2,403 research outputs found

    Health Economic Evidence and Modeling Challenges for Liquid Biopsy Assays in Cancer Management:A Systematic Literature Review

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    BACKGROUND: Cancer-derived material circulating in the bloodstream and other bodily fluids, referred to as liquid biopsies (LBs), has become an appealing adjunct or alternative to tissue biopsies, showing vital promise in several clinical applications.PURPOSE: A systematic literature review was conducted to (1) summarize the current health economic evidence for LB assays and (2) identify and analyze the studies addressed or reported on the challenges of health economic modeling in precision medicine.METHODS: Relevant studies were identified in the EMBASE, MEDLINE, Cochrane Library, EconLit, and the University of Melbourne Full Text Journal databases from 1 January 2013 to 16 September 2022. Included papers were selected if they were economic evaluations and/or budget impact analyses.RESULTS: A total of 24 studies were included and analyzed, with the majority being full economic evaluations (n = 19, 79.2%). Four studies (16.7%) were health and budget impact analyses, and one study (4.1%) incorporated both an economic evaluation and a budget impact analysis. Cohort-level modeling techniques were the most common approach (n = 16; 80%). LB technologies were cost-effective in 15 studies (75%) considering different biomarkers, cancer types and stages, and economic analyses. These studies evaluated LBs for screening and early detection (66.7%), treatment selection (26.7%), and monitoring treatment response (6.6%). Budget impact analysis results were varied among included studies, with the majority of studies (n = 4; 80%) reporting either cost savings, minimal, or modest budget impact, while one study (20%) reported LBs as an efficient strategy. The reviewed studies often inadequately reported or addressed modeling challenges, such as patient-level processes, the combination of tests and treatments, preferences, and uncertainty.CONCLUSION: LBs could provide a cost-effective approach for treatment selection in lung cancer and aid in the screening and early detection of other cancers, including colorectal, gastric, breast, and brain cancers. This is in comparison with various alternatives, such as the standard of care (SOC) and no screening scenario. However, it is important to mention that in some comparisons, LBs were used in combination with SOC instead of replacing it. Importantly, few studies have pointed toward LBs' cost-effectiveness for monitoring treatment response. Most health and budget impact analyses, especially those focused on lung cancer, suggest potential cost savings or a minimal-to-moderate budget impact. Nevertheless, additional research is needed to ascertain their effectiveness across various stages of lung and colorectal cancer, as well as to address potential modeling challenges.SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022307939.</p

    Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks

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    In this review we summarize our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions

    Responsible research and innovation in science education: insights from evaluating the impact of using digital media and arts-based methods on RRI values

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    The European Commission policy approach of Responsible Research and Innovation (RRI) is gaining momentum in European research planning and development as a strategy to align scientific and technological progress with socially desirable and acceptable ends. One of the RRI agendas is science education, aiming to foster future generations' acquisition of skills and values needed to engage in society responsibly. To this end, it is argued that RRI-based science education can benefit from more interdisciplinary methods such as those based on arts and digital technologies. However, the evidence existing on the impact of science education activities using digital media and arts-based methods on RRI values remains underexplored. This article comparatively reviews previous evidence on the evaluation of these activities, from primary to higher education, to examine whether and how RRI-related learning outcomes are evaluated and how these activities impact on students' learning. Forty academic publications were selected and its content analysed according to five RRI values: creative and critical thinking, engagement, inclusiveness, gender equality and integration of ethical issues. When evaluating the impact of digital and arts-based methods in science education activities, creative and critical thinking, engagement and partly inclusiveness are the RRI values mainly addressed. In contrast, gender equality and ethics integration are neglected. Digital-based methods seem to be more focused on students' questioning and inquiry skills, whereas those using arts often examine imagination, curiosity and autonomy. Differences in the evaluation focus between studies on digital media and those on arts partly explain differences in their impact on RRI values, but also result in non-documented outcomes and undermine their potential. Further developments in interdisciplinary approaches to science education following the RRI policy agenda should reinforce the design of the activities as well as procedural aspects of the evaluation research

    Ono: an open platform for social robotics

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    In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform

