Scientific Research Ethics

Given the sordid history of injustices linking genetics to race and ethnicity, considerations of justice are central to ensuring the responsible development of precision medicine programmes around the world. While considerations of justice may be in tension with other areas of concern, such as scientific value or privacy, there are also be tensions between different aspects of justice. This paper focuses on three particular aspects of justice relevant to this context: social justice, distributive justice and human rights. The implications of (...) each for the use of race and ethnicity in precision medicine is described, along with how they intersect and potentially conflict with one another. By attending to these intersections, we aim to enrich and add nuance to debates over how best to proceed with precision medicine initiatives. (shrink)

The future of health research will be characterised by three continuing trends: rising demand for health data; increasing impracticability of obtaining specific consent for secondary research; and decreasing capacity to effectively anonymise data. In this context, governments, clinicians and the research community must demonstrate that they can be responsible stewards of health data. IRBs and RECs sit at heart of this process because in many jurisdictions they have the capacity to grant consent waivers when research is judged to be of (...) particular value. However, several different terms are used to refer to this value, indicating a lack of conceptual clarity regarding the appropriate test for access to health data for research without consent. In this paper we do three things. First we describe the current confusion and instability in terminology relating to public interest in the context of consent waivers. Second we argue for harmonisation of terminology on the grounds of clarity, transparency and consistency. Third we argue that the term ‘public interest’ best reflects the normative work required to justify consent waivers because it is the broadest of the competing terms. ‘Public interest’ contains within its scope positive and negative implications of a study, as well as welfare, justice and rights considerations. In making this argument, we explain the normative basis for consent waivers, and provide a starting place for further discussion about the precise conditions in which a given study can be said to advance the public interest. Ipsos MORI study found that: … the public would be broadly happy with administrative data linking for research projects provided Those projects have social value, broadly defined. Data are de-identified. Data are kept secure. Businesses are not able to access the data for profit. (shrink)

The numerous researches devoted to 'jaundice' during the Second World War have brought to light the existence of an infectious type of hepatic jaundice or 'homologous serum jaundice' following parenteral injection of vaccines containing human serum and blood transfusions, which were carried out on a large scale at the time. This type of serum jaundice was then gradually differentiated from 'catarrhal', contagious or epidemic jaundice by clinical trials along with large series of animal studies. Finally, the epidemiological, clinical and biological (...) data obtained made it possible to establish, between 1944 and 1954, the viral etiology of these two types of jaundice: the A virus, present in the patients' blood and stools, was considered to be the agent responsible for epidemic hepatitis; the B virus, present primarily in the blood, was held to be responsible for serum hepatitis. (shrink)

Of central concern to the philosophy of medicine is an understanding of the relationship that arises between science and ethics when decisions involve human beings. To examine this relationship, we must consider the status of claims to medical knowledge and whether there exists within medical practice a style of collecting and analyzing data and mak- ing therapeutic decisions that is properly called science. Since ideally, in medicine, knowledge guides practice, to a significant extent our factual claims will legislate our behavior (...) toward our fellowman. Clearly, other considerations compete with science for influence over medical deci- sions—for example, law, custom, patient preferences, convenience. However, without a "science of clinical medicine" and without a clear understanding of how we distinguish between valid and invalid factual claims, medical opinion loses much of its moral force. (shrink)

This document is an up-to-date map on curricula in which research integrity (RI) or research ethics (RE) is currently included. It contains a collection of curricula in which RI/RE or associated fields are mentioned from the Path2Integrity partner countries Bulgaria, Denmark, Germany, Poland and Spain. Moving forward, the Path2Integrity training programme for educators will develop research integrity courses for trainers using this map as a reference. In this way, the project aims to support educators in closing possible gaps. At a (...) broader level, Path2Integrity is involved in discourse with various stakeholders to establish a board of educational policymakers and stakeholders comprised of members from at least eight different countries to foster RI and parts of RI in European curricula. (shrink)

We live in an age alleged devoted to evidence-based medicine. Evidence-based medicine, however, depends on reliable data and if the data are largely, if not completely, manipulated by the manufacturer of pharmaceuticals, then the data are not reliable. Evidence-based medicine is an illusion. -/- This book raises and attempts to answer the following questions: What are the ways in which the profit motive of industry undermines the integrity of science? How is science protected from corporate malfeasance in a capitalist economy? (...) Our particular focus is the relationship between the pharmaceutical industry and medicine. We argue that medicine desperately needs to re-evaluate its relationship with the pharmaceutical industry and re-affirm the ideal of evidence-based medicine. In our view, Karl Popper’s philosophy of science, Falsificationism and Critical Rationalism, provides a rigorous conception of science required to preserve the integrity of the scientific basis of medicine against the commercial influences. (shrink)

Conducting research on animals is supposed to be valuable because it provides information on how human mechanisms work. But for the use of animal models to be ethically justified, it must be epistemically justified. The inference from an observation about an animal model to a conclusion about humans must be warranted for the use of animals to be moral. When researchers infer from animals to humans, it’s an extrapolation. Often non-human primates are used as animal models in laboratory behavioral research. (...) The target populations are humans and other non-human primates. I argue that the epistemology of extrapolation renders the use of non-human primates in laboratory behavioral research unreliable. If the model is relevantly similar to the target, then the experimental conditions introduce confounding variables. If the model is not relevantly similar to the target, then the observations of the model cannot be extrapolated to the target. Since using non-human primates in as animal models in laboratory behavioral research is not epistemically justified, using them as animal models in laboratory behavioral research is not ethically justified. (shrink)

