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Journal articles on the topic 'Pharmaco-genomics'

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1

Paige, Adam JW, and Robert Brown. "Pharmaco(epi)genomics in ovarian cancer." Pharmacogenomics 9, no. 12 (2008): 1825–34. http://dx.doi.org/10.2217/14622416.9.12.1825.

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2

Cavallari, Larisa M., Vicki L. Ellingrod, Jill M. Kolesar, and Peter J. Wedlund. "Lcxi-Comp's Pharmaco-Genomics Handbook, 2nd Edition." Annals of Pharmacotherapy 40, no. 7-8 (2006): 1480. http://dx.doi.org/10.1345/aph.1h079.

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3

Isobe, Toshiaki, Masato Taoka, Akiko Wakamiya, Hiroshi Nakayama, and Tohru Natsume. "The Role of Proteomics in Pharmaco-Genomics." Japanese Journal of Pharmacology 82 (2000): 17. http://dx.doi.org/10.1016/s0021-5198(19)47545-8.

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4

Bhaskar, SBala, and Sukhminder JitSingh Bajwa. "Pharmaco‑genomics and anaesthesia: Mysteries, correlations and facts." Indian Journal of Anaesthesia 57, no. 4 (2013): 336. http://dx.doi.org/10.4103/0019-5049.118517.

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5

Buysschaert, Ian, Thomas Schmidt, Carmen Roncal, Peter Carmeliet, and Diether Lambrechts. "Genetics, epigenetics and pharmaco-(epi)genomics in angiogenesis." Journal of Cellular and Molecular Medicine 12, no. 6b (2008): 2533–51. http://dx.doi.org/10.1111/j.1582-4934.2008.00515.x.

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6

Bracken, M. "Innovative Designs and Data Sources: How can they Contribute to Pharmaco-Epidemiology and Pharmaco-Genomics?" American Journal of Epidemiology 163, suppl_11 (2006): S246. http://dx.doi.org/10.1093/aje/163.suppl_11.s246-d.

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7

Dhieb, Dhoha, and Kholoud Bastaki. "Pharmaco-Multiomics: A New Frontier in Precision Psychiatry." International Journal of Molecular Sciences 26, no. 3 (2025): 1082. https://doi.org/10.3390/ijms26031082.

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The landscape of psychiatric care is poised for transformation through the integration of pharmaco-multiomics, encompassing genomics, proteomics, metabolomics, transcriptomics, epigenomics, and microbiomics. This review discusses how these approaches can revolutionize personalized treatment strategies in psychiatry by providing a nuanced understanding of the molecular bases of psychiatric disorders and individual pharmacotherapy responses. With nearly one billion affected individuals globally, the shortcomings of traditional treatments, characterized by inconsistent efficacy and frequent adver
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8

Rosenberg, Fieke M., Zoha Kamali, Angelique N. Voorberg, et al. "Transcriptomics- and Genomics-Guided Drug Repurposing for the Treatment of Vesicular Hand Eczema." Pharmaceutics 16, no. 4 (2024): 476. http://dx.doi.org/10.3390/pharmaceutics16040476.

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Vesicular hand eczema (VHE), a clinical subtype of hand eczema (HE), showed limited responsiveness to alitretinoin, the only approved systemic treatment for severe chronic HE. This emphasizes the need for alternative treatment approaches. Therefore, our study aimed to identify drug repurposing opportunities for VHE using transcriptomics and genomics data. We constructed a gene network by combining 52 differentially expressed genes (DEGs) from a VHE transcriptomics study with 3 quantitative trait locus (QTL) genes associated with HE. Through network analysis, clustering, and functional enrichme
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9

Ambade, Rakhee. "Precision medicine, pharmaco-genomics and neutro-genomics and genomic medicine: A newer approach for patient management from clinic to basic." Panacea Journal of Medical Sciences 8, no. 3 (2020): 93–95. http://dx.doi.org/10.18231/2348-7682.2018.0021.

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10

Antonatos, Charalabos, Paschalia Asmenoudi, Mariza Panoutsopoulou, and Yiannis Vasilopoulos. "Pharmaco-Omics in Psoriasis: Paving the Way towards Personalized Medicine." International Journal of Molecular Sciences 24, no. 8 (2023): 7090. http://dx.doi.org/10.3390/ijms24087090.

