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Henriquez JE, Badwaik VD, Bianchi E, Chen W, Corvaro M, LaRocca J, Lunsman TD, Zu C, Johnson KJ. From Pipeline to Plant Protection Products: Using New Approach Methodologies (NAMs) in Agrochemical Safety Assessment. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:10710-10724. [PMID: 38688008 DOI: 10.1021/acs.jafc.4c00958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
The human population will be approximately 9.7 billion by 2050, and food security has been identified as one of the key issues facing the global population. Agrochemicals are an important tool available to farmers that enable high crop yields and continued access to healthy foods, but the average new agrochemical active ingredient takes more than ten years, 350 million dollars, and 20,000 animals to develop and register. The time, monetary, and animal costs incentivize the use of New Approach Methodologies (NAMs) in early-stage screening to prioritize chemical candidates. This review outlines NAMs that are currently available or can be adapted for use in early-stage screening agrochemical programs. It covers new in vitro screens that are on the horizon in key areas of regulatory concern. Overall, early-stage screening with NAMs enables the prioritization of development for agrochemicals without human and environmental health concerns through a more directed, agile, and iterative development program before animal-based regulatory testing is even considered.
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Affiliation(s)
| | - Vivek D Badwaik
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | - Enrica Bianchi
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | - Wei Chen
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | | | - Jessica LaRocca
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | | | - Chengli Zu
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
| | - Kamin J Johnson
- Corteva Agriscience, Indianapolis, Indiana 46268, United States
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Huang Z, Lou S, Wang H, Li W, Liu G, Tang Y. AttentiveSkin: To Predict Skin Corrosion/Irritation Potentials of Chemicals via Explainable Machine Learning Methods. Chem Res Toxicol 2024; 37:361-373. [PMID: 38294881 DOI: 10.1021/acs.chemrestox.3c00332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
Skin Corrosion/Irritation (Corr./Irrit.) has long been a health hazard in the Globally Harmonized System (GHS). Several in silico models have been built to predict Skin Corr./Irrit. as an alternative to the increasingly restricted animal testing. However, current studies are limited by data amount/quality and model availability. To address these issues, we compiled a traceable consensus GHS data set comprising 731 Corr., 1283 Irrit., and 1205 negative (Neg.) samples from 6 governmental databases and 2 external data sets. Then, a series of binary classifiers were developed with five machine learning (ML) algorithms and six molecular representations. For 10-fold cross-validation, the best Corr. vs Neg. classifier achieved an Area Under the Receiver Operating Characteristic Curve (AUC) of 97.1%, while the best Irrit. vs Neg. classifier achieved an AUC of 84.7%. Compared with existing in silico tools on external validation, our Attentive FP classifiers showed the highest metrics on Corr. vs Neg. and the second highest accuracy on Irrit. vs Neg. The SHapley Additive exPlanation approach was further applied to figure out important molecular features, and the attention weights were visualized to perform interpretable prediction. Structural alerts associated with Skin Corr./Irrit. were also identified. The interpretable Attentive FP classifiers were integrated into the software AttentiveSkin at https://github.com/BeeBeeWong/AttentiveSkin. The conventional ML classifiers are also provided on our platform admetSAR at http://lmmd.ecust.edu.cn/admetsar2/. Considering the data deficiency and the limited model availability of Skin Corr./Irrit., we believe that our data set and models could facilitate chemical safety assessment and relevant studies.
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Affiliation(s)
- Zejun Huang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Shang Lou
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Haoqiang Wang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Weihua Li
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Guixia Liu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yun Tang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
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Takkellapati S, Gonzalez MA. Application of read-across methods as a framework for the estimation of emissions from chemical processes. CLEAN TECHNOLOGIES AND RECYCLING 2023; 3:283-300. [PMID: 38357098 PMCID: PMC10866300 DOI: 10.3934/ctr.2023018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/16/2024]
Abstract
The read-across method is a popular data gap filling technique with developed application for multiple purposes, including regulatory. Within the US Environmental Protection Agency's (US EPA) New Chemicals Program under Toxic Substances Control Act (TSCA), read-across has been widely used, as well as within technical guidance published by the Organization for Economic Co-operation and Development, the European Chemicals Agency, and the European Center for Ecotoxicology and Toxicology of Chemicals for filling chemical toxicity data gaps. Under the TSCA New Chemicals Review Program, US EPA is tasked with reviewing proposed new chemical applications prior to commencing commercial manufacturing within or importing into the United States. The primary goal of this review is to identify any unreasonable human health and environmental risks, arising from environmental releases/emissions during manufacturing and the resulting exposure from these environmental releases. The authors propose the application of read-across techniques for the development and use of a framework for estimating the emissions arising during the chemical manufacturing process. This methodology is to utilize available emissions data from a structurally similar analogue chemical or a group of structurally similar chemicals in a chemical family taking into consideration their physicochemical properties under specified chemical process unit operations and conditions. This framework is also designed to apply existing knowledge of read-across principles previously utilized in toxicity estimation for an analogue or category of chemicals and introduced and extended with a concurrent case study.
