Open AccessCommentary
Personomics: The Missing Link in the Evolution from Precision Medicine to Personalized Medicine
J. Pers. Med. 2017, 7(4), 11; doi:10.3390/jpm7040011 -
Abstract
Clinical practice guidelines have been developed for many common conditions based on data from randomized controlled trials. When medicine is informed solely by clinical practice guidelines, however, the patient is not treated as an individual, but rather a member of a group. Precision
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Clinical practice guidelines have been developed for many common conditions based on data from randomized controlled trials. When medicine is informed solely by clinical practice guidelines, however, the patient is not treated as an individual, but rather a member of a group. Precision medicine, as defined herein, characterizes unique biological characteristics of the individual or of specimens obtained from an individual to tailor diagnostics and therapeutics to a specific patient. These unique biological characteristics are defined by the tools of precision medicine: genomics, proteomics, metabolomics, epigenomics, pharmacogenomics, and other “-omics.” Personalized medicine, as defined herein, uses additional information about the individual derived from knowing the patient as a person. These unique personal characteristics are defined by tools known as personomics which takes into account an individual’s personality, preferences, values, goals, health beliefs, social support network, financial resources, and unique life circumstances that affect how and when a given health condition will manifest in that person and how that condition will respond to treatment. In this paradigm, precision medicine may be considered a necessary step in the evolution of medical care to personalized medicine, with personomics as the missing link. Full article
Open AccessReview
Immortalized Muscle Cell Model to Test the Exon Skipping Efficacy for Duchenne Muscular Dystrophy
J. Pers. Med. 2017, 7(4), 13; doi:10.3390/jpm7040013 -
Abstract
Duchenne muscular dystrophy (DMD) is a lethal genetic disorder that most commonly results from mutations disrupting the reading frame of the dystrophin (DMD) gene. Among the therapeutic approaches employed, exon skipping using antisense oligonucleotides (AOs) is one of the most promising
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Duchenne muscular dystrophy (DMD) is a lethal genetic disorder that most commonly results from mutations disrupting the reading frame of the dystrophin (DMD) gene. Among the therapeutic approaches employed, exon skipping using antisense oligonucleotides (AOs) is one of the most promising strategies. This strategy aims to restore the reading frame, thus producing a truncated, yet functioning dystrophin protein. In 2016, the Food and Drug Administration (FDA) conditionally approved the first AO-based drug, eteplirsen (Exondys 51), developed for DMD exon 51 skipping. An accurate and reproducible method to quantify exon skipping efficacy is essential for evaluating the therapeutic potential of different AOs sequences. However, previous in vitro screening studies have been hampered by the limited proliferative capacity and insufficient amounts of dystrophin expressed by primary muscle cell lines that have been the main system used to evaluate AOs sequences. In this paper, we illustrate the challenges associated with primary muscle cell lines and describe a novel approach that utilizes immortalized cell lines to quantitatively evaluate the exon skipping efficacy in in vitro studies. Full article
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Open AccessReview
Personalized Nanomedicine: A Revolution at the Nanoscale
J. Pers. Med. 2017, 7(4), 12; doi:10.3390/jpm7040012 -
Abstract
Nanomedicine is an interdisciplinary research field that results from the application of nanotechnology to medicine and has the potential to significantly improve some current treatments. Specifically, in the field of personalized medicine, it is expected to have a great impact in the near
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Nanomedicine is an interdisciplinary research field that results from the application of nanotechnology to medicine and has the potential to significantly improve some current treatments. Specifically, in the field of personalized medicine, it is expected to have a great impact in the near future due to its multiple advantages, namely its versatility to adapt a drug to a cohort of patients. In the present review, the properties and requirements of pharmaceutical dosage forms at the nanoscale, so-called nanomedicines, are been highlighted. An overview of the main current nanomedicines in pre-clinical and clinical development is presented, detailing the challenges to the personalization of these therapies. Next, the process of development of novel nanomedicines is described, from their design in research labs to their arrival on the market, including considerations for the design of nanomedicines adapted to the requirements of the market to achieve safe, effective, and quality products. Finally, attention is given to the point of view of the pharmaceutical industry, including regulation issues applied to the specific case of personalized medicine. The authors expect this review to be a useful overview of the current state of the art of nanomedicine research and industrial production, and the future opportunities of personalized medicine in the upcoming years. The authors encourage the development and marketing of novel personalized nanomedicines. Full article
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Open AccessReview
Value-Based Pricing and Reimbursement in Personalised Healthcare: Introduction to the Basic Health Economics
J. Pers. Med. 2017, 7(3), 10; doi:10.3390/jpm7030010 -
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.