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The emergence of high-throughput approaches has had a profound impact on personalized medicine, evolving the identification of inheritable variation to trajectory analyses of transient states and paving the way for the unveiling of response biomarkers. The utilization of the multi-layered pharmaco-omics data, including genomics, transcriptomics, proteomics, and relevant biological information, has facilitated the identification of key molecular biomarkers that can predict the response to therapy, thereby optimizing treatment regiments and providing the framework for a tailored treatment plan.
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11

Findlay, Izac, Dilana Staudt, Padraic Kearney, et al. "CSIG-10. PHARMACO-PHOSPHO-PROTEO-GENOMICS OF PEDIATRIC HIGH-GRADE GLIOMAS – A PILOT STUDY." Neuro-Oncology 24, Supplement_7 (2022): vii40—vii41. http://dx.doi.org/10.1093/neuonc/noac209.159.

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Abstract Pediatric high-grade gliomas (pHGG) are the leading cause of cancer-related death in children and young adults. Current treatment strategies are centered on maximal safe resection, followed by radiotherapy, and interrogation of the tumor genome to identify targetable mutations. Unfortunately, we are yet to see an improvement in patient outcomes with a median overall survival remaining 15-months. To improve patient outcomes, we have begun to characterize the genome, proteome, and phosphoproteome of 168 pHGGs to better understand the functional consequences of their somatic alterations
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12

Liguang, Xu, Gao Yifan, Kuang Hua, M. Liz‐Marzán Luis, and Xu Chuanlai. "MicroRNA-Directed Intracellular Self-Assembly of Chiral Nanorod Dimers." Angewandte Chemie International Edition 57, no. 33 (2018): 10548–44. https://doi.org/10.1002/anie.201805640.

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MicroRNAs (miRNAs), a kind of single‐stranded small RNA molecules, play a crucial role in physiological and pathological processes in human beings. We describe here the detection of miRNA, by side‐by‐side self‐assembly of plasmonic nanorod dimers in living cells, which gives rise to a distinct intense chiroplasmonic response and surface‐enhanced Raman scattering (SERS). The dynamic assembly of chiral nanorods was confirmed by fluorescence resonance energy transfer (FRET), also in living cells. Our study provides insights into in situ self‐assembly of plasmonic probes for the real‐time measurem
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13

Seki Kioshima, Erika, Patrícia de Souza Bonfim de Mendonça, Marcus de Melo Teixeira, et al. "One Century of Study: What We Learned about Paracoccidioides and How This Pathogen Contributed to Advances in Antifungal Therapy." Journal of Fungi 7, no. 2 (2021): 106. http://dx.doi.org/10.3390/jof7020106.

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Paracoccidioidomycosis (PCM) is a notable fungal infection restricted to Latin America. Since the first description of the disease by Lutz up to the present day, Brazilian researchers have contributed to the understanding of the life cycle of this pathogen and provided the possibility of new targets for antifungal therapy based on the structural and functional genomics of Paracoccidioides. In this context, in silico approaches have selected molecules that act on specific targets, such as the thioredoxin system, with promising antifungal activity against Paracoccidioides. Some of these are alre
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14

Touw, D. J. "The developing role of pharmacogenetics in psychiatry." Acta Neuropsychiatrica 11, no. 2 (1999): 77–79. http://dx.doi.org/10.1017/s092427080003622x.

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A great interindividual variability exists in biological response to drugs. This variability is partly attributable to pharmacodynamic factors (drug - receptor interactions) and partly to pharmacokinetic factors. Drugs can be eliminated from the body by renal clearance, metabolism or both. Although every tissue has some ability to metabolise xenobiotics like drugs, the liver is the principal organ of biotransformation. Major metabolising enzymes are the cytochrome-P450 mono-oxygenases, epoxide hydrolase, glucuronosyl-transferase, acetyl-transferase, sulfo-transferase and xanthine oxidase. Some
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15

Edara, Amulya, and Divya Lakshmi Ravi. "Tailored Treatments: The Future of Healthcare with Precision Medicine." International Journal of Innovative Science and Research Technology (IJISRT) 10, no. 2 (2025): 435–41. https://doi.org/10.5281/zenodo.14915630.

