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Modified Dilemma Game + (You and your group will be asked to fill o … You and your group will be asked to fill out tables to identify the principles and practices of the European Code of Conduct for Research Integrity, and scientific virtues, that are relevant to the dilemma at stake. [[File:Modified Dilemma Game Table 1.png|thumb|'''Table 1: Which principles from European Code for Research Integrity can you identify in each dilemma?''']] [[File:Modified Dilemma Game Table 2.png|thumb|'''Table 2. Which research misbehaviors can you identify in this dilemma?''']] [[File:Modified Dilemma Game Table 3.jpg|thumb|'''Table 3. Which scientific virtues are important when deciding on a course of action?''']] [[File:Modified Dilemma Game Table 3.jpg|thumb|'''Table 3. Which scientific virtues are important when deciding on a course of action?''']] )
Modified Dilemma Game + (You will be asked to reflect on the proces … You will be asked to reflect on the process, and to evaluate if the learning objectives were met. You will be invited to have a brief dialogue on what you might have just learned as a group. You may be asked to seek answers to questions such as the following: *Was it easy or difficult to identify the relevant principles and virtues in the chosen dilemma?*Did this exercise help you with identifying and connecting to formally defined principles, such as those in the European Code of Conduct for Research Integrity?*Did most of the players agree or disagree with the final choice?*What were the main points of contention?*How come people disagreed (e.g. differences in experience, training, background, values, norms…)?*Was any alternative option proposed?*Did anybody change her/his mind as a result of the discussion?*What is needed in order to do the moral good in your work setting? What were the most convincing arguments used in the discussion?*On which areas do you feel there is insufficient consensus?*How to best address such future dilemmas in your daily work?address such future dilemmas in your daily work?)
Modified Dilemma Game + (You will be invited to the plenary. The trainer will ask you to reflect on your individual choices and engage in a dialogue with other participants.)
Modified Dilemma Game + (You, as a group, will be asked to present a brief summary of what has just been discussed in your group. You may assign a member as a spokesman to shortly present the results of your discussion.)
Deneyimler üzerine fikir yürütme ve alıştırmaları uygulama + (Yüz yüze alıştırmaları kolaylaştırıcı olar … Yüz yüze alıştırmaları kolaylaştırıcı olarak yönetme ve kullanma konusundaki deneyim ve uzmanlığınıza dayanarak;katılımcılarla birlikte, kendi hedef gruplarının yeterlilik düzeyi ve öğrenme ihtiyaçları, bu grupların ayrıntılı olarak tartışmak istediği şeyler ve bu konuların alıştırmalara nasıl katılabileceği üzerine tartışın. Katılımcılara İyi Bilim Elçiliği web sitesindeki eğitim materyallerine nasıl erişebileceklerini gösterin. Ayrıca, bu platformdaki toplulukla platformun tartışma sayfası üzerinden nasıl etkileşime geçebileceklerini ve eğitim materyalleri üzerinde nasıl değişiklik talep edebileceklerini de açıklayabilirsiniz.ep edebileceklerini de açıklayabilirsiniz.)
Critical Thinking, Standpoint & Ethics + ([[File:A drop of water.png|center|frameles … [[File:A drop of water.png|center|frameless|600x600px]]Researchers in many fields have long known that the act of looking at something can change it. This holds true for people, for animals, and for particles. Below you will see four well known examples of how an observer can have an impact on what they are observing. For this drag and drop exercise, match the impact type to the meaning.'''Exercise Feedback'''These phenomena are well known in research. For instance, being observed makes psychiatric patients a third less likely to require sedation (Damsa et al, 2006), or the famous double slit experiment in modern physics. But many people believe that what we see is never what ‘really is’, even in the most highly controlled experimental settings. What do you think? experimental settings. What do you think?)
Gene Editing Case Study with Human Application + ([[File:A group of different people.jpg|cen … [[File:A group of different people.jpg|center|frameless|600x600px]]<div><div>This checklist is intended for use as a supplement to the usual ethics review process regarding matters that are mainly specific to gene editing in humans. All usual aspects of research ethics review will also need to be considered, for instance, the appropriate processing of sensitive data or the involvement of vulnerable persons, like young children. Additionally, the checklist is not exhaustive;there may be other issues pertaining to individual studies that are not included here. Nevertheless, alongside general guidelines and processes, it provides a useful starting point for ethics reviewers. ''' ''''''1. Somatic or germline gene editing'''a. Does the project aim to involve somatic or germline gene editing or both?b. If germline gene editing, does the project comply with national legislation?c. If germline gene editing, what steps have been undertaken to ensure societal acceptability?d. If somatic gene editing, could the intervention affect the germline accidentally?''' ''''''2. Novelty of gene editing in the project'''a. Does the project use a novel technique, one that has already been tried in humans, or both?b. If this is the first time it has been tested in humans, have comprehensive studies been undertaken in vitro and in animals to demonstrate proof of concept and safety?c. If the technology has already been tested in humans, what do the findings tell us about potential risks and benefits?''' ''''''3. Technological and other risks'''a. Are risks of on-target effects clearly described and addressed?b. Are risks of off-target effects clearly described and addressed?c. Are risks of genetic mosaicism clearly described and addressed?d. Are risks of immunogenicity clearly described and addressed?e. Are risks associated with the treatment process clearly described and addressed?f. Are risks of incidental findings clearly described and addressed?'''4. Enhancement and slippery slope'''a. Is the gene editing to be used purely for therapeutic purposes?b. If for therapeutic purposes, are there risks that the technology could also be applied for enhancement purposes?c. If so, how is this risk addressed?'''5. Consent'''a. How is the consent process being managed?b. How is the option to opt out of the procedure being managed?c. Is participant information sufficiently comprehensive and comprehensible so that the potential participants (or their legal representatives) will understand enough about the technology to assess the potential for harms and benefits meaningfully?d. Are the potential participants being offered adequate support and time to reach a decision?'''6. Data'''a. What measures and protections are in place to prevent the exploitation of genetic and/or other biological data, for example, for profit?b. What measures and protections are in place to prevent the misuse exploitation of genetic and/or other biological data and leading to, for example, discrimination, harassment, or marginalisation?'''7. Equity'''a. Who are the potential beneficiaries of this study?b. Will the resultant therapy or other benefits be broadly accessible?c. How are any matters of potential inequity in access addressed and justified?'''8. Study justification'''a. Is there a medical need for this study?b. Might the same objectives be achieved via less risky and/or less costly methods?[https://classroom.eneri.eu/sites/default/files/2024-10/Checklist%20for%20gene%20editing.pdf You can download the checklist here]</div></div><div></div>editing.pdf You can download the checklist here] </div></div><div></div>)
Critical Thinking, Standpoint & Ethics + ([[File:A pair of eyes.png|center|frameless … [[File:A pair of eyes.png|center|frameless|600x600px]]For most people, the ultimate proof that something is true is to see it for themselves. But how reliable are your observations? In the following pages, we will consider three potential influencing factors:*The sense perception of the observer*The impacts of the observer*The viewpoint of the observerhe observer *The viewpoint of the observer)
Critical Thinking, Standpoint & Ethics + ([[File:A spyglass.png|center|frameless|600 … [[File:A spyglass.png|center|frameless|600x600px]]Sometimes its not just the presence but the viewpoint which changes the interaction with the observed.The third influencing factor upon what is observed stems from the viewpoint of the observer. Researchers are not neutral processors of information. As human beings, they bring with them a host of assumptions and preconceptions.Observation is dependent upon and coloured by our individual senses and our background beliefs and assumptions. In research, many of our background beliefs and assumptions are associated with the paradigm in which we operate, as we consider next. in which we operate, as we consider next.)
