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Much of the work carried out by DTT is in support of the National Toxicology Program (NTP), an interagency partnership of the Food and Drug Administration, National Institute for Occupational Safety and Health, and NIEHS.

Kamel Mansouri, Ph.D., joined the NTP Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM) as a Staff Scientist in 2020, where he leads cutting-edge computational chemistry initiatives with a strong emphasis on predictive toxicology. He earned his Ph.D. in computational chemistry from the University of Milano Bicocca, supported by the prestigious Marie Curie fellowship program.

Before his tenure at NICEATM, Mansouri, Ph.D., honed his expertise at Integrated Laboratory Systems, Inc., ScitoVation, and the U.S. EPA, specializing in cheminformatics, QSAR modeling, and machine learning applications in toxicology. His foundational work at NIEHS/DTT in computational chemistry, where he served as a federal contractor, set the stage for his subsequent leadership role in cheminformatics.

At NICEATM, Mansouri, Ph.D., has spearheaded significant projects aligned with DTT's strategic goals, such as enhancing the Integrated Chemical Environment (ICE) and optimizing the OPERA suite of QSAR models. His efforts have been crucial in meeting regulatory needs and advancing NICEATM-sponsored studies that evaluate the toxicological potential of tens of thousands of chemicals, facilitating applications from environmental fate assessments to physiologically based pharmacokinetic modeling.

Mansouri’s, Ph.D., impact on computational toxicology is profound, evidenced by his leadership in high-profile international collaborations like the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP), the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA), and the Collaborative Acute Toxicity Modeling Suite (CATMoS). These initiatives have produced consensus models recognized by regulatory agencies, including the US EPA and the European Chemicals Agency (ECHA).

A recent highlight of Mansouri's, Ph.D., career was his organization of a workshop focused on the latest advancements and best practices in chemical clustering and classification. This cross-divisional effort addressed complex needs for evaluating diverse chemistries, leading to a publication in Environmental Health Perspectives. This work, which emphasized the significance of chemical similarity in toxicological research, received acclaim in a prominent toxicological blog as a vital commentary on advancing understanding and application of these methods.

Mansouri, Ph.D., is also the architect of the Open-QSAR modeling suite OPERA, a free and open-source resource that has garnered thousands of downloads and citations. This tool has become a cornerstone for global regulatory assessments of chemical toxicity, with its original 2018 publication cited hundreds of times in peer-reviewed publications.

With more than 50 publications in high-impact journals, Mansouri's, Ph.D., contributions to the scientific community have been recognized through multiple accolades, including the NIEHS 2023 Individual Merit Award, the QSAR 2021 Promising Early Career Award, and the Young Scientist category of the Lush Prize in 2017. His work continues to push the boundaries of predictive toxicology and regulatory science.

Most Significant Publications

  • Mansouri K, Taylor K, Auerbach S, Ferguson S, Frawley R, Hsieh JH, Jahnke G, Kleinstreuer N, Mehta S, Moreira-Filho JT, Parham F, Rider C, Rooney AA, Wang A, Sutherland V. Unlocking the Potential of Clustering and Classification Approaches: Navigating Supervised and Unsupervised Chemical Similarity. Environ Health Perspect. 2024 Aug;132(8):85002. doi: 10.1289/EHP14001. Epub 2024 Aug 6. PMID: 39106156; PMCID: PMC11302584. [Abstract]
  • Mansouri K, Karmaus AL, Fitzpatrick J, Patlewicz G, Pradeep P, Alberga D, Alepee N, Allen TEH, Allen D, Alves VM, Andrade CH, Auernhammer TR, Ballabio D, Bell S, Benfenati E, Bhattacharya S, Bastos JV, Boyd S, Brown JB, Capuzzi SJ, Chushak Y, Ciallella H, Clark AM, Consonni V, Daga PR, Ekins S, Farag S, Fedorov M, Fourches D, Gadaleta D, Gao F, Gearhart JM, Goh G, Goodman JM, Grisoni F, Grulke CM, Hartung T, Hirn M, Karpov P, Korotcov A, Lavado GJ, Lawless M, Li X, Luechtefeld T, Lunghini F, Mangiatordi GF, Marcou G, Marsh D, Martin T, Mauri A, Muratov EN, Myatt GJ, Nguyen DT, Nicolotti O, Note R, Pande P, Parks AK, Peryea T, Polash AH, Rallo R, Roncaglioni A, Rowlands C, Ruiz P, Russo DP, Sayed A, Sayre R, Sheils T, Siegel C, Silva AC, Simeonov A, Sosnin S, Southall N, Strickland J, Tang Y, Teppen B, Tetko IV, Thomas D, Tkachenko V, Todeschini R, Toma C, Tripodi I, Trisciuzzi D, Tropsha A, Varnek A, Vukovic K, Wang Z, Wang L, Waters KM, Wedlake AJ, Wijeyesakere SJ, Wilson D, Xiao Z, Yang H, Zahoranszky-Kohalmi G, Zakharov AV, Zhang FF, Zhang Z, Zhao T, Zhu H, Zorn KM, Casey W, Kleinstreuer NC. CATMoS: Collaborative Acute Toxicity Modeling Suite. Environ Health Perspect. 2021 Apr;129(4):47013. doi: 10.1289/EHP8495. PMID: 33929906; PMCID: PMC8086800. [Abstract]
  • Mansouri K, Kleinstreuer N, Abdelaziz AM, Alberga D, Alves VM, Andersson PL, Andrade CH, Bai F, Balabin I, Ballabio D, Benfenati E, Bhhatarai B, Boyer S, Chen J, Consonni V, Farag S, Fourches D, García-Sosa AT, Gramatica P, Grisoni F, Grulke CM, Hong H, Horvath D, Hu X, Huang R, Jeliazkova N, Li J, Li X, Liu H, Manganelli S, Mangiatordi GF, Maran U, Marcou G, Martin T, Muratov E, Nguyen DT, Nicolotti O, Nikolov NG, Norinder U, Papa E, Petitjean M, Piir G, Pogodin P, Poroikov V, Qiao X, Richard AM, Roncaglioni A, Ruiz P, Rupakheti C, Sakkiah S, Sangion A, Schramm KW, Selvaraj C, Shah I, Sild S, Sun L, Taboureau O, Tang Y, Tetko IV, Todeschini R, Tong W, Trisciuzzi D, Tropsha A, Van Den Driessche G, Varnek A, Wang Z, Wedebye EB, Williams AJ, Xie H, Zakharov AV, Zheng Z, Judson RS. CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity. Environ Health Perspect. 2020 Feb;128(2):27002. doi: 10.1289/EHP5580. Epub 2020 Feb 7. PMID: 32074470; PMCID: PMC7064318. [Abstract]
  • Mansouri K, Grulke CM, Judson RS, Williams AJ. OPERA models for predicting physicochemical properties and environmental fate endpoints. J Cheminform. 2018 Mar 8;10(1):10. doi: 10.1186/s13321-018-0263-1. PMID: 29520515; PMCID: PMC5843579. [Abstract]
  • Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E, Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg SA, Slavov S, Hu X, Judson RS. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environ Health Perspect. 2016 Jul;124(7):1023-33. doi: 10.1289/ehp.1510267. Epub 2016 Feb 23. PMID: 26908244; PMCID: PMC4937869. [Abstract]

Recent Publications

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