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Precision medicine represents a transformative approach to healthcare, focusing on customizing treatments for specific subpopulations who share a common susceptibility to certain diseases or exhibit similar responses to particular drugs. While the concept traces back to the era of Sir William Osler, it gained renewed momentum through the Precision Medicine Initiative, launched by Barack Obama in 2015. This approach leverages Big Data, artificial intelligence, multiple omics fields, pharmaco-omics, and various environmental and social factors, integrating these elements with preventive and popu
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16

Findlay, Izac J., Geoffry N. De Iuliis, Ryan J. Duchatel, et al. "Pharmaco-proteogenomic profiling of pediatric diffuse midline glioma to inform future treatment strategies." Oncogene 41, no. 4 (2021): 461–75. http://dx.doi.org/10.1038/s41388-021-02102-y.

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AbstractDiffuse midline glioma (DMG) is a deadly pediatric and adolescent central nervous system (CNS) tumor localized along the midline structures of the brain atop the spinal cord. With a median overall survival (OS) of just 9–11-months, DMG is characterized by global hypomethylation of histone H3 at lysine 27 (H3K27me3), driven by recurring somatic mutations in H3 genes including, HIST1H3B/C (H3.1K27M) or H3F3A (H3.3K27M), or through overexpression of EZHIP in patients harboring wildtype H3. The recent World Health Organization’s 5th Classification of CNS Tumors now designates DMG as, ‘H3 K
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17

Dighe, Pratiksha, Rinette Woo, Nathan Salomonis, et al. "EXTH-62. COMBINATORIAL THERAPY TARGETING TRANSCIPTION AND IMMUNO-METABOLISM IN RECURRENT GLIOBLASTOMA." Neuro-Oncology 23, Supplement_6 (2021): vi177. http://dx.doi.org/10.1093/neuonc/noab196.701.

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Abstract Recurrent glioblastomas (GBM) are notoriously difficult to treat, and in spite of aggressive chemo- and radiation therapy they inevitably recur in almost all GBM patients within 14 months following initial diagnosis. To interrogate pathways driving therapeutic resistance, we compared matched primary and recurrent IDH wild type glioblastoma samples from a cohort of patients, using RNA-Seq. Our analyses showed that pathways involved with tumor immune and metabolic reprogramming were up-regulated in recurrent GBMs compared to untreated, primary samples. Based on these findings, we tested
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18

Silberberg, Gilad, Stefano Cairo, Mara Gilardi, Brandon Walling, Marianna Zipeto, and Michael Ritchie. "Abstract 3717: A digital patient & simulated clinical trial of cytarabine treatment." Cancer Research 85, no. 8_Supplement_1 (2025): 3717. https://doi.org/10.1158/1538-7445.am2025-3717.

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Abstract Historically, computational models have primarily relied on single-omic datasets, particularly transcriptomic data, to predict cancer sensitivity to drugs. These models often identified single gene alterations as biomarkers of drug response. While informative, the predictive potential of these biomarker panels remains limited. Moreover, these same panels have failed to predict potential toxicities associated with anti-cancer drugs. This underscores the urgent need to construct more robust biomarker panels capable of not only predicting patient response but also anticipating potential
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19

"Pharmaco-genomics in breast cancer." European Journal of Cancer 37 (April 2001): S134. http://dx.doi.org/10.1016/s0959-8049(01)80981-3.

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20

Swamini, Dumbare, Kumavat Nandini, and S. D. Mankar. "The Impact of Human Genome on Interindividual variability in Drug Response." Research Journal of Pharmacology and Pharmacodynamics, February 29, 2024, 19–24. http://dx.doi.org/10.52711/2321-5836.2024.00004.

