2 3 Pharmacogenomics



Pharmacogenomics is one of the emerging approaches to precision medicine, tailoring drug selection and dosing to the patient's genetic features.This specific field aims to tailor treatment based on the DNA of individuals or group of individuals. Pharmacogenomics measures how DNA effects how you respond on drugs. It is possible for your DNA to influence whether you have a bad reaction to a drug or if it has any effect on you.
Thanks to this new approach it's possible to test more effectively drug safety , improving your health. By knowing this information, your doctor can prescribe the most effective medicine for you.To discover and develop new drugs, multigene profiling, and whole-genome single nucleotide polymorphisms (SNPs) are used in modern approaches.

Scientists study the effects of drugs on individuals by focusing on two major factors:
(1) the amount of a drug that is required to reach its target in the body.
(2) the response of target cells, such as neurons or heart tissue.
In pharmacogenomics, these two determinants are called pharmacokinetics and pharmacodynamics, and both are critically important.

History of Pharmacogenomics

The history of Pharmacogenomics can be traced back to 500 BCE, when Pythagoras discovered that eating fava beans was fatal for some individuals but nourishing for others , and that the beans could be used to treat constipation.

The next major discovery in the advent of Pharmacogenomics was by Archibald Garrod, who hypothesized that the ingestion of substances affects genes at the molecular level,and that specific enzymes are required for detoxification.

According to Garrod, the lack of theseenzymes led to metabolic disorders and potential fatality. By the 1940s and 1950s, scientists had begun to observe and report a range of atypical esponses to medications. During World WarII, some soldiers, after being administered antimalarial drugs, developed a range of adverse side effects, including anemia. It was later found that these soldiers were deficient in the enzyme glucose 6-dehydrogenase. Within the same period, the anesthesia drug succinylcholine was found to prolong paralysis and induce fatal reactions in some individuals with a mutated genetic variant linked to the absence of the enzyme butyrylcholinesterase.6 Nevertheless, it was not until the late1950s that Friedrich Vogel coined the term ‘pharmacogenetics.’

During this period, the single most important contribution that propelled genetic studies in the 20th century was the discovery of the double helical structure of DNA by James Watson and Francis Crick. Later, the term ‘pharmacogenomics’ became official during the launch of the Human Genome Project in 1990,and, once human DNA mapping was completedin 2003, the field of Pharmacogenomics began to grow.


Figure 1: provides a mind map of the development of Pharmacogenomics

Pharmacogenomics and modern medicine

The study of Pharmacogenomics led to the birth of a booming biotechnology industry that continues to identify new cures and therapeutic treatments for diseases.
Nonetheless, pharmaceutical companies face high costs in producing and marketing these drugs.9 Collaboration between pharmaceutical companies and other biotechnology entities has become a necessity in the search for affordable and effective treatments.
This research has resulted in considerable advancement in the fields of medicine and nursing, and has helped elucidate how genes interact with medications to open new pathways in identifying genotypes and phenotypes suitable for specific medications. Research has broadened practitioners’ understanding of psychotropic medications and how to minimize adverse drug reactions.


In recent years, several pharmacogenetic guidelines have been published by international scientific consortia, but the uptake in clinical practice is still poor. Many coordinated international efforts are ongoing in order to overcome the existing barriers to pharmacogenomic implementation. On the other hand, existing validated pharmacogenomic markers can explain only a minor part of the observed clinical variability in the therapeutic outcome. New investigational approaches are warranted, including the study of the pharmacogenomic role of the immune system genetics and of previously neglected rare genetic variants, reported to account for a large part of the inter-individual variability in drug metabolism.
In this Special Issue, eleven papers are published, covering different aspects of research and clinical application in the field of pharmacogenomics.
Six reports are about the discovery of new genetic markers of the outcome of a pharmacological treatment in terms of either efficacy or toxicity.Two papers focus on the pharmacogenomics of platinum derivatives( they can radically resected ovarian cancer patients from TCGA).Three papers report analise the improvement of the clinical practice achieved using pharmacogenomic.