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‘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; doi:10.3390/jpm7030009 -
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
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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
Open AccessArticle
Dairy Product Consumption Interacts with Glucokinase (GCK) Gene Polymorphisms Associated with Insulin Resistance
J. Pers. Med. 2017, 7(3), 8; doi:10.3390/jpm7030008 -
Abstract
Dairy product intake and a person’s genetic background have been reported to be associated with the risk of type 2 diabetes (T2D). The objective of this study was to examine the interaction between dairy products and genes related to T2D on glucose-insulin homeostasis
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Dairy product intake and a person’s genetic background have been reported to be associated with the risk of type 2 diabetes (T2D). The objective of this study was to examine the interaction between dairy products and genes related to T2D on glucose-insulin homeostasis parameters. A validated food frequency questionnaire, fasting blood samples, and glucokinase (GCK) genotypes were analyzed in 210 healthy participants. An interaction between rs1799884 in GCK and dairy intake on the homeostasis model assessment of insulin resistance was identified. Secondly, human hepatocellular carcinoma cells (HepG2) were grown in a high-glucose medium and incubated with either 1-dairy proteins: whey, caseins, and a mixture of whey and casein; and 2-four amino acids (AA) or mixtures of AA. The expression of GCK-related genes insulin receptor substrate-1 (IRS-1) and fatty acid synthase (FASN) was increased with whey protein isolate or hydrolysate. Individually, leucine increased IRS-1 expression, whereas isoleucine and valine decreased FASN expression. A branched-chain AA mixture decreased IRS-1 and FASN expression. In conclusion, carriers of the A allele for rs1799884 in the GCK gene may benefit from a higher intake of dairy products to maintain optimal insulin sensitivity. Moreover, the results show that whey proteins affect the expression of genes related to glucose metabolism. Full article
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Open AccessReview
Empowering Mayo Clinic Individualized Medicine with Genomic Data Warehousing
J. Pers. Med. 2017, 7(3), 7; doi:10.3390/jpm7030007 -
Abstract
Individualized medicine enables better diagnoses and treatment decisions for patients and promotes research in understanding the molecular underpinnings of disease. Linking individual patient’s genomic and molecular information with their clinical phenotypes is crucial to these efforts. To address this need, the Center for
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Individualized medicine enables better diagnoses and treatment decisions for patients and promotes research in understanding the molecular underpinnings of disease. Linking individual patient’s genomic and molecular information with their clinical phenotypes is crucial to these efforts. To address this need, the Center for Individualized Medicine at Mayo Clinic has implemented a genomic data warehouse and a workflow management system to bring data from institutional electronic health records and genomic sequencing data from both clinical and research bioinformatics sources into the warehouse. The system is the foundation for Mayo Clinic to build a suite of tools and interfaces to support various clinical and research use cases. The genomic data warehouse is positioned to play a key role in enhancing the research capabilities and advancing individualized patient care at Mayo Clinic. Full article
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Open AccessArticle
The Clinical and Economic Impact of Inaccurate EGFR Mutation Tests in the Treatment of Metastatic Non-Small Cell Lung Cancer
J. Pers. Med. 2017, 7(3), 5; doi:10.3390/jpm7030005 -
Abstract
Advances in personalized medicine are supported by companion diagnostic molecular tests. Testing accuracy is critical for selecting patients for optimal therapy and reducing treatment-related toxicity. We assessed the clinical and economic impact of inaccurate test results between laboratory developed tests (LDTs) and a
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Advances in personalized medicine are supported by companion diagnostic molecular tests. Testing accuracy is critical for selecting patients for optimal therapy and reducing treatment-related toxicity. We assessed the clinical and economic impact of inaccurate test results between laboratory developed tests (LDTs) and a US Food and Drug Administration (FDA)-approved test for detection of epidermal growth factor receptor (EGFR) mutations. Using a hypothetical US cohort of newly diagnosed metastatic non-small cell lung cancer (NSCLC) patients and EURTAC (erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer) clinical trial data, we developed a decision analytic model to estimate the probability of misclassification