Original title: GEN: A new pattern of pharmacogenetics [ China Pharmaceutical Network Science and Technology News ] Various studies on the same disease, pharmacogenetics and pharmacogenomics have confirmed that genetic differences are related to the sensitivity of chemotherapy drugs. Genotyping has been used as a basic method for the study of the correlation between gene composition and pharmacological efficiency; in addition, genotyping determines to some extent the patient's medication therapy and dose ratio. 
The use of genetic analysis can provide doctors with strong evidence and information. When implementing treatment programs, doctors can choose the most effective drug treatment plan for patients, which not only improves the efficacy, but also reduces the side effects of chemotherapy and improves the quality of life of patients.
If genotyping results are widely adopted, some obstacles will have to be overcome, especially the changes brought about by the assay and reporting delays, making it difficult to convert genotypes into specific actions in a timely manner, which may lack economic and/or clinical value. Fortunately, however, technological advances and access to genetic information will significantly change the application prospects of pharmacogenetics.
The efficacy of any medication depends on many factors, the most common being the pharmacokinetic parameters of absorption, distribution, metabolism, and excretion (collectively "ADME"). These factors combine to determine whether a patient needs to increase or decrease the dose, or whether the therapy can be used; in addition, these factors determine the patient's interaction between the combination drugs.
Genotype variation
This paper briefly investigates the diversity of genotypes in providing a genotypic intrinsic complexity, and the detailed description of specific genotypic variations is beyond the scope of this paper. Taking the most highly polymorphic gene, the human leukocyte antigen (HLA) gene, for example, more than 3,600 HLA class II alleles have been described. More than 50 human cytochrome P450s (CYPs) have been identified, and most have several single nucleotide polymorphisms (SNPs). Currently, more than 100 CYP2D6 have been identified as having single nucleotide polymorphisms. These characteristic loci are translated into a star allele polymorphism in combination to predict the therapeutic response of the treatment.
As expected, any single enzyme can metabolize multiple drugs, most drugs can be metabolized by multiple enzymes; drugs can inhibit metabolic enzymes, which convert high-activity compounds into active metabolites to stimulate drugs to react. In general, clinical changes in the functional activity of enzymes can classify patients into very poor, moderate, and ultra-speed metabolism.
The FDA has approved 166 drugs including labels containing pharmacogenomic information, including specific reactions based on biomarkers. The genetic analysis of most drugs is currently used as laboratory laboratory projects (LDTs); therefore, for any given target, there are extensive reports on specific variants. As noted above, CYP2D6 has more than 100 identifiable SNPs.
Historically, most of the past genetic tests used multiplex polymerase chain reaction (PCR) methods, the cost/energy of identifying genotyping was about the same as the cost of making a panel. In addition, because some functional variants vary from copy number, multiple assays may be required (eg, quantitative PCR copy number of copy number plus PCR genotyping).
Is there a better way? Recently, microarray technology has opened up a possibility for more complete analysis of genotypes and copy number, which can simultaneously detect multiple genes to reduce costs and increase the efficiency of pharmacogenomics. For example, Affymetrix's DMETAxiomAssay can analyze more than 4,000 genotypings from 900 gene copies in a single experiment.
From a regulatory point of view, the use of different techniques by the laboratory to generate genetic pharmacology will make it difficult for the FDA to define these devices. However, because microarray chips can provide genotypes and copy number multiple times, and at a low cost, multiple benefits of clinical analysis and effectiveness can be accelerated or the FDA's approval of the technology will be accelerated.
In addition, parameters such as age, race, body mass index, and gender can affect pharmacokinetics in certain specific situations. Establishing guidelines can help doctors choose the appropriate treatment using pharmacogenomic information. Currently in the United States is the Clinical Pharmaceutical Genetics Practice Alliance (CPIC) leading the way around specific genes and specific drugs.
Pre-emptive genotyping <br> <br> In most cases, doctors need to make treatment decisions immediately, rather than wait for the results of genotype. Obviously, in order to solve this pain point, we must develop a pre-emptive genotyping solution. Currently part of the Meta-Pharmacogenomics Project of the Mayo Clinic, Mount Sinai Hospital, St.Jude Children's Research Hospital, University of Florida and Fro Hospital and Vanderbilt University Medical Center.
Preemptive genotyping requires extensive deployment, and electronic health record information (EHRs) need to be updated to facilitate the retrieval, storage, and reporting of complex genotyping data. In addition, alleles, alternative drug dosing guidelines or recommendations that provide translation of complex genotyping data for specific drugs such as staralleles will be required to link the guidelines to other supporting information.
The most complex electronic medical records currently only consider EHR information that affects the dose of the drug, such as the patient's race, weight, gender, and other medications. Therefore, the preemptive genotyping trend will significantly change this pattern. On the one hand, health care institutions are increasingly recognizing the role of medical information officers; on the other hand, high-income companies such as technology giants Google and Apple have taken medical informatics and large-scale genetic/genetic analysis as areas of accelerated development.
Third-party payers are generally reluctant to pay for pharmacogenomic testing, which may become a major obstacle to pharmacogenetics. In the United States, it is currently dominated by government or non-profit organizations. The most famous is the Million Veterans Program, which aims to explore the pharmacogenetic association between metformin and kidney disease in diabetes.
The pace of future perspectives <br> <br> pharmacogenetics into the healthcare affected by several factors, including lower cost of genotyping, installation of medical information infrastructures, consumer demand for increased personal genetic information and so on. Under these factors, the pre-emptive genotyping results will become the norm in the future of medical development, not an exception.
