scholarly journals Personalized medicine: the impact on chemistry

2010 ◽  
Vol 1 (5) ◽  
pp. 651-665 ◽  
Author(s):  
John Watkins ◽  
Andrew Marsh ◽  
Paul C Taylor ◽  
Donald RJ Singer
Keyword(s):  
Personalized Medicine ◽  
The Impact

Are more genes better in clinical-genomic studies? A mathematical model to define identification power for clinically relevant genes

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e22136-e22136
Author(s):  
M. R. Crager ◽  
S. Shak
Keyword(s):  
Personalized Medicine ◽  
Clinical Outcome ◽  
Statistical Power ◽  
Empirical Bayes ◽  
Strong Association ◽  
Individual Gene ◽  
Number Of Genes ◽  
Genomic Studies ◽  
The Impact ◽  
Clinical Genomic

e22136 Background: Modern molecular technologies that drive personalized medicine can generate expression data for thousands of candidate genes, or indeed, data for the “whole genome”. Clinical-genomic studies aim to identify genes that are truly associated with clinical outcome. We investigated the impact of large numbers of genes with little or no association with clinical outcome on the statistical power of studies to identify individual genes with strong association. Methods: We adapted Efron's (Ann Stat 2007) empirical Bayes approach to develop a method to calculate the identification power for individual genes in analyses that control the false discovery rate (FDR), the expected proportion of false positives. The identification power is the probability that a gene with a given true magnitude of association with clinical outcome will be identified when we control the FDR at a specified level. The identification power also depends on the proportion of genes studied that are not associated with outcome and the distribution of the degree of association among genes that are. Results: The identification power for clinically relevant genes decreases dramatically as the proportion of genes having no association with clinical outcome increases. For example, in a scenario in which 100 genes have some association with clinical outcome [median hazard ratio (HR) 1.125], increasing the number of genes having no association from 400 to 4000 decreases the identification power an individual gene having strong association (HR 1.42) from 80% to 36%. Similarly, when the number of genes having no association is 400 and the median HR among the 100 genes that have an association is decreased from 1.125 to 1.06, identification power for a gene with an association HR of 1.42 decreases from 80% to 62%. Conclusions: Identification power can be used to optimize strategies for gene finding and enable personalized medicine. Although technology allows the assay of ever-increasing numbers of genes, inclusion in a single study of many genes unrelated to clinical outcome is detrimental to the identification power for clinically relevant genes. Even with increased power, replication of results in independent studies will continue to be critically important. [Table: see text]

scholarly journals 4106 Personalizing Care For Colorectal Cancer: Identifying Novel Opportunities

2020 ◽  
Vol 4 (s1) ◽  
pp. 111-112
Author(s):  
Zachary Rivers ◽  
David Stenehjem ◽  
Emil Lou ◽  
Andrew Nelson ◽  
Pamala Jacobson ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cost Effectiveness ◽  
Personalized Medicine ◽  
Genetic Variants ◽  
Genetic Variant ◽  
Cost Effectiveness Analysis ◽  
Epidemiological Methods ◽  
Financial Outcomes ◽  
Effectiveness Analysis ◽  
The Impact

OBJECTIVES/GOALS: This project seeks to understand how personalized medicine can optimize care for patients with colorectal cancer. It identifies opportunities for personalized medicine to improve clinical outcomes, and uses cost-effectiveness analysis to assess the clinical and financial impact of this approach. METHODS/STUDY POPULATION: This project uses two methods to understand the impact of personalized medicine. First, this project has used SEER-Medicare data in conjunction with Clinical Pharmacogenetics Implementation Consortium guidelines to identify medications used by patients with colorectal cancer that can be impacted by genetic variants. This data will then be combined with population genetic variant rates to understand the likely impact screening for a given variant will have on medication response and adverse events. Medication use frequencies and genetic variant rates are then used to populate cost-effectiveness models that simulate the clinical and financial outcomes, identifying optimal genes to screen. RESULTS/ANTICIPATED RESULTS: The first result will be a comprehensive overview of treatment patterns for patients with colorectal cancer in the United States, as well as the treatments used for disease-induced comorbidities. The second result will be the identification of genetic variants based on population rates and medication utilization that should be screened in this patient population. The final result will be a breakdown of the clinical and financial outcomes associated with implementing screening for the identified genes. Preliminary results from a two-gene cost-effectiveness analysis demonstrates that screening for variants in those genes improves both clinical and financial outcomes. DISCUSSION/SIGNIFICANCE OF IMPACT: This project demonstrates how current treatment approaches can be optimized via personalized medicine. It uses epidemiological methods to identify opportunities to integrate genetic findings from other diseases, and uses cost-effectiveness analysis to understand the impact of transforming care. CONFLICT OF INTEREST DESCRIPTION: Stocks-Aurinia, Syndax, Adaptimmune, Rigel pharma

scholarly journals Personalized medicine and circadian rhythms: Opportunities for modern society

2020 ◽  
Vol 217 (6) ◽  
Author(s):  
Carolina Magdalen Greco ◽  
Paolo Sassone-Corsi
Keyword(s):  
Circadian Rhythms ◽  
Personalized Medicine ◽  
Modern Society ◽  
The Impact

Circadian rhythms govern physiology and metabolism, leading to controlled homeostasis. We discuss the impact of circadian rhythms on society and the challenges for the imminent future of personalized medicine.