with LDTs compared to a FDA-approved test. We estimated the clinical and economic impact of inaccurate test results by quantifying progression-free and quality-adjusted progression-free life years (PFLYs, QAPFLYs) lost, and costs due to incorrect treatment. The base-case analysis estimated 2.3% (n = 1422) of 60,502 newly diagnosed metastatic NSCLC patients would be misclassified with LDTs compared to 1% (n = 577) with a FDA-approved test. An average of 477 and 194 PFLYs were lost among the misclassified patients tested with LDTs compared to the FDA-approved test, respectively. Aggregate treatment costs for patients tested with LDTs were approximately $7.3 million more than with the FDA-approved test, due to higher drug and adverse event costs among patients incorrectly treated with targeted therapy or chemotherapy, respectively. Invalid tests contributed to greater probability of patient misclassification and incorrect therapy. In conclusion, risks associated with inaccurate EGFR mutation tests pose marked clinical and economic consequences to society. Utilization of molecular diagnostic tests with demonstrated accuracy could help to maximize the potential of personalized medicine. Full article
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Open AccessArticle
Development and Initial Assessment of a Patient Education Video about Pharmacogenetics
J. Pers. Med. 2017, 7(2), 4; doi:10.3390/jpm7020004 -
Abstract
As few patient-friendly resources about pharmacogenetics are currently available, we aimed to create and assess a patient educational video on pharmacogenetic testing. A primary literature and resources review was conducted to inform the content and the format of the video. The educational video
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As few patient-friendly resources about pharmacogenetics are currently available, we aimed to create and assess a patient educational video on pharmacogenetic testing. A primary literature and resources review was conducted to inform the content and the format of the video. The educational video was then created using a commercially available animation program and pilot tested in focus groups of the general public and by an online survey of pharmacists. Emerging themes from the focus groups and survey indicate a desire for appropriate risk contextualization and specific examples when pharmacogenetic testing may be beneficial. Focus group participants also expressed a preference for a video with live action, and more text to reinforce concepts. Pharmacists generally felt that the video was understandable for patients and relevant for decision-making regarding testing. Using this initial feedback and the identification of important concepts to include in pharmacogenetics educational tools, we plan to revise the video, perform additional evaluations, and publish the video for public use in the future. Full article
Open AccessArticle
Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort
J. Pers. Med. 2017, 7(2), 3; doi:10.3390/jpm7020003 -
Abstract
The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart
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The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. In conclusion, most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/). Full article
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Open AccessReview
Methods for the In Vitro Characterization of Nanomedicines—Biological Component Interaction
J. Pers. Med. 2017, 7(1), 2; doi:10.3390/jpm7010002 -
Abstract
The design of colloidal nanosystems intended for biomedical applications, specifically in the field of personalized medicine, has increased notably in the last years. Consequently, a variety of characterization techniques devoted to studying nanomedicine interactions with proteins and cells have been developed, since a
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The design of colloidal nanosystems intended for biomedical applications, specifically in the field of personalized medicine, has increased notably in the last years. Consequently, a variety of characterization techniques devoted to studying nanomedicine interactions with proteins and cells have been developed, since a deep characterization of nanosystems is required before starting preclinical and clinical studies. In this context, this review aims to summarize the main techniques used to assess the interaction of nanomedicines with biological systems, highlighting their advantages and disadvantages. Testing designed nanomaterials with these techniques is required in order to have more information about their behavior on a physiological environment. Moreover, techniques used to study the interaction of nanomedicines with proteins, such as albumin and fibrinogen, are summarized. These interactions are not desired, since they usually are the first signal to the body for the activation of the immune system, which leads to the clearance of the exogenous components. On the other hand, techniques for studying the cell toxicity of nanosystems are also summarized, since this information is required before starting preclinical steps. The translation of knowledge from novel designed nanosystems at a research laboratory scale to real human therapies is usually a limiting or even a final point due to the lack of systematic studies regarding these two aspects: nanoparticle interaction with biological components and nanoparticle cytotoxicity. In conclusion, this review will be a useful support for those scientists aiming to develop nanosystems for nanomedicine purposes. Full article