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Pharmacogenomics is an important aspects of clinical genomics i.e an increasingly large number of patients it have extremely broad cast application a pharmacogenomics has evolved from early Pharmacogenetic studies of candidate gene often genes. Pharmacogenomics has the potential to mitigate adverse drug reaction and optimise pharmaco therapy in individual it has the potential to revolutionize the practice of medicine and promises to in an area of personised medicine in which drug and drug combination optimised for each Individual unique genetic makeup. It is well recognised that most medicatio
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21

Nguyen, Thanh Thanh L., Duan Liu, Ming-Fen Ho, Arjun P. Athreya, and Richard Weinshilboum. "Selective Serotonin Reuptake Inhibitor Pharmaco-Omics: Mechanisms and Prediction." Frontiers in Pharmacology 11 (January 11, 2021). http://dx.doi.org/10.3389/fphar.2020.614048.

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Selective serotonin reuptake inhibitors (SSRIs) are a standard of care for the pharmacotherapy of patients suffering from Major Depressive Disorder (MDD). However, only one-half to two-thirds of MDD patients respond to SSRI therapy. Recently, a “multiple omics” research strategy was applied to identify genetic differences between patients who did and did not respond to SSRI therapy. As a first step, plasma metabolites were assayed using samples from the 803 patients in the PGRN-AMPS SSRI MDD trial. The metabolomics data were then used to “inform” genomics by performing a genome-wide associatio
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22

Nguyen, Thanh Thanh L., Duan Liu, Ming-Fen Ho, Arjun P. Athreya, and Richard Weinshilboum. "Selective Serotonin Reuptake Inhibitor Pharmaco-Omics: Mechanisms and Prediction." Frontiers in Pharmacology 11 (January 11, 2021). http://dx.doi.org/10.3389/fphar.2020.614048.

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Selective serotonin reuptake inhibitors (SSRIs) are a standard of care for the pharmacotherapy of patients suffering from Major Depressive Disorder (MDD). However, only one-half to two-thirds of MDD patients respond to SSRI therapy. Recently, a “multiple omics” research strategy was applied to identify genetic differences between patients who did and did not respond to SSRI therapy. As a first step, plasma metabolites were assayed using samples from the 803 patients in the PGRN-AMPS SSRI MDD trial. The metabolomics data were then used to “inform” genomics by performing a genome-wide associatio
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23

Yang, Jingbo, Denan Zhang, Lei Liu, et al. "Computational drug repositioning based on the relationships between substructure–indication." Briefings in Bioinformatics, December 14, 2020. http://dx.doi.org/10.1093/bib/bbaa348.

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Abstract At present, computational methods for drug repositioning are mainly based on the whole structures of drugs, which limits the discovery of new functions due to the similarities between local structures of drugs. In this article, we, for the first time, integrated the features of chemical-genomics (substructure–domain) and pharmaco-genomics (domain–indication) based on the assumption that drug–target interactions are mediated by the substructures of drugs and the domains of proteins to identify the relationships between substructure–indication and establish a drug–substructure–indicatio
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24

Liu, Yijun, Fuhu Song, Zhi Li, et al. "A comprehensive tool for tumor precision medicine with pharmaco-omics data analysis." Frontiers in Pharmacology 14 (January 12, 2023). http://dx.doi.org/10.3389/fphar.2023.1085765.

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Background: Cancer precision medicine is an effective strategy to fight cancers by bridging genomics and drug discovery to provide specific treatment for patients with different genetic characteristics. Although some public databases and modelling frameworks have been developed through studies on drug response, most of them only considered the ramifications of the drug on the cell line and the effects on the patient still require a huge amount of work to integrate data from various databases and calculations, especially concerning precision treatment. Furthermore, not only efficacy but also th
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25

Ebomoyi, E. William. "Genomic Epidemiology of Congestive Heart Disease, Pharmacogenomics and the Relevant Health Education Implications in the Age of Genomic Medicine." July 31, 2011. https://doi.org/10.5281/zenodo.7769.

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This project investigated genomic epidemiology of congestive heart disease, the clinical and non-invasive techniques for diagnosis and the modifiable and non-modifiable risk factors associated with the disease were explored. Trends in the morbidity and mortality of CHD revealed an increase in the disease frequency with minor drop in its’ trajectory into the twenty-first century. While the modifiable risk factors were discussed with suitable interventions, the non-modifiable risk factors demand prompt medical diagnosis and treatment if any. The genes incriminated were listed. The relevanc
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