D. Randall. Seton Hill College.
The precise structures of both the Information Commons and Knowledge Network of Disease remain to be determined and would be informed by pilot studies cheap levitra with dapoxetine 40/60 mg with mastercard, as discussed in Chapter 4 purchase levitra with dapoxetine 40/60 mg. Given the inclusion of multiple parameters ranging from genomic to environmentally modulated disease factors discount levitra with dapoxetine 40/60mg free shipping, the Information Commons would likely have a multi-layered structure with each layer containing the information for one disease parameter, such as “signs and symptoms”, genetic mutations, epigenetic patterns, metabolic characteristics, or other risk factors (including social, behavioral, and environmental influences). The Information Commons should register all measurements with respect to individuals so that the multitude of influences on pathophysiological states can be viewed at scales that span all the way from the molecular to the social level. Only in this way could, for example, individual environmental exposures be matched to individual changes in molecular profiles. These data would need to be stored in an escrowed, encrypted depository that allows graded release of data depending on the questions asked, the access level of the individual making the inquiry, and other parameters that would undoubtedly emerge in the course of pilot studies. The Committee realizes that this is a radical approach and intense public education and outreach about the value of the Information Commons to the progress of medicine would be essential to harness informed volunteerism, the support of disease-specific advocacy groups, and the engagement of other stakeholders. The Committee regards careful handling of policies to ensure privacy as the central issue in its entire vision of the Information Commons, the Knowledge Network of Disease, and the New Taxonomy. The Knowledge Network of Disease, created by integrating data in the Information Commons with fundamental biological knowledge, drawn from the biomedical literature and existing community databases such as Genbank, would be the centerpiece of the informational resources underlying the New Taxonomy. In order to extract relationship information between multiple parameters—for example, the transciptome and the exposome—the multiple data layers must be inter-connected (see Figure 3-1: Building a Biomedical Knowledge Network for Basic Discovery and Medicine. Ideally, each information layer would be connected to every other layer: thus, “signs and symptoms” would be linked to mutations, mutations to metabolic defects, exposome to the epigenome, and so forth. The links could be one-to-one but most commonly would be many-to-one, and one-to-many (e. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease 45 layers could be characterized through a variety of representations that attempt to extract meaning from the Information Commons. Meanwhile, different types of lymphomas, defined by transcriptome analysis, may have distinct metabolomic profiles. The similarities of multiple diseases could be discerned either from relationships among the networks of individual parameters (e. A highly interconnected Knowledge Network would link multiple individual networks of parameters in a flexible way. A user could chose to interrogate only a small part of the network by limiting his or her analysis to a single information layer, or even a small portion of this layer; alternatively, a user could interrogate the complex interrelationship of multiple parameters. High flexibility ensures easy cross-comparison and cross-correlation of any desired dataset, making it a versatile tool for a wide spectrum of applications ranging from basic research to clinical studies and healthy system administration. Widely accessible The Knowledge Network would need to be accessible and usable by a wide range of stakeholders from basic scientists to clinicians, health- care workers and the public. Furthermore, the available information would need to be mineable in ways that are custom-tailored to the needs of different users, possibly by implementation of purpose-specific user interfaces. While the Committee agreed upon the generalities listed above and illustrated in Figure 3-1, about the Information Commons and Knowledge Network —and their relationship to a New Taxonomy— specifics of implementation such as the detailed design of the Information Commons, the information technology platforms used to create it, questions about where key infrastructure should be physically housed, who would oversee it, and how the Information Commons would be financed, were considered beyond the scope of the Committee’s charge in a framework study. Nonetheless, dramatic developments in the fields of medical information technology—and other developments discussed in Chapter 2—give the Committee confidence that the creation and implementation of this ambitious and novel infrastructure is a feasible goal. The Proposed Knowledge Network Would Fundamentally Differ from Current Biomedical Information Systems Immense progress has been made during the past 25 years in organizing our knowledge of basic biology, health, and disease, even as many components of this knowledge base have grown super-exponentially. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease 46 The key difference is that the information commons, which would underlie the other databases, would be “individual-centric. An independent researcher, who was not involved in the study that contributed these entries, has no way of knowing that they are from the same individual. As a consequence, relationships between multiple parameters that determine disease status in a given individual are impossible to extract. This information was not collected in a way that allows the individual to be the central organizing principle, and no amount of redesign of the inter-connections between different entries in the current system could achieve the goals the Committee has outlined. The Committee would like to emphasize the novelty and power of an Information Commons that is “individual-centric. For example, given the coordinates of a large number of, say, backyard barbecue grills, one can suddenly overlay a vast amount of socio-economic, ethnic, climatological, and other data on what—at the start of the investigation—appeared a peculiar, anecdotal inquiry. Despite significant challenges to constructing an individual-centric Information Commons, the Committee concluded that this is a realistic undertaking and would be essential to the success of the Knowledge-Network/ New Taxonomy initiative. The Committee is of the opinion that “precision medicine,” designed to provide the best accessible care for each individual, is not achievable without a massive reorientation of the information systems on which researchers and health-care providers depend: these systems, like the medicine they aspire to support, must be individualized. Generalizations must be built up from information on large numbers of individuals. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease 47 is lost when molecular profiles, data on other aspects of an individual’s circumstances, and health histories are abstracted away from the individual at the very beginning of investigations into the determinants of health and disease. A Knowledge Network of Disease Would Continuously Evolve Although knowledge of disease, and particularly molecular mechanisms of pathogenesis, is still limited, the pace of progress has never been greater. New insights into the biology of disease are emerging rapidly from a wealth of molecular approaches, as well as from new insights into the importance of environmental factors. However, the system for updating current disease taxonomies, at intervals of many years does not permit the rapid incorporation of new information, thereby contributing to the delayed introduction of advances that have the potential, over time, to guide mainstream practice. The individual-centric nature of an Information Commons is an important means of ensuring that the data underlying the Knowledge Network, and its derived taxonomy, would be constantly updated. Such a dynamic system would not only accept new inputs for established disease parameters, it would also accommodate new types of information generated by newly developed technologies, to identify, acquire, measure, and analyze new biological features of disease. The New Taxonomy Would Require Continuous Validation Bad information is worse than no information. A key feature of a clinically useful taxonomy is the requirement for a validation system. The logic of the classification scheme, and especially its utility for practical applications, needs to be carefully and continuously tested. This is particularly important when patients and clinicians use the New Taxonomy to inform clinical decisions. The New Taxonomy should be routinely tested to provide all stakeholders with data indicating the extent to which decisions guided by it can be made with confidence. Clearly, some patients and clinicians will be more comfortable than others with making decisions that are based on clinical intuition rather than proven evidence. However, a physician should be able to interrogate the Knowledge Network that underlies the New Taxonomy to learn whether others have had to make a similar decision, and, if so, what the consequences were. For example, if a drug has been introduced to target a particular driver mutation in a cancer, a physician needs to know whether or not rigorous clinical testing has determined that the drug is safe and effective. Is the drug effective only in some patients who can be identified in some way, such as by analyzing variants of genes that affect cell growth or drug metabolism? Similarly, if a laboratory test is considered to be a candidate predictor for the later development of disease, has that hypothesis been rigorously validated? Whether a given test is used to identify predictors of disease or the existence of disease, the test result must be interpreted in the context of knowledge about the “normal range” of results. This requirement is not a trivial consideration, especially for tests based on integration of vast amounts of data, such as the genome, transcriptome, and metabolome of the patient.
