ArticleMedicine, health care, and philosophy2016
Rethinking risk assessment for emerging technology first-in-human trials.
Article in Medicine, health care, and philosophy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Early-Phase Clinical Trials of Bio-Artificial Organ Technology: A Systematic Review of Ethical Issues.Transplant international : official journal of the European Society for Organ Transplantation · 2022Pooled it
- Development of consensus-driven SPIRIT and CONSORT extensions for early phase dose-finding trials: the DEFINE study.BMC medicine · 2023Review
- States of Uncertainty, Risk-Benefit Assessment and Early Clinical Research: A Conceptual Investigation.Science and engineering ethics · 2022Article
- Designing Preclinical Studies in Germline Gene Editing: Scientific and Ethical Aspects.Journal of bioethical inquiry · 2019Article
- Stakeholder views on participant selection for first-in-human trials in cancer nanomedicine.Current oncology (Toronto, Ont.) · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent progress in synthetic biology (SynBio) has enabled the development of novel therapeutic opportunities for the treatment of human disease. In the near future, first-in-human trials (FIH) will be indicated. FIH trials mark a key milestone in the translation of medical SynBio applications into clinical practice. Fostered by uncertainty of possible adverse events for trial participants, a variety of ethical concerns emerge with regards to SynBio FIH trials, including 'risk' minimization. These concerns are associated with any FIH trial, however, due to the novelty of the approach, they become more pronounced for medical applications of emerging technologies (emTech) like SynBio. To minimize potential harm for trial participants, scholars, guidelines, regulations and policy makers alike suggest using 'risk assessment' as evaluation tool for such trials. Conversely, in the context of emTech FIH trials, we believe it to be at least questionable to contextualize uncertainty of potential adverse events as 'risk' and apply traditional risk assessment methods. Hence, this issue needs to be discussed to enable alterations of the evaluation process before the translational phase of SynBio applications begins. In this paper, we will take the opportunity to start the debate and highlight how a misunderstanding of the concept of risk, and the possibilities and limitations of risk assessment, respectively, might impair decision-making by the relevant regulatory authorities and research ethics committees, and discuss possible solutions to tackle the issue.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.