Personalized medicine : the impact on chemistry

An effective strategy for personalized medicine requires a major conceptual change in the development and application of therapeutics. In this article, we argue that further advances in this field should be made with reference to another conceptual shift, that of network pharmacology. We examine the intersection of personalized medicine and network pharmacology to identify strategies for the development of personalized therapies that are fully informed by network pharmacology concepts. This provides a framework for discussion of the impact personalized medicine will have on chemistry in terms of drug discovery, formulation and delivery, the adaptations and changes in ideology required and the contribution chemistry is already making. New ways of conceptualizing chemistry’s relationship with medicine will lead to new approaches to drug discovery and hold promise of delivering safer and more effective therapies

Clinical applications of personalized medicine: a new paradigm and challenge

The personalized medicine is an emergent and rapidly developing method of clinical practice that uses new technologies to provide decisions in regard to the prediction, prevention, diagnosis and treatment of disease. The continue evolution of technology and the developments in molecular diagnostics and genomic analysis increased the possibility of an even more understanding and interpretation of the human genome and exome, allowing a "personalized" approach to clinical care, so that the concepts of "Systems Medicine" and "System Biology" are increasingly actual. The purpose of this study is to evaluate the personalized medicine about its indications and benefits, actual clinical applications and future perspectives as well as its issues and health care implications. It was made a careful review of the scientific literature on this field that highlighted the applicability and usefulness of this new medical approach as well as the fact that personalized medicine strategy is even more increasing in numerous fields of applications

Clinical proteomics for precision medicine: the bladder cancer case

Precision medicine can improve patient management by guiding therapeutic decision based on molecular characteristics. The concept has been extensively addressed through the application of –omics based approaches. Proteomics attract high interest, as proteins reflect a “real-time” dynamic molecular phenotype. Focusing on proteomics applications for personalized medicine, a literature search was conducted to cover: a) disease prevention, b) monitoring/ prediction of treatment response, c) stratification to guide intervention and d) identification of drug targets. The review indicates the potential of proteomics for personalized medicine by also highlighting multiple challenges to be addressed prior to actual implementation. In oncology, particularly bladder cancer, application of precision medicine appears especially promising. The high heterogeneity and recurrence rates together with the limited treatment options, suggests that earlier and more efficient intervention, continuous monitoring and the development of alternative therapies could be accomplished by applying proteomics-guided personalized approaches. This notion is backed by studies presenting biomarkers that are of value in patient stratification and prognosis, and by recent studies demonstrating the identification of promising therapeutic targets. Herein, we aim to present an approach whereby combining the knowledge on biomarkers and therapeutic targets in bladder cancer could serve as basis towards proteomics- guided personalized patient management

Stroke genetics: prospects for personalized medicine.

Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice

Conference scene : Golden Helix Pharmacogenomics Days : educational activities on pharmacogenomics and personalized medicine

The Golden Helix Pharmacogenomics Days are high-profile international educational scientific meetings discussing pharmacogenomics and personalized medicine. Here, we provide an overview of the scientific lectures and the topics discussed during the 4th Golden Helix Pharmacogenomics Day, held in Cagliari, Italy, on 7 October 2011, and the 5th Golden Helix Pharmacogenomics Day, that was held in Msida, Malta, on 3 December 2011. The scientific programs of both events included scientific and company lectures on pharmacogenomics, bioinformatics and personalized medicine by local and international speakers from Europe and the USA.peer-reviewe

Active Clinical Trials for Personalized Medicine

Individualized treatment rules (ITRs) tailor treatments according to individual patient characteristics. They can significantly improve patient care and are thus becoming increasingly popular. The data collected during randomized clinical trials are often used to estimate the optimal ITRs. However, these trials are generally expensive to run, and, moreover, they are not designed to efficiently estimate ITRs. In this paper, we propose a cost-effective estimation method from an active learning perspective. In particular, our method recruits only the "most informative" patients (in terms of learning the optimal ITRs) from an ongoing clinical trial. Simulation studies and real-data examples show that our active clinical trial method significantly improves on competing methods. We derive risk bounds and show that they support these observed empirical advantages.Comment: 48 Page, 9 Figures. To Appear in JASA--T&

Personalized medicine

pre-printWith the completion of the Human Genome Project in 2003, the world's attention has focused on converting this vast storehouse of information into innovative health care solutions. The ultimate promise, assuming we know everyone's genotype, is to ensure that every person has optimum health throughout his/her life. This promise has many parts, including optimum nutrition, clean air and water supplies, up-to-date immunizations and regular health screenings. The part of the promise to be fulfilled by knowledge and information stemming from genomics, proteomics and other "omics" is yet unfolding, but the first cautious steps are being taken and are called "Personalized Medicine". Personalized Medicine implies that optimum health goes beyond the basics of clean air and water and takes advantage of the "omics" knowledge to allow the person and his/her clinicians to make therapeutic and lifestyle choices which take the "omics" into account

Finasteride as a model for personalized medicine

The side effects of Finasteride are currently a subject of controversy. Some studies report minor or acceptable adverse effects, which decrease after a variable period of time so that they do not necessitate terminating Finasteride administration. However, several clinical and neuro-endocrine studies show that some adverse effects persist indefinitely in the form of post-Finasteride syndrome, even after the drug cessation. This paper presents a possible explanation for these inconsistent findings. First, the study design of either informing or not informing patients prior therapy about possible adverse effects can influence the incidence and magnitude of reported adverse effects. Second, structural and information dichotomies of the brain generate four distinct neuronal networks, which are activated through specific cerebral neuromodulators and that are able to support four distinct minds within an individual body. As a conclusion, the “mind psychophysiology” and the corresponding mental impairments differ across individuals, such that not only the prediction of adverse effects should be addressed from a more individualized medical perspective, but also the therapeutic strategies could be tailored to the four distinct mental profiles described. It is a personalized approach that would be applicable to several interrelated domains of neuroscience, like psychology, psychiatry and sexuality. Finally, this perspective may represent a starting point for a more individualized understanding of mental events, perhaps even a step forward in the understanding of the mind-body problem

How to teach personcentered medicine during the coronavirus disease 2019 pandemic?

Personalized medicine refers to sophisticated diagnostic and therapeutic interventions tailored to the patient’s individual needs. The development of personalized medicine in the last two decades created a global movement of person-centered medicine and health care. Prominent medical organizations and institutions that advocate a personalized approach to medicine established an international network called the International College of Person-Centered Medicine (1,2)