A new paper by our graduate student, Elena Chung, presents a hybrid method that combines structural alerts and QSAR modeling to predict human hepatotoxicity. We would like to thank our collaborators, Xia Wen and Lauren Aleksunes, for their monumental contributions to this project.  Please check out our newest publication here in the Journal of Hazardous Materials!

Posted April 24th, 2024

Our lab attended this year's Society of Toxicology Annual Meeting in Salt Lake City, Utah! Dr. Zhu presented our latest advancements in ongoing projects during a platform session. Additionally, our students actively participated in the Computational Toxicology I poster session, presenting our novel methodologies and findings in predictive toxicology. Our efforts and contributions were acknowledged with many awards by various SOT component groups, highlighting the impact and significance of our work:

1.  Xuelian Jia - Top 10 Best SOT-Computational Toxicology Specialty Section (CTSS) Abstract Award

2.  Tong Wang - American Association of Chinese in Toxicology (AACT) Best Publication Award

3.  Tong Wang - Top 3 Best SOT-CTSS Abstract Award

4.  Elena Chung - Korean Toxicologists Association in America Korea Institute of Toxicology (KIT) Best Presentations by Graduate Student

5.  Elena Chung - Sustainable Chemicals through Contemporary Toxicology Specialty Section (SCCTSS) Best Abstract Graduate Student Award

6.  Elena Chung - Top 3 Best SOT-CTSS Abstract Award

7.  Elena Chung - Regulatory Safety Evaluation Specialty Section (RSESS) Elsevier Award: Three-Minute Thesis (TMT)

8.  Elena Chung - 2024 RSESS Graduate Student Excellence Award by the International Society of Regulatory Toxicology and Pharmacology (ISTRP)

9.  Elena Chung - Northeast SOT (NESOT) Regional Chapter Paper of the Year 

10.  Elena Chung - Drug Discovery Toxicology Specialty Section (DDTSS) Paper of the Year 

11.  Elena Chung - Biological Modeling Specialty Section (BMSS) Best Trainee Abstract Award

12.  Nada Daood - CTSS Elsevier Student Award

Congratulations! 

Posted March 19th, 2024

Welcome, new lab members: Sean Carey, Dingxin Zhang, and Xinyu Yang. We are excited to have you all!

Posted September 4th, 2023

Currently we are moving to Tulane University to join the Division of Biomedical Informatics and Genomics at the School of Medicine. In this process, we wish to recruit new talented students and postdocs to our group at Tulane. Please contact Dr. Zhu (hzhu10@tulane.edu) for details.

We will still be affiliated with the Department of Chemistry and Biochemistry at Rowan University. 

Posted August 22, 2023

Congratulations to Dan on his paper titled "Integrating Concentration-Dependent Toxicity Data and Toxicokinetics to Inform Hepatotoxicity Response Pathways." This paper discusses a method that identifies and categorizes high-throughput screening assays into groups of key biological targets and processes associated with hepatotoxicity. Check out the paper here!

Posted August 13th, 2023

Nada Naood, our second-year Ph.D. student, was recently awarded the American Society for Cellular and Computational Toxicology (ASCCT) Travel Award for the QSAR2023 International Workshop in Copenhagen, Denmark. Congratulations! 

Posted June 13, 2023

Our Ph.D. students, Xuelian Jia and Tong Wang, published a review paper in ES&T. This review specifically examines how interpretable machine learning can be applied in computational toxicology, emphasizing the importance of developing new algorithms to uncover toxicity mechanisms and enhance chemical risk assessments.

Please check out the review here to learn more! 

Posted May 24, 2023

Dr. Zhu and his research group was awarded a new NIH four year R01 grant (R01GM148743) titled "Virtual Nanostructure Simulation (VINAS) Portal" with a total of $1,048,277.00. This project aims to develop a data and model sharing platform for nanotoxicity and other nano-bio interaction data.

Posted May 1, 2023

Our newest paper by the group and our collaborators, with Elena as the first author, is now online on ES&T. Congratulations!

Please check out the paper here!

Posted April 12, 2023

We are thrilled to announce that our students won awards last week at the Society of Toxicology Annual Meeting in Nashville, TN!

Among the winners were Xuelian Jia, Tong Wang, and Elena Chung. 

