International Journal of Molecular Medical Science, 2024, Vol.14, No.1, 61-68 http://medscipublisher.com/index.php/ijmms 62 1 Association between Genomic Information and Drug Treatment 1.1 How genomic information affects drug response and efficacy Genomic information is the core of personalized medicine, which profoundly affects the response and efficacy of drugs in an individual. Each person's genome is unique, which determines the differences in the body's absorption, distribution, metabolism and excretion of drugs. Therefore, genomic information is crucial for predicting and optimizing drug treatment regimens. Genomic information has great potential in optimizing drug treatments through strategies such as genome-guided drug discovery and development, drug dosage adjustment, and drug combination and optimization of treatment regimens. Better use of genomic information to develop personalized treatment plans, improve treatment effectiveness and reduce the risk of side effects. In 2017, a survey by Giacomini and others found that genomic information can reveal an individual's response mechanism to drugs. Certain genetic variations may lead to changes in drug targets, thereby affecting the efficacy of drugs. Genomic information can also help understand the metabolic pathways and speeds of drugs in the body, which is important for adjusting drug dosage and avoiding side effects caused by drug accumulation (Giacomini et al., 2017). Yang et al. (2021) systematically analyzed the relationship between genomic information and drug response to reveal the key factors affecting drug treatment effects, providing new perspectives and methods for drug development and treatment strategies. It is also hoped that this research can promote the development of personalized medicine and bring better treatment effects and quality of life to patients. Huang et al. (2016) found that the bioavailability and metabolism of PPIs are mainly affected by the drug metabolizing enzyme CYP2C19 and partly affected by CYP3A4. The differences in CYP3A4 and CYP2C19 enzyme activities caused by individual genetic factors are the molecular mechanisms responsible for the differences in PPI efficacy. one. Mutations in the CYP2C19 encoding gene can cause changes in the metabolic activity of the CYP2C19 enzyme, resulting in differences in blood drug concentrations and even different clinical reactions in different patients after taking drugs with CYP2C19 as the key metabolic enzyme. In addition, non-genetic factors such as concomitant medication and diet are also important factors affecting the efficacy of PPIs. 1.2 Effects of genetic polymorphisms, mutations and expression levels on drug response Gene polymorphisms, mutations, and expression levels are three important aspects of genomic information that all have a significant impact on drug response. Gene polymorphism refers to the presence of multiple alleles at the same genetic locus. These alleles may contribute to individual differences in response to and efficacy of drugs. For example, certain genetic polymorphisms are related to the activity of drug-metabolizing enzymes, which in turn affects the concentration and efficacy of drugs in the body. Min et al. (2015) used a clinical prospective randomized controlled study method to randomly divide 149 patients with extensive burns into a control group and an experimental group. The control group was given opioids in the normal mode, and the experimental group was given opioids based on the patient's genetic testing results. The patients' pain assessment scores at different time points were recorded. The results showed differences in the patient's genotype. The dosage of opioids was adjusted and individualized administration was performed. The design of drug regimen can save the dosage of opioids, increase the analgesic effect, and reduce the incidence of adverse reactions. Barton et al. (2015) found that gene expression level refers to the degree to which a gene is transcribed into mRNA and translated into protein. Differences in gene expression levels may lead to changes in the quantity or activity of drug targets, thereby affecting the efficacy of the drug. By analyzing gene expression levels, we can better understand the mechanism of action of drugs in an individual and optimize treatment options accordingly. Wu et al. (2015) took the Chinese Mongolian population as the research object, used the PCR-RFLP method to analyze CYP2D6 genotypes, and grouped them according to genotypes: CYP2D6*1/*1, CYP2D6*1/*10 and
RkJQdWJsaXNoZXIy MjQ4ODYzNQ==