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Research ArticleResearch

Characterizing Extractables and Leachables Chemical Space to Support In Silico Toxicological Hazard Assessments

Candice Johnson, Arianna Bassan, Doug Kiehl, Diane Paskiet, Manuela Pavan, Patricia Parris, Geraldine Whelan, Anders Burild and Glenn J. Myatt
PDA Journal of Pharmaceutical Science and Technology May 2024, 78 (3) 237-311; DOI: https://doi.org/10.5731/pdajpst.2022.012819
Candice Johnson
1Instem, 1393 Dublin Road, Columbus, OH;
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  • For correspondence: candice.johnson@instem.com
Arianna Bassan
2Innovatune, Via Giulio Zanon 130/D, 35129 Padova, Italy;
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Doug Kiehl
3Eli Lilly and Company, Indianapolis, IN 46285;
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Diane Paskiet
4West Pharmaceutical Services, Inc., 530 Herman O. West Drive, Exton, PA 19341;
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Manuela Pavan
2Innovatune, Via Giulio Zanon 130/D, 35129 Padova, Italy;
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Patricia Parris
5Pfizer Worldwide Research, Development and Medical, Sandwich, United Kingdom;
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Geraldine Whelan
6GlaxoSmithKline, Ware, United Kingdom; and
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Anders Burild
7Novo Nordisk A/S, Safety Sciences and Imaging, Måløv, Denmark;
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Glenn J. Myatt
1Instem, 1393 Dublin Road, Columbus, OH;
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Abstract

This article describes the development of a representative dataset of extractables and leachables (E&L) from the combined Extractables and Leachables Safety Information Exchange (ELSIE) Consortium and the Product Quality Research Institute (PQRI) published datasets, representing a total of 783 chemicals. A chemical structure-based clustering of the combined dataset identified 142 distinct chemical classes with two or more chemicals across the combined dataset. The majority of these classes (105 chemical classes out of 142) contained chemicals from both datasets, whereas 8 classes contained only chemicals from the ELSIE dataset and 29 classes contain only chemicals from the PQRI dataset. This evaluation also identified classes containing chemicals that were flagged as potentially mutagenic as well as potent (strong or extreme) dermal sensitizers by in silico tools. The prevalence of alerting structures in the E&L datasets was approximately 9% (69 examples) for mutagens and 3% (25 examples) for potent sensitizers. This analysis showed that most (80%; 20 of 25) E&L predicted to be strong or extreme dermal sensitizers were also flagged as potential mutagens. Only two chemical classes, each containing three chemicals (alkyl bromides and isothiocyanates), were uniquely identified in the PQRI dataset and contained chemicals predicted to be potential mutagens and/or potent dermal sensitizers.

  • Dermal sensitization
  • Mutagenicity
  • Extractables and leachables
  • Computational assessments
  • Chemical class analysis
  • © PDA, Inc. 2024
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PDA Journal of Pharmaceutical Science and Technology: 78 (3)
PDA Journal of Pharmaceutical Science and Technology
Vol. 78, Issue 3
May/June 2024
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Characterizing Extractables and Leachables Chemical Space to Support In Silico Toxicological Hazard Assessments
Candice Johnson, Arianna Bassan, Doug Kiehl, Diane Paskiet, Manuela Pavan, Patricia Parris, Geraldine Whelan, Anders Burild, Glenn J. Myatt
PDA Journal of Pharmaceutical Science and Technology May 2024, 78 (3) 237-311; DOI: 10.5731/pdajpst.2022.012819

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Characterizing Extractables and Leachables Chemical Space to Support In Silico Toxicological Hazard Assessments
Candice Johnson, Arianna Bassan, Doug Kiehl, Diane Paskiet, Manuela Pavan, Patricia Parris, Geraldine Whelan, Anders Burild, Glenn J. Myatt
PDA Journal of Pharmaceutical Science and Technology May 2024, 78 (3) 237-311; DOI: 10.5731/pdajpst.2022.012819
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Keywords

  • Dermal sensitization
  • Mutagenicity
  • Extractables and leachables
  • Computational assessments
  • Chemical class analysis

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