudsen , S. Laffan, S. Makris , and M. Martin. (Crit. Rev. Tox.) Comparing rat and rabbit embryo-fetal developmental toxicity studies for 379 pharmaceuticals: On systemic dose and developmental effects. CRITICAL REVIEWS IN TOXICOLOGY. CRC Press LLC, Boca Raton, FL, USA, 1-13, (2016).

A database of embryo-fetal developmental toxicity (EFDT) studies of 379 pharmaceutical compounds in rat and rabbit. This dataset is not publicly accessible because: this paper uses EPA public data to build new datasets and analysis by non-EPA authors. It can be accessed through the following means: EPA data is publicly accessible. Format: N/A. This dataset is associated with the following publication: Theunissen, P., S. Beken, B. Beyer, W. Breslin, G.D. Cappon, C. Chen, G. Chmielewski, L. De Schaepdrijver, B. Enright, J. Foreman, W. Harrouk, K. Hew, A. Hoberman, J. Hui, T. Knudsen , S. Laffan, S. Makris , and M. Martin. (Crit. Rev. Tox.) Comparing rat and rabbit embryo-fetal developmental toxicity studies for 379 pharmaceuticals: On systemic dose and developmental effects. CRITICAL REVIEWS IN TOXICOLOGY. CRC Press LLC, Boca Raton, FL, USA, 1-13, (2016).

Data on morphology of rat and human neurons in cell culture. This dataset is associated with the following publication: Druwe, I., T. Freudenrich , K. Wallace , T. Shafer , and W. Mundy. Comparison of Human Induced PluripotentStem Cell-Derived Neurons and Rat Primary CorticalNeurons as In Vitro Models of Neurite Outgrowth. Applied In vitro Toxicology. Mary Ann Liebert, Inc., Larchmont, NY, USA, 2(1): 26-36, (2016).