Realizing the promise of precision medical in psychiatry is an effort that should be praised and beneficial, because it must significantly reduce morbidity and mortality and, basically, ease the economic and social burden of psychiatric disorders. This review is aimed at summarizing important problems in pharmacogenomics in psychiatry which have placed the foundation of personalized pharmacotherapy and, in a broader sense, precision medicine.
We present the main pharmacogenomic biomarkers and their applications in various psychiatric disorders, such as depression, attention – deficit / hyperactivity (ADHD), narcolepsy, schizophrenia, and bipolar disorders. In addition, we extend the scope to epilepsy, because antiepileptic drugs are widely used to treat psychiatric disorders, although epilepsy is considered conventional considered a neurological disorder.
Using personal genome data in primary care: Bioinformatics Approach for Pharmacogenomics
One personalized drug application is a drug adjustment for individuals, so the drug will have the highest chance for success. To have individual drugs, one must have a complete inventory of all current pharmaceutical compounds (detailed formulations) combined with pharmacogenetic datasets, patient genetic makeup, family history (medical) and other health related data. For health professionals to utilize this information in the best way, it must be visualized in a way that makes the most relevant data medically accessible for their decision making. Similarly, to activate the bioinformatics analysis of this data, it must be prepared and provided through the interface for controlled computing analysis.
Because the level of personal information gathered for these initiatives, the choice of privacy-sensitive implementation and ethical standards is the most important. The personal genetic locker project provides an approach to allow the use of personal genome data in primary care. In this paper, we provide a personal genetic locker project description and show its utility through cases of use based on open standards, illustrated by the 4DBox system.
Pharmacogenomics and all treatments: How to optimize therapy
The inherited genetic variation can change the sensitivity of the drug in patients with acute lymphoblastic leukemia, predisposing to adverse treatment side effects. In this review, we discuss evidence of children and adolescents with acute lymphoblastic leukemia to review the pharmacogenomic data available with an emphasis on clinical inventions that can be followed up and emerge, for example, genetic variants on metopurin methyltransferase and nudt15 that change the dose of 6-mercaptopurine , We also highlight the need for ongoing pharmacogenomic research to validate the latest significance of findings. Further research in young adults, as well as with new therapy, is needed to provide optimal therapy in future trials.
Obstacles, solutions, and effects using pharmacogenomic data to support opioid recipes
The use and abuse of opioids continue the problems faced by doctors in all aspects of health care. As a doctor struggling to manage opioid recipes effectively, Pharmacogenomics (PGX) further offers the enhanced prescribers of the ability to understand the genetic potential of individual patients to influence the efficacy and safety of opioids. When PGX data is available at the initial pereseping point, the doctor can apply the data to the drug therapy selection. However, continued obstacles exist relative to the distribution and interpretation of PGX data, which has created difficulties for widespread PGX implementation.
This article briefly describes potential obstacles to PGX data integration, strategies to overcome these obstacles, and potential positive effects of successful data distribution on opioid recipes. The prescription drug monitoring program (PDMP) has been successfully operationalized to share substances recipe data that is controlled in all health care settings. Such data sharing allows doctors, among others, better understand the risks associated with abuse. Because relatively limited PGX data volume is currently related to opioid recipes, the PGX data can be added to PDMP as a way to communicate genetic information in the current technology platform.
This will not only integrate into the clinical workflow model where PDMP data is accessed at this point from recipes and / or expenses, but related clinical guides for PGX data interpretation in the context of the opioid can be integrated into the work process. Such clinical decision support can be given directly through the PDMP interface for uniformity or can be given through a system that accesses PDMP data.
Clinical, economic, and policy implications from the inclusion of PGX data in PDMP are also discussed. Through using PDMP to share data, some obstacles for PGX implementation can be reduced, and doctors may have better access to PGX data to optimize opioid recipes. Disclosure: There are no external funds that support this research. Bright has a delayed patent related to the risk assessment of opioid disorders which includes genetic information and is a collaborator on research projects funded by companies related to pharmacogenomics. Petry has been a consultant for the North Dakota Health Department and has received grants from Ignite I and Ignite II (NIH), not related to this work. Other authors realized there was no conflict of financial interests.
Drug response in relationships with pharmacogenomics and pharmacomycicrobiomic: towards better personalized drugs
Researchers have long been presented with challenges imposed by the role of genetic heterogeneity in drug response. Over the years, pharmacogenomics and pharmacomicrobiomik have investigated the influence of individual genetic backgrounds on drug responsibilities and dispositions. Recently, human intestinal microbiomas have been shown to play an important role in the way patients respond to various therapeutic drugs and have been demonstrated that by understanding the composition of human microbiomas, we can increase drug efficacy and effectively identify the target of the drug.
However, our knowledge of the influence of the host genetics of certain intestinal microbes is associated with variations of drug metabolism enzymes, the drug remains limited and therefore limits the implementation of the study of associations of micro-microbioma genomes together. In this paper, we provide a historical picture of complex interactions between hosts, human microbiomas and drugs.
While discussing the application, challenges, and opportunities of this study, we draw attention to critical needs to incorporate a diverse population and pharmacogenomic development and a combination of pharmacogenomic approaches, which can provide an important basis in personalized treatment.