Critical Thinking, Standpoint & Ethics + ([[File:A view of mountains high up on a hi … [[File:A view of mountains high up on a hill.png|center|frameless|600x600px]]Which paradigm are you working in? Look at the descriptions on the end points of each question, and try to work out where you and your research project might fall along each continuum. Are you more of a realist or more of a relativist? Is your approach to knowledge generation more positivist or interpretivist? Do these aspects fit with the methodological stance that you take in your research?Most people operate somewhere between the extremes. Additionally, it is possible to alter one’s positionality in response to different contexts. For instance, when addressing a research question which requires broad statistics, one might take a more positivist stance;when in-depth inquiry of a qualitative nature is required, one might take a more interpretivist stance. The important point is that we are cognisant of our perspective and its influence upon the knowledge that we create.fluence upon the knowledge that we create.)
AI In Healthcare: Technology Basics + ([[File:AI Image1.png|center|frameless|600x … [[File:AI Image1.png|center|frameless|600x600px]]AI, or artificial intelligence, refers to the development of digital systems that can perform tasks that typically require human intelligence.These tasks include learning, reasoning, problem-solving, perception, language understanding, and speech recognition.At its core, AI leverages principles from computer science, mathematics, and cognitive psychology to replicate intelligent behaviour in machines.AI utilises algorithms, data, and computational power to simulate intelligent behaviour, enabling machines to adapt, improve, and perform complex functions autonomously.Several core scientific concepts underpin the development and functionality of AI. Work your way through the presentation below to hear about some of them:This list of core scientific concepts in AI is subject to ongoing research and development. The field of AI is rapidly evolving, and new techniques, algorithms, and applications are continuously emerging.As researchers and scientists make advancements in AI technology and explore novel use cases, the understanding and implementation of these concepts may evolve.Generative AI is a type of foundation model that is becoming more and more evident in everyday life as well as in healthcare. Test your understanding of generative AI by answering the following questions.e AI by answering the following questions.)
AI In Healthcare: Technology Basics + ([[File:AI Image10.png|center|frameless|600x600px]] <div><div> Think about places where data relating to your own health might be stored – tick all that apply </div></div><div> * </div>)
AI In Healthcare: Technology Basics + ([[File:AI Image11.png|center|frameless|600 … [[File:AI Image11.png|center|frameless|600x600px]]Consider the following questions to reflect on the potential impact of AI technologies in healthcare on the patient-doctor relationship:Awareness and Trust:*Do you think patients may have concerns or reservations about relying on AI-driven insights over traditional doctor-patient interactions?Communication and Understanding:*In what ways do you think AI technologies could enhance or hinder communication between patients and healthcare professionals?Personalisation and Empathy:*Do you think the integration of AI could impact the empathetic aspects of the patient-doctor relationship? If so, in what ways?Role of the Healthcare Professional:*What role do you envision for healthcare professionals in a future where AI technologies play a significant role in diagnosis and treatment?*How can doctors maintain their essential role as caregivers and decision-makers while working alongside AI systems?Balancing Technology and Human Touch:*Reflect on the importance of finding a balance between AI technologies and the human touch in healthcare. How can technology enhance, rather than replace, the human connection between patients and healthcare providers?between patients and healthcare providers?)
AI In Healthcare: Technology Basics + ([[File:AI Image12.png|center|frameless|600 … [[File:AI Image12.png|center|frameless|600x600px]]In navigating the entry of new actors into the health domain, policymakers, healthcare providers, and technology companies must work together to ensure that innovations align with patient needs, adhere to ethical standards, and contribute to the overall improvement of healthcare delivery. Balancing innovation with regulatory oversight and patient protection remains a key challenge in this evolving landscape. key challenge in this evolving landscape.)
AI In Healthcare: Technology Basics + ([[File:AI Image13.png|center|frameless|600x600px]] You can try these questions to see whether your learning from this module addresses the intended learning outcomes. No one else will see your answers. No personal data is collected.)
AI In Healthcare: Technology Basics + ([[File:AI Image2.png|center|frameless|600x … [[File:AI Image2.png|center|frameless|600x600px]]AI systems are built through a process that involves several key steps.Building AI systems is an iterative process, that involves ongoing refinement and improvement to keep up with evolving requirements and challenges.Additionally, advancements in research and technology may prompt updates to models and algorithms.y prompt updates to models and algorithms.)
AI In Healthcare: Technology Basics + ([[File:AI Image3.png|center|frameless|600x … [[File:AI Image3.png|center|frameless|600x600px]]Artificial Intelligence (AI) is revolutionising the healthcare domain, introducing transformative applications that can enhance diagnosis, treatment, and patient care. The synergy between advanced algorithms, machine learning, and healthcare data has paved the way for innovative solutions with the potential to improve outcomes, increase efficiency, and streamline processes. Key applications of AI in the healthcare sector include:'''Diagnostic imagery:''' AI excels in interpreting medical imaging data, such as X-rays, MRIs, and CT scans. Deep learning algorithms can detect patterns and abnormalities, aiding radiologists in accurate and swift diagnoses. This not only speeds up the diagnostic process but also enhances precision when identifying subtle anomalies.'''Disease prediction & prevention:''' Predictive analytics powered by AI enables healthcare providers to forecast disease risks and identify individuals who may be predisposed to certain conditions. By analysing patient data and lifestyle factors, AI models can assist in implementing preventive measures and personalised interventions to mitigate potential health risks.'''Drug discovery & development:''' AI can accelerate the drug discovery process by analysing vast datasets to identify potential drug candidates and predict their efficacy. Machine learning algorithms can analyse molecular structures, predict drug interactions, and optimise formulations, significantly reducing the time and cost associated with bringing new drugs to market.'''Personalised medicine:''' AI enables the development of personalised treatment plans by analysing patient-specific data, including genetic information, medical history, and lifestyle factors. This approach allows healthcare providers to tailor interventions and medications to individual patient needs, improving treatment effectiveness and minimising adverse effects.'''Chatbots:''' Chatbots and virtual health assistants powered by AI are used to enhance patient engagement and provide on-demand healthcare information. These tools can offer guidance on symptoms, medication reminders, and lifestyle recommendations. Proponents of virtual health assistants claim that they can improve patient adherence to treatment plans and foster better communication between patients and healthcare providers. However, this is disputed by those who are concerned about what may be lost through a decrease in human-to-human interactions.'''Natural language processing and health records: T'''he use of NLP algorithms to extract valuable insights from unstructured clinical notes and electronic health records facilitates efficient data management, enables faster information retrieval, and supports clinical decision-making. NLP also plays a crucial role in automating administrative tasks, allowing healthcare professionals to focus more on patient care.'''Robotic surgery assistance:''' AI-powered robotic systems assist surgeons in performing complex procedures with precision and minimal invasiveness. These robotic platforms enhance surgical outcomes, reduce recovery times, and contribute to advancements in minimally invasive surgery techniques.'''Remote patient monitoring:''' AI can be used to facilitate the continuous monitoring of patients' health remotely through wearable devices and sensors. Real-time data analysis allows healthcare providers to track vital signs, detect abnormalities, and intervene promptly, especially for patients with chronic conditions., especially for patients with chronic conditions.)