There are now well-established genetic causes of many prevalent diseases with high mortality rates. Based on sibling analyses, it has been predicted how much genetics contributes to diseases such as obesity and diabetes. Likewise, some rare gene mutations give insight into more complex biological processes. CETP (cholesteryl ester transfer protein) can clearly be demonstrated to exert an influence on HDL levels in patients when HDL levels in their blood are extreme. An individual with mutations caused by the Janus kinase 3 (JAK3) gene may have a severe combination of immune-deficient syndromes, as loss of JAK3 might affect the human immune system. In this way, pharmacogenetics was applied in order to investigate drugs inhibiting CETP and JAK3. As a result of the advent of pharmacogenomics, we can now establish relationships between disease states and human genes and identify suitable therapeutic targets.

Nowadays, many academic institutions and pharmaceutical companies strive to determine whether disease phenotypes correlate with genetic variations in order to categorize diseases. Nevertheless, the collection of medical phenotypes with DNA samples provides a prominent opportunity for the study of the genetic variation found among patients. A particular patient's DNA can be collected to study genetic variation. The relationship between phenotypic novel lipase genes and HDL levels was demonstrated in a study using DNA extracted from a patient who had been participating in lipid lowering trials. These studies follow a sound hypothesis which is linked to candidate's biological gene selection, according to literature reports. In this way, it is now easy to cross-examine the genome selection based on phenotypic criteria. Over the last few years, these stages have substituted over 300,000 SNPs across the genome, utilizing only a few haplotype-defining SNPs. By using high-density oligonucleotide arrays and restriction enzyme-based genomic reduction, Perlegen sciences have developed technologies for genotyping massive numbers of markers. Despite advances in technology, we still do not know exactly how many haplotype-defining SNPs there are. Several recent studies have revealed that in order to detect more than 80% of all haplotypes, it is necessary to achieve a r2 of >0.8% to measure polymorphisms across selected gene regions. As a result of the HapMap project progress with defined LD patterns, scientists studying genes can thoroughly assess the degree of LD in represented regions or select regions. In this way, we can explore more about selection of SNPs regardless of study design. Understanding of complex diseases such as psychiatric and cardiovascular illnesses will also become more efficient with genome approaches, since they do not rely upon the selection of candidate genes. According to some researchers, the new horizons on LD coverage about insights into the human genome and SNP density will provide phenotypic information and show significant genomic portions. A total of 7283 SNPs connected to 17.1 megabases (Mb) of DNA were genotyped as part of a study to assess the Perlegen Sciences chip-based array-based platform and to justify the haplotype tagging approach used to identify genetic associations. In addition, SNPs connected with 50 CETP haploblock genes were found to be the most valuable associations in the dataset. Several companies, such as Perlegen, and projects, such as the Hap Map project, recently announced their intentions to provide SNP markers for public provinces to be used for such experiments.

Clinical researchers might be able to minimize possible adverse effects if clinicians use genetic information in deciding which drug to use and at what dose for which patient. For instance, traditional treatment for hypertension involves trying a wide range of pharmaceuticals until a desired blood pressure level is reached with adequate drug tolerability. Few first-line drugs/agents in this case failed to lower blood pressure or resulted in intolerable side effects. Ultimately, patients suffered because of this method of selecting medications. Pharmacogenetics, based on DNA analysis, provides the greatest response with the greatest tolerability. A pharmacogenetic approach may enable the creation of new drugs with fewer side effects based on genetic regulators of cellular functions. In fact, chromosome translocation and its derived enzymes are responsible for life-threatening chronic myeloid leukemia (CML) resulting in the faster FDA approval of Imatinib, an inhibitor of the translocation-created enzyme. The goal of this core subject is to improve the quality and lower the total cost of healthcare by minimizing adverse reactions and reducing treatment failure, resulting in the development of new genetic targets for disease treatment.

What role do genes play in how medicines work?


The same genes that determine our hair color and eye color also determine how our bodies respond to medicine.
Different people can have different versions of the same gene, each of which has a slightly different DNA sequence, which is how proteins are built. Genes are instructions, written in DNA. Some variants are common, while others are rare. In addition, some variants have a negative impact on health, such as those associated with certain diseases.
Scientists know that certain proteins affect how drugs work. Pharmacogenomics examines the genetics of these proteins.
Such proteins include liver enzymes that chemically change drugs.
Sometimes chemical changes can make the drugs more—or less—active in the body. Drug safety or effectiveness can be negatively impacted by even small differences in the genes that code for these liver enzymes.
One liver enzyme, known as CYP2D6, acts on a quarter of all prescription drugs.
It converts per example the painkiller codeine into its active form, morphine. CYP2D6 has more than 160 versions. Most of the variants don´t affect how people respond to the drug.
Normally people have 2 copies of each gene. The CYP2D6 gene is found in some people in large numbers, even in thousands. Those with extra copies produce too much of the CYP2D6 enzyme and process the drug very fast. Their bodies may convert codeine to morphine so quickly and completely that they may overdose from a standard dose. On the other hand, some CYP2D6 variants don't produce an enzyme.
Codeine is processed slowly by individuals who have these variants, resulting in little, if any, pain relief. For people like this, doctors can prescribe a different drug.

