MétaCan
Menu
Back to cohort
Record W4415363924 · doi:10.3389/fmed.2025.1705977

Editorial: Reviews in: regulatory science 2024-2025

2025· editorial· en· W4415363924 on OpenAlexaboutno aff
Mette Due Theilade, Lisbeth E. Knudsen

Bibliographic record

VenueFrontiers in Medicine · 2025
Typeeditorial
Languageen
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsChinaRegulatory scienceRegulatory authorityTest (biology)Drug developmentDrug approvalAlternative medicineDrug industry

Abstract

fetched live from OpenAlex

The "Reviews in Regulatory Science" call presents a number of publications from 2024 and 2025, covering among other examples of regulatory approaches to GDPR and approaches to new technologies in pharmaceutical development. Oku and Someya (2025), both authors from the Japanese Pharmaceuticals and Medical Devices Agencies (PMDA), analyse the trends of GLP-compliant non-clinical studies submitted to PMDA from 2017 to 2023. USA/Canada contribute with most GLP studies submitted to PMDA, followed by Japan, Europe, and the United Kingdom. The number of GLP studies from China and Taiwan has been on the rise over the last 3 years, reflecting increased development in China of new drugs, particularly in the oncology field. China is not a part of the OECD Mutual Acceptance of Data (MAD) framework, where nonclinical safety studies conducted in test facilities successfully inspected by a competent GLP-compliance monitoring authority in one OECD country become accepted by other OECD countries. The PMDA accepts data from test facilities in non-MAD countries only if the product-based inspection of the studies conducted by the PMDA is successful. The authors found that a decrease in the percentage of studies conducted in Japan, suggesting reduced drug development activities in Japan. They also found a considerable time lag for many of the studies, which were submitted to the PMDA later than to the US or EU, and this is considered a serious issue for patients with life-threatening diseases in Japan. Christofidou et al (2025) provides an important contribution to the discussion on the practical application of informed consent when adhering to European legislation. The review investigates the gaps that the European General Data Protection Regulation (GDPR) has left regarding interpretation and practical application of consent towards the secondary use of health data and furthermore discusses potential solutions. The requirements for "informed consent" defined within the GDPR are not well defined in the context of e.g. genome research. The review proposes that the Data Governance Act ("DGA") through the concept of "data altruism" can be used as a cohesive solution to this. A systematic review by Chen et al (2025) utilised bibliometric and visualisation analyses of the core collection of Web of Science databases to evaluate the status and trends in the field of illicit drugs on the global level. The review includes a total of 5,797 publications between 2015 and 2024. Literature on substance abuse research mainly focused on addiction mechanisms, mental health impacts, and intervention strategies. Of interest is a rise in clinical applications of non-pharmacological approaches such as Mindfulness-Based Interventions and cognitive behavioural therapy. Although the United States has made substantial contributions to the field of illicit drug research, they do not play a significant role in global research cooperation. With a low level of international cooperation, research remains domestically oriented, which may impede the global impact and innovative capacity of research conducted. Data sharing, technological exchange, and collaborative actions among nations are instrumental in the establishment of a more efficient and coordinated global drug governance system, better equipping the international community to address the threats posed by drugs to public health and social security. Agyralides G (2024) discusses the impact of innovative technologies on the ecosystem of pharmaceutical development. Technology rapidly evolves, and it is dominated by artificial Intelligence including Machine Learning and the use of Big Data and Real-World Data (RWD) to produce Real-World Evidence (RWE). Nanotechnology is an inter-science field that gives new opportunities for the manufacturing of devices and products that have dimensions of a billionth of a meter. Artificial Neural Networks and Deep Learning are mimicking the use of the human brain, combining computer science with new theoretical foundations for complex systems. The author also discusses technologies like personalized medicines, gene therapy and CRISPR. The rapid development in new technologies contributes to significantly speeding up the process and reducing the costs for development of new medicines, and offers more options for better, safer, and more effective treatments, with a more solid, data-driven and evidence-concrete approach to be brought to the patient. However, focus should be maintained on a safe and ethical data-sharing culture. Nanotechnology is also the focus of the review by Rodríguez-Gómez et al (2025). The integration of nanotechnology into healthcare has introduced Nanotechnology-Enabled Health Products (NHPs) with promise of revolutionary advancements in medical treatments and diagnostics. NHPs show potential in four principal areas: nano-diagnosis, controlled drug delivery, treatment, and regenerative medicine. Despite their potential, the regulatory navigation for these products remains complex. Rodríguez-Gómez et al (2025) provides an excellent overview of the regulatory landscape for NHPs in the European Union and the United States, identifying applicable requirements and the main regulatory guidelines currently available for meeting regulatory expectations. The regulation of health technologies consistently lags behind rapid advancements in research and development, and the delay in establishing specific regulatory guidelines for NHPs is pronounced. The evolving regulatory landscape for NHPs across the EU and the US—and increasingly in emerging markets such as China and Japan—continues to face persistent hurdles. These include the absence of harmonized definitions, complex physicochemical characterization requirements, and intricacies in evaluating nanotoxicity. Altogether, efforts to modernise regulatory frameworks and encourage standardized testing, coupled with the emergence of AI-driven methodologies and the shift toward greener nanomanufacturing, signal a promising future for nanomedicine, however further collaboration across scientific, governmental, and industrial spheres is essential to fully harness these opportunities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.041
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.053
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0070.003
Science and technology studies0.0030.004
Scholarly communication0.0120.008
Open science0.0070.003
Research integrity0.0290.020
Insufficient payload (model declined to judge)0.0410.044

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.364
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in MedicineSame topicScience, Research, and MedicineFrench-language works237,207