Understanding the evolutionary reasons for our susceptibility to disease com- plements the traditional biomedical understanding of the etiology and patho- genesis of disease buy levitra with dapoxetine online from canada. Together order levitra with dapoxetine 40/60mg on line, these two perspectives on health and disease buy levitra with dapoxetine no prescription, the ulti- mate and the proximate causes of disease, can help us understand why we get sick as well as how we get sick, and may provide insights into interventions that might reduce the burden of disease. The distribution of the sickle-cell trait in East Africa and elsewhere, and its apparent relationship to the incidence of subtertian malaria. Darwin and the doctors: Evolution, diathesis, and germs in 19th-cen- tury Britain. Medical education in the United States and Canada:A report to the Carnegie Foundation for the advancement of teaching. Cause and effect in biology revisited: Is Mayr’s proximate-ulti- mate dichotomy still useful? Glucose-6-phosphate dehydrogenase defi- cient red cells: Resistance to infection by malarial parasites. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of the information contained therein. More information on the European Union is available on the internet (http://europa. It is a new paradigm in medicine based on the smart use of technology, coupled with greater participation by patients in the management of their own health, to help prevent disease and promote healthy living. When diseases can be prevented and not only treated, the cost of healthcare will come down, creating a virtuous circle for health policy. The Personalised Medicine conference addressed the broader policy perspective and challenges by showcasing integrated healthcare models in Member States and business approaches which involve patients more directly in their healthcare. This can be summarised in one sentence: to be involved in decision-making affecting their own healthcare. This means involving patients in the formulation of treatment guidelines and protocols, the design of clinical trials and medicine reimbursement. Therefore it is critical that systems are in place for obtaining patient consent, and patient participation in decision-making about the use of those data. Furthermore it was explained how Scotland uses information technology to predict and manage disease on a population level within the Scottish National Health Service. Another example was presented from Estonia, which has organised its entire health system around electronic registries. These enable patients, doctors and other healthcare professionals to conduct transactions such as ordering prescriptions, while also supporting basic research. A challenge for policymakers is to ensure that the system for obtaining patient consent is robust and the purpose for which it will be used is transparent. Some doubt was aired about whether practitioners currently have all the analytical tools and standards in place to do this. The challenge is to standardise and validate these systems without losing sight of the purpose for which they were intended – to improve patient care. The discussion about information technology was taken further by illustrating how new sequencing technologies can be used to identify gene mutations, which in turn become targets for developing novel therapies. Genomic and phenotypic data can be combined with epidemiological data to design disease prevention campaigns. The North Karelia Project in Finland succeeded in reducing mortality rates from chronic heart disease by means of a sustained campaign. Good results were also achieved in the clinical arena by researchers in Belgium by identifying a mutation present in a subgroup of cancer patients and repositioning a marketed drug for those patients. In stratified clinical trials, patients are selected based on the likelihood of their response to a new treatment. All three examples illustrate the need for practitioners to work with well-defined targets, monitor the results carefully, and be prepared for the unexpected. A challenge for policymakers is to have a system in place for validating biomarkers for use in trials and public health campaigns. Currently, different companies produce different biomarkers for the same indications. This discussion focused on incentives for bringing personalised medicine to the market. Each personalised medicine approach or drug will be developed for a relatively small patient population. Companies need incentives to undertake this work, which will not be as remunerative as developing drugs for a large market. Options discussed included a risk-sharing agreement under which the public authority would guarantee a market share in exchange for an agreement to undertake the risk of drug development. It was also suggested that in order to ease market entry for new products, gaps in the regulatory system could be closed. This would require bringing health technology officials into talks with pharmaceutical regulators, so that prospective new drugs and approaches were given the best chance of market access, as is already practised by the European 5 Medicines Agency. The orphan drug policy is seen as a huge success, as it combines industry incentives with clearly defined patient populations and encourages patient participation in the drug development process. Any adaptation of this policy to personalised medicine would require guarantees to contain prices and avoid