Toxics | Highly Cited Papers Published in 2024–2025 in the “Novel Methods in Toxicology Research” Section

All articles published in Toxics (ISSN: 2305-6304) are open access so our readers have free and unlimited access to the full text of all articles. We invite you to read our highly cited papers in the “Novel Methods in Toxicology Research” Section, which are listed below:

1. “Recent Advances in Omics, Computational Models, and Advanced Screening Methods for Drug Safety and Efficacy”
by Ahrum Son, Jongham Park, Woojin Kim, Yoonki Yoon, Sangwoon Lee, Jaeho Ji and Hyunsoo Kim
Toxics 2024, 12(11), 822; https://doi.org/10.3390/toxics12110822
Available online: http://www.mdpi.com/2305-6304/12/11/822

2. “Health Risk Assessment of Heavy Metals in Agricultural Soils Based on Multi-Receptor Modeling Combined with Monte Carlo Simulation”
by Yundong Wu, Yan Xia, Li Mu, Wenjie Liu, Qiuying Wang, Tianyan Su, Qiu Yang, Amani Milinga and Yanwei Zhang
Toxics 2024, 12(9), 643; https://doi.org/10.3390/toxics12090643
Available online: http://www.mdpi.com/2305-6304/12/9/643

3. “Artificial Intelligence and Machine Learning Methods to Evaluate Cardiotoxicity following the Adverse Outcome Pathway Frameworks”
by Edoardo Luca Viganò, Davide Ballabio and Alessandra Roncaglioni
Toxics 2024, 12(1), 87; https://doi.org/10.3390/toxics12010087
Available online: https://www.mdpi.com/2305-6304/12/1/87

4. “In Vitro Toxicity Screening of Fifty Complex Mixtures in HepG2 Cells”
by Sunmi Kim, Kyounghee Kang, Haena Kim and Myungwon Seo
Toxics 2024, 12(2), 126; https://doi.org/10.3390/toxics12020126
Available online: https://www.mdpi.com/2305-6304/12/2/126

5. “Interlaboratory Study on Zebrafish in Toxicology: Systematic Evaluation of the Application of Zebrafish in Toxicology’s (SEAZIT’s) Evaluation of Developmental Toxicity”
by Jon T. Hamm, Jui-Hua Hsieh, Georgia K. Roberts, Bradley Collins, Jenni Gorospe, Barney Sparrow, Nigel J. Walker, Lisa Truong, Robyn L. Tanguay, Sylvia Dyballa et al.
Toxics 2024, 12(1), 93; https://doi.org/10.3390/toxics12010093
Available online: https://www.mdpi.com/2305-6304/12/1/93

6. “A Machine-Learning-Driven Pathophysiology-Based New Approach Method for the Dose-Dependent Assessment of Hazardous Chemical Mixtures and Experimental Validations”
by Sarita Limbu, Eric Glasgow, Tessa Block and Sivanesan Dakshanamurthy
Toxics 2024, 12(7), 481; https://doi.org/10.3390/toxics12070481
Available online: https://www.mdpi.com/2305-6304/12/7/481

7. “Selenomethionine and Allicin Synergistically Mitigate Intestinal Oxidative Injury by Activating the Nrf2 Pathway”
by Yongshi Liu, Xi Lv, Heling Yuan, Xiaoming Wang, Jinhu Huang and Liping Wang
Toxics 2024, 12(10), 719; https://doi.org/10.3390/toxics12100719
Available online: https://www.mdpi.com/2305-6304/12/10/719

8. “Machine Learning to Predict Drug-Induced Liver Injury and Its Validation on Failed Drug Candidates in Development”
by Fahad Mostafa, Victoria Howle and Minjun Chen
Toxics 2024, 12(6), 385; https://doi.org/10.3390/toxics12060385
Available online: https://www.mdpi.com/2305-6304/12/6/385

9. “Effects of Environmental Chemical Pollutants on Microbiome Diversity: Insights from Shotgun Metagenomics”
by Seid Muhie, Aarti Gautam, John Mylroie, Bintu Sowe, Ross Campbell, Edward J. Perkins, Rasha Hammamieh and Natàlia Garcia-Reyero
Toxics 2025, 13(2), 142; https://doi.org/10.3390/toxics13020142
Available online: https://www.mdpi.com/2305-6304/13/2/142

10. “New Horizons in Skin Sensitization Assessment of Complex Mixtures: The Use of New Approach Methodologies Beyond Regulatory Approaches”
by Argel Islas-Robles, Meera Ramani, Jakeb Phillips and Gertrude-Emilia Costin
Toxics 2025, 13(8), 693; https://doi.org/10.3390/toxics13080693
Available online: https://www.mdpi.com/2305-6304/13/8/693