Computational Toxicology
The toxicity of drugs is one of the main reasons for the clinical failure of newly developed drugs. Computational toxicology has received attention from relevant legislation and research institutions in the US and EU in recent years, and is increasingly used to predict the possible metabolites and toxicity of drugs in the body. BOC Sciences provides computational toxicology services to predict the toxicity of drugs at the early stage of drug development and to eliminate toxic compounds from lead compounds as early as possible, which can help shorten the development cycle, reduce the development cost and improve the success rate of new drug development.
Introduction
Toxicology is a discipline that studies the harmful effects of exogenous factors (chemical, physical, biological) on biological systems. Usually, researchers need to apply some toxic and harmful substances to experimental animals, and then observe, evaluate and analyze the damage to these animals.
Computational toxicology uses mathematical models, artificial intelligence and other advanced computer-aided tools, based on the knowledge of statistics, biology, chemistry, physics and other basic disciplines, to analyze the relevant toxicological test data, estimate the exposure concentration of toxic substances in the environment, and finally achieve the risk assessment of toxic substances.
Compared with traditional toxicology research, computational toxicology has many advantages, including:
- Saving experimental animals and meeting the ethical spirit.
- Cost saving and efficiency in chemical substance evaluation.
- Through large-scale data screening, the accuracy and repeatability of the results can be greatly improved.
- Cross-species extrapolation can be achieved.
Applications of Computational Toxicology
Computational toxicology research methods are widely used in chemical, pesticide, pharmaceutical, food and environmental regulations, scientific research, product development and other fields, providing scientific techniques and theories for toxicity prediction.
For example, the toxicity of drugs is an important part of the modern study of medicine. Traditional toxicity prediction methods often cost a lot of energy, material resources and complicated steps. Computational toxicology provides a simple, accurate and reliable preliminary screening tool for toxic substances, playing an important role in the prediction of the hepatotoxic and nephrotoxic components of the drug. The overall advantages of computational toxicology provide ideas for the toxicity research of complex drug systems.
Service Content
QSAR
(Quantitative) structure-activity relationships. A (quantitative) model relationship between substance effects and molecular descriptors that allows qualitative/quantitative prediction of the physicochemical, toxicological, ecotoxicological and environmental behavior properties of a substance based on its structure. (Q)SAR was first applied to drug and pesticide development, and in recent years, (Q)SAR has been applied to substance toxicity prediction and experimental result prediction.
Read-across
Cross-referencing. A method for predicting the same endpoint information of another chemical with similar structure (target substance) based on the endpoint information of one chemical (reference substance).
TTC
When the human exposure dose of a chemical substance is below the corresponding threshold, the potential health hazard of the chemical substance to humans will be low and no toxicological concern is required.
TTC is a risk assessment method based on a database of toxicity related to the structure of a compound and is now used in many countries and regions around the world for safety risk assessment of food contact materials, food additives, pharmaceutical impurities, etc.
Molecular Simulation
Molecular simulation generally refers to computer-based techniques for simulating and calculating the properties and reactions of molecules. The results of molecular simulations can explain experimental phenomena, reveal the mechanism of microscopic processes, and also assist in experimental design and prediction of molecular properties. Three common molecular simulation methods include quantum mechanics (QM) methods, molecular mechanics (MM) methods, and coupling of the two (QM/MM) methods.
Quantum Chemistry Calculations
Quantum chemistry employs the basic principles of quantum mechanics to study the theory of electronic structure, energy, intermolecular interactions, and chemical reactions of target systems such as atoms and molecules.
Quantum chemical calculations can be used to determine the active sites of intermolecular interactions, predict the products of chemical reactions, design novel drugs and materials, etc.
AOP
Adverse outcome pathways (AOP). The principle is to assume that the toxicity of chemical substances originates from the interaction of exogenous chemical molecules with biological macromolecules, i.e., molecular initiation events, and triggers a series of key events such as subsequent cellular signaling, which eventually exhibit harmful effects at the macroscopic scale. A multi-scale picture of the toxic effects of chemicals is presented.
Our Advantages
- Complementary in vivo toxicity tests to minimize animal testing
- Large-scale data screening, accurate and reproducible results
- Statistical analysis based on large amount of experimental data with low error
- Multiple computational toxicology tools, such as simulation tools for systems biology and molecular dynamics
- High quality database to store data on chemical toxicity and other chemical properties
- Expert systems, including stand-alone applications for predicting toxicity
- Predict toxicity, optimize compounds, and guide toxicity testing
- Reduced risk of drug design failure
BOC Sciences is a leading CRO in drug development with a focus on formulation development. Determining the toxicity of a chemical is necessary to identify its harmful effects on humans, animals, or the environment. We apply computational toxicology methods and tools to analyze, simulate, visualize, or predict drugs toxicity to provide guidance to our clients' drug development and reduce project risk.