Digital Transformation Dissertations

Permanent URI for this collection

https://hdl.handle.net/20.500.14136/124

Browse

Now showing 1 - 16 of 16

A Data-Driven Approach to mRNA Vaccine Acceptance in Ireland: Leveraging Big Data for Public Health Strategy
(2025-05) Shaji, Nicymol
In this study, it was revealed that uptake of mRNA vaccines in Ireland is shaped by a complex interplay of demographic, social, and informational determinants. In the context of the COVID19 pandemic, a data-driven approach was employed to establish the determinants of vaccine uptake, to inform public health policy. A cross-sectional quantitative survey was conducted among students, parents, healthcare workers, and the general population. Information was captured on the history of vaccination among respondents, willingness to receive future mRNA vaccines, familiarity with vaccine technology, perceived adverse effects, and trust in various sources of information. The results showed that overall mRNA vaccine acceptance was high but with persistent hesitancy among some subgroups due to safety concerns, apprehensions over long-term adverse effects, and a lack of understanding about how mRNA works. Participants who relied on health professionals and official health bodies as primary sources of information had the highest levels of acceptance. On the other hand, participants exposed primarily to vaccine-related information on social media or through word of mouth were more likely to be sceptical or hesitant. Misinformation, especially on social media, emerged as a significant stimulant for scepticism and confusion. The findings underscore the need for clear, open, and accessible public health communication in supporting vaccine confidence. The health institution and professional trust greatly boosted willingness to get mRNA vaccines, and hence the value of bringing in trusted individuals as part of future outreach efforts. Targeted communication that addresses directly held concerns, particularly in high-hesitancy populations such as those in rural or underserved settings, is essential. Equipping healthcare professionals with tools and training to address misinformation and encourage informed decision-making is advised by the research. While the study provided valuable quantitative findings, additional research employing qualitative or longitudinal study designs is suggested to determine shifting public opinion and underlying psychological reasons for vaccine hesitancy. The findings provide pragmatic recommendations for designing effective communication programs and enhancing public trust in vaccine programs in Ireland and other regions
Application of Artificial Intelligence (AI) in Optimising Patient Recruitment in Clinical Trial Enrolment Processes
(2025-05) Kandimalla, Rajitha
In this study, an evaluation of AI technologies in clinical trial recruitment was conducted through a quantitative survey of 120 professionals including Clinical Research Associate, Clinical Trial Coordinator, Clinical Research Physician, Clinical Data Manager, Digital Technology Specialist, Clinical Research Manager, AI Implementation Specialists and Clinical Operations Director. The research examined AI's impact on recruitment efficiency, participant diversity enhancement, implementation challenges, and operational outcomes. Findings revealed substantial AI adoption (71.7%) with significant efficiency benefits, as 65.9% of respondents agreed AI reduces recruitment time, with 46.6% reporting time savings exceeding 50%. AI demonstrated particular effectiveness in participant screening (32.5%) and database management (29.2%). Regarding diversity enhancement, perceptions were mixed (42.5% reporting positive impacts), with language barriers (25.0%) identified as the most addressable diversity challenge. Data privacy emerged as the predominant implementation concern (79.2%), alongside balanced challenges in skilled personnel availability, tool complexity, and resistance to change. Operationally, AI showed promise in patient monitoring (72.5% reporting improvements) and overall efficiency (35.0%). Statistical analysis revealed significant differences between AI users and non-users across multiple dimensions, suggesting implementation experience substantially enhances perceived benefits. The research indicates AI offers meaningful advantages for clinical trial recruitment, though successful implementation requires addressing interconnected technical, organizational, and human factors through comprehensive, phased implementation strategies.
Assessing Perception and Adoption of Robotics Among Healthcare Professionals in Kerala : A Quantitative Study on Acceptance of Robotics Within Healthcare Sector.
(2024) Mathew, Christeena
Robotics, initially developed for automation and precision tasks across various industries, have now established a vital role in healthcare by alleviating burdens for both patients and medical professionals. This study primarily seeks to investigate how healthcare professionals in Kerala perceive robotics and to assess the extent of their adoption of these technologies. It aims to understand the acceptance of robotics in the healthcare sector, providing insights into potential barriers and facilitators for integrating robotics into medical practice in Kerala. Utilizing the Technology Acceptance Model (TAM) and employing structured surveys and statistical analysis, the study delivers robust insights into the current state of robotics integration in healthcare by assessing the perceptions of professionals employed in hospitals, clinics, and other healthcare facilities across Kerala. Surveying 70 healthcare professionals, the research unveils significant enthusiasm, particularly among younger professionals aged 24-34. Overall, 67% of the respondents recognize the benefits of robotics in automating routine tasks, enhancing surgical precision, and improving operational efficiency through error reduction. The study highlights key challenges: 49% of respondents report a lack of comprehensive training as a major barrier to training, while 38% cite financial constraints as major challenge to broader adoption. Despite these challenges, 53% of professionals express strong support for integrating robotics, showcasing their readiness to leverage technology for enhanced patient care and surgical outcomes.Additionally, the study identifies a positive relationship between increased awareness of robotics and greater comfort in using this technology, suggesting that enhancing knowledge could significantly improve comfort levels and adoption rates among healthcare professionals. These findings underscore a generational shift towards embracing advanced technologies and emphasize the need for targeted training programs and strategic policy development to facilitate the adoption of robotics, aiming to make healthcare services in Kerala more precise, efficient, and cost-effective.
Bioprinting Solutions for Diabetic Kidney Failure: The Future of Tissue-Engineered Organs
(2025-05) Amin, Reema