• Xuelian received the Colgate-Palmolive Award for Student Research Training in Alternative Methods and AACT Best Publication Award. 

• Tong received SOT Travel Award and CTSS Graduate Student Award. 

• Elena received the RSESS 3-Minute Thesis Award and CTSS Graduate Student Award. She also now serves as the Graduate Student Representative for CTSS. 

Congratulations!

Posted March 27, 2023

Dr. Zhu played a role in the consensus study report by offering practical suggestions on how the Office of Research and Development (ORD) at the Environmental Protection Agency can integrate emerging science and systems thinking into their research planning. This would enable ORD to enhance its effectiveness in addressing present and future environmental challenges. Find out more here.

Posted March 9, 2023

Congratulations Xuelian, on this award! We look forward to you showcasing our group's research emphasizing alternative methods to animal testing at the upcoming SOT. 

Posted February 1, 2023

We are excited to have you in our group. We look forward to your growth as a researcher and other successes. Welcome aboard!

Posted January 30, 2023

Tong published his first-first author paper in the lab titled, "Integrating structure annotation and machine learning approaches to develop graphene toxicity models." Check it out here! 

Posted December 30, 2022

A new NSF grant was awarded to Dr. Zhu. This project titled "New Machine Learning Empowered Nanoinformatics System for Advancing Nanomaterial Design" was awarded a total of $800,000. Dr. Zhu is the leading PI of this four-year multi-PI collaborative research. 

Posted June 6, 2022

Heather successfully defended her Ph.D. thesis, "Predicting developmental and reproductive toxicity with AI and high-throughput screening data". Congratulations, Dr. Ciallella!

Posted August 26, 2022

NIEHS recognized Xuelian's research paper as the Extramural Paper of the Month. Please see the details of this report here. 

Posted August 3, 2022

Xuelian Jia was awarded the Best Graduate Student of the Computational Toxicology Speciality Section (CTSS). 

Heather Ciallella was awarded the CTSS Best Computational Toxicology Research Paper of the Year.

Posted March 31, 2022

The research paper titled "Mechanism-driven Modeling of Chemical Hepatotoxicity Using Structural Alerts and an In Vitro Screening Assay" was published in the Journal of Hazard Materials. The first author is Xuelian Jia, a third-year Ph.D. student in the Zhu lab. Please see the details of this paper here.

Posted September 10, 2022

Dr. Zhu published an editorial to describe the importance of sustainable chemistry in ACS Sustainable Chemistry and Engineering, which is supported by the recent progress of low-cost and short-time methodologies. Please see the details of this editorial here.

Posted November 3, 2021

Dr. Zhu was recently awarded an NIH R35 grant titled “Discovering Chemical Activity Networks-Predicting Bioactivity Based on Structure”. The major research goal of this project is to use comprehensive in vitro, in vivo, and computational models to develop a predictive chemical network for risk assessment purposes. 

Dr. Robyn Tanguay at Oregon State University is the leading PI of this project, and the total amount awarded to Zhu lab is $576,818.

Posted November 3, 2021

The research paper, “Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network Approach,” was published in Environmental Science and Technology. The first author is Heather Ciallella, a Ph.D. candidate in CCIB. We want to thank our collaborators, Dr. Lauren Aleksunes and Dr. Fabian Grimm, who contribute critically to this project. 

Please see the details of this paper here.

Dr. Zhu was awarded the 2021 Chancellor’s Award for Outstanding Research and Creative Activity. 

Please see the awardee list here.

Posted August 10, 2021

The research paper, titled “Construction of a Virtual Opioid Bioprofile: a Data-driven QSAR Modeling Study to Identify New Analgesic Opioids,” was published in ACS Sustainable Chemistry and Engineering. The first author is Xuelian Jia, who passed her oral exam as a Ph.D. candidate in CCIB. We want to thank our collaborator Dr. Morgan James who contribute critical helps to this project. 

Please see the details of this paper here. 

Posted August 10, 2021

Dr. Zhu and his recently NIH-awarded project were featured in Rutgers-Camden News as a school research highlight. Please view this news here. 

