Pharmakologie und Toxikologie

  • ISSN: 2174-8365
  • H-Index der Zeitschrift: 1
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  • SHERPA ROMEO
  • Internationales Komitee der Herausgeber medizinischer Fachzeitschriften (ICMJE)
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Abstrakt

According to Person to the Citizenry: Including Birthrate Geographic Diversity in Experimental Studies of Pharmacology

Rituparna Maiti

Due to a variety of circumstances, including previous and ongoing stressors, age, sex, and genetic make-up, humans react to chemical exposures differently. However, the impact of population-level variability within dose-response relationships has not been taken into account in the great majority of laboratory-based toxicity research. Risk assessment is made more difficult by the absence of information on how genetic variety affects how the body reacts to chemical exposure since everyone in the population will react differently to toxicant exposure. Notably, genetic variety is becoming increasingly important in laboratory models because it significantly influences how people' responses to drugs or chemicals vary at the population level. Here, we provide numerous assay models that can be utilised in laboratories. genetically different cell lines, human primary cells, and genetically diverse mouse panels were used to study the impact of genetic variation on an individual's sensitivity to chemicals. To illustrate the potential, viability, and strength of each of these models, we also offer a brief summary of a number of important studies. The purpose of this article is to draw attention to the significance of incorporating population-level genetic variation into toxicological study designs using laboratory-based models in order to offer and augment data for evaluating the risk that chemicals pose to the general population. As a result, taking genetic variability into account will benefit risk assessment based on human behaviour and give empirical evidence to support and guide decision-making processes in connection to chemical exposures.

Keywords

Genetic Variability, Risk Assessment, Population-Based Models

Haftungsausschluss: Dieser Abstract wurde mit Hilfe von Künstlicher Intelligenz übersetzt und wurde noch nicht überprüft oder verifiziert