As this trend accelerates, advances in genotyping technology, especially high-density genotyping and medical informatics with low cost and high reproducibility will become a reality, and the increase in genotyping data and other additional related information will Leading to more and more precise processing algorithms, the beginning of a virtuous cycle in the medical ecosystem.
The use of genetic analysis can provide doctors with strong evidence and information. When implementing treatment programs, doctors can choose the most effective drug treatment plan for patients, which not only improves the efficacy, but also reduces the side effects of chemotherapy and improves the quality of life of patients.
If genotyping results are widely adopted, some obstacles will have to be overcome, especially the changes brought about by the assay and reporting delays, making it difficult to convert genotypes into specific actions in a timely manner, which may lack economic and/or clinical value. Fortunately, however, technological advances and access to genetic information will significantly change the application prospects of pharmacogenetics.
The efficacy of any medication depends on many factors, the most common being the pharmacokinetic parameters of absorption, distribution, metabolism, and excretion (collectively "ADME"). These factors combine to determine whether a patient needs to increase or decrease the dose, or whether the therapy can be used; in addition, these factors determine the patient's interaction between the combination drugs.
Genotype variation
This paper briefly investigates the diversity of genotypes in providing a genotypic intrinsic complexity, and the detailed description of specific genotypic variations is beyond the scope of this paper. Taking the most highly polymorphic gene, the human leukocyte antigen (HLA) gene, for example, more than 3,600 HLA class II alleles have been described. More than 50 human cytochrome P450s (CYPs) have been identified, and most have several single nucleotide polymorphisms (SNPs). Currently, more than 100 CYP2D6 have been identified as having single nucleotide polymorphisms. These characteristic loci are translated into a star allele polymorphism in combination to predict the therapeutic response of the treatment.
As expected, any single enzyme can metabolize multiple drugs, most drugs can be metabolized by multiple enzymes; drugs can inhibit metabolic enzymes, which convert high-activity compounds into active metabolites to stimulate drugs to react. In general, clinical changes in the functional activity of enzymes can classify patients into very poor, moderate, and ultra-speed metabolism.
The FDA has approved 166 drugs including labels containing pharmacogenomic information, including specific reactions based on biomarkers. The genetic analysis of most drugs is currently used as laboratory laboratory projects (LDTs); therefore, for any given target, there are extensive reports on specific variants. As noted above, CYP2D6 has more than 100 identifiable SNPs.
Historically, most of the past genetic tests used multiplex polymerase chain reaction (PCR) methods, the cost/energy of identifying genotyping was about the same as the cost of making a panel. In addition, because some functional variants vary from copy number, multiple assays may be required (eg, quantitative PCR copy number of copy number plus PCR genotyping).
Is there a better way? Recently, microarray technology has opened up a possibility for more complete analysis of genotypes and copy number, which can simultaneously detect multiple genes to reduce costs and increase the efficiency of pharmacogenomics. For example, Affymetrix's DMETAxiomAssay can analyze more than 4,000 genotypings from 900 gene copies in a single experiment.
From a regulatory point of view, the use of different techniques by the laboratory to generate genetic pharmacology will make it difficult for the FDA to define these devices. However, because microarray chips can provide genotypes and copy number multiple times, and at a low cost, multiple benefits of clinical analysis and effectiveness can be accelerated or the FDA's approval of the technology will be accelerated.
In addition, parameters such as age, race, body mass index, and gender can affect pharmacokinetics in certain specific situations. Establishing guidelines can help doctors choose the appropriate treatment using pharmacogenomic information. Currently in the United States is the Clinical Pharmaceutical Genetics Practice Alliance (CPIC) leading the way around specific genes and specific drugs.
Pre-emptive genotyping <br> <br> In most cases, doctors need to make treatment decisions immediately, rather than wait for the results of genotype. Obviously, in order to solve this pain point, we must develop a pre-emptive genotyping solution. Currently part of the Meta-Pharmacogenomics Project of the Mayo Clinic, Mount Sinai Hospital, St.Jude Children's Research Hospital, University of Florida and Fro Hospital and Vanderbilt University Medical Center.
Preemptive genotyping requires extensive deployment, and electronic health record information (EHRs) need to be updated to facilitate the retrieval, storage, and reporting of complex genotyping data. In addition, alleles, alternative drug dosing guidelines or recommendations that provide translation of complex genotyping data for specific drugs such as staralleles will be required to link the guidelines to other supporting information.
The most complex electronic medical records currently only consider EHR information that affects the dose of the drug, such as the patient's race, weight, gender, and other medications. Therefore, the preemptive genotyping trend will significantly change this pattern. On the one hand, health care institutions are increasingly recognizing the role of medical information officers; on the other hand, high-income companies such as technology giants Google and Apple have taken medical informatics and large-scale genetic/genetic analysis as areas of accelerated development.
Third-party payers are generally reluctant to pay for pharmacogenomic testing, which may become a major obstacle to pharmacogenetics. In the United States, it is currently dominated by government or non-profit organizations. The most famous is the Million Veterans Program, which aims to explore the pharmacogenetic association between metformin and kidney disease in diabetes.
The pace of future perspectives <br> <br> pharmacogenetics into the healthcare affected by several factors, including lower cost of genotyping, installation of medical information infrastructures, consumer demand for increased personal genetic information and so on. Under these factors, the pre-emptive genotyping results will become the norm in the future of medical development, not an exception.
As this trend accelerates, advances in genotyping technology, especially high-density genotyping and medical informatics with low cost and high reproducibility will become a reality, and the increase in genotyping data and other additional related information will Leading to more and more precise processing algorithms, the beginning of a virtuous cycle in the medical ecosystem.
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