The impact of personalized medicine of Type 2 diabetes mellitus in the global health context

2016 ◽  
Vol 13 (4) ◽  
pp. 381-393 ◽  
Author(s):  
Pierre Paul Michel Thomas ◽  
Salih Mohammed Alshehri ◽  
Henk J van Kranen ◽  
Elena Ambrosino
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Personalized Medicine ◽  
Global Health ◽  
The Impact

scholarly journals Shared decision making in mental health: prospects for personalized medicine

2009 ◽  
Vol 11 (4) ◽  
pp. 455-463 ◽  
Keyword(s):  
Mental Health ◽  
Decision Making ◽  
Personalized Medicine ◽  
Shared Decision Making ◽  
Clinical Care ◽  
Biological Data ◽  
Current Status ◽  
Routine Practice ◽  
Shared Decision ◽  
The Impact

This paper describes the shared decision-making model, reviews its current status in the mental health field, and discusses its potential impact on personalized medicine. Shared decision making denotes a structured process that encourages full participation by patient and provider. Current research shows that shared decision making can improve the participation of mental health patients and the quality of decisions in terms of knowledge and values. The impact of shared decision making on adherence, illness self-management, and health outcomes remains to be studied. Implementing shared decision making broadly will require re-engineering the flow of clinical care in routine practice settings and much greater use of information technology. Similar changes will be needed to combine genomic and other biological data with patients' values and preferences and with clinicians' expertise. The future of personalized medicine is clearly linked with our ability to create the infrastructure and cultural receptivity to these changes.

scholarly journals Obesogenic Alterations in Adrenal Function and Neurotransmitter Balance Improved with Dietary Supplementation (P21-008-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Ingrid Kohlstadt ◽  
Jeffrey Firewalker Schmitt ◽  
Roy Watkins
Keyword(s):  
Personalized Medicine ◽  
Hpa Axis ◽  
Dietary Supplementation ◽  
Clinical Analysis ◽  
Life Questionnaire ◽  
Funding Sources ◽  
Morning Cortisol ◽  
Post Test ◽  
Amino Acid Precursors ◽  
The Impact

Abstract Objectives Dysfunction of the HPA axis, as evidenced by alterations in the diurnal salivary cortisol rhythm, has been shown to contribute to the pathophysiology of obesity both directly by skewing body composition and indirectly by altering appetite and microbiome. The aim of this study was to assess the impact of a laboratory and clinical-guided dietary supplemental protocol on HPA axis dysfunction. Methods This study examines a cohort of 703 patients utilizing a clinical analysis of 1. Hypothalamic-pituitary-adrenal axis tests which were 4 point salivary cotisol, 2 point salivary DHEA, and 6 urinary neurotransmitters. 2. Self-reported Quality of Life questionnaire 3. Personalized dietary supplementation with neurotransmitter amino acid precursors and/or adrenal support monitored for 8 months. Results Pre and post test demonstrated improved sleep quality (47%, P < 0.05); increased serotonin by 172% (P < 0.05); increased norepinephrine (P < 0.05); improved adrenal tone with increased morning cortisol (P < 0.05) and decreased evening cortisol (P < 0.08). Conclusions A personalized medicine approach consisting of symptom analysis, noninvasive laboratory testing and dietary supplementation improved parameters of HPA axis dysfunction. Lab-guided personalized medicine may be able to diagnose early and treatable HPA axis dysfunction and in this way curtail a known pathway to obesity. Funding Sources No grant funding was received. The research is an IRB-exempted analysis of data collected by Sanesco International, Inc. Supporting Tables, Images and/or Graphs

scholarly journals The impact of twenty-first century personalized medicine versus twenty-first century medicine’s impact on personalization

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Camille Abettan ◽  
Jos V. M. Welie
Keyword(s):  
Personalized Medicine ◽  
Continuous Process ◽  
First Century ◽  
Objective Data ◽  
Ethical Challenges ◽  
Ethical Debate ◽  
Twenty First Century ◽  
The Impact ◽  
The Relationship ◽  
Philosophical Understanding

Abstract Background Over the past decade, the exponential growth of the literature devoted to personalized medicine has been paralleled by an ever louder chorus of epistemic and ethical criticisms. Their differences notwithstanding, both advocates and critics share an outdated philosophical understanding of the concept of personhood and hence tend to assume too simplistic an understanding of personalization in health care. Methods In this article, we question this philosophical understanding of personhood and personalization, as these concepts shape the field of personalized medicine. We establish a dialogue with phenomenology and hermeneutics (especially with E. Husserl, M. Merleau-Ponty and P. Ricoeur) in order to achieve a more sophisticated understanding of the meaning of these concepts We particularly focus on the relationship between personal subjectivity and objective data. Results We first explore the gap between the ideal of personalized healthcare and the reality of today’s personalized medicine. We show that the nearly exclusive focus of personalized medicine on the objective part of personhood leads to a flawed ethical debate that needs to be reframed. Second, we seek to contribute to this reframing by drawing on the phenomenological-hermeneutical movement in philosophy. Third, we show that these admittedly theoretical analyses open up new conceptual possibilities to tackle the very practical ethical challenges that personalized medicine faces. Conclusion Finally, we propose a reversal: if personalization is a continuous process by which the person reappropriates all manner of objective data, giving them meaning and thereby shaping his or her own way of being human, then personalized medicine, rather than being personalized itself, can facilitate personalization of those it serves through the data it provides.

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