Pharmacogenomics, sometimes known as "personalised medicine," is the process of adapting medication therapies to a patient's genetic profile.
Drugs have varied effects on different people. Most people react positively, and their health gets better. A small percentage of patients experience negative effects, and some do not benefit from the treatment.
Your body processes (metabolises) drugs after you take them. Your genes play a role in how the medicine is digested and how you react to it.
These genes have an impact on the equipment used to manufacture the medication.
Doctors can more precisely choose the treatment and dosage that is optimal for each patient if they are aware of how different genetics affect how a drug is digested.
Pharmacogenomics is the study of a person's genome to determine the genetic components that affect how they respond to medications.
By identifying these genes, scientists hope to develop genetic tests that predict how patients will respond to a medicine and the appropriate dosage. In the future, doctors may be able to choose the optimal medications for their patients based on the findings of these tests.
This will assist them pick the treatment that will most effectively treat their ailment with the fewest negative effects. This is individualised medical care. In addition to minimising the risk of side effects, pharmacogenomics enables more effective treatment administration.
Some cancer treatments, for instance, can be extremely expensive but may only be beneficial for a limited proportion of patients. With a greater understanding of the disease and treatment thanks to pharmacogenomics, resources can be allocated to medicines that are more likely to be beneficial for a given patient, regardless of cost.
The reason individuals respond differently to medicinal treatments is due to genetic variances or variation. Following the completion of the Human Genome Project, researchers have concentrated on comparing human genomes to better comprehend genetic variation and determine which genetic variants are crucial for health and treatment response.
Common types of variation in the human genome are as follows: Single nucleotide polymorphisms (SNPs): SNPs, or single nucleotide polymorphisms, are variations in single nucleotide bases (A, C, G and T). Structural variation: alterations impacting sections of DNA that can alter the chromosome's overall structure.
SNPs are analogous to changing a single letter in the metaphorical "recipe book of life," whereas structural variation is analogous to losing or duplicating entire paragraphs or pages.
Long before it was possible to sequence and compare numerous genomes, scientists were aware of SNPs, but the magnitude of structural variation, particularly copy number changes, was not known.
Approximately twelve percent of the genome appears to be subject to structural variation. It has been reported to cause numerous genetic disorders.
Humans share approximately 99.5% of their genes. Our susceptibility to sickness and treatment response are influenced by the 0.5% of variation that exists between us. Although this may not seem like much, it indicates that there are millions of changes between two persons' DNA.
For instance, SNPs are prevalent throughout the genome. Therefore, it is difficult to determine which single-letter mutations cause disease and which are merely along for the ride and have no influence on health. How then can it be determined which genetic variations cause disease and which are merely passengers?
Scientists examine disease variations by comparing the genetic makeup of a large number of individuals with and without a certain disease. This allows scientists to search for genetic variants that are more prevalent in diseased individuals compared to healthy individuals.
For instance, if a certain genetic variant is present in 80% of patients with an illness but in only 20% of the healthy population, this may indicate that the variant increases the risk of that disease.
The simplest example is searching for a disease that is caused by variations in a single gene. There are numerous complex disorders associated with variations in numerous genes.
Therefore, for this form of comparison to be useful, extremely large groups of individuals, typically in the tens of thousands, must be researched to identify variations with minor impacts on illness risk.
Researchers often attempt to select diseased and healthy individuals with similar characteristics, making it easier to find and analyse disease genes.
Although pharmacogenomics is likely to play a significant role in future medical care, there are numerous barriers to overcome before it becomes standard practise:
It is uncommon for a single genetic mutation to influence the reaction to a particular medicine. A specific genetic variant may enhance the probability of a negative reaction, but it does not guarantee it.
Consequently, some individuals with the variation may not experience an unfavourable pharmacological reaction. Similarly, the absence of the gene variant does not guarantee that an individual would not experience an unfavourable reaction.
There are frequently a significant number of genetic and environmental factors that interact to determine the medication response. Even when clear connections between a genetic variant and a therapeutic response have been shown, relevant tests must be devised and their efficacy must be demonstrated in clinical trials.
A clinical trial-successful test must still demonstrate utility and cost-effectiveness in a healthcare context. Regulatory bodies will need to evaluate how they evaluate and approve pharmacogenetic products.
Health services will need to adopt new methods for determining the optimal medicine to administer to an individual. The behaviour of individual physicians must alter. Many adverse effects are caused by people not taking their medications as directed or by doctors providing the incorrect dose.
Some successful applications of pharmacogenomics, such as abacavir and HIV, demonstrate that these obstacles are occasionally surmountable. In most instances, however, the introduction of pharmacogenomics discoveries is likely to be a complex process.