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A framework for investigating signals in pharmaceutical regulatory quality assurance
Get PDFPharmaceutical regulatory assurance is a pillar in the regulatory sciences that leads to t he availability of safe, effective, and quality medicinal products. A structured approach to using signals as an instructive tool of process management in regulatory sciences is an innovative, relatively unexplored concept in the evolution of pharmaceutical regulatory sciences. This research explores a gap in the identification of disruptive signals from sources within the quality management system, categorisation of identified signals, and development of signal minimisation action plans at the heart of the regulatory, scientific field. Strategic lines of inquiry in the regulatory and scientific field can be unfolded. The objective is to formulate a novel investigative framework for identified signals within regulatory sciences quality management systems. The hypothesis is that signal categorisation serves to enhance a quality management system by strengthening the regulation to safeguard the availability of quality, safe and effective medicines. Method: The study employs a retrospective analysis of internal audit reports, quality improvement, and deviation forms within a competent authority in the medicine regulatory department. The analysis focuses on identified signals associated with operational and regulatory aspects within pharmaceutical sciences. A structured framework for categorising signals is devised, drawing upon the principles Pharmacy Education 24(7) 398 - 409 Regulatory sciences and quality outlined in Module IV of the Guideline on Good Pharmacovigilance Practice, focusing on Pharmacovigilance Audits. The assessment tool incorporates definitions for terms such as "critical," "major," "minor," and "others" and thresholds to facilitate the systematic classification of signals. In this context, 'critical' denotes a foundational deficiency within regulatory pharmaceutical procedures or methodologies, leading to adverse impacts on the regulatory framework and/or constituting a severe breach of relevant regulatory standards. 'Major' signifies a notable deficiency within regulatory pharmaceutical procedures or methodologies or a fundamental fault therein that undermines the regulatory process and/or breaches applicable regulatory standards, albeit without reaching a level of severity deemed critical. 'Minor' denotes a deficiency within regulatory pharmaceutical procedures or methodologies that is not anticipated to have adverse effects on the regulatory framework. 'Other' encompasses deficiencies or inadequacies in regulatory pharmaceutical processes or practices that do not fit within the aforementioned terms. These may include less consequential deviations from regulatory requirements or minor issues that do not present substantial risks to the regulatory integrity or compliance criteria. The competent Authority in question is patient-centric, and the relation of signal categorisation to patient safety needs to be elaborated upon. Results: The analysis of the internal documentation revealed that no cases were of a critical and major nature. Predominantly, findings were categorised as minor or other. These findings hold significance in fostering a proactive approach to signal management within the regulatory framework of signals for quality assurance, contingent upon the established classification framework. These findings are anticipated to strengthen regulatory integrity and ensure adherence to established standards. Conclusion: This research has yielded the development of a structured categorisation framework tool inspired by Module IV Pharmacovigilance Audits, as outlined in the Guideline on Good Pharmacovigilance Practice. The interaction between data, communication, and governance offers a systematic approach to organising identified signals and facilitating streamlined processes in signal classification.peer-reviewe
A remedy for heterogeneous data : clustered federated learning with gradient trajectory
Get PDFFederated Learning (FL) has recently attracted a lot of attention due to its ability to train a machine learning model using data from multiple clients without divulging their privacy. However, the training data across clients can be very heterogeneous in terms of quality, amount, occurrences of specific features, etc. In this paper, we demonstrate how the server can observe data heterogeneity by mining gradient trajectories that the clients compute from a two-dimensional mapping of high-dimensional gradients computed by each client from its bottom layer. Based on these ideas, we propose a new Clustered Federated Learning method called CFLGT, which dynamically clusters clients together based on the gradient trajectories. We analyze CFLGT both theoretically and experimentally to show that it overcomes several drawbacks of mainstream Clustered Federated Learning methods and outperforms other baselines.peer-reviewe
Contemporary tools for creating customer value
Get PDFPURPOSE: The purpose of this paper is to explore the integration of Artificial Intelligence (AI)
in marketing and its transformative role in creating customer value. The study focuses on
how AI technologies-such as machine learning, natural language processing, and predictive
analytics-enhance personalization, predict customer behavior, and improve operational
efficiency in business practices. The research also examines the challenges businesses face in
integrating AI into marketing strategies and offers recommendations for maximizing
customer satisfaction and loyalty through AI-driven approaches.DESIGN/METHODOLOGY/APPROACH: The paper is based on a selective literature review
combined with an analytical approach to evaluate the application of AI technologies in
marketing. It reviews key academic sources and industry reports, focusing on case studies
and examples of contemporary AI tools used by businesses to personalize customer
experiences, enhance predictive analytics, and optimize customer support operations. This
method allows for a focused analysis of the most relevant and impactful research and
applications within the field.FINDINGS: The research highlights that AI significantly improves customer value by enabling