How is Pharmacogenomics affecting medical treatment?

The doctors prescribe drugs based mostly on factors such as a patient´s age, weight, sex, liver, and kidney function. For some drugs, researchers have identified gene variants that affect how people respond. In these cases, each doctor can choose a medication and dose tailored to the patient.
To know how patients respond to each medication, helps to discern the different forms of their diseases.

How is Pharmacogenomics affecting drug design, development, and prescribing guidelines?


The long-term future of pharmacogenomics-based drug development looks something like: Lead compounds coming out of preclinical pharmacogenomic testing will ideally be chosen based on the fact that they are metabolised and eliminated by several alternative pathways. Phase I volunteers who might be at risk for toxicity due to metabolic status for these same paths of elimination might be identified and studied for dose limiting tolerance.

Genetic traits that predict efficacy (ie, receptor status) will be a focus of pharmacogenomic studies during Phase II-IV clinical studies to optimise the population of patients who will respond positively to treatment. Pharmacogenomic tests validated as positive markers of response will be developed as molecular diagnostic tests. Pharmaceutical companies will partner with pharmacogenomic and diagnostic companies to develop panels of tests that will be submitted for regulatory approval in parallel with the new drug applications.

Investors demand that pharmaceutical companies deliver several new drugs to the marketplace each year. Additional pressure in the form of price control comes from government, managed care and insurance reimbursement institutions. Pharmaceutical companies are rethinking the old drug development paradigm and many are investing in pharmacogenomics as a new approach to the discovery, development and marketing of new drugs.

Pharmacogenomics will increase the number of new viable drug targets and decrease the risks associated with development. Incorporating pharmacogenomics into drug development will eliminate the unpredictable response of drug treatment due to genetic polymorphisms that affect metabolism, clearance and tolerance.

The efficacy of new drugs will become more predictable as we correlate genetic changes in drug targets, receptors and transporters with associated patient response.

Ultimately, pharmacogenomics promises to change how physicians choose drugs and the correct dose based on each individual’s unique genetic profile. For now, this important tool can impact the way pharmaceutical companies develop drugs provided they are willing to accept a new paradigm that recognises that drugs rarely work in all patients.

Figure 3 illustrates the theoretical differences in the stability of drug sales from the conventional paradigm to one that incorporates pharmacogenomic testing as a crucial element of product launch. The model accounts for the loss in market share when drugs ultimately demonstrate either toxicity or lack of efficacy in a subgroup of patients (Figure 3, Green Line).


Additional loss of market potential occurs when the drug ends up as second choice and physicians choose competing products because of uncertainties regarding both toxicity and efficacy in drugs prescribed to patients. In theory, the market share will be further eroded when competitor compounds linked to pharmacogenomics enter the market (Figure 3, Red Line). The basis, in part, for this theory is that physicians will initiate therapy and continue patients on drugs based on personalised medicine, that is, prescribing drugs based on previously established pharmacogenomic tests that predict efficacy and lack of toxicity (Figure 3, Blue Line).

For now the industry is waiting for the first successful launch of a drug that requires genetic testing prior to prescribing. Several companies are contemplating the co-development and approval of pharmacogenomic drugs and diagnostic tests, primarily for compounds that demonstrate very good efficacy in a patient subpopulation. The floodgates may be opened after the first successful demonstration of this new approach.

What is the future of pharmacogenomics?
Greater clinical uptake of pharmacogenomic testing and consumerism is anticipated to grow exponentially in the future. Professional pharmacy organizations such as American Society of Health System Pharmacists (ASHP) support efforts to incorporate pharmacogenomics into clinical practice.



This page was created by Amanda Balan, Oumaima Ahouzi, Selen Bulut .

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