Introduction
Pharmacogenomics, in an integrative way, examines the variations in genes’ generated by the systemic interplays within medications and the entire genome, utilizing the benefits from genomics, transcriptomics, and epigenomics in psychiatry. Genetic precise profiling could have a positive effect on interpatient variety in therapeutic effectiveness and decrease adverse drug reactions (ADR). In terms of conventional medicine, the World Health Organisation (WHO) states that only thirty-seven percent of cases of non-psychotic extreme depression proclaimed remission to a selective serotonin reuptake inhibitor (SSRI) as a primary drug (Tauser, 2020). Moreover, over sixteen percent of subjects discontinued the treatment due to reduced tolerance, and only half of the antidepressant-based treatment patients have a response. Lastly, over fifty percent underwent at least one ADR (Tauser, 2020). Therefore, it is essential to study alternative solutions that can be applied in psychiatry, and pharmacogenomics is considered highly promising. Scholars have researched pharmacogenomics, primarily comparing them to conventional treatment, analyzing the competency of medical staff, testing its effectiveness for young adults, and determining its connectedness to Artificial Intelligence.
Comparison between Conventional Therapy and Pharmacogenomic Testing
The 2020 study conducted by Hauser overviews the contemporary advancements in the clinical applicability of pharmacogenomics to personalized psychotropic treatment. The author explores recent pharmacogenomics studies with the central aim to interpret and explain the influence on the clinical results and well-being of psychiatric patients (Tauser, 2020). The primary focus is on the genetic variants in dopamine, serotonin, metabolic routes of medications, and the personal leukocyte antigen system (Tauser, 2020). The article concentrates on highly used classes of drugs, including, antidepressants, antipsychotics, and mood stabilizers. The significance of pharmacogenomics has facilitated the growth and business endorsement of some predictive tests, which are currently incorporated into various psychotropic medications labels. Therefore, the study analyzed the issues with traditionally applied medical solutions and explained the way pharmacogenomics can apply to psychotropic treatment.
The study suggests that predictive pharmacogenomics tests have replaced the traditional way of drug prescription, where patients had to try different standard drugs and see if it has any effects on them. This is mainly because the idea that one type of drug and dose of this drug can similarly fit all patients is not efficient in personalized therapy. Additionally, pharmacogenomics efficiently leads the composition of clinical studies by considerably decreasing the failure frequencies, costs, and vulnerability risks of non-responding to new medications (Tauser, 2020). Overall, the study highlights the contemporary advancement and potential prospects in the area of pharmacogenomics designed to assist with personalized therapy in different ways. Primarily, the field can influence the choice of the appropriate drug, prescribed in its most suitable dose, to the appropriate subject. The analysis should be based on their distinct genetic biomarkers. Lastly, it has the potential to help in making clinical trials more accessible and less costly. Thus, this study adds to the understanding of the essential issues within contemporary personalized therapy, as it tends to be too general to fit every patient.
Other researchers compare pharmacogenomics to conventional medicine. The study by Greden et al. (2019) was designed to evaluate the efficacy of pharmacogenomic testing in subjects suffering from major depressive disorder (MDD). The scholars conducted the Genomics Used to Improve Depression Decisions (GUIDED) experiment. Overall, this trial is the most comprehensive, randomized, and long-term within the course of pharmacogenomic examination for MDD (Greden et al. 2019). In this study, the treatment managed by pharmacogenomic testing was examined in contrast to unguided therapy among individuals with MDD. The latter patients were not able to have a responsibility to at least one sufficient medication test. Subjects were monitored for twenty-four weeks; in particular, scholars examined symptom improvement responsiveness and possible remission. A pharmacogenomic method assessed the genotypes of fifty-nine alleles and modifications across eight genes.
The results of this experiment assist in clarifying several matters and applications concerning the efficacy of pharmacogenomic testing in cases of complex MDD. Primarily, the scholars state that multi-gene pharmacogenomic measurement for individuals with therapy resistance notably increased the probability of achieving responsiveness and potential remission over treatment as usual (TAU) medication. This analysis revealed statistically significant changes amongst cases on congruent versus incongruent drugs at week eight and further in the experiment (Greden et al. 2019). Moreover, the trial presented noticeably fewer individuals who shifted to congruent medications endured side effects, unlike those who did not. Overall, the study is essential due to its size and length, which substantially adds to the knowledge available about the use of pharmacogenomic testing.
Competency of Professionals
Furthermore, researchers attempt to analyze whether contemporary specialists are aware of pharmacogenomics testing procedures. The study conducted by Chen et al. (2017), intends to determine the views and beliefs of clinicians within psychiatry settings toward pharmacogenomics examination. In particular, to comprehend potential limitations and dangers connected to the implementation of this method (Chen et al. 2017). The scholar anonymously surveyed health professionals and pharmacologists that were practicing in psychiatry. Other essential characteristics of participants included particular issues on pharmacogenomics; including self-assessed competency, understanding the value in clinical circumstances, recognized dangers, and selected method of their studies were assessed. Overall, 194 psychiatrists and pharmacists operating within the public and private healthcare in Singapore Medical Council took part in the qualitative research (Chen et al. 2017). Such experiments are particularly crucial because learning from other health professionals, mainly involved in the psychiatry field is vital for future development and quality improvement of both pharmacogenomics and personalized therapy.
