International Journal of Molecular Medical Science, 2024, Vol.14, No.1, 61-68 http://medscipublisher.com/index.php/ijmms 63 CYP2D6*10/*10. Blood samples were dynamically collected to measure codeine and its metabolites morphine, morphine3 -glucuronide (M-3-G), and morphine-6-glucuronide from subjects who took a single oral administration of codeine. (morphine 6-glucuronide, M-6-G) plasma concentration. Although there is no significant difference in the pharmacokinetic parameters of codeine in subjects with different genotypes, there are significant differences in Cmax and the area under the drug-time curve of morphine, M-3-G, and M-6-G between groups (P<0.05). 1.3 Application of genomic information in predicting drug responses and side effects Genomic information has important application value in predicting drug responses and side effects. By parsing an individual's genomic information, it is possible to predict their response and efficacy to specific drugs, thus avoiding unnecessary drug trials and potential side effects. Genetic variations are associated with drug resistance, meaning some patients may not respond to certain drugs. (Xu et al., 2019). In this case, predicting drug response through genomic information can help doctors choose more effective treatments for patients. Genomic information can also be used to predict the side effects a drug may cause. By identifying genetic variants associated with drug side effects, doctors can assess patients' risk before administering the drug and take appropriate preventive measures. Tsigelny (2019) By in-depth understanding of how genomic information affects drug response and efficacy, as well as the impact of genetic polymorphisms, mutations, and expression levels on drug response, we can better predict and adjust drug treatment plans and achieve the goal of personalized medicine. Wu et al. (2015) observed the impact of different CPY2D6*10 genotypes on the use of fentanyl for postoperative analgesia in Chinese gastric cancer patients after surgery, and also obtained similar findings, which confirmed the above results, that is, the postoperative mutant type (m/m The cumulative opioid consumption of patients in the) group increased significantly; at the same time, no significant difference in adverse reactions was observed among the groups (P>0.05). Therefore, CPY2D6*10 gene polymorphism can affect patients' postoperative response to opioid analgesia. 2 Strategies for Optimizing Drug Treatment using Genomic Information 2.1 Genome-oriented drug discovery and development process The genome-directed drug discovery and development process is a revolutionary approach that uses genomic information to guide drug development, resulting in more efficient and precise treatments. This process begins with genomic research on specific diseases, which provides important clues for the screening of drug targets by identifying gene variations and expression patterns related to the occurrence and development of the disease. After obtaining potential drug targets, researchers will use genomic information to design and optimize drug candidates (Yang et al., 2021). This includes using genomic data to predict the ability of drugs to bind to targets, and to evaluate the efficacy and side effects of drugs. In addition, genomic information can help researchers identify potential safety risks in the early stages of drug development, thereby avoiding failures in later clinical trials. Cancer treatment based on gene technology allows cancer to be prescribed from "seeing the doctor" to "prescribing medicine based on the person". This is the first time that humans have begun human trials using gene-edited T cells to treat cancer. It can be said that this is also a leap forward in the development of personalized cancer treatment. As the official press release of Nature magazine pointed out, this is the first intersection of the two hot fields of personalized gene editing and anti-cancer cell therapy, which is expected to have a profound impact on cancer treatment. Antoni Ribas, the corresponding author of the study, also said: This is a major leap forward in personalized cancer treatment using isolated immune receptors to specifically recognize patients' own cancer mutations (Foy et al., 2023). Nielsen et al. (2016) tested the influence of multiple genes on pain sensitivity in healthy subjects. Experimental tests included thermal cutaneous pain stimulation, muscle and bone stimulation, mechanical, electrical and
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