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Open AccessReview
Biomarker-Guided Non-Adaptive Trial Designs in Phase II and Phase III: A Methodological Review
J. Pers. Med. 2017, 7(1), 1; doi:10.3390/jpm7010001 -
Abstract
Biomarker-guided treatment is a rapidly developing area of medicine, where treatment choice is personalised according to one or more of an individual’s biomarker measurements. A number of biomarker-guided trial designs have been proposed in the past decade, including both adaptive and non-adaptive trial
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Biomarker-guided treatment is a rapidly developing area of medicine, where treatment choice is personalised according to one or more of an individual’s biomarker measurements. A number of biomarker-guided trial designs have been proposed in the past decade, including both adaptive and non-adaptive trial designs which test the effectiveness of a biomarker-guided approach to treatment with the aim of improving patient health. A better understanding of them is needed as challenges occur both in terms of trial design and analysis. We have undertaken a comprehensive literature review based on an in-depth search strategy with a view to providing the research community with clarity in definition, methodology and terminology of the various biomarker-guided trial designs (both adaptive and non-adaptive designs) from a total of 211 included papers. In the present paper, we focus on non-adaptive biomarker-guided trial designs for which we have identified five distinct main types mentioned in 100 papers. We have graphically displayed each non-adaptive trial design and provided an in-depth overview of their key characteristics. Substantial variability has been observed in terms of how trial designs are described and particularly in the terminology used by different authors. Our comprehensive review provides guidance for those designing biomarker-guided trials. Full article
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Open AccessConcept Paper
Precision Health Economics and Outcomes Research to Support Precision Medicine: Big Data Meets Patient Heterogeneity on the Road to Value
J. Pers. Med. 2016, 6(4), 20; doi:10.3390/jpm6040020 -
Abstract
The “big data” era represents an exciting opportunity to utilize powerful new sources of information to reduce clinical and health economic uncertainty on an individual patient level. In turn, health economic outcomes research (HEOR) practices will need to evolve to accommodate individual patient–level
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The “big data” era represents an exciting opportunity to utilize powerful new sources of information to reduce clinical and health economic uncertainty on an individual patient level. In turn, health economic outcomes research (HEOR) practices will need to evolve to accommodate individual patient–level HEOR analyses. We propose the concept of “precision HEOR”, which utilizes a combination of costs and outcomes derived from big data to inform healthcare decision-making that is tailored to highly specific patient clusters or individuals. To explore this concept, we discuss the current and future roles of HEOR in health sector decision-making, big data and predictive analytics, and several key HEOR contexts in which big data and predictive analytics might transform traditional HEOR into precision HEOR. The guidance document addresses issues related to the transition from traditional to precision HEOR practices, the evaluation of patient similarity analysis and its appropriateness for precision HEOR analysis, and future challenges to precision HEOR adoption. Precision HEOR should make precision medicine more realizable by aiding and adapting healthcare resource allocation. The combined hopes for precision medicine and precision HEOR are that individual patients receive the best possible medical care while overall healthcare costs remain manageable or become more cost-efficient. Full article
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Open AccessArticle
IDICAP: A Novel Tool for Integrating Drug Intervention Based on Cancer Panel
J. Pers. Med. 2016, 6(4), 19; doi:10.3390/jpm6040019 -
Abstract
Cancer is a heterogeneous disease afflicting millions of people of all ages and their families worldwide. Tremendous resources have been and continue to be devoted to the development of cancer treatments that target the unique mutation profiles of patients, namely targeted cancer therapy.