In this study I determined the feasibility of 3D bioprinting for diabetic kidney failure management, discussing its suitability, economic pros and cons, and practical barriers when moving to a clinical setting with bioprinted kidneys. Insights were generated using a dual method of analysis, which involved a systematic review of literature and direct surveys with diabetic patients, their family members, and medical professionals. The primary objective was to determine whether 3D bioprinting is a viable and acceptable alternative for kidney transplants, primarily to address the scarcity of available organs and to control diabetes associated with kidney complications. Though the participants’ awareness of the bioprinting technology was low, the study identified potential for bioprinted kidneys when these were proven safe and effective. The rate of kidney-related hospitalizationsin survey participants was associated with increased willingness to consider bioprinting for kidney replacement. Analysis of the research and data showed that there are number of significant barriers to widespread implementation averaging safety concerns, excessive cost, unclear regulations and insufficient clinical preparation. However, the entry of superior biomaterials, stem cell-derived organoids, and cost-effective printing technologies is evidence that the technology is advancing fast to practicality. The research shows that bioprinted kidneys are not yet a clinical possibility for kidney replacement but the preparation for the incorporation of bioprinted kidneys in medical practice is developing rapidly. Patients who were afflicted by kidney failure expressed the greatest enthusiasm for this technology, showing the need for personal as well as cost-effective treatments. In creating a readily accessible knowledge data bank, this dissertation advances the scholarly and clinical arguments about kidney bioprinting programs. To promote the incorporation of bioprinted kidneys into day-to-day healthcare, the study recommends increased public education, the development of ethical frameworks, and policy provisions in unethical provision
Digital Transformation in the Pharmaceutical Sector: A Consumer-Centric Approach to Accessibility, Affordability, and Transparency
(2025-05) Simon, Rini
This study explores how older adults use digital health technologies designed to improve medication affordability and accessibility, with a particular focus on multicultural and resource-poor settings. In a trial involving 86 persons aged 60 years and above+, important results were found related to determinants influencing the adoption and effective use of these tools. Older people expressed interest in using digital technologies to support their medication; however, uptake was conditioned by a range of interconnected factors. Digital literacy, clarity of information, and ease of navigation were widely cited as impacting confidence and comfort with digital usage. Language accessibility and cultural familiarity also shaped general satisfaction, with participants reacting positively to technologies that offered clear visuals, simple-to-follow instructions, and logical layouts. The survey was carried out in English, Irish, and Malayalam, so as to be inclusive across language groups and gain a broader understanding of the difficulties and likes within this heterogeneous sample. Hybrid models that blended digital technologies with face-to-face healthcare support—like pharmacist, caregiver, or community support—were particularly valued. Such frameworks provided reassurance, reduced confusion, and enabled ongoing interaction, particularly in those who had less confidence in the use of technology. The integration of human support appeared to increase trust and have a positive impact on medication adherence. The results point to the promise of digital health technologies in lowering medication access and affordability barriers, if designed with accessibility and inclusivity in mind. Incorporating features like intuitive interfaces, culturally tailored design elements, and multilingual capabilities can facilitate usability and promote wider uptake among older adults. To fully realise the potential of such tools, it is important to promote cooperation among healthcare providers, technology creators, and policy makers. Developing solutions that are not just functional but also attuned to the specific needs of ageing populations, particularly those residing in diverse and underserved populations, can facilitate greater equity in access to health services. Enablement programmes that focus on elevating digital literacy and promoting community outreach can also help augment uptake and ensure older adults are able to manage medications effectively in an ever-digitising world.
Ensuring Product Quality in Irish Biologic and Biopharmaceutical Logistics through IoT-enabled Cold Chain Monitoring
(2024-05) Manikantan Nair, Nisha
The fourth industrial revolution along with the advancement in digital technologies have revolutionized the realm of biologics and biopharmaceutical logistics. This dissertation embarks on a journey to explore the integration of Internet of things (IoT) enabled technologies in cold chain monitoring within the Irish biologic and biopharmaceutical logistics sector. The study focuses on ensuring the quality and safety of temperature-sensitive biologics and biopharmaceutical products like gene therapies, monoclonal antibodies, vaccines, diagnostic kits and reagents during storage and transportation till it reaches the end customer. The study is relevant especially for a country like Ireland renowned for being one of the leading global hubs in biopharmaceuticals, medical device technology and digital health technology. The biologic and biopharmaceutical logistics industry of Ireland rely heavily on efficient and reliable cold chain monitoring to ensure the quality, safety, and efficacy of temperature sensitive medications, vaccines, and biologics. The ever-increasing demand for vaccines, gene therapies, monoclonal antibodies, and biomedical products like diagnostic reagents and medical laboratory supplies post COVID-19 pandemic has made it important to maintain the optimal storage conditions throughout their transit within the supply chain. Industry 4.0 technologies like the Internet of things (IoT) can be a game changer in the cold chain logistics through its capabilities in offering real-time monitoring of temperature and other environmental factors like humidity, pressure, etc. Through time-monitoring, anomalies in temperature and other environmental factors can be detected immediately and immediate measures can be taken to prevent any adversities, thus ensuring the safety and efficacy of the product. This research further aims to emphasise the understanding of available IoT technologies having the potential to transform the biologic and biopharmaceutical cold chain, thus enhancing product quality and ensuring patient safety.
Evaluating the impact of Digital Health Tools on Patient Outcomes and Healthcare delivery in Ireland
(2025-05) Jijoy, Jeny Annie
The digital transformation of healthcare is fundamentally reshaping the delivery and experience of medical