Using Computational Tools to Improve Chemical Safety and Public Health

Dear Colleagues,

Computational tools and new alternative methods are playing an increasingly important role in how we understand and manage the risks chemicals and drugs may pose to people and the environment. These approaches help scientists and public health professionals evaluate exposure, predict harmful effects, and make more informed decisions to protect communities. By combining modeling techniques, data-driven methods, and biological insights, computational approaches offer practical ways to assess chemical and drug safety when traditional testing alone is not enough.

This Special Issue focuses on how these tools are being used in chemical safety evaluation and public health-oriented risk assessment. We welcome studies that use computational or alternative approaches to examine chemical or drug exposure, identify potential health effects, evaluate dose–response relationships, or support decision-making in real-world public health contexts. Submissions may address human health, environmental health, regulatory needs, or population-level considerations.

Even with available tools, important gaps remain in exposure data, toxicity information, and biological indicators needed to fully understand chemical risks. The aim of this Special Issue is to bring together research that uses computational and alternative methods to fill these gaps, improve chemical and drug safety evaluations, and strengthen the scientific foundation for public health protection.

This Special Issue welcomes original research articles and systematic reviews on topics including, but not limited to, the following:

Computational toxicology;

Computational systems biology;

Machine learning and artificial intelligence for safety assessments;

Quantitative Structure–Activity Relationship (QSAR) modeling;

Molecular docking and molecular dynamics simulations;

Physiologically Based Pharmacokinetic (PBPK) and pharmacokinetic (PK) modeling;

Environmental fate and transport modeling;

Integrated Testing Strategies (ITS) that support chemical or drug evaluation;

Adverse Outcome Pathway (AOP) applications;

New Approach Methodologies (NAMs) for evaluating chemical or drug safety;

Assessment and modeling of chemical or drug mixtures;

Emerging chemicals and computational modeling applications.

Dr. Patricia Ruiz
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Toxics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• computational toxicology
• computational pharmacology
• in silico modeling
• machine learning and AI for chemical evaluation
• QSAR (quantitative structure–activity relationship)
• PBPK modeling
• molecular docking
• molecular dynamics
• toxicity prediction
• high-throughput screening (HTS)
• integrated testing strategies (ITS)
• new approach methodologies (NAMs)
• adverse outcome pathways (AOP)
• exposure assessment
• chemical mixtures evaluation
• predictive toxicology
• data-driven chemical safety
• environmental health modeling