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Challa AP, Beam AL, Shen M, Peryea T, Lavieri RR, Lippmann ES, Aronoff DM. Machine learning on drug-specific data to predict small molecule teratogenicity. Reprod Toxicol 2020; 95:148-158. [PMID: 32428651 PMCID: PMC7577422 DOI: 10.1016/j.reprotox.2020.05.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 05/04/2020] [Accepted: 05/06/2020] [Indexed: 12/23/2022]
Abstract
Pregnant women are an especially vulnerable population, given the sensitivity of a developing fetus to chemical exposures. However, prescribing behavior for the gravid patient is guided on limited human data and conflicting cases of adverse outcomes due to the exclusion of pregnant populations from randomized, controlled trials. These factors increase risk for adverse drug outcomes and reduce quality of care for pregnant populations. Herein, we propose the application of artificial intelligence to systematically predict the teratogenicity of a prescriptible small molecule from information inherent to the drug. Using unsupervised and supervised machine learning, our model probes all small molecules with known structure and teratogenicity data published in research-amenable formats to identify patterns among structural, meta-structural, and in vitro bioactivity data for each drug and its teratogenicity score. With this workflow, we discovered three chemical functionalities that predispose a drug towards increased teratogenicity and two moieties with potentially protective effects. Our models predict three clinically-relevant classes of teratogenicity with AUC = 0.8 and nearly double the predictive accuracy of a blind control for the same task, suggesting successful modeling. We also present extensive barriers to translational research that restrict data-driven studies in pregnancy and therapeutically "orphan" pregnant populations. Collectively, this work represents a first-in-kind platform for the application of computing to study and predict teratogenicity.
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Affiliation(s)
- Anup P Challa
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville 37203, TN, United States; Department of Biomedical Informatics, Harvard Medical School, Boston 02115, MA, United States; National Center for Advancing Translational Sciences, National Institutes of Health, Rockville 20850, MD, United States; Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville 37212, TN, United States.
| | - Andrew L Beam
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston 02115, MA, United States; Department of Biomedical Informatics, Harvard Medical School, Boston 02115, MA, United States
| | - Min Shen
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville 20850, MD, United States
| | - Tyler Peryea
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville 20850, MD, United States
| | - Robert R Lavieri
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville 37203, TN, United States
| | - Ethan S Lippmann
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville 37212, TN, United States
| | - David M Aronoff
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville 37203, TN, United States; Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville 37203, TN, United States; Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville 37203, TN, United States
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Challa AP, Lavieri RR, Lippmann ES, Goldstein JA, Bastarache L, Pulley JM, Aronoff DM. EHRs could clarify drug safety in pregnant people. Nat Med 2020; 26:820-821. [PMID: 32457445 DOI: 10.1038/s41591-020-0925-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Anup P Challa
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA.
| | - Robert R Lavieri
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ethan S Lippmann
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, USA
| | - Jeffery A Goldstein
- Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jill M Pulley
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - David M Aronoff
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
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3
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Cendoya X, Quevedo C, Ipiñazar M, Planes FJ. Computational approach for collection and prediction of molecular initiating events in developmental toxicity. Reprod Toxicol 2020; 94:55-64. [PMID: 32344110 DOI: 10.1016/j.reprotox.2020.03.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 03/04/2020] [Accepted: 03/20/2020] [Indexed: 02/06/2023]
Abstract
Developmental toxicity is defined as the occurrence of adverse effects on the developing organism as a result from exposure to a toxic agent. These alterations can have long-term acute effects. Current in vitro models present important limitations and the evaluation of toxicity is not entirely objective. In silico methods have also shown limited success, in part due to complex and varied mechanisms of action that mediate developmental toxicity, which are sometimes poorly understood. In this article, we compiled a dataset of compounds with developmental toxicity categories and annotated mechanisms of action for both toxic and non-toxic compounds (DVTOX). With it, we selected a panel of protein targets that might be part of putative Molecular Initiating Events (MIEs) of Adverse Outcome Pathways of developmental toxicity. The validity of this list of candidate MIEs was studied through the evaluation of new drug-target relationships that include such proteins, but were not part of the original database. Finally, an orthology analysis of this protein panel was conducted to select an appropriate animal model to assess developmental toxicity. We tested our approach using the zebrafish embryo toxicity test, finding positive results.
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Affiliation(s)
- Xabier Cendoya
- TECNUN, University of Navarra, San Sebastian, 20018, Spain
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Pulley JM, Rhoads JP, Jerome RN, Challa AP, Erreger KB, Joly MM, Lavieri RR, Perry KE, Zaleski NM, Shirey-Rice JK, Aronoff DM. Using What We Already Have: Uncovering New Drug Repurposing Strategies in Existing Omics Data. Annu Rev Pharmacol Toxicol 2019; 60:333-352. [PMID: 31337270 DOI: 10.1146/annurev-pharmtox-010919-023537] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The promise of drug repurposing is to accelerate the translation of knowledge to treatment of human disease, bypassing common challenges associated with drug development to be more time- and cost-efficient. Repurposing has an increased chance of success due to the previous validation of drug safety and allows for the incorporation of omics. Hypothesis-generating omics processes inform drug repurposing decision-making methods on drug efficacy and toxicity. This review summarizes drug repurposing strategies and methodologies in the context of the following omics fields: genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, phenomics, pregomics, and personomics. While each omics field has specific strengths and limitations, incorporating omics into the drug repurposing landscape is integral to its success.
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Affiliation(s)
- Jill M Pulley
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - Jillian P Rhoads
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - Rebecca N Jerome
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - Anup P Challa
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - Kevin B Erreger
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - Meghan M Joly
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - Robert R Lavieri
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - Kelly E Perry
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - Nicole M Zaleski
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - Jana K Shirey-Rice
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee 37203, USA
| | - David M Aronoff
- Department of Medicine, Division of Infectious Diseases, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA.,Departments of Obstetrics and Gynecology, and Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA;
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