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Cancer is a heterogeneous disease afflicting millions of people of all ages and their families worldwide. Tremendous resources have been and continue to be devoted to the development of cancer treatments that target the unique mutation profiles of patients, namely targeted cancer therapy. However, the sheer volume of drugs coupled with cancer heterogeneity becomes a challenge for physicians to prescribe effective therapies targeting patients’ unique genetic mutations. Developing a web service that allows clinicians as well as patients to identify effective drug therapies, both approved and experimental, would be helpful for both parties. We have developed an innovative web service, IDICAP, which stands for Integrated Drug Intervention for CAncer Panel. It uses genes that have been linked to a cancer type to search for drug and clinical trial information from ClinicalTrials.gov and DrugBank. IDICAP selects and integrates information pertaining to clinical trials, disease conditions, drugs under trial, locations of trials, drugs that are known to target the queried gene, and any known single nucleotide polymorphism (SNP) effects. We tested IDICAP by gene panels that contribute to breast cancer, ovarian cancer, and cancer in general. Clinical trials and drugs listed by our tool showed improved precision compared to the results from ClinicalTrials.gov and Drug Gene Interaction Database (DGIdb). Furthermore, IDICAP provides patients and doctors with a list of clinical facilities in their proximity, a characteristic that lends credence to the Precision Medicine Initiative launched by the White House in the United States in 2015. Full article
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Open AccessEditorial
Implementing Personalized Medicine in the Academic Health Center
J. Pers. Med. 2016, 6(3), 18; doi:10.3390/jpm6030018 -
Abstract
Recently we at Partners Health Care had a series of articles in the Journal of Personalized Medicine describing how we are going about implementing Personalized Medicine in an academic health care system [1–10].[...] Full article
Open AccessArticle
Implementation of Electronic Consent at a Biobank: An Opportunity for Precision Medicine Research
J. Pers. Med. 2016, 6(2), 17; doi:10.3390/jpm6020017 -
Abstract
The purpose of this study is to characterize the potential benefits and challenges of electronic informed consent (eIC) as a strategy for rapidly expanding the reach of large biobanks while reducing costs and potentially enhancing participant engagement. The Partners HealthCare Biobank (Partners Biobank)
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The purpose of this study is to characterize the potential benefits and challenges of electronic informed consent (eIC) as a strategy for rapidly expanding the reach of large biobanks while reducing costs and potentially enhancing participant engagement. The Partners HealthCare Biobank (Partners Biobank) implemented eIC tools and processes to complement traditional recruitment strategies in June 2014. Since then, the Partners Biobank has rigorously collected and tracked a variety of metrics relating to this novel recruitment method. From June 2014 through January 2016, the Partners Biobank sent email invitations to 184,387 patients at Massachusetts General Hospital and Brigham and Women’s Hospital. During the same time period, 7078 patients provided their consent via eIC. The rate of consent of emailed patients was 3.5%, and the rate of consent of patients who log into the eIC website at Partners Biobank was 30%. Banking of biospecimens linked to electronic health records has become a critical element of genomic research and a foundation for the NIH’s Precision Medicine Initiative (PMI). eIC is a feasible and potentially game-changing strategy for these large research studies that depend on patient recruitment. Full article
Open AccessArticle
Personalized Medicine in the U.S. and Germany: Awareness, Acceptance, Use and Preconditions for the Wide Implementation into the Medical Standard
J. Pers. Med. 2016, 6(2), 15; doi:10.3390/jpm6020015 -
Abstract
The aim of our research was to collect comprehensive data about the public and physician awareness, acceptance and use of Personalized Medicine (PM), as well as their opinions on PM reimbursement and genetic privacy protection in the U.S. and Germany. In order to
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The aim of our research was to collect comprehensive data about the public and physician awareness, acceptance and use of Personalized Medicine (PM), as well as their opinions on PM reimbursement and genetic privacy protection in the U.S. and Germany. In order to give a better overview, we compared our survey results with the results from other studies and discussed Personalized Medicine preconditions for its wide implementation into the medical standard. For the data collection, using the same methodology, we performed several surveys in Pennsylvania (U.S.) and Bavaria (Germany). Physicians were contacted via letter, while public representatives in person. Survey results, analyzed by means of descriptive and non-parametric statistic methods, have shown that awareness, acceptance, use and opinions on PM aspects in Pennsylvania and Bavaria were not significantly different. In both states there were strong concerns about genetic privacy protection and no support of one genetic database. The costs for Personalized Medicine were expected to be covered by health insurances and governmental funds. Summarizing, we came to the conclusion that for PM wide implementation there will be need to adjust the healthcare reimbursement system, as well as adopt new laws which protect against genetic misuse and simultaneously enable voluntary data provision. Full article