    INTEGRATIVE ANALYSIS OF OMICS DATA IN ADULT GLIOMA AND OTHER TCGA CANCERS TO GUIDE PRECISION MEDICINE

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    Transcriptomic profiling and gene expression signatures have been widely applied as effective approaches for enhancing the molecular classification, diagnosis, prognosis or prediction of therapeutic response towards personalized therapy for cancer patients. Thanks to modern genome-wide profiling technology, scientists are able to build engines leveraging massive genomic variations and integrating with clinical data to identify “at risk” individuals for the sake of prevention, diagnosis and therapeutic interventions. In my graduate work for my Ph.D. thesis, I have investigated genomic sequencing data mining to comprehensively characterise molecular classifications and aberrant genomic events associated with clinical prognosis and treatment response, through applying high-dimensional omics genomic data to promote the understanding of gene signatures and somatic molecular alterations contributing to cancer progression and clinical outcomes. Following this motivation, my dissertation has been focused on the following three topics in translational genomics. 1) Characterization of transcriptomic plasticity and its association with the tumor microenvironment in glioblastoma (GBM). I have integrated transcriptomic, genomic, protein and clinical data to increase the accuracy of GBM classification, and identify the association between the GBM mesenchymal subtype and reduced tumorpurity, accompanied with increased presence of tumor-associated microglia. Then I have tackled the sole source of microglial as intrinsic tumor bulk but not their corresponding neurosphere cells through both transcriptional and protein level analysis using a panel of sphere-forming glioma cultures and their parent GBM samples.FurthermoreI have demonstrated my hypothesis through longitudinal analysis of paired primary and recurrent GBM samples that the phenotypic alterations of GBM subtypes are not due to intrinsic proneural-to-mesenchymal transition in tumor cells, rather it is intertwined with increased level of microglia upon disease recurrence. Collectively I have elucidated the critical role of tumor microenvironment (Microglia and macrophages from central nervous system) contributing to the intra-tumor heterogeneity and accurate classification of GBM patients based on transcriptomic profiling, which will not only significantly impact on clinical perspective but also pave the way for preclinical cancer research. 2) Identification of prognostic gene signatures that stratify adult diffuse glioma patientsharboring1p/19q co-deletions. I have compared multiple statistical methods and derived a gene signature significantly associated with survival by applying a machine learning algorithm. Then I have identified inflammatory response and acetylation activity that associated with malignant progression of 1p/19q co-deleted glioma. In addition, I showed this signature translates to other types of adult diffuse glioma, suggesting its universality in the pathobiology of other subset gliomas. My efforts on integrative data analysis of this highly curated data set usingoptimizedstatistical models will reflect the pending update to WHO classification system oftumorsin the central nervous system (CNS). 3) Comprehensive characterization of somatic fusion transcripts in Pan-Cancers. I have identified a panel of novel fusion transcripts across all of TCGA cancer types through transcriptomic profiling. Then I have predicted fusion proteins with kinase activity and hub function of pathway network based on the annotation of genetically mobile domains and functional domain architectures. I have evaluated a panel of in -frame gene fusions as potential driver mutations based on network fusion centrality hypothesis. I have also characterised the emerging complexity of genetic architecture in fusion transcripts through integrating genomic structure and somatic variants and delineating the distinct genomic patterns of fusion events across different cancer types. Overall my exploration of the pathogenetic impact and clinical relevance of candidate gene fusions have provided fundamental insights into the management of a subset of cancer patients by predicting the oncogenic signalling and specific drug targets encoded by these fusion genes. Taken together, the translational genomic research I have conducted during my Ph.D. study will shed new light on precision medicine and contribute to the cancer research community. The novel classification concept, gene signature and fusion transcripts I have identified will address several hotly debated issues in translational genomics, such as complex interactions between tumor bulks and their adjacent microenvironments, prognostic markers for clinical diagnostics and personalized therapy, distinct patterns of genomic structure alterations and oncogenic events in different cancer types, therefore facilitating our understanding of genomic alterations and moving us towards the development of precision medicine

    Book of Abstracts 15th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and 3rd Conference on Imaging and Visualization