businesses to offer highly personalized experiences, predict consumer needs more
accurately, and streamline operations. However, it also identifies key challenges, such as
data privacy concerns and the high cost of technology adoption, which need to be addressed
for effective AI implementation. The findings provide actionable recommendations for
businesses on how to integrate AI technologies strategically to enhance customer
satisfaction, loyalty, and overall value.PRACTICAL IMPLICATIONS: The paper provides practical guidance for businesses seeking to
leverage AI to improve customer engagement and value. It outlines best practices for
incorporating AI into marketing strategies, focusing on investment priorities, data
management practices, and staying updated on technological advancements. The insights
can be valuable for companies aiming to enhance their competitive advantage through AIdriven marketing approaches.ORIGINALITY/VALUE: This research contributes to the growing body of knowledge on AI in
marketing by offering a detailed examination of how AI tools create customer value. The
originality of the study lies in its integrated perspective on the interplay between AI
technologies and customer-centric strategies, making it a useful resource for both academics
and practitioners.peer-reviewe
The effects of a weaning protocol in ITU
Get PDFBACKGROUND: Protocol driven ventilator discontinuation procedures have reduced ventilator days for patients in Intensive Care Unit (ITU) and are associated with better patient prognosis. In order to improve successful extubations, a weaning protocol was created for the Mater Dei Hospital (MDH) ITU using evidence-based criteria.AIM: The purpose of this audit was to assess whether implementation of a mechanical ventilation weaning protocol had an impact on successful extubations as well as improved clinician and nursing knowledge regarding weaning.METHOD: A prospective study was carried out to assess successful extubations before and after implementation of a ventilation weaning protocol. Adult patients who were ventilated for more than 7 days were included in the study. A questionnaire about mechanical ventilation and weaning was distributed to ITU physicians and nurses before and after implementation of the weaning protocol.RESULTS: We could not find any statistically significant differences in weaning success after the introduction of the weaning protocol. Information retention did not improve after usage of the protocol.CONCLUSION: The introduction of an ITU weaning protocol at Mater Dei Hospital did not increase the number of successful extubations. Despite enhanced staff perception of weaning, a mechanical ventilation questionnaire did not improve retention of knowledge.peer-reviewe
Strengthening the health workforce in the use of digital technologies
Get PDFDigital health is the use of information and communications technology in support of health and health-related fields. Technology is
reshaping the healthcare system and as a result the relationship between the patient and the healthcare professional. To address the
needs of digitalisation in healthcare implies the combination of knowing which technologies to use, aligned with skilled professionals
to appropriately use these technologies. As the requirements of the varied health professional roles evolve, recognition of specific
digital competences describing the required understanding, abilities and mindsets for effective professional practice are essential. This
recognition is important to anticipate and equip healthcare professionals for the evolving landscape of healthcare technology, especially
with the introduction of generative AI.peer-reviewe
The “ruined landscapes” of Mediterranean islands : an ecological framework for their restoration in the context of SDG 15 “life on land”
Get PDFThe “ruined landscapes” of the Mediterranean littoral are a consequence of millennia of
human impact and include abandoned agricultural lands, deforested areas, and degraded coastal
areas. One of the drivers is the historical pattern of land use, which has resulted in the clearing of
vegetation, soil erosion, and overgrazing. These have caused significant damage to natural ecosystems
and landscapes leading to soil degradation, loss of biodiversity, and the destruction of habitats.
The UN Sustainable Development Goal 15 “Life on Land” recommends a substantial increase in
afforestation (SDG 15.2). Whilst this goal is certainly necessary in places, it should be implemented
with caution. The general perception that certain ecosystems, such as forests, are inherently more
valuable than grasslands and shrublands contributes to afforestation drives prioritising quick and
visible results. This, however, increases the possibility of misguided afforestation, particularly in
areas that never supported forests under the present climatic conditions. We argue that in areas that
have not supported forest ecosystems, targeted reinforcement of existing populations and recreation
of historical ones is preferable to wholesale ecosystem modification disguised as afforestation. We
present a possible strategy for targeted reinforcement in areas that never supported forests and that
would still achieve the goals of SDGs 15.5 and 15.8.peer-reviewe
Composites based on PLA/PHBV blends with nanocrystalline cellulose NCC : mechanical and thermal investigation
Get PDFThis study investigates the physical and mechanical properties of biodegradable composites based on PLA/PHBV blends modified with different content of nanocrystalline cellulose (NCC) of 5, 10, and 15 wt.%. Density measurements reveal that the density of the composite increases with increasing NCC content. Water absorption tests demonstrate a gradual increase in the composite water content with increasing incubation time, reaching stabilization after approximately 30 days. Mechanical testing was also carried out on both on conditioned samples after the process of hydrolytic degradation and accelerated thermal aging. The conditioned composites show an increase in the stiffness of the materials with increasing content of nanocrystalline cellulose. The ability to deform and the ability to absorb energy when the sample is dynamically loaded decrease. The repeated strength tests, after the process of incubation of samples in water and after the process of accelerated thermal aging, show the degradation of composite materials; however, it is noticed that the introduction of cellulose addition reduces the impact of the applied artificial environment in aging tests. The findings of this study indicate promising applications for these types of materials, characterized by high strength and biodegradability under appropriate conditions. Household items such as various containers or reusable packaging represent potential applications of these composites.peer-reviewe