AI In Healthcare: Technology Basics + ([[File:AI Image4.png|center|frameless|600x … [[File:AI Image4.png|center|frameless|600x600px]]Alexei Grinbaum shares his thoughts on the benefits of AI.'''Benefits of AI'''Alexei Grinbaum – French Alternative Energies and Atomic Energy Commission (CEA)AI in healthcare can bring two kinds of benefits. One for the patients, AI does non-human calculation. It can probably, through computation, discover things that we haven't discovered humanly, meaning new drugs, new treatments. And that is happening already. We are discovering new molecules that we had never thought about humanly. So that's for the patients.Now for the doctors, for medical doctors, AI can probably free up a lot of time from doing routine things that the doctors don't enjoy doing, like writing reports or things like that AI can have a lot of benefits for all sorts of people involved in healthcare on different sides, for medical professionals and for the patients, but very different kinds of benefits.nts, but very different kinds of benefits.)
AI In Healthcare: Technology Basics + ([[File:AI Image5.png|center|frameless|600x … [[File:AI Image5.png|center|frameless|600x600px]]Alexei Grinbaum shares his thoughts on reasons to be cautious about AI.'''Reasons to be cautious about the use of AI'''Like with all artificial intelligence systems, there should be limits, filters, and controls. We shouldn't just let it go uncontrolled completely. So unchecked completely. First, of course, there is the classic question of data, personal data, sensitive data. This is about health, our data. Some of it is genetic. Some of it lets us identify people. How do we treat that data? So, that is a very classic question. But beyond that, there are very interesting questions about human autonomy. AI systems, will they overtake the doctors? Will they still leave a place for human contact, human warmth?If we seek advice from an AI system, does it mean that somehow the medical profession is changing completely? So, these kinds of questions are important. Again, they're not exactly specific to the medical sphere. They also exist, for example, for AI assistance. But in the medical sphere, there are interesting questions that are a little bit more specific. Some would say, cybersecurity, you know, it's everywhere. We have all heard about robustness and cybersecurity. But in the medical sphere, if you have a device that is interacting with your body, and if somebody can hack it, well then of course, it's a direct threat to our well-being, to our health. So, the questions of cybersecurity are also very touchy, I would say, in the medical sphere.And then beyond that, we have classic big questions about organisations. Will the whole sphere of medical care with the hospitals, you know, the emergency rooms and all of these things, how will that evolve? Should it be managed not by humans, but by robots or AI systems? Will they respond faster? How will that change the way we build our social institutions? And that's another dimension of AI in health care.So, there are definitely benefits at each of these levels. But there are also risks, or I would say, reasons to be cautious, reasons not to go too fast with the deployment of AI systems, because the human profession doesn't change in 10 days, right? We need time to evolve. We need time to learn new skills.So not going too fast, teaching medical doctors and healthcare professionals to work together with these systems rather than be replaced by these systems. That is something that is very important. Take time. Take the time. Be cautious about bias, discrimination, accessibility, autonomy, control, all of those different things, and not go too fast.ose different things, and not go too fast.)
AI In Healthcare: Technology Basics + ([[File:AI Image6.png|center|frameless|600x … [[File:AI Image6.png|center|frameless|600x600px]]What are some of the key benefits of the use of AI applications in healthcare?As AI continues to evolve, its applications in healthcare hold immense promise for improving the quality of care, optimising resource utilization, and potentially shaping a more patient-centered and efficient healthcare ecosystem. However, careful implementation and ongoing scrutiny is vital to ensure the responsible and beneficial use of AI in healthcare.If you would like to explore the topic of AI implementation in more depth, you can access the Coalition for Health’s Blueprint for Trustworthy AI Implementation Guidance and Assurance for Healthcare in the further resources section.althcare in the further resources section.)
AI In Healthcare: Technology Basics + ([[File:AI Image8.png|center|frameless|600x … [[File:AI Image8.png|center|frameless|600x600px]]<div><div>As healthcare organizations strive to harness the benefits of AI while safeguarding patient data, a delicate balance must be maintained.Stringent security protocols, transparent data governance, and ethical AI development practices are crucial for upholding the confidentiality and integrity of healthcare data in the era of AI-driven advancements.Policymakers, healthcare providers, and technology developers must work collaboratively to establish robust frameworks, regulations, and ethical guidelines to ensure the responsible and secure use of health data in AI applications.</div></div><div></div>ealth data in AI applications. </div></div><div></div>)
AI In Healthcare: Technology Basics + ([[File:AI Image9.png|center|frameless|600x … [[File:AI Image9.png|center|frameless|600x600px]]Antonija Mijatovic shares her thoughts on challenges for data privacy and security.'''Challenges for data privacy and security'''When it comes to data security and privacy, the major issues are data breaches. Because many applications in AI involve health data, and health data is sensitive and confidential by nature.So, data breaches can lead to privacy violations, identity theft, even health risks. And they result in financial losses for healthcare organizations. Because healthcare is the top industry targeted by ransomware. Ransomware is a common cyber-attack. But aside of ransomware, data breaches can occur through hacking, phishing, and even if a device storing health information is lost or stolen. And data breaches can also happen unintentionally. For example, if patient data is emailed to the wrong recipient or posted online. And these incidents happen very often.For example, in the United States alone, only in the last year there have been more than 500 cases of cyber-attacks. So, this is why it is important to address. Researchers need to take multiple measures to ensure data security and privacy. And these include cyber security measures, such as strong passwords, restricted access, two-factor authentication, and even encryption of very sensitive data. In addition, researchers should create backups of very important folders. And also, because 90% of cyber-attacks were allowed due to human error, researchers who work with sensitive data should receive proper training in the subject.Ethics reviewers need to check whether researchers took all necessary measures to ensure data privacy and security. And they should also check whether researchers adhered to regulatory compliance. For example, in the European Union, personal data is regulated through the [https://gdpr.eu/what-is-gdpr/ GDPR] and personal data in AI is regulated through the [https://artificialintelligenceact.eu/ Artificial Intelligence Act]. While in the United States there are several guidelines such as the [https://aspe.hhs.gov/reports/health-insurance-portability-accountability-act-1996 Health Accountability and Portability Act].ealth Accountability and Portability Act].)