stifling innovation. To be sustainable, any strategy for personalised medicine needs to enjoy broad support from the population. This starts with having sound policies on informed consent and the use of personal data. It continues with the building of electronic patient records, registries and biobanks, all of which need to be integrated into a system that has practical benefits for people. The benefits include information on disease prevention and treatment and the importance of a healthy lifestyle. If the system is synchronised and enjoys public support, there are massive opportunities for improving public health and bringing the cost of healthcare down. The presentations and a video recording of the proceedings can be viewed online at: www. The views and opinions expressed in this report are not necessarily those of the European Commission. The summary of the presentations and interventions of the speakers should be checked against actual delivery. Personalised medicine is an approach to healthcare that puts the citizen in the centre. By developing tailor-made diagnostic, treatment and prevention strategies, patients receive therapies that specifically work for them. It also allows people to participate in the management of their own health by having access to information about the prevention and treatment of disease. There is no universally accepted definition of personalised medicine and the concept is evolving with the advance of technology.
The most innovative approaches with capacities could ensure faster patient access to innovative their strong intellectual property protection are especially technologies and cost-efective translation discount 40/60mg levitra with dapoxetine with amex, which could re- complicating for shared decision-making processes purchase levitra with dapoxetine with amex. Therefore generic levitra with dapoxetine 40/60 mg otc, public–private healthcare systems (Goldman, 2012; Said & Zerhouni, 2014). Thus, managed entry-agree- number of patients involved, for example in the case of rare ments, coverage with evidence schemes and new ways of diseases and stratifcation. Gaps of evidence and uncertainty innovative public procurement processes are good candi- management: When uncertainties regarding outcomes are dates for addressing most of the issues that are currently still in the pipeline and added value from existing eviden- under debate. Mechanisms exist that can be valuable in the case of new evidence generation while ensuring access to a. Practice Guidelines for Quality Assurance, Provision and Use of Genome-based Information and Techno- logies’). The implementation of the concept of public Key Enablers for Challenge 5 health genomics, being the responsible and efective Europe: e. Ministries of health, regulatory au- logies for the beneft of population health, requires thorities’ (e. In this concept, genome-based 37 information is highly holistic and includes not only all the adoption of technologies with proven value in ‚omics‘ data but also environmental, socioeconomic hospitals. Decision-makers in hospitals are thereby of the projects in health sector that are already in pla- informed of the likely value of a health technology for ce can be viewed at http://www. It is a clear example of well-presented in- labelling and the defning of functional and other cri- formation for patients and professionals and provides teria. EuroRec is organised as a permanent network of a comprehensive health information service to help national centres and provides services to industry (de- put individuals in control of their healthcare. The web- velopers and vendors), healthcare providers (buyers), site helps people make choices about health, from de- policy makers and patients. There are also hundreds of thousands of and Certifcation of Electronic Health Record systems entries in more than 50 directories. The forum has published vari- archiving and distribution of personally identifiable ous papers that address value-based pricing and ad- genetic and phenotypic data resulting from biome- aptive licensing (http://www. To this end, stakeholders representing all pies, for example by the validation of biomarkers. But too relevant perspectives were included, such as research po- many current approaches result in failure at some point licy and funding, healthcare provision, and citizens’/pati- along the development pipeline or do not demonstrate ents’ needs and interests. For these reasons, additional participation, a very broad spectrum of recommendations funding for clinical implementation and ‘real-world’ as- and potential felds of action has been identifed. Research projects that are carri- it has been a signifcant challenge to pinpoint reasonable ed out in close collaboration with, for example, regulatory concrete actions. This will confront rese- ges as well as the 35 recommendations several enablers archers with hitherto unfamiliar communication and co- have to join forces on either European or national level. Several recommendations relate to more than one of the As a result, the challenge for research funders and decisi- defned fve challenges or cut across more than one of the on-makers will be to fund research beyond the classical three broad areas of activity which have been identifed