{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T22:06:47Z","timestamp":1773785207787,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,1,26]],"date-time":"2025-01-26T00:00:00Z","timestamp":1737849600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"PT national funds (FCT\/MCTES, Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia and Minist\u00e9rio da Ci\u00eancia, Tecnologia e Ensino Superior)","award":["UID\/50006"],"award-info":[{"award-number":["UID\/50006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>Pharmaceutical and Personal Care Products (PPCPs) have become a significant environmental concern due to their widespread use, persistence, and potential toxicity, often referred to as forever chemicals. This study aims to develop and validate robust in silico models for predicting the aquatic toxicity of PPCPs. To do so, we resorted to the ECOTOX database and employed a Python-based tool to prepare and curate the dataset. Multitasking Quantitative Structure\u2013Toxicity Relationship (mt-QSTR) models were then developed employing the Box\u2013Jenkins moving average approach, incorporating both linear and non-linear frameworks based on diverse feature selection algorithms and machine learning techniques. To further improve the external predictivity, a consensus modeling approach was also implemented. The most accurate model achieved an overall predictive accuracy exceeding 85%, providing valuable insights into the structural features influencing PPCP toxicity. Key factors contributing to high aquatic toxicity included high lipophilicity, mass density, molecular mass, and reduced electronegativity. This work offers a foundation for designing safer PPCPs with reduced environmental impact, aligning with sustainable chemical development goals.<\/jats:p>","DOI":"10.3390\/app15031246","type":"journal-article","created":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T03:54:27Z","timestamp":1737950067000},"page":"1246","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Predicting the Aquatic Toxicity of Pharmaceutical and Personal Care Products: A Multitasking Modeling Approach"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4818-9047","authenticated-orcid":false,"given":"Amit Kumar","family":"Halder","sequence":"first","affiliation":[{"name":"LAQV@REQUIMTE, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal"},{"name":"Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, West Bengal, India"}]},{"given":"Tanushree","family":"Pradhan","sequence":"additional","affiliation":[{"name":"Dr. B. C. Roy College of Pharmacy and Allied Health Sciences, Dr. Meghnad Saha Sarani, Bidhannagar, Durgapur 713206, West Bengal, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3375-8670","authenticated-orcid":false,"given":"M. Nat\u00e1lia D. S.","family":"Cordeiro","sequence":"additional","affiliation":[{"name":"LAQV@REQUIMTE, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.jhazmat.2013.08.040","article-title":"Pharmaceuticals and personal care products in the aquatic environment in China: A review","volume":"262","author":"Bu","year":"2013","journal-title":"J. Hazard. 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