Some of the essential findings are that over ninety-six percent of respondents stated that it is the psychiatrist who should be able to decide whether pharmacogenomic testing is suitable for every given clinical circumstance. Nevertheless, recognized competency was low, as only fifty to sixty percent of subjects appeared qualified in the different aspects of such testing (Chen et al. 2017). Moreover, pharmacists perceived themselves as more competent than doctors in recommending pharmacogenomic tests, recognizing appropriate clinical circumstances, and notifying patients about potential benefits and risks (Chen et al. 2017). However, most respondents acknowledged that that pharmacogenomic tests could be useful in the context of medication intolerance. Furthermore, one of the respondents stated “It is mainly in academic and research settings that these tests are accessible. The challenge will be how to implement them for routine usage with clinicians” (p. 534). Thus, although most respondents see potential in such testing, they also realize that pharmacogenomics is understudied and require additional research before active implementation in practice.
Pharmacogenomic Testing and Young-Adults
Lastly, researchers analyze pharmacogenomics in the context of other sciences. The research conducted by Wehry et al. (2018) considered the improvement in pharmacogenomic testing and the accelerated speed at which data are gathered in pediatric patients. Therefore, the researchers strived to review the core principles of pharmacogenomic testing in young people suffering from psychiatric disorders with the help of current literature on the topic (Wehry et al. 2018). Different pharmacodynamic genes have been classified as related to the tools of action for antidepressants, stimulants, and anti-adrenergic medications. Thus, the overall variation in these genes is examined concerning psychopharmacologic interference equally in children and adults. However, this study is particularly useful because it focuses the discussion on a narrow topic of psychotropic treatment, which positively contributes to knowledge of such in the context of one distinct group of individuals.
The article highlights that psychiatric illnesses are prevalent in children and adolescents and often result in notable morbidity, including adverse effects on the quality of life and well-being. Therefore, it is typical for individuals with psychiatric disorders to undergo tests of various psychotropic drugs before classifying a medication that can be the most suitable in this particular situation. The research is expanding for the addition of pharmacodynamic genes in the type of panels used for these purposes (Wehry et al. 2018). There are clear limitations to the implementation of pharmacogenetic testing. Still, it has the potential to reduce sickness rates, modify side effects, advances therapy response, decrease re-admissions because of the lack of effectiveness of the initial treatment (Wehry et al. 2018). Therefore, this helps to reduce the cost of treatment for the subject and their family. Despite the positive discoveries, more research needs to be done to fully recognize the effects of pharmacogenomics testing on the clinical therapy of children and adolescents.
Pharmacogenomic Testing and Artificial Intelligence
A 2020 study researched by Lin, Lin, and Lane has mentioned the increasing evidence that implies that pharmacogenomics is considered to be an essential pillar of medical studies by providing access to precise medication to subjects with psychiatric disorders. Moreover, based on the recent improvements in artificial intelligence (AI) and machine learning systems, various associated practices are being observed in the accuracy of psychiatry analysis by applying neuroimaging and multi-omics (Lin, Lin, and Lane, 2017). Thus, in their study, scholars focused on the developments for pharmacogenomics research involving AI and machine learning procedures, including deep learning and neural network algorithms, as well as multi-omics and neuroimaging data.
Neuroimaging-driven and multi-omics-driven techniques have great potential for clinical examinations regarding AI and machine learning methods to determine therapeutic outcomes or specialized medications that may add to possible solutions. Therefore, healthcare administrators, the federal government, and the public should acknowledge these concerns and objections with a high priority. Researchers concluded that they presume that treatments for psychiatric disorders over the next few years need to comprehend the interplays between multi-omics and neuroimaging datasets (Lin, Lin, and Lane, 2017). The contemporary improvements in data-intensive medical sciences and single-cell sequencing tools could give a start to unique AI software structures, which can be beneficial for domestic and global well-being. This research shows the complexity of pharmacogenomics and its connectedness to other industries and specializations. Lastly, it presents the importance of constant cooperation between various groups of individuals, including developers, pharmacists, doctors, governments, and the public.
Conclusion
To conclude, the treatment of mental illness is usually achieved on a foundation of trial-and-error, while healing from drugs prescribed that way is not always ensured. Thus, pharmacogenomic treatment and testing helps to address the fundamental neurochemical bases of psychiatry and is a valuable instrument in therapy. Although some healthcare settings are starting to realize the advantages of these genetic improvements, the area of psychiatry has yet to apply these advancements widely. Thus, the literature analysis is essential in learning more about the topic, and the potential benefits pharmacogenomics has on the field.
Reference List
Chen, C. et al. (2017) ‘Clinicians’ perceptions of pharmacogenomics use in psychiatry’, Pharmacogenomics, 18(6), pp. 531-538. Web.
Greden, J. F. et al. (2019) ‘Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: A large, patient- and rater-blinded, randomised, controlled study’, Journal of Psychiatric Research, 111, pp. 59–67. Web.
Lin, E., Lin, C. H. and Lane, H. Y. (2017) ‘Precision psychiatry applications with pharmacogenomics: Artificial Intelligence and machine learning approaches’, International Journal of Molecular Sciences, 21(3), p. 969. Web.
Tauser. R. (2020) ‘Pharmacogenomics in psychiatric disorders’, Broad Research in Artificial Intelligence and Neuroscience, 11(1), pp. 57-66. Web.
Wehry, A. M. et al. (2018) ‘Pharmacogenomic testing in child and adolescent psychiatry: An evidence-based review’, Current Problems in Pediatric and Adolescent Health Care, 48(2), pp. 40–49. Web.