funding schemes. In these cases, the recommendations communication and training modules, more outreach have been ascribed to the challenge or activity area to activities, and more non-research cross-sectoral projects which they mainly relate, in the interest of producing a to complement ‘classical’ basic and translational research clearer picture. Funding also needs to provide incentives to in- linked package of measures will provide sufcient impact clude specialists from a wide range of areas such as: on the wellbeing of citizens, the sustainability of health- care systems and the competitiveness of relevant indus- • Big data and information and communication techno- tries in Europe and beyond. Some of these recom- mendations are also related to other challenges, therefore they are shown again within the circle. Furthermore, there are manifold interrelations between the fve challenges; these have not been indicated in order to keep the clearness of the fgure. Research to investigate diferent trial designs and their Such an investigation would inform the regulatory pro- results; whether they have been successful in addressing cess and the drug development process. Research on tools for more personalised healthcare and Paving the way for providers to implement standardised, rehabilitation. Already existing software applications and tools have to be integrated into a security framework. The challenge is to bring together multiple applications and multiple data standards to allow a datafow in a meaningful and secure way. Reclassifcation of diseases at the molecular level for Development of new and more efective diagnostic and optimisation of therapeutic strategies. Modelling of health and diseases by interdisciplinary The aim is the representation of health and disease research projects, for example via systems medicine and based on the simultaneous consideration of clinical, in silico modelling/simulation approaches. Support clinical validation of pharmacogenomics appro- The fndings will accelerate the translation from basic aches that integrate age and gender considerations into research biomarker development to their efcient genetically divergent populations. Research on phenotype–genotype correlations on exis- Optimal use of national resources for established co- ting data and specifcally established cohorts. Correlation studies of phenotypic evolution of diseases Evidence on the impact of the environment on the in subgroups or individuals within longitudinal cohorts, evolution of diseases. Support for decision makers and for example in terms of poly-pathologies, socio-econo- providers to set up public health measures for disease mic inequalities and access to care. Develop inexpensive and rapid test systems to produce A better understanding of disease mechanisms related a short development cycle for diagnosis and therapy, to genetic variants and the design of biopharmaceutical e. Earlier diagnostic markers would support the assessment of prognosis, monitoring and identifcation of the most efective treat- ment for a given group of patients. Optimise individual drug therapies and poly-pharmacy More specifc and efective drug therapies particularly especially in the case of multi-morbidity. Reduction of drugs prescribed, side-efects and costs through fewer and more specifc therapies. Research on drug interaction (drug–drug and drug– Optimised therapies with minimised side-efects. Increasing the number of well validated and robust biomarkers with proven stratifcation potential ready for clinical routine. Furthermore, all research activities have to be supported by adapted frameworks in Europe as well as at the national level in terms of health systems, insurers, providers, and regulatory bodies. Additionally the responsible authorities need to put in place appropriate regulatory frameworks, recognise and overcome the normative and ethical chal- lenges and, crucially, ensure that the patients’ and citizens‘ needs and interests are implemented (see also Challen- ges 1, 2, 4 and 5). However, evidence for real benefts to national health sys- Unfortunately independent international communica- tems remains scarce. Such a cross-bor- in the implementation of personalised prevention, diag- der research funding scheme would be synergetic and nosis and therapy. Regulation, Reimbursement & Market Access ents‘ Forum, Belgium: Citizens’ Perspective and 4. Improve communication and education strategies to increase patient health literacy. All recommendations have been colour-coded according to the activities referred to, which are grouped into three broad 6. However, many recommendations do have a share in system and increase the patient’s role in all phases two or sometimes all three types of activity (see also fgure 3 of research and development. In these cases, the recommendation has been assigned to the activity deemed to have the major share. Develop common principles and legal frameworks that enable sharing of patient-level data for rese- arch in a way that is ethical and acceptable to pati- The colour-coding is as follows: ents and the public. Promote the development of high quality sustain- Challenge 1 – Developing Aware- able databases including clinical, health and well- ness and Empowerment being information.