Posted July 29, 2020

Zhu lab published a keynote review, titled “Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling” on Drug Discovery Today. Linlin Zhao is the first author and Heather Ciallella is the second author. Please see the details of this paper here.

Posted July 22, 2020

Dr. Zhu was awarded a five-year NIH R01 grant, titled “Mechanism-Driven Virtual Adverse Outcome Pathway Modeling for Hepatotoxicity, “from the National Institute of Environmental Health Sciences. This grant, with a total amount of $2,271,161, will provide Dr. Zhu necessary support to develop predictive models for potential liver toxicants using new AI algorithms and public big data sources. I want to specially acknowledge my long-time collaborator, Dr. Lauren Aleksunes, for her significant contributions to this project. 

I am also looking for talented students and postdocs to join my lab to work on this project.

Posted June 27, 2020

The Lubrizol Corporation provided Dr. Zhu with a one-year contract of $25,000 to study developmental toxicity. This collaboration project also involves using Lubrizol toxicity data for modeling purposes. 

Posted June 27, 2020

The research paper, titled “Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations”, was published on Nature Communications. The first author was Xiliang Yan, who finished this project as a visiting student in Zhu lab. I want to thank Dr. Bing Yan for his supporting of experimental data as the major data source of this project. The paper can be viewed here.

Posted June 27, 2020

In two virtual thesis defense seminars in April,

Linlin Zhao defended her Ph.D. thesis, titled “Computational modeling for chemical toxicity assessment in the big data era: combining data-driven profiling and mechanism-driven read-across”.

Swati Sharma defended her master thesis, “Hybrid modeling of reproductive and developmental toxicity”.

Congratulations to Dr. Linlin Zhao and Swati Sharma.

Posted June 27, 2020

Linlin’s research paper, titled “Mechanism-driven Read-Across of Chemical Hepatotoxicants Based on Chemical Structures and Biological Data”, was published on Toxicology Science. Please see the details of this paper here.

This is Linlin’s fourth first-author paper in her five year graduate study under my guidance and the sixth research paper in press from my group in the first two months of 2020. Congratulations.

Posted February 26, 2020

Dr. Zhu’s review paper “From machine learning to deep learning: progress in machine intelligence for rational drug discovery” was recognized as the Top Citation Paper by Drug Discovery Today. This paper was cited over 100 times within the past two years (2018-2019) and can be viewed here.

Posted February 7, 2020

The collaborative research of PM2.5 particle modeling for their potential inflammatory effects was published in Ecotoxicology and Environmental Safety. I want to thank Dr. Yan and his group for the contributions of original data and experimental validations. Please see the details of this paper here.

Posted January 24, 2020

Dr. Zhu has three collaborative research papers accepted in the first week of 2020:

Nanomaterial research on ACS Nano

Toxicity pathway study on Chemical Research in Toxicology

Food informatics on Food Chemistry

I want to thank all our collaborators for the multiple successful projects.

Posted January 9, 2020

Dr. Zhu published an editor-invited review titled “Big Data and Artificial Intelligence Modeling for Drug Discovery“, in the Annual Review of Pharmacology and Toxicology.

Posted January 9, 2020

Dr. Zhu’s research is being supported by ExxonMobil for a one-year contract. This research project aims to develop predictive models for estrogen receptor binding models to evaluate new compounds for ExxonMobil.

Posted December 14, 2019

Dr. Zhu gave an invited seminar titled “Big data, AI and intelligent modeling for modern computational toxicology” in the Department of Civil Engineering at Case Western Reserve University on November 15, 2019.

Posted November 20, 2019

Daniel Russo, who passed his Ph.D. defense with honors in August 2019, will leave our school for his new job at the US FDA this week. In the past five years, he did excellent research under my guidance, resulting in 10 peer-reviewed papers and one book chapter, including this year’s NIEHS Extramural Paper of the Month. He sets up an excellent model for future graduate students, and I wish him the best in his career path.

Farewell, Dr. Russo.

Posted November 13, 2019

Dr. Zhu’s recent EHP paper (Daniel Russo as the first author) was featured by NIEHS as one of the Extramural Papers of the Month. Please see the details here.

Posted June 29, 2019

Dr. Zhu and Daniel Russo (PhD student of Zhu lab) were featured by ScienceNode for the recent research progress. Please see the details here.