Open AccessArticle
Barriers and Facilitators to Adoption of Genomic Services for Colorectal Care within the Veterans Health Administration
J. Pers. Med. 2016, 6(2), 16; doi:10.3390/jpm6020016 -
Abstract
We examined facilitators and barriers to adoption of genomic services for colorectal care, one of the first genomic medicine applications, within the Veterans Health Administration to shed light on areas for practice change. We conducted semi-structured interviews with 58 clinicians to understand use
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We examined facilitators and barriers to adoption of genomic services for colorectal care, one of the first genomic medicine applications, within the Veterans Health Administration to shed light on areas for practice change. We conducted semi-structured interviews with 58 clinicians to understand use of the following genomic services for colorectal care: family health history documentation, molecular and genetic testing, and genetic counseling. Data collection and analysis were informed by two conceptual frameworks, the Greenhalgh Diffusion of Innovation and Andersen Behavioral Model, to allow for concurrent examination of both access and innovation factors. Specialists were more likely than primary care clinicians to obtain family history to investigate hereditary colorectal cancer (CRC), but with limited detail; clinicians suggested templates to facilitate retrieval and documentation of family history according to guidelines. Clinicians identified advantage of molecular tumor analysis prior to genetic testing, but tumor testing was infrequently used due to perceived low disease burden. Support from genetic counselors was regarded as facilitative for considering hereditary basis of CRC diagnosis, but there was variability in awareness of and access to this expertise. Our data suggest the need for tools and policies to establish and disseminate well-defined processes for accessing services and adhering to guidelines. Full article
Open AccessFeature PaperReview
Personal Genome Sequencing in Ostensibly Healthy Individuals and the PeopleSeq Consortium
J. Pers. Med. 2016, 6(2), 14; doi:10.3390/jpm6020014 -
Abstract
Thousands of ostensibly healthy individuals have had their exome or genome sequenced, but a much smaller number of these individuals have received any personal genomic results from that sequencing. We term those projects in which ostensibly healthy participants can receive sequencing-derived genetic findings
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Thousands of ostensibly healthy individuals have had their exome or genome sequenced, but a much smaller number of these individuals have received any personal genomic results from that sequencing. We term those projects in which ostensibly healthy participants can receive sequencing-derived genetic findings and may also have access to their genomic data as participatory predispositional personal genome sequencing (PPGS). Here we are focused on genome sequencing applied in a pre-symptomatic context and so define PPGS to exclude diagnostic genome sequencing intended to identify the molecular cause of suspected or diagnosed genetic disease. In this report we describe the design of completed and underway PPGS projects, briefly summarize the results reported to date and introduce the PeopleSeq Consortium, a newly formed collaboration of PPGS projects designed to collect much-needed longitudinal outcome data. Full article
Open AccessArticle
Bioinformatics Workflow for Clinical Whole Genome Sequencing at Partners HealthCare Personalized Medicine
J. Pers. Med. 2016, 6(1), 12; doi:10.3390/jpm6010012 -
Abstract
Effective implementation of precision medicine will be enhanced by a thorough understanding of each patient’s genetic composition to better treat his or her presenting symptoms or mitigate the onset of disease. This ideally includes the sequence information of a complete genome for each
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Effective implementation of precision medicine will be enhanced by a thorough understanding of each patient’s genetic composition to better treat his or her presenting symptoms or mitigate the onset of disease. This ideally includes the sequence information of a complete genome for each individual. At Partners HealthCare Personalized Medicine, we have developed a clinical process for whole genome sequencing (WGS) with application in both healthy individuals and those with disease. In this manuscript, we will describe our bioinformatics strategy to efficiently process and deliver genomic data to geneticists for clinical interpretation. We describe the handling of data from FASTQ to the final variant list for clinical review for the final report. We will also discuss our methodology for validating this workflow and the cost implications of running WGS. Full article