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Affiliation(s)
- Sudhakar Takkellapati
- US Environmental Protection Agency, Office of Research and Development, Center for Environmental Solutions and Emergency Response, Land Remediation and Technology Division, Environmental Decision Analytics Branch, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, USA
| | - Michael A. Gonzalez
- US Environmental Protection Agency, Office of Research and Development, Center for Environmental Solutions and Emergency Response, Land Remediation and Technology Division, Environmental Decision Analytics Branch, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, USA
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Lee SH, Kim J, Kim J, Park J, Park S, Kim KB, Lee BM, Kwon S. Current trends in read-across applications for chemical risk assessments and chemical registrations in the Republic of Korea. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2022; 25:393-404. [PMID: 36250612 DOI: 10.1080/10937404.2022.2133033] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Read-across, an alternative approach for hazard assessment, has been widely adopted when in vivo data are unavailable for chemicals of interest. Read-across is enabled via in silico tools such as quantitative structure activity relationship (QSAR) modeling. In this study, the current status of structure activity relationship (SAR)-based read-across applications in the Republic of Korea (ROK) was examined considering both chemical risk assessments and chemical registrations from different sectors, including regulatory agencies, industry, and academia. From the regulatory perspective, the Ministry of Environment (MOE) established the Act on Registration and Evaluation of Chemicals (AREC) in 2019 to enable registrants to submit alternative data such as information from read-across instead of in vivo data to support hazard assessment and determine chemical-specific risks. Further, the Ministry of Food and Drug Safety (MFDS) began to consider read-across approaches for establishing acceptable intake (AI) limits of impurities occurring during pharmaceutical manufacturing processes under the ICH M7 guideline. Although read-across has its advantages, this approach also has limitations including (1) lack of standardized criteria for regulatory acceptance, (2) inconsistencies in the robustness of scientific evidence, and (3) deficiencies in the objective reliability of read-across data. The application and acceptance rate of read-across may vary among regulatory agencies. Therefore, sufficient data need to be prepared to verify the hypothesis that structural similarities might lead to similarities in properties of substances (between source and target chemicals) prior to adopting a read-across approach. In some cases, additional tests may be required during the registration process to clarify long-term effects on human health or the environment for certain substances that are data deficient. To improve the quality of read-across data for regulatory acceptance, cooperative efforts from regulatory agencies, academia, and industry are needed to minimize limitations of read-across applications.
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Affiliation(s)
- Sang Hee Lee
- Chemicals Registration & Evaluation Team, Risk Assessment Research Division, National Institute of Environmental Research, Ministry of Environment, Inchon, Republic of Korea
| | - Jongwoon Kim
- Chemical Safety Research Center, Korea Research Institute of Chemical Technology, Daejeon, Republic of Korea
| | - Jinyong Kim
- Environment, Safety and Health DepartmentChemical Products and Biocides Safety Center, Korea Environmental Industry and Technology Institute (KEITI), Inchon, Republic of Korea
| | - Jaehyun Park
- Pharmaceutical Standardization Division, Drug Evaluation Department, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Osong Health Technology Administration Complex, Cheongju, Chungcheongbuk-do, Republic of Korea
| | | | - Kyu-Bong Kim
- College of Pharmacy, Dankook University, Chungnam 31116, Republic of Korea
| | - Byung-Mu Lee
- Division of Toxicology, College of Pharmacy, Sungkyunkwan University, Seobu-ro 2066, Suwon, Republic of Korea
| | - Seok Kwon
- Global Product Stewardship, Research & Development, Singapore Innovation Center, Procter & Gamble (P&G) International Operationsr, Singapore
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Date MS, O'Brien D, Botelho DJ, Schultz TW, Liebler DC, Penning TM, Salvito DT. Clustering a Chemical Inventory for Safety Assessment of Fragrance Ingredients: Identifying Read-Across Analogs to Address Data Gaps. Chem Res Toxicol 2020; 33:1709-1718. [PMID: 32338872 PMCID: PMC7374741 DOI: 10.1021/acs.chemrestox.9b00518] [Citation(s) in RCA: 317] [Impact Index Per Article: 79.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
![]()
A valuable
approach to chemical safety assessment is the use of
read-across chemicals to provide safety data to support the assessment
of structurally similar chemicals. An inventory of over 6000 discrete
organic chemicals used as fragrance materials in consumer products
has been clustered into chemical class-based groups for efficient
search of read-across sources. We developed a robust, tiered system
for chemical classification based on (1) organic functional group,
(2) structural similarity and reactivity features of the hydrocarbon
skeletons, (3) predicted or experimentally verified Phase I and Phase
II metabolism, and (4) expert pruning to consider these variables
in the context of specific toxicity end points. The systematic combination
of these data yielded clusters, which may be visualized as a top-down
hierarchical clustering tree. In this tree, chemical classes are formed
at the highest level according to organic functional groups. Each
subsequent subcluster stemming from classes in this hierarchy of the
cluster is a chemical cluster defined by common organic functional
groups and close similarity in the hydrocarbon skeleton. By examining
the available experimental data for a toxicological endpoint within
each cluster, users can better identify potential read-across chemicals
to support safety assessments.
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Affiliation(s)
- Mihir S Date
- Research Institute of Fragrance Materials, Incorporated, 50 Tice Boulevard, Woodcliff Lake, New Jersey 07677, United States
| | | | | | - Terry W Schultz
- The University of Tennessee, College of Veterinary Medicine, 2407 River Drive, Knoxville, Tennessee 37996-4500, United States
| | - Daniel C Liebler
- Protypia, LLC., 111 10th Avenue South, Suite 102, Nashville, Tennessee 37203, United States
| | - Trevor M Penning
- Center of Excellence in Environmental Toxicology, The University of Pennsylvania, Perelman School of Medicine, 1315 Biomedical Research Building (BRB) II/III, 421 Curie Boulevard, Philadelphia, Pennsylvania 19104-3083, United States
| | - Daniel T Salvito
- Research Institute of Fragrance Materials, Incorporated, 50 Tice Boulevard, Woodcliff Lake, New Jersey 07677, United States
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