AI in Healthcare: Ethics Issues + ([[File:AI Img1.png|center|frameless|600x60 … [[File:AI Img1.png|center|frameless|600x600px]]Informed consent processes can be challenging when AI technologies are involved. Bearing the important concepts of transparency and explainability in mind when designing consent documents and processes will help to centralise patients/participants’ needs and ensure a fair process.Answer the following questions to test your understanding of informed consent, transparency and explainability regarding the use of AI technologies in healthcare. the use of AI technologies in healthcare.)
AI in Healthcare: Ethics Issues + ([[File:AI Img10.png|center|frameless|600x600px]] You can try these questions to see whether your learning from this module addresses the intended learning outcomes. No one else will see your answers. No personal data is collected.)
AI in Healthcare: Ethics Issues + ([[File:AI Img2.png|center|frameless|600x60 … [[File:AI Img2.png|center|frameless|600x600px]]<div><div>With the integration of AI technologies into healthcare, shaping diagnostic tools, treatment plans, and patient care, critical questions emerge about data-related ethics issues.Here are some examples:</div></div><div></div>sues. Here are some examples: </div></div><div></div>)

AI in Healthcare: Ethics Issues + ([[File:AI Img3.png|center|frameless|600x600px]])

AI in Healthcare: Ethics Issues + ([[File:AI Img8.png|center|frameless|600x60 … [[File:AI Img8.png|center|frameless|600x600px]]It is important for students, researchers and research ethics reviewers involved with research using and/or developing AI technologies in the healthcare domain to be aware of relevant guidelines and regulations that apply to their projects.The [https://www.who.int/publications/i/item/9789240029200 WHO’s Ethics and governance of artificial intelligence for health] calls for the embedding of ethics and human rights at the heart of AI design, deployment.Click on the hotspots below to see WHO’s key ethical principles for research involving AI in healthcare.The guidelines state that ‘each component in itself is necessary but not sufficient for the achievement of Trustworthy AI. Ideally, all three components work in harmony and overlap in their operation. If, in practice, tensions arise between these components, society should endeavour to align them’., society should endeavour to align them’.)
AI in Healthcare: Ethics Issues + ([[File:AI img10.png|center|frameless|600x6 … [[File:AI img10.png|center|frameless|600x600px]]Comité Consultatif National D’Ethique pour les Sciences de la Vie et de la Santé: Medical Diagnosis and Artificial Intelligence: Ethical Issues. Joint opinion of the CCNE and CNPEN, CCNE Opinion 141, CNPEN Opinion 4. November 2022 https://www.ccne-ethique.fr/sites/default/files/2023-05/Opinion%20No.141.pdf Council of Europe: Guidelines on artificial intelligence and data protection (2019) https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021- [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf 2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-] [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf for-artificial-intelligence_he_en.pdf] Deutscher Ethikrat (German Ethics Council): Opinion: Humans and Machines – Challenges of Artificial Intelligence (2023) https://www.ethikrat.org/en/publications/publication-details/?tx_wwt3shop_detail%5Bproduct%5D=168&tx_wwt3shop_detail%5Baction%5D=index&tx_wwt3shop_detail%5Bcontroller%5D=Products&cookieLevel=accept-all&cHash=4d430bf45ea980ea5f83daad9550ef88 (currently only available in German, an English translation will be available in due course) European Commission: Ethics By Design and Ethics of Use Approaches for Artificial Intelligence (2021) https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021- [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf 2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-] [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf for-artificial-intelligence_he_en.pdf] European Commission Science Policy, Advice & Ethics Unit, DG Research & Innovation:The ethics appraisal scheme in Horizon Europe (2021)https://www.bbmri-eric.eu/wp-content/uploads/The-Ethics-Appraisal-Scheme-_BBMRI-webinar-september-2021_version-for-dessimination.pdf Chapter 8 of the ethics issues table in the EU ethics appraisal scheme is of particular importance in Horizon Europe as it specifically addresses research ethical aspects of AI. Other relevant chapters include chapter 1 on human participants, chapter 4 on personal data and chapter 10 on the potential misuse of results. The inclusion of a chapter on AI in Horizon Europe is a recent addition. The EC introduced this chapter because it identified pressing ethical concerns related to discrimination and bias, safety and liability, transparency and opaque algorithms, as well as privacy and data protection. These concerns were deemed highly urgent and thus warranted a dedicated section within the ethics appraisal scheme. The key values to be respected within the projects submitted to the EU appraisal scheme are (1) human agency and oversight, (2) privacy and data protection, (3) fairness, diversity and non-discrimination, (4) accountability, (5) transparency, and (6) societal and environmental wellbeing.Ethics guidelines for trustworthy AI (2019) https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines- [https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai trustworthy-ai] OECD Legal Instruments:Recommendation of the Council on Artificial Intelligence (2019) https://legalinstruments.oecd.org/en/instruments/oecd-legal-0449 UNESCO: Recommendations on the Ethics of Artificial Intelligence (2022) https://unesdoc.unesco.org/ark:/48223/pf0000381137 World Health Organisation: Ethics and governance of artificial intelligence for health (2021) https://www.who.int/publications/i/item/9789240029200 See Chapter 4 for an overview of laws, policies, and principles that apply to the use of AI in healthcare. Chapter 5 proposes six key ethical principles which can serve as useful reminders for those involved in research utilising AI in healthcareAlso worth exploring are guidelines produced by [https://blog.neurips.cc/2021/12/03/a-retrospective-on-the-neurips-2021-ethics-review-process/ Stanford University], [https://unesdoc.unesco.org/ark:/48223/pf0000380455#:~:text=AI%20actors%20and%20Member%20States,law%2C%20in%20particular%20Member%20States%27 UNESCO] and the Horizon Europe Project [https://www.sienna-project.eu/ SIENNA] which developed ethical frameworks and recommendations for AI and robotics. Isaak, J., & Hanna, M. J. (2018). User data privacy: Facebook, Cambridge Analytica, and privacy protection. Computer, 51(8), 56-59. https://ieeexplore.ieee.org/abstract/document/8436400r, 51(8), 56-59. https://ieeexplore.ieee.org/abstract/document/8436400)
AI in Healthcare: Ethics Issues + ([[File:AI img4.png|center|frameless|600x60 … [[File:AI img4.png|center|frameless|600x600px]]How and at what points can bias be introduced into AI systems in healthcare? Click on the image below to find out more.It is important for researchers and reviewers of research to be aware of the data-related ethics issues, that may arise in projects using AI technologies in the healthcare domain.Vigilance about these matters is essential at the initial design stages and throughout projects.ial design stages and throughout projects.)
