Project Collection "Personalised Medicine–Bringing Innovation to the Healthcare System"

A project collection of Journal of Personalized Medicine (ISSN 2075-4426).

Papers displayed on this page all arise from the same project. Editorial decisions were made independently of project staff and handled by the Editor-in-Chief or qualified Editorial Board members.

Editors

Dr. Denis Horgan
Website
Collection Editor
European Alliance for Personalised Medicine, Brussels, Belgium
Interests: personalised medicine; incentives in healthcare; health literacy; decision making frameworks
Prof. Dr. Gordon McVie
Website
Collection Editor
Institute of Molecular Oncology (IFOM) Milan, Cancer Studies, Kings College London, UK
Interests: cancer; communication; oncology

Project Overview

Dear Colleagues

A major pillar in bringing new, targeted medicines to patients is, of course, innovation. This, in the realm of health, means the translation of knowledge and insight into what we can call ‘value’. In addition, that value covers the value to patients, but also has to take into account value to healthcare systems, society and, of course, the manufacturers.

Of course, a personalised medicine approach is not always required. However, when it is, we should be working towards segmenting the use of even existing medicines (many of which do their job perfectly well) into responders and non-responders, which will in turn assist in the development of novel medicines.

On top of this, the technology now exists to apply the personalised medicine, genetic-based techniques in prevention, possibly via individual risk maps which may suggest specific guidance on living a healthy life.

All of this is built upon thorough research, of course. Which then needs to be translated via various process on the way to market, not least of which are regulatory approval and pricing.

This Project Collection deals with these areas.

Yours Sincerely,

Dr. Denis Horgan
Prof. Dr. Gordon McVie
Collection Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Innovation
  • Healthcare professionals
  • Reimbursement
  • Access
  • Translational Research
  • Education of Healthcare Professionals
  • European Medicine Agency
  • European Union
  • healthcare system
  • Regulatory authorities

Published Papers (5 papers)

2019

Jump to: 2017

Open AccessArticle
Impacts of Sex Differences in Pulse Pressure among Patients with Chronic Kidney Disease
J. Pers. Med. 2019, 9(4), 52; https://doi.org/10.3390/jpm9040052 - 09 Dec 2019
Cited by 2
Abstract
Introduction: Though disease-related differences between the sexes have increasingly attracted attention, the renal impact of pulse pressure (PP) in patients with chronic kidney disease (CKD) has never been investigated comprehensively in relation to differences associated with sex. We aimed to examine sex [...] Read more.
Introduction: Though disease-related differences between the sexes have increasingly attracted attention, the renal impact of pulse pressure (PP) in patients with chronic kidney disease (CKD) has never been investigated comprehensively in relation to differences associated with sex. We aimed to examine sex differences in PP as a related factor of CKD progression from the perspective of atherosclerosis. Methods: A total of 156 patients with CKD matched according to age and estimated glomerular filtration rate (eGFR) were separated into sex-based cohorts. Multivariate Cox proportional hazards analyses were performed to identify factors associated with renal outcomes. Kaplan–Meier analyses were performed to assess disease progression, which was defined as a ≥50% estimated glomerular filtration rate (eGFR) decline or end-stage renal disease. Results: The mean age of the study participants was 58.9 ± 13.1 years, and the median follow-up period was 114.0 months. A multivariate Cox regression analysis showed that PP was significantly associated with disease progression among the entire cohort (p = 0.007). In the sex-based sub-cohort analyses, PP was significantly associated with disease progression in men (p = 0.0004) but not in women. Among the entire cohort, PP was correlated positively with age (p = 0.03) and negatively with high-density lipoprotein-cholesterol (HDL-C) level (p = 0.003). PP was significantly correlated with visceral fat area (VFA) (p = 0.04) and hemoglobin level (p = 0.04) in men and with HDL-C level (p = 0.003) in women. Conclusion: A high PP is a significant related factor of CKD progression, especially in men, in whom it is significantly associated with greater VFA and lower hemoglobin level. Full article
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Figure 1

