Publications by authors named "Alessandro Blasimme"

Background: Tissue engineering is a multidisciplinary field that combines principles from cell biology, bioengineering, material sciences, medicine and surgery to create functional and viable bioproducts that can be used to repair or replace damaged or diseased tissues in the human body. The complexity of tissue engineering can affect the prospects of efficiently translating scientific discoveries in the field into scalable clinical approaches that could benefit patients. Organizational challenges may play a key role in the clinical translation of tissue engineering for the benefit of patients.

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In the evolving landscape of digital medicine, digital biomarkers have emerged as a transformative source of health data, positioning them as an indispensable element for the future of the discipline. This necessitates a comprehensive exploration of the ethical complexities and challenges intrinsic to this cutting-edge technology. To address this imperative, we conducted a scoping review, seeking to distill the scientific literature exploring the ethical dimensions of the use of digital biomarkers.

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Digital health innovation is expected to transform healthcare, but it also generates ethical and societal concerns, such as privacy risks, and biases that can compound existing health inequalities. While such concerns are widely recognized, existing regulatory principles, oversight methods and ethical frameworks seem out of sync with digital health innovation. New governance and innovation best practices are thus needed to bring such principles to bear with the reality of business, innovation, and regulation.

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Data access and data sharing are vital to advance medicine. A growing number of public private partnerships are set up to facilitate data access and sharing, as private and public actors possess highly complementary health data sets and treatment development resources. However, the priorities and incentives of public and private organizations are frequently in conflict.

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Background: There are intense discussions about the ethical and societal implications of biomedical engineering, but little data to suggest how scientists think about the ethics of their work. The aim of this study is to describe how scientists frame the ethics of their research, with a focus on the field of molecular systems engineering.

Methods: Semi-structured qualitative interviews were conducted during 2021-2022, as part of a larger study.

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Over the last decade, bioengineering has seen a sustained growth in scientific publications, patents, and clinical trials. As the field attempts to bridge the gap between discovery and clinical application, a broader societal dialogue is needed to build public trust and address potential ethical, societal, and regulatory challenges. In this essay, we discuss societal aspects linked to the clinical use of biomedical engineering approaches and technologies, with a specific focus on molecular systems engineering.

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Recent research has challenged the notion that dementia is an inevitable outcome of age-related cognitive decline, highlighting the possibility of preventing or delaying onset by addressing specific risk factors. This paradigm shift suggests that prevention through lifestyle modifications and early interventions is possible, potentially averting millions of cases worldwide. This study explores the translation of scientific evidence on dementia prevention into public health policy in Switzerland.

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Article Synopsis
  • Dersimelagon (MT-7117) is being studied as a potential alternative treatment for Erythropoietic protoporphyria (EPP) in a phase III trial in the US and Europe.
  • The trial currently includes a placebo group, but this raises ethical concerns because there is already an approved treatment for EPP.
  • The authors propose using a noninferiority active-control trial instead of a placebo to ethically and scientifically assess dersimelagon's efficacy compared to existing treatments.
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Organ chips are microfabricated devices containing living engineered organ substructures in a controlled microenvironment. Research on organ chips has increased considerably over the past two decades. This paper offers an overview of the emerging knowledge ecosystem of organ chip research in Europe.

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Pediatric health care providers caring for patients and families with genetic disease will encounter a range of ethical issues. These include traditional pediatric health care issues, such as surrogate decision making and end-of-life care. Genetic testing raises the importance of informed consent for potential risks that move beyond the oft discussed physical risks and into longer term concepts such as psychological impact, privacy and potential discrimination.

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As digital technologies such as smartphones and fitness bands become more ubiquitous, individuals can engage in self-monitoring and self-care, gaining greater control over their health trajectories along the life-course. These technologies appeal particularly to young people, who are more familiar with digital devices. How this digital transformation facilitates health promotion is therefore a topic of animated debate.

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Human pluripotent stem cells can be used to derive in vitro models recapitulating post-implantation human embryos. While useful for research purposes, such integrated embryo models raise ethical issues that need to be addressed to facilitate ethically appropriate policies and regulations that permit scientific ingenuity and medical progress.

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Drugs addressing unmet medical needs can change the lives of millions. Developing and validating new drugs can, however, take many years. To streamline the assessment of new drugs, regulatory agencies have long established shortened review pathways.

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Fuelled by adaptations to clinical trial implementation during the COVID-19 pandemic, decentralised clinical trials are burgeoning. Decentralised clinical trials involve many digital tools to facilitate research without physical contact between research teams and participants at various stages, such as recruitment, enrolment, informed consent, administering study interventions, obtaining patient-reported outcome measures, and safety monitoring. These tools can provide ways of ensuring participants' safety and research integrity, while sometimes reducing participant burden and trial cost.

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Spurred by recent advances in machine learning and electronic hardware, digital health promises to profoundly transform medicine. At the same time, however, it raises conspicuous ethical and regulatory issues. This has led to a growing number of calls for responsible digital health.

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Machine learning has become a key driver of the digital health revolution. That comes with a fair share of high hopes and hype. We conducted a scoping review on machine learning in medical imaging, providing a comprehensive outlook of the field's potential, limitations, and future directions.

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Introduction: Artificial intelligence (AI) has the potential to transform clinical decision-making as we know it. Powered by sophisticated machine learning algorithms, clinical decision support systems (CDSS) can generate unprecedented amounts of predictive information about individuals' health. Yet, despite the potential of these systems to promote proactive decision-making and improve health outcomes, their utility and impact remain poorly understood due to their still rare application in clinical practice.

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This paper describes the results of a multi-country survey of governance approaches for the use of digital contact tracing (DCT) in response to the COVID-19 pandemic. We argue that the countries in our survey represent two distinct models of DCT governance, both of which are flawed. The "data protection model" emphasizes privacy protections at the expense of public health benefit, while the "emergency response model" sacrifices transparency and accountability, prompting concerns about excessive governance surveillance.

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The SARS-CoV-2 pandemic is a public health challenge of unprecedented scale. In the midst of the first wave of the pandemic, governments worldwide introduced digital contact tracing systems as part of a strategy to contain the spread of the virus. In Europe, after intense discussion about privacy-related risks involving policymakers, technology experts, information technology companies, and-albeit to a limited extent-the public at large, technical protocols were created to support the development of privacy-compatible proximity tracing apps.

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The online space has become a digital public square, where individuals interact and share ideas on the most trivial to the most serious of matters, including discussions of controversial ethical issues in science, technology and medicine. In the last decade, new disciplines like computational social science and social data science have created methods to collect and analyse such data that have considerably expanded the scope of social science research. Empirical bioethics can benefit from the integration of such digital methods to investigate novel digital phenomena and trace how bioethical issues take shape online.

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On June 7, 2021, the US Food and Drug Administration (FDA) approved aducanumab, a monoclonal amyloid targeting β-amyloid, for the treatment for Alzheimer's disease (AD). This decision was achieved through the Accelerated Approval Pathway and was essentially motivated by the evidence that aducanumab reduces brain amyloid plaques. This news is causing a heated debate in the scientific community.

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In this paper, I present an emerging explanatory framework about ageing and care. In particular, I focus on how, in contrast to most classical accounts of ageing, biomedicine today construes the ageing process as a modifiable trajectory. This framing turns ageing from a stage of inexorable decline into the focus of preventive strategies, harnessing the functional plasticity of the ageing organism.

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