AI in Healthcare: Ethics Issues + ([[File:AI img5.png|center|frameless|600x60 … [[File:AI img5.png|center|frameless|600x600px]]Societal values are the shared beliefs, principles, and norms that guide the behaviour and interactions of individuals within a society. These values play a crucial role in shaping the culture, social cohesion, and overall functioning of a community.AI clearly has the potential to cause harms to society, as was evident in [https://ieeexplore.ieee.org/abstract/document/8436400 the case of Cambridge Analytica] when social media data was misused to manipulate the outcome of democratic elections. Concerns related to accountability/responsibility, patient-healthcare provider relationship, question of trust, surveillance, etc. in AI are significant [https://pubmed.ncbi.nlm.nih.gov/32702587/ and are being studied]. However, in such a rapidly changing field, questions around the continuing evolution and potential uses of AI in healthcare and their broader impacts upon individuals, communities, and society in general will remain open.The use of robots in the delivery of care offers a useful illustration of the complexity of questions to be considered about the impact of AI machines for individuals, communities, and society. James Wright observed the trialling of three types of care robots in a Japanese care home:* Hug, an assistive robot, which was used to lift patients out of bed and reduce the need for staff to undertake manual lifting.* Paro, a robotic furry seal, which was used to provide a form of animal therapy and companionship for elderly residents.* Pepper, a humanoid robot, which was used to lead activities such as karaoke or exercise sessions. The introduction of care robots into healthcare settings raises complex ethical and societal issues which extend beyond the concerns of dehumanisation of care, impact on staff morale, confusion of roles, and waste of resources highlighted by this case. Consideration also needs to be given to other values and principles including but not limited to: autonomy, moral agency, trust and reliability. [https://www.sciencedirect.com/science/article/pii/S0921889016305292?pes=vor The ethics of healthcare robotics] sets out the need for a dialogic and collaborative approach to embed ethics throughout such projects, ensuring a responsible approach to research and innovation in this developing field.h and innovation in this developing field.)
AI in Healthcare: Ethics Issues + ([[File:AI img6.png|center|frameless|600x600px]])
AI in Healthcare: Ethics Issues + ([[File:AI img7.png|center|frameless|600x60 … [[File:AI img7.png|center|frameless|600x600px]]As AI continues to reshape the healthcare landscape, it brings about a myriad of societal and ethical considerations. This sorting exercise aims to explore the broader issues surrounding the intersection of AI and healthcare.Please categorise each scenario into the appropriate societal or ethical dimension:appropriate societal or ethical dimension:)
AI in Healthcare: Ethics Issues + ([[File:AI img8.png|center|frameless|600x600px]])
AI in Healthcare: Ethics Issues + ([[File:AI img9.png|center|frameless|600x60 … [[File:AI img9.png|center|frameless|600x600px]]Alexei Grinbaum shares some considerations for researchers and research ethics reviewers. In this interview, you will hear Alexei discuss different categories of questions that need to be asked about studies involving the use of AI technologies in healthcare. [https://classroom.eneri.eu/sites/default/files/2024-10/20240513%20Checklist%20AI%20in%20health.pdf The Ethics of AI in Healthcare: A checklist for Research Ethics Committees], which we mentioned at the beginning of the module is a useful resource to identify relevant questions.l resource to identify relevant questions.)
Gene Editing Case Study with Human Application + ([[File:A_child_using_building_blocks.jpeg| … [[File:A_child_using_building_blocks.jpeg|600px]]Watch the video below to learn about Hunter syndrome, its treatments and effects.[[File:Irecs_What_is_Hunter_syndrome.mp4|600px|thumb|centre]]====Video Transcript====What is Hunter syndrome? Hunter syndrome is a rare genetic disorder that primarily affects males. It is part of a group of diseases known as mucopolysaccharidoses or MPS, which are caused by the body's inability to break down certain complex sugars called glycosaminoglycans or GAGs. For people with Hunter syndrome, a lack of the enzyme iduronate-2-sulfatase or IDS, means that GAGs build up inside the body leading to a wide variety of symptoms including developmental issues, physical problems and mental decline. For example:*Physical development impacts like coarse facial features, thickened skin, enlarged tongue, and joint stiffness.*Developmental delays in children affecting motor skills, speech, and learning.*Respiratory problems with frequent respiratory infections, sleep apnoea, and other breathing difficulties.*Hearing loss.*Enlarged liver and spleen, leading to abdominal distension.*Heart problems with heart valve abnormalities and other cardiac issues.*Skeletal abnormalities like joint stiffness, short stature, and abnormal bone development.*The onset of the disease is usually between the ages of 2 and 4 years and developmental decline is usually evident between the ages of 18 and 36 months. There is currently no cure for Hunter syndrome, but treatments can help to manage the symptoms and improve quality of life. Options include: Enzyme replacement therapy (ERT). Regular, often weekly, infusions of a synthetic version of the missing enzyme can help reduce the buildup of GAGs. However, the enzyme is not able to pass the blood-brain-barrier, so this form of treatment does not help to protect against brain damage.# Symptomatic treatments for specific issues including physical therapy for joint problems, medications for respiratory and heart problems, and surgical interventions for specific complications.# Despite treatment, those with severe disease usually die in their teens. Those with a milder form of Hunter syndrome might live with more gradual deterioration in health until middle age.more gradual deterioration in health until middle age.)
Biobanking: Technology Basics + ([[File:Alert Signs.png|center|frameless|60 … [[File:Alert Signs.png|center|frameless|600x600px|]]Biobanks can be classified according to different criteria. However, they are most often classified as population-based or disease-based biobanks. Overall, these biobank types play pivotal roles in advancing scientific understanding, improving diagnostics, and driving innovations in personalized healthcare, ultimately contributing to the evolution of precision medicine and improved patient outcomes.In addition, virtual biobanks or virtual repositories are a relatively new management model employed in biobanking, formed of digital rather than physical repositories of biological samples and associated data.of biological samples and associated data.)