Open AccessReview
Precision Oncology—The Quest for Evidence
J. Pers. Med. 2019, 9(3), 43; https://doi.org/10.3390/jpm9030043 - 05 Sep 2019
Cited by 1
Abstract
The molecular characterization of patient tumors provides a rational and highly promising approach for guiding oncologists in treatment decision-making. Notwithstanding, genomic medicine still remains in its infancy, with innovators and early adopters continuing to carry a significant portion of the clinical and financial [...] Read more.
The molecular characterization of patient tumors provides a rational and highly promising approach for guiding oncologists in treatment decision-making. Notwithstanding, genomic medicine still remains in its infancy, with innovators and early adopters continuing to carry a significant portion of the clinical and financial risk. Numerous innovative precision oncology trials have emerged globally to address the associated need for evidence of clinical utility. These studies seek to capitalize on the power of predictive biomarkers and/or treatment decision support analytics, to expeditiously and cost-effectively demonstrate the positive impact of these technologies on drug resistance/response, patient survival, and/or quality of life. Here, we discuss the molecular foundations of these approaches and highlight the diversity of innovative trial strategies that are capitalizing on this emergent knowledge. We conclude that, as increasing volumes of clinico-molecular outcomes data become available, in future, we will begin to transition away from expert systems for treatment decision support (TDS), towards the power of AI-assisted TDS—an evolution that may truly revolutionize the nature and success of cancer patient care. Full article
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Open AccessReview
Blockchains for Secure Digitized Medicine
J. Pers. Med. 2019, 9(3), 35; https://doi.org/10.3390/jpm9030035 - 13 Jul 2019
Cited by 10
Abstract
Blockchain as an emerging technology has been gaining in popularity, with more possible applications to utilize the technology in the near future. With the offer of a decentralized, distributed environment without the need for a third trusted party (TTP), blockchains are being used [...] Read more.
Blockchain as an emerging technology has been gaining in popularity, with more possible applications to utilize the technology in the near future. With the offer of a decentralized, distributed environment without the need for a third trusted party (TTP), blockchains are being used to solve issues in systems that are susceptible to cyberattacks. One possible field that could benefit from blockchains that researchers have been focusing on is healthcare. Current healthcare information systems face several challenges, such as fragmented patient data, centralized systems which are viewed as single points of attacks, and the lack of patient-oriented services. In this paper, we investigate and analyze recent literature related to the use of blockchains to tackle issues found in modern healthcare information systems. This is done to understand issues that researchers commonly focus on, to discover remaining areas of concern in any proposed solution, and to understand the possible directions of the integration of blockchains in healthcare and personalized medicine. Background information regarding blockchains and existing healthcare information systems is reviewed, followed by the methodology used in the preparation of this review, where the research questions to consider are stated. Afterwards, an analysis of the results is provided, concluding with a discussion of the remaining issues that need to be focused on, and how blockchains could benefit the healthcare sector and empower personalized medicine. Full article
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2017

Jump to: 2019

Open AccessReview
Value-Based Pricing and Reimbursement in Personalised Healthcare: Introduction to the Basic Health Economics
J. Pers. Med. 2017, 7(3), 10; https://doi.org/10.3390/jpm7030010 - 04 Sep 2017
Cited by 20
Abstract
‘Value-based’ outcomes, pricing, and reimbursement are widely discussed as health sector reforms these days. In this paper, we discuss their meaning and relationship in the context of personalized healthcare, defined as receipt of care conditional on the results of a biomarker-based diagnostic test. [...] Read more.
‘Value-based’ outcomes, pricing, and reimbursement are widely discussed as health sector reforms these days. In this paper, we discuss their meaning and relationship in the context of personalized healthcare, defined as receipt of care conditional on the results of a biomarker-based diagnostic test. We address the question: “What kinds of pricing and reimbursement models should be applied in personalized healthcare?” The simple answer is that competing innovators and technology adopters should have incentives that promote long-term dynamic efficiency. We argue that—to meet this social objective of optimal innovation in personalized healthcare—payers, as agents of their plan participants, should aim to send clear signals to their suppliers about what they value. We begin by revisiting the concept of value from an economic perspective, and argue that a broader concept of value is needed in the context of personalized healthcare. We discuss the market for personalized healthcare and the interplay between price and reimbursement. We close by emphasizing the potential barrier posed by inflexible or cost-based reimbursement systems, especially for biomarker-based predictive tests, and how these personalized technologies have global public goods characteristics that require global value-based differential pricing to achieve dynamic efficiency in terms of the optimal rate of innovation and adoption. Full article
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Open AccessCommentary
Personalized Computational Models as Biomarkers
J. Pers. Med. 2017, 7(3), 9; https://doi.org/10.3390/jpm7030009 - 01 Sep 2017
Cited by 7
Abstract
Biomarkers are cornerstones of clinical medicine, and personalized medicine, in particular, is highly dependent on reliable and highly accurate biomarkers for individualized diagnosis and treatment choice. Modern omics technologies, such as genome sequencing, allow molecular profiling of individual patients with unprecedented resolution, but [...] Read more.
Biomarkers are cornerstones of clinical medicine, and personalized medicine, in particular, is highly dependent on reliable and highly accurate biomarkers for individualized diagnosis and treatment choice. Modern omics technologies, such as genome sequencing, allow molecular profiling of individual patients with unprecedented resolution, but biomarkers based on these technologies often lack the dynamic element to follow the progression of a disease or response to therapy. Here, we discuss computational models as a new conceptual approach to biomarker discovery and design. Being able to integrate a large amount of information, including dynamic information, computational models can simulate disease evolution and response to therapy with high sensitivity and specificity. By populating these models with personal data, they can be highly individualized and will provide a powerful new tool in the armory of personalized medicine. Full article
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