As we look beyond our terrestrial boundary to a multi-planetary future for humankind, it becomes paramount to anticipate the challenges of various human factors on the most likely scenario for this future: permanent human settlement of Mars. Even if technical hurdles are circumvented to provide adequate resources for basic physiological and psychological needs, Homo sapiens will not survive on an alien planet if a dysfunctional psyche prohibits the utilization of these resources. No matter how far we soar into the stars, (...) our psychologies for future generations will be forever tethered to the totality of our surroundings. By shaping our environment toward survival and welfare during the voyage to Mars and in a Martian colony, we indirectly shape our psyches and prepare them for a mission of unprecedented alienation and duration. Once on Mars, human factors such as leadership structure, social organization and code of conduct, group size, gender balance, developmental cycle, mobility, length of stay and the ecological settings and type and manner of subsistence, will create a novel Martian culture. The degree that settlers are severed from the Earth will affect how radically foreign this culture will be when compared with cultures on Earth. (shrink)

Ethical decision-making frameworks assist in identifying the issues at stake in a particular setting and thinking through, in a methodical manner, the ethical issues that require consideration as well as the values that need to be considered and promoted. Decisions made about the use, sharing, and re-use of big data are complex and laden with values. This paper sets out an Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, Health and (...) Policy-relevant Ethics in Singapore Initiative. It presents the aim and rationale for this framework supported by the underlying ethical concerns that relate to all health and research contexts. It also describes a set of substantive and procedural values that can be weighed up in addressing these concerns, and a step-by-step process for identifying, considering, and resolving the ethical issues arising from big data uses in health and research. This Framework is subsequently applied in the papers published in this Special Issue. These papers each address one of six domains where big data is currently employed: openness in big data and data repositories, precision medicine and big data, real-world data to generate evidence about healthcare interventions, AI-assisted decision-making in healthcare, public-private partnerships in healthcare and research, and cross-sectoral big data. (shrink)

Survival of the fittest in evolutionary biology has a counterpart in the evolution of research paradigms. It’s called survival of the funded, and there is a sense in which paradigms are even more adaptable than species. Whereas species may become extinct if their fitness declines below a critical threshold, paradigms can rise again, perhaps with a new name, following fiscal collapse, provided only that funding is once again made available.A current example is the born-again concept of comparative effectiveness research , (...) which achieved resurrection status with the passage of the Affordable Care Act of 2010. The ACA established a private, nonprofit entity to oversee publicly financed CER. According to .. (shrink)

A cluster randomized controlled trial is a research design in which organizational, social, or geographically defined units, rather than individuals, are randomized between or among comparator interventions. Interventions are often targeted at caregivers rather than those receiving care. Applying the definition of a “research subject” found in the U.S. federal regulations governing human subjects research may yield counterintuitive results. We explicate the identification of research subjects by evaluating different types of cluster trials and provide examples to illustrate the relevant concepts. (...) We also present the results of an empirical study of a representative cohort of reports of cluster trials performed in the United States, which confirm that investigators often do not correctly identify the subjects of their research. (shrink)

A single-blind run-in phase is often employed in randomized controlled trials. During these types of trials, all participants are given a placebo but are not informed of this fact. In many trials, participants who are judged to be “placebo responders” or who don’t follow instructions for taking the drug are excluded from further participation at the conclusion of this phase. Because participants are not informed of these procedures, this represents the use of deception in research.

Experimental randomization is defended as a procedure to select an allocation of treatments in comparative experiments. To be convincing, a comparative experiment should allow many alternative allocations of treatments over experimental units, that look equally informative "on paper," but may have underlying differences. Randomization prevents these underlying differences to be causally influential when an allocation is chosen for implementation. Randomization helps prevent bias. ;Both Bayesian criticisms of randomization and what seems to be the opinion of the early Fisher are rejected. (...) The Bayesian decision theoretic argument against randomization is shown to rest on a faulty analysis of experimental randomization that goes back, at least, to Abraham Wald. An improved decision theoretic framework is formulated in which randomization can indeed give higher expected utility. Against the early Fisher it is argued that the choice of a randomization scheme depends on the identification of equally informative, alternative allocations. Randomization alone can never validate a statistical analysis because what allocation is actually implemented, is relevant information that has to be taken into account in the statistical analysis. This does not, however, turn randomization into a useless ritual. The manner in which an allocation is obtained is equally relevant information. (shrink)

In the era of “big data,” science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of (...) particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use. -/- After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now used by over one hundred ontology projects around the world, and offers examples of domain ontologies that utilize BFO. The book also describes Web Ontology Language (OWL), a common framework for Semantic Web technologies. Throughout, the book provides concrete recommendations for the design and construction of domain ontologies. (shrink)

Science cannot be based on dogma or authority of any kind, nor on any intuition or revelation, unless indeed it be of the Book of Nature that lies open before our eyes. We need not dwell on the processes of acquiring knowledge by observation, experiment, and inductive and deductive reasoning. The study of scientific method both in theory and practice is of great importance. It is inherent in the philosophy that the record may be imperfect and the conceptions erroneous; the (...) potential fallibility of our science is not only acknowledged but also insisted upon.—R. Robinson [i]. (shrink)

This article has provided a critical review of sampling procedures in the context of Sierra Leone. The basics of the two major types of sampling procedures (probability and non-probability) have been explained, with a view of shedding light on their usage to assist researchers in their pursuance of addressing proposed hypothetical statements. Problems associated with low literacy rate in Sierra Leone have been highlighted as a major concern, more so in the process of ensuring ethical code of conducts are adhered (...) to during the execution of sampling research. Research practices in the country needs a complete overhaul, particularly with its very low investment in ‘Higher Education Institutions (HEIs)’ to help support the backbone of research, and backed by investment in technology to assist with the enhancement of exploring sampling data in pursuit of addressing hypothetical postulates / research questions during research. (shrink)