Biobanking: Ethics Issues + ([[File:Bio2Image1.png|center|frameless|600 … [[File:Bio2Image1.png|center|frameless|600x600px]]The following case study about the 2013-15 Ebola outbreak in Sierra Leone illustrates some of the key ethical issues related to biobanking.'''The Ebola outbreak in Sierra Leone'''During the 2013-15 Ebola outbreak in Sierra Leone, ethical issues emerged in the context of biobanking, as researchers sought to understand and combat the deadly virus. A prominent case involved the establishment of biobanks to collect and store biological samples from Ebola patients for research purposes. Following a large-scale collection of diagnostic samples, diagnostic tests were mainly carried out by external laboratories under memoranda of cooperation or material transfer agreements.Biobanking operations in Sierra Leone contributed significantly to gaining an understanding of the outbreak, but the meeting of ethical standards was deemed inadequate with a lack of a complete inventory of the samples collected, and incomplete information about their potential future use, location, and ownership.One ethical concern centered around obtaining informed consent from individuals affected by the outbreak. With the urgency of the situation and the widespread fear of the virus, ensuring truly voluntary and informed participation became challenging. Issues of comprehension, especially in remote and vulnerable communities, raised questions about the validity of the consent process.Another ethical dilemma was the potential for exploitation. The influx of international researchers and organisations into Sierra Leone raised concerns about the fair distribution of benefits and resources. There were fears that the biological samples collected might be used for research benefiting external entities, potentially neglecting the welfare and healthcare needs of the local population.'''Feedback'''<div>Balancing the need for rapid research to address the Ebola crisis with ethical considerations regarding consent, community engagement, and equitable benefits posed significant challenges during this public health emergency. The case underscores the importance of establishing and adhering to clear ethical guidelines and community involvement protocols in biobanking practices, especially in the context of infectious disease outbreaks in resource-limited settings.</div><div></div>in resource-limited settings. </div><div> </div>)
Biobanking: Ethics Issues + ([[File:Bio2Image10.png|center|frameless|60 … [[File:Bio2Image10.png|center|frameless|600x600px]]'''Data sharing across borders'''International collaborations strive for diverse sample populations to avoid biases in research outcomes and to ensure that research findings are applicable and beneficial to global populations. However, the sharing of data across international borders increases the risk of privacy breaches and unauthorised access due to variations in data protection laws, hence robust security measures and compliance with diverse regulatory frameworks are crucial.Informed consent for international data sharing can be complex due to differences in cultural norms, legal requirements, and language barriers. Respect for the cultural values and norms of different donor populations might require adaption of the protocols for collection and use of samples and data to align with each cultural context.Additionally, determining who has control and sovereignty over the shared data can be contentious, and striking a balance between collaboration and respecting the rights of individual countries or institutions might pose an ongoing ethical challenge. Researchers and RECs will need to navigate the complexities of multiple jurisdictions to uphold consistent ethical standards.ns to uphold consistent ethical standards.)
Biobanking: Ethics Issues + ([[File:Bio2Image11.png|center|frameless|600x600px]])
Biobanking: Ethics Issues + ([[File:Bio2Image12.png|center|frameless|60 … [[File:Bio2Image12.png|center|frameless|600x600px]]'''An example of a protocol to deal with incidental findings'''In addition to collecting biological samples, the population-based UK [https://www.nature.com/articles/s41467-020-15948-9#Sec19 Biobank also collect multi-modal images] from some donors which include MRIs, x-rays, and ultrasounds. Their protocol for dealing with incidental findings included the recruitment of 3rd party consultant radiologists to review scans that the biobank radiologists had flagged up if they had noticed signs of something clinically serious at the time of collection. The consultant radiologist then reviewed the images and advised the biobank if the donor and their healthcare practitioner should be notified. Of the donors who were notified of an incidental finding, all consulted their doctor, and 90% went on to further clinical assessments.% went on to further clinical assessments.)
Biobanking: Ethics Issues + ([[File:Bio2Image13.png|center|frameless|60 … [[File:Bio2Image13.png|center|frameless|600x600px]]Work has been conducted in [https://www.nature.com/articles/s41431-023-01299-8 Germany] and the [https://www.bbmri.nl/sites/bbmri/files/Erasmus_MC_Handreiking_Interactieve_pdf_Engels_29_04_2020_V3.pdf Netherlands] to design guidelines for dealing with incidental findings arising from biobank research. Both sets of guidelines emphasise that processes for dealing with incidental findings need to be in place from the design stage of studies.'''Feedback'''Researchers working with secondary data collected by biobanks need to be aware of the original conditions of consent given by biobank donors, including whether they have been given the option to be notified of incidental findings and if so, did they opt in or out. Other considerations to take into account are the length of time that has passed since the donation was made, and whether the data has been utilised previously by other researchers. Notification of findings long after the donation, or by multiple researchers may be unwelcome to the donor. However, any such decisions about communicating incidental findings derived from secondary biobank data should be guided by the conditions of consent under which the original data was contributed.r which the original data was contributed.)
Biobanking: Ethics Issues + ([[File:Bio2Image14.png|center|frameless|60 … [[File:Bio2Image14.png|center|frameless|600x600px]]'''Ethics review processes for biobanking'''Ethics review processes for biobanking vary across the world. Looking at European countries as an example of the variations, we see that in many countries, independent ethics review bodies, typically RECs, evaluate the ethical acceptability of research projects that intend to use biobank resources. In some countries, RECs also review the establishment of a biobank itself. In other countries, REC approval for biobank research is only necessary in exceptional cases. For example, in the UK, biobanks may obtain general ethics approval to conduct a broad range of biobank research, thereby relieving researchers of the need to seek separate ethics approval. In Finland, REC permission is required to set up a biobank, and the evaluation of biobank research is typically performed by the directors of the biobank, with REC approval necessary only under specific circumstances.It is also worth noting that in some countries, RECs are responsible for additional obligations, such as allowing biobank controllers to identify and contact gene donors to get their written consent for renewing, supplementing or verifying a description of their state of health. They might also be responsible for authorising the transfer of biobanked samples and health-related data to other biobanks established in the same country or abroad.Different ethics governance practices across different biobanks in Europe also reflect different models of oversight recommended at the international level. For instance, the [https://www.oecd.org/health/biotech/guidelines-for-human-biobanks-and-genetic-research-databases.htm OECD guidelines for Human Biobanks and Genetic Research Databases] recommend that RECs should assess biobank research with a specific focus on determining whether the purpose of the planned biobank research study falls within the scope of previously given consent or whether it requires (re)consent. Meanwhile, the [https://www.wma.net/policies-post/wma-declaration-of-taipei-on-ethical-considerations-regarding-health-databases-and-biobanks/ WMA Taipei Declaration] expands the scope of ethical oversight by recommending that RECs should evaluate not only biobank research, but also approve the establishment of a biobank and monitor ongoing biobank activities.nk and monitor ongoing biobank activities.)
