Journal of Clinical and Experimental Toxicology

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Book Review - Journal of Clinical and Experimental Toxicology (2023) Volume 7, Issue 3

Toxicity testing methods: From the clinical trials to experimental models.

Michae Chen*

Department of Clinical science, International University of Japan, Minamiuonuma, Japan

*Corresponding Author:
Michae Chen
Department of Clinical science
International University of Japan
Minamiuonuma, Japan

Received: 05-June-2023, Manuscript No. AACETY-23-101361; Editor assigned: 06-June-2023, PreQC No. AACETY-23-1013601 (PQ); Reviewed: 19-June-2023, QC No.AACETY-23-101361; Revised: 21-June-2023, Manuscript No. AACETY-23-101361 (R); Published: 28-June-2023, DOI: 10.35841/aacety-7.3.142

Citation: Chen M. Toxicity testing methods: From the clinical trials to experimental models. J Clin Exp Tox. 2023 ;7(3):142

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Toxicity testing is a fundamental aspect of ensuring the safety and efficacy of pharmaceuticals, chemicals, and consumer products. This review explores the diverse range of toxicity testing methods employed, from clinical trials involving human subjects to experimental models utilizing in vitro and in vivo systems. It examines the strengths and limitations of each approach, highlighting recent advancements and emerging technologies that have revolutionized the field. By providing an overview of these testing methods, this review aims to inform researchers, regulators, and healthcare professionals about the current landscape of toxicity testing and encourage the adoption of innovative approaches for improved safety assessments.


Toxicity testing, Clinical trials, Experimental models, In vitro, Safety assessment.


Toxicity testing plays a crucial role in evaluating the potential adverse effects of substances on human health and the environment. This review focuses on the diverse methods employed in toxicity testing, ranging from traditional clinical trials involving human subjects to experimental models utilizing in vitro and in vivo systems. Understanding the strengths and limitations of these methods is essential for ensuring accurate safety assessments [1].

Clinical Trials in Toxicity Testing

Clinical trials represent a critical phase in toxicity testing, particularly for pharmaceuticals and medical interventions. These trials involve human subjects and aim to assess the safety, tolerability, and efficacy of the tested substance. Regulatory guidelines dictate the design and conduct of clinical trials, including the selection of appropriate endpoints, sample sizes, and statistical analyses. The inclusion of diverse populations and the integration of pharmacokinetic and pharmacodynamic data enhance the reliability of the results obtained from clinical trials [2].

In Vitro Testing Methods

In vitro testing methods utilize cell-based or biochemical assays to evaluate the toxicity of substances. These methods offer several advantages, including cost-effectiveness, high throughput, and the ability to mimic specific target organs or cellular processes. Various cell culture models, such as 2D monolayers and 3D organoids, provide valuable insights into cytotoxicity, genotoxicity, and molecular mechanisms of toxicity. The integration of human-derived cells and advanced imaging techniques further enhances the relevance and predictive value of in vitro toxicity testing [3].

High-Throughput Screening

High-throughput screening (HTS) techniques involve the rapid screening of large compound libraries to identify potential toxicants. HTS employs a variety of assays, including cellbased assays, reporter gene assays, and computational models, to assess the toxicity of numerous substances simultaneously. The integration of robotics, automation, and artificial intelligence enables the efficient processing and analysis of large datasets, accelerating the identification of potential toxicants and the prioritization of further testing [4].

Omics Technologies

Omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics, have significantly contributed to toxicity testing by providing comprehensive molecular profiles of toxic responses. These technologies allow for the identification of biomarkers, the characterization of toxicity pathways, and the elucidation of mechanisms underlying adverse effects. Integration of omics data with computational modeling facilitates the prediction of toxicity outcomes and the identification of potential adverse effects early in the drug development process [5].

Emerging Technologies

Recent advancements in technology have led to the development of innovative toxicity testing methods. These include organ-on-a-chip systems, microfluidic devices, and bioengineered tissues, which offer more physiologically relevant and organ-specific models for toxicity assessments. The incorporation of 3D printing and bioprinting techniques allows for the creation of complex tissue structures, further enhancing the accuracy and reliability of experimental models [6].


Toxicity testing methods encompass a wide array of approaches, ranging from clinical trials to experimental models. Each method has its strengths and limitations, and the choice of the appropriate approach depends on the specific objectives and resources available. By embracing emerging technologies and advancements in in vitro and in vivo models, researchers and regulators can improve the accuracy, efficiency, and ethical considerations of toxicity testing, ultimately promoting the development of safer products and interventions.


  1. Zhao Y, Du X, Duan Y, et al. High-throughput screening identifies established drugs as SARS-CoV-2 PLpro inhibitors. Protein Cell. 2021(11):877-88.
  2. Indexed at, Google Scholar, Cross Ref

  3. Brock K, Homer V. An analysis of toxicity and response outcomes from dose-finding clinical trials in cancer. BMC cancer. 2021; 21:1-8.
  4. Indexed at, Google Scholar, Cross Ref

  5. Rani NN, Hussein ZM. Exploring the possible targeting strategies of liposomes against methicillin-resistant Staphylococcus aureus (MRSA). Eur J Pharm Biopharm 2021; 165:84-105.
  6. Indexed at, Google Scholar, Cross Ref

  7. Zhao D, Zhu J, Wang L. Bayesian interval-based oncology dose-finding design with repeated quasi-continuous toxicity model. Contemp Clin Trials. 2021; 102:106265.
  8. Indexed at, Google Scholar, Cross Ref

  9. Falk MJ. The pursuit of precision mitochondrial medicine: Harnessing preclinical cellular and animal models to optimize mitochondrial disease therapeutic discovery. J  Inherit Metab Dis. 2022; 44(2):312-24.
  10. Indexed at, Google Scholar, Cross Ref

  11. Yuan S, Zhou T, Lin Y, Ji Y. The Ci3+ 3 design for dual-agent combination dose-finding clinical trials. J Biopharm Stat. 2021; 31(6):745-64.
  12. Indexed at, Google Scholar, Cross Ref

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