An AI-based prosthesis framework fostering an adaptive amputee healthcare service
Get PDFDespite technological and medical advances, amputations continue to increase. Amputees face significant
challenges when acquiring and using prosthetic devices, challenges which are made worse as their emotional
needs, aspirations, mobility, prosthesis requirements and problems change over time. These challenges require
custom solutions for each individual amputee, a fact that current amputee centered prosthesis services tend to
ignore. The work reported in this paper contributes an AI based Prosthesis Development Service Framework
to cater for the current and evolving needs of amputees.peer-reviewe
Sustainable development management and strategic awareness of the Metropolis GZM inhabitants
Get PDFPURPOSE: The main objective of the research was to diagnose and analyse the level of
understanding sustainability and strategic awareness, as well as prioritization of United
Nations Sustainable Development Goals (UN SDG) among the Metropolis GZM inhabitants.DESIGN/METHODOLOGY/APPROACH: Taking into account managerial approach the main
research methods which were used in the study were literature review, diagnostic survey
research and basic statistical analysis. The study was conducted on the basis of a survey
questionnaire, using the CAWI method with selected research sample of 3301 respondents -
Metropolis GZM inhabitants. The research results were presented in a comparative
approach, both for the entire representative population of the Metropolis GZM and in crosssectional approaches, which include specifics by gender, age, place of residence or
diagnosed level of life satisfaction.FINDINGS: The concept of "sustainable local development" was practically understood by
Metropolis GZM inhabitants, most important UN SDG were diagnosed. The level of
knowledge of Metropolis GZM inhabitants about their municipal strategy was presented for
the groups of cities (relatively big, medium and small) and for all the cities with country
rights individually. To analyse strategic awareness in Metropolis GZM for cities with county rights or group of cities new strategic awareness indicator (SAI) was proposed both from
methodological indicator construction and it interpretation.PRACTICAL IMPLICATIONS: The results of the research can be used, among others, by local
authorities as a guide for shaping development policies in line with the expectations of the
inhabitants of the Metropolis GZM, both in terms of content relating to the practical
understanding of sustainable development and the UN SDG, as well as in organizational and
promotional terms referring to the level of strategic awareness related to the development
strategy and the process of its creation. The results are also the basis for further in-depth
research, taking into account, among other, comparative possibilities with other domestic
and foreign metropolitan areas and the evolution of the studied phenomena over time.ORIGINALITY/VALUE: One of the first and biggest survey regarding all the Metropolis GZM
related to strategic awareness, UN SDG prioritization and understanding sustainability; new
authors’ Strategic Awareness Indicator (SAI) was proposed, used and interpreted.peer-reviewe
The role of AI in company's image management
Get PDFPURPOSE: The purpose of this article is to explore the impact of artificial intelligence (AI) on
company image management. The research investigates how AI-driven innovations
contribute to improving a company’s reputation, perception by stakeholders, and overall
competitiveness in the market. It aims to identify the specific AI functions that have the most
significant influence on enhancing corporate image and long-term growth.DESIGN/METHODOLOGY/APPROACH: The study utilizes a quantitative research design,
employing a stratified sampling method to gather data from companies across various
sectors that are actively using AI in their operations. Data was collected through an
original questionnaire with 20 determinants, rated on a seven-point Likert scale.
Statistical methods, including descriptive statistics, were used to analyze the impact of AI
on sustainable growth and image management. The snowball sampling method ensured
diversity in the analyzed enterprises.FINDINGS: The results indicate that AI plays a pivotal role in improving a company's image
by enhancing functions such as Monitoring Online Reviews, Detecting Social Trends, and
User Recommendation Analysis. These AI applications are rated highly by respondents in
terms of their contribution to reputation building. However, functions like Price Strategy
Optimization received lower ratings, suggesting areas for further development. Most
variables have a mean score above 4.5, reflecting the positive perception of AI's role in
image management.PRACTICAL IMPLICATIONS: The findings provide practical insights for companies looking to
leverage AI to improve their public perception and stakeholder relations. Businesses can
prioritize AI functions such as online review monitoring and social trend detection to
strengthen their image. Additionally, the study highlights the need for continuous monitoring
and optimization of AI applications to maximize their impact on reputation and
competitiveness.ORIGINALITY/VALUE: This research contributes to the growing body of knowledge on the
intersection of AI and corporate image management. It offers empirical evidence on the
specific AI functions that most significantly influence how companies are perceived by
stakeholders, filling a gap in the literature on AI's role in intangible asset management. The study provides valuable insights for both academics and practitioners interested in the
strategic use of AI for reputation enhancement and long-term business growth.peer-reviewe