Biobanking: Ethics Issues + ([[File:Bio2Image15.png|center|frameless|60 … [[File:Bio2Image15.png|center|frameless|600x600px]]You can try these questions to see whether your learning from this module addresses the intended learning outcomes. No one else will see your answers. No personal data is collected.What is a key distinction between the broad consent and study-specific consent models used for individuals donating biological samples to a biobank? donating biological samples to a biobank?)
Biobanking: Ethics Issues + ([[File:Bio2Image2.png|center|frameless|600 … [[File:Bio2Image2.png|center|frameless|600x600px]]'''Issues relating to consent to donate biomaterials and data to biobanks'''Clear procedures enabling biobank donors to give their informed consent to donate biological materials and health-related information are vital to ensure that they fully understand how their samples and data will be used. Donors should be made aware that biobanks do not routinely provide individual diagnoses, so that they are not falsely reassured when they do not receive results from the analysis of their biospecimens and data. RECs must assess the clarity and comprehensibility of consent forms, addressing any potential risks and benefits.[https://www.wma.net/policies-post/wma-declaration-of-taipei-on-ethical-considerations-regarding-health-databases-and-biobanks/ The WMA’s Declaration of Taipei] sets out the following criteria for informed consent for multiple and indefinite uses of biomaterials stored in a biobank, stating that consent is only valid if the concerned individuals have been adequately informed about: the purpose of the health database or biobank,the risks and burdens associated with collection, storage and use of data and material,the nature of the data or material to be collected,the procedures for return of results including incidental findings,the rules of access to the health database or biobank,how privacy is protected,the governance arrangements of the biobank,That if the data and material are made non-identifiable the individual may not be able to know what is done with their data/material and that they will not have the option of withdrawing their consent,Their fundamental rights and safeguards established in the Declaration,and when applicable, commercial use and benefit sharing, intellectual property issues and the transfer of data or material to other institutions or third countries. to other institutions or third countries.)
Biobanking: Ethics Issues + ([[File:Bio2Image3.png|center|frameless|600 … [[File:Bio2Image3.png|center|frameless|600x600px]]Different models of consent offer distinct advantages and drawbacks in balancing ethical considerations and scientific advancements. We will first look at broad consent, before moving on to look at other models. For this form of consent, participants give permission for their data or biological samples to be used in a range of future research studies, rather than being limited to a single, specific study.Jurate Lekstutiene shares her thoughts on how the broad consent model is used in biobanking. Biobanking would not be possible without support from the society, without consent from biobank participants. However, during the consent process, usually it's impossible to accurately determine which health-related research will be conducted in the future.There are several ways how we could address this uncertainty. And the idea behind the broad consent model is that a person gives consent once, usually in writing, and then based on this consent, a biobank can collect and store samples and data for unlimited time, even after a biobank participants' death. And these samples and data can be used for extensive research involving different diseases.ive research involving different diseases.)
Biobanking: Ethics Issues + ([[File:Bio2Image4.png|center|frameless|600 … [[File:Bio2Image4.png|center|frameless|600x600px]]=== '''Dynamic Consent''' ===Dynamic consent utilises digital technology to enable ongoing communication with donors. It allows donors to tailor their consent preferences over time, providing a mechanism for enhanced donor engagement. While it fosters a more participatory approach to consent, its implementation can be resource-intensive and may pose technical and practical challenges. Practically, the need for continuous engagement puts a greater administrative burden on biobanks. This includes the labour associated with managing donor inquiries, concerns, and requests for consent withdrawal or modification, which can escalate costs and require more personnel. Furthermore, it can create a potential digital divide if some donors lack access to or familiarity with the necessary technology to engage with the consent process, potentially raising issues of equity and inclusivity.=== '''Study Specific Consent''' ===Involves donors providing informed consent for their data and samples being used for a single specific research study. Fresh consent would need to be sought by researchers should they wish to use data or samples in a new study.=== '''Tiered Consent''' ===Involving donors choosing from predefined categories of research by agreeing to the sub-area of medicine for which samples and data can be used in the future. They might, for example, select specific disease groups like cancer or cardiovascular disorders. This model of consent enhances donor autonomy and transparency but may hinder the adaptability of research projects. Additionally, it requires constant updates to accommodate evolving research fields.=== '''Meta Consent''' ===Involving pre-defined consent models for different layers. Based on this model, one person may choose broad consent for all types of health data and their usage contexts. Meanwhile, another person may choose broad consent for nationally funded projects involving genetic data, and specific consent for the use of any data in international and commercial scientific projects. To sum up, meta-consent is not just about granting or prohibiting consent but about applying different consent models to different layers of biobank research.s to different layers of biobank research.)
Biobanking: Ethics Issues + ([[File:Bio2Image5.png|center|frameless|600 … [[File:Bio2Image5.png|center|frameless|600x600px]]Use the links below to access and read the UK Biobank’s information sheet and consent form.[https://www.ukbiobank.ac.uk/media/ei3bagfb/participant_information_leaflet-baseline.pdf Example of a biobank information sheet from the UK Biobank][https://www.ukbiobank.ac.uk/media/t22hbo35/consent-form.pdf Example of a biobank consent form from the UK Biobank]'''Feedback'''Broad consent models are commonly used by biobanks to streamline sample collection for diverse research purposes. These models allow participants to consent to a wide range of potential future studies, facilitating efficient research while maintaining ethical standards. However, ensuring transparency and understanding among participants regarding the scope of research remains paramount for ethical practice.What type of consent model is UK Biobank using in these examples?del is UK Biobank using in these examples?)
Biobanking: Ethics Issues + ([[File:Bio2Image6.png|center|frameless|600 … [[File:Bio2Image6.png|center|frameless|600x600px]]== '''Consent Issues for Children Donating Materials to Biobanks''' ==Consent extends beyond choosing an appropriate model for use, to other nuanced issues that need addressing in the training of researchers. These include involving children in biobanking, allowing for the withdrawal of consent, managing consent upon a donor's death, handling samples used without consent, respecting cultural norms and practices, and public health emergencies.[[File:Bio2Image7.png|center|frameless|300x300px]]'''Consent issues for children donating materials to biobanks'''In most jurisdictions, children cannot provide legally valid consent on their own, particularly for complex matters such as donating biological materials to biobanks. The ability to provide informed consent is typically associated with reaching the age of majority, which varies globally but is often around 18 years old.In situations involving children, the consent process usually involves obtaining permission from parents or legal guardians. These individuals are considered to have the legal authority to make decisions on behalf of the child, taking into account the child's best interests. The process of obtaining parental or guardian consent involves providing comprehensive information about the purpose of the donation, potential risks, and the intended use of the biological materials and health-related data.However, ethical considerations become more nuanced when dealing with older minors who may demonstrate the capacity for informed decision-making. In such cases, the involvement of the minor in the consent process, along with parental or guardian consent, may be considered. The specific regulations and ethical guidelines surrounding the involvement of minors in research may vary by jurisdiction and should be followed carefully to ensure the protection of minors' rights and wellbeing in the context of biobanking activities.g in the context of biobanking activities.)
Biobanking: Ethics Issues + ([[File:Bio2Image8.png|center|frameless|600 … [[File:Bio2Image8.png|center|frameless|600x600px]]'''The right to withdraw consent'''The right to withdraw consent is a fundamental aspect of ethical research. While the motives behind withdrawal can differ greatly, operationalising withdrawal of consent remains complex, particularly if biobank data or samples have already been used in research. The withdrawal of consent should be documented, and samples and data should be destroyed safely or returned to the donor.'''The death of a donor'''The death of a donor can create ambiguity in terms of ongoing consent for the use of their samples. Guidelines differ globally: some suggest that consent should be presumed to continue after death, others advocate for re-consenting by next of kin.'''The use of samples without consent'''The use of samples without consent, often in the case of historical or residual samples, is another complex issue for consent, as well as for data sharing and privacy issues. In this case, decision-making about the use of samples involves balancing donor interests with the potential scientific value of such samples. '''Respecting cultural norms and practices'''Respecting cultural norms and practices, as in any research study, researchers and RECs should bear in mind the need to respect cultural norms when seeking informed consent from an individual. For instance, in some cultures it is expected that the head of a household or community elders would be asked to provide their consent for a member of the family/community participating in a research study or donating biospecimens and health-related data to a biobank.mens and health-related data to a biobank.)
Biobanking: Ethics Issues + ([[File:Bio2Image9.png|center|frameless|600 … [[File:Bio2Image9.png|center|frameless|600x600px]]Personal data processing in biobanks raises ethical issues that need careful consideration to ensure the protection of individuals' rights, privacy, and the responsible conduct of research. During the Ebola outbreak in Sierra Leone, data processing failures contributed to a lack of a complete inventory of the samples collected, and incomplete information about their potential future use, location and ownership. Navigating such issues requires adherence to established guidelines, ongoing ethical review, and engagement with stakeholders to ensure that data processing in biobanks aligns with ethical principles, legal frameworks, and societal expectations. Some key ethics issues connected to data processing in biobanks are described below after a short clarification of relevant terms.The terms anonymous and de-identified are often used interchangeably but do have different meanings. For the purposes of this module, we are using the terms in this way:* Anonymous – The dataset does not contain any identifiable information and there is no way to link the information back to identifiable information. This is an irreversible process.* De-identified – The dataset does not contain any identifiable information, but there is a way to link the information back to identifiable information.'''Data ownership'''Ethical concerns surrounding data ownership in biobanks revolve around defining and respecting the rights of various stakeholders involved. Donors contribute valuable biospecimens and personal data, raising questions about who ultimately owns this information. Generally, donors retain some rights over their samples and associated data, but biobanks also have responsibilities to steward these resources for the public good. Policies will vary from country to country and across different organisations. As an example, UK Biobank states that it is the owner of the intellectual property rights of the data and samples contained in the resource. The biobank grants researchers a limited, revocable, worldwide, royalty-free, non-exclusive licence (but not ownership rights) to use samples for a permitted purpose only. However, the intellectual property rights to the results data deriving from the research for the permitted purpose will under most circumstances belong to the researcher.Striking a balance between the interests of researchers, institutions, and donors is crucial. Clear and transparent consent processes are essential to inform donors about how their data will be used and who will have ownership or control over it.ho will have ownership or control over it.)
Biobanking Case Study + ([[File:Bio3Image1.png|center|frameless|600 … [[File:Bio3Image1.png|center|frameless|600x600px]]'''The proposal - Investigating the progression of COVID-19 in diverse population subgroups in Country X and Country Y'''(a hypothetical case study) '''Collaborating Institutions:'''- XYZ Global Health Institute, Country X- ABC Medical Research Center, Country Y'''Background:'''COVID-19 has affected populations worldwide, but the progression and severity of the disease appear to vary significantly among different population subgroups, based on factors such as genetics, socioeconomic status, environmental exposures, and healthcare access. These variations are particularly pronounced between high-income countries and low- or middle-income countries. Understanding these differences is critical to improving public health responses to COVID-19 and future pandemics.This study aims to investigate the progression of COVID-19 in two diverse countries—Country X (a high-income country in Europe) and Country Y (a low- or middle-income country in Africa)—to identify genetic, environmental, and social factors influencing COVID-19 outcomes. Insights gained will be used to develop predictive models for disease severity and inform public health strategies for more effective pandemic preparedness and response.'''Research objectives:'''1. Comparative COVID-19 progression analysis: Examine how COVID-19 progresses in different subgroups (e.g., age, gender, ethnicity, and socioeconomic background) in Country X and Country Y.2. Genetic and environmental risk factors: Identify genetic markers and environmental exposures (e.g., air pollution, living conditions) that affect COVID-19 severity and outcomes in the two countries.3. Development of predictive models: Create models to predict disease risk and progression, incorporating genetic, demographic, and environmental data.'''Study design:'''The study will be conducted over three years and will involve both prospective and retrospective analysis. It will combine newly collected biosamples and health data with previously donated samples from existing biobanks.1. Participant recruitment: The study will recruit 5,000 participants from each country. Participants will be selected based on age, gender, ethnicity, and socioeconomic status to ensure diverse representation. 2. Data collection: Biosamples (blood, nasal swabs, saliva) and demographic data (medical history, socioeconomic status, environmental exposures) will be collected from each participant. The samples will be processed and stored in a newly established biobank in both Country X and Country Y for long-term research use.3. Secondary data use: The study will also utilise biosamples from pre-existing biobanks in both countries, originally collected for other health-related research purposes. These samples will be integrated into the analysis.4. Data analysis: Researchers will conduct genomic sequencing and environmental exposure analysis to identify factors influencing disease severity. Statistical models will be developed to predict high-risk groups based on the data.'''Expected outcomes:'''1. Identification of key risk factors: The study will provide insights into the genetic, environmental, and social factors that influence COVID-19 severity in different subgroups across Country X and Country Y.2. Predictive tools: The research will result in the development of predictive models to inform healthcare providers and public health officials about populations at higher risk of severe COVID-19 outcomes.3. Improved public health response: The findings will contribute to more targeted interventions, enhancing pandemic preparedness and healthcare access, particularly for vulnerable groups in Country Y.'''Expected contribution:'''This research will provide critical knowledge about the progression of COVID-19 in diverse populations and help inform global and local public health strategies. It will also contribute to a more equitable understanding of pandemic impacts and ensure that all populations benefit from the insights gained.ulations benefit from the insights gained.)