Posted June 29, 2019

Dr. Zhu was interviewed by LiveScience together with Dr. Warren Casey, the director of the U.S. National Toxicology Program’s Interagency Center for the Evaluation of Alternative Toxicological Methods. This interview is about the current status and future of alternative toxicity models.

Please see the details of this interview here.

Posted June 29, 2019

Innovation Toronto: “Animal-free chemical toxicity testing may become outdated with a new algorithm“

Siliconrepublic: “New algorithm could save thousands of animals from toxic testing“

Chemical Watch: “Rutgers team predicts toxicity by mining PubChem data“

Laboratory Equipment: “New Algorithm Allows for Faster, Animal-free Chemical Toxicity Testing”

Medical Life Science: “Low-cost, high-speed algorithm may allow animal-free chemical toxicity testing”

Lab Manager: “New Algorithm Allows for Faster, Animal-Free Chemical Toxicity Testing”

Science Daily: “New algorithm allows for faster, animal-free chemical toxicity testing”

Futurity: “Can an algorithm replace animal testing for chemicals?”

PhysOrg: “New algorithm allows for faster, animal-free chemical toxicity testing”

Posted April 25, 2019

The paper titled “Using a Hybrid Read-Across Method to Evaluate Chemical Toxicity Based on Chemical Structure and Biological Data” was accepted by Ecotoxicology and Environmental Safety. Congratulations to Linlin for her contributions and thanks to our collaborators from the Beijing Institute of Technology. Please see the details of this paper here.

Posted April 25, 2019

One of Zhu lab’s research projects was featured by Rutgers Today with the title “New Algorithm Allows Faster, Animal-Free Chemical Toxicity Testing”. Please see this media report here.

Posted April 18, 2019

The paper titled “In silico profiling nanoparticles: predictive nanomodeling using universal nanodescriptors and various machine learning approaches” was published on Nanoscale. I want to acknowledge Xiliang for his hard work on this project and the contributions from Dr. Yan. Please see the details of this paper here.

Posted April 15, 2019

The paper titled “Nonanimal Models for Acute Toxicity Evaluations: Applying Data-Driven Profiling and Read-Across” was published on Environmental and Health Perspectives. This three year project was finally published and it represented a major milestone of the big data modeling research in my lab. I would like to thank Dan for his hard work as a PhD student and the great contributions of all authors: Dr. Strickland, Dr. Karmaus, Dr. Wang, Dr. Shende, Dr. Hartung and Dr. Aleksunes. Without you guys, this project will not be possible.

Please see the details of this paper here (an open access paper).

Posted April 2, 2019

The perspective titled “Advancing Computational Toxicology in the Big Data Era by Artificial Intelligence: Data-Driven and Mechanism-Driven Modeling for Chemical Toxicity” was published on Chemical Research in Toxicology. I want to thank Heather for her contributions to this paper and the invitation of CRT editor board. Please see the details of this paper here.

Posted March 25, 2019

Dr. Zhu was awarded the Colgate-Palmolive Grant for Alternative Research by SOT in the 2019 annual meeting and attended the awards ceremony on March 10th. Please see the report of Dr. Zhu’s award by NIEHS here.

Posted March 24, 2019

Dr. Zhu gave an invited lecture titled “Digital Nano: Rational Design of Biocompatible Nanomaterials by Digitalizing Nanostructures” at the Department of Chemistry and Chemical Biology of Rutgers-New Brunswick on March 5th. Please see the details of this event here.

Posted March 24, 2019

The recent success of Dan was featured by Rutgers news. Please see the media report here.

Posted January 23, 2019

Dr. Zhu’s research project titled “Computational Adverse Outcome Pathway Modeling for Developmental and Reproductive Toxicity (DART)” was featured by the Society of Toxicology (SOT) and was awarded a one-year grant support from Colgate-Palmolive.

Please see all SOT award recipients here.

Posted January 22, 2019

The paper titled “Universal nanohydrophobicity predictions using virtual nanoparticle library” was accepted by the Journal of Cheminformatics. I want to acknowledge the contributions of Wenyi, who has started her new career in a company after graduation, and Dr. Yan’s Lab.

Please see the details of the paper here.

Posted January 22, 2019