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    In this edition, the two events will run together as a single conference, highlighting the strong connection with the Taylor & Francis journals: Computer Methods in Biomechanics and Biomedical Engineering (John Middleton and Christopher Jacobs, Eds.) and Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization (JoãoManuel R.S. Tavares, Ed.). The conference has become a major international meeting on computational biomechanics, imaging andvisualization. In this edition, the main program includes 212 presentations. In addition, sixteen renowned researchers will give plenary keynotes, addressing current challenges in computational biomechanics and biomedical imaging. In Lisbon, for the first time, a session dedicated to award the winner of the Best Paper in CMBBE Journal will take place. We believe that CMBBE2018 will have a strong impact on the development of computational biomechanics and biomedical imaging and visualization, identifying emerging areas of research and promoting the collaboration and networking between participants. This impact is evidenced through the well-known research groups, commercial companies and scientific organizations, who continue to support and sponsor the CMBBE meeting series. In fact, the conference is enriched with five workshops on specific scientific topics and commercial software.info:eu-repo/semantics/draf

    Deoxy technologies: a medical technology startup project: business plan for UK market

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    L26, O32DEOXY Technologies is a seed-stage medical technology project whose future core business will be based on an innovative Gene Expression profiling (GEP) nanotechnology, developed and patented at Harvard University. The project is located at Ludwig-Maximilian University (Germany) and its goal is to develop diagnostic tests for clinical market where price, speed and automation are competitive advantages. DEOXY Technologies intends to become a global and "lean" company focused on development and manufacturing of molecular tests (in vitro medical devices). This is a strategic analysis and a feasibility study for the breast cancer market. Breast cancer is the most frequent female cancer affecting 12% of women, worldwide and is seen as a paradigm of precision medicine success. The promoter identifies a clinical application for the GEP technology and proposes an alliance with an USA biomarker-focused company whose assets are complementary to the technology. The strategic analysis was based on a macroenvironmental analysis for the entrance market: United Kingdom, where regulatory and reimbursement contexts were systematized, and for Germany the country of development and manufacturing, where the impact of governmental support and the integration in a biotechnology cluster are critical favorable factors. In the microenvironmental analysis the high barriers to entrance and the importance of planning an exit strategy were underlined. The economic and financial viability analysis revealed that governmental funding is a critical success factor, as demonstrated by the positivity of the APV and emphasized the importance of a market expansion plan before starting operations. The scenario analysis explored how reimbursement and healthcare policies may impact the economic and financial viability of the project.A DEOXY Technologies é um projeto, baseado numa nanotecnologia inovadora de análise perfis de expressão genética (APEG), descoberta e patenteada na Universidade de Harvard. O projeto está integrado na Universidade de Ludwig-Maximilians, (Alemanha) e é candidato a fundos de investimento governamentais. A DEOXY Technologies acredita que por possuir uma tecnologia inovadora pode desenvolver máquinas de APEG e testes moleculares para o mercado clínico, onde o preço, automatização e rapidez serão vantagens competitivas. A DEOXY Technologies planeia tornar-se uma empresa global e "lean", focada no desenvolvimento e produção de testes moleculares "in vitro". Este plano de negócios contém a análise estratégica e económico-financeira para o mercado do cancro da mama, em Inglaterra (Reino Unido). O cancro da mama é o cancro mais frequente na mulher, afetando 12% desta população, e é paradigmático do sucesso da medicina de precisão. O promotor identifica uma necessidade clínica e para sua concretização propõe uma aliança com uma empresa biotecnológica detentora de ativos intelectuais complementares aos da DEOXY Technologies. A estratégia proposta baseia-se na análise PEST para o Reino Unido, contendo a regulamentação e etapas-chave para obter reembolso, e análise PEST para Alemanha, destacando-se a relevância do apoio governamental e da inserção num cluster biotecnológico como fatores críticos de sucesso. Da análise micro-ambiental salientam-se as barreiras à entrada e a importância da estratégia de saída nesta indústria. O estudo de viabilidade económico-financeira revelou que os fundos governamentais são um fator critico para a exequibilidade e viabilidade económico-financeira do projeto, sendo o valor atualizado ajustado o único indicador positivo. A análise de cenários demonstra como as políticas de cuidados de saúde influenciam a estratégia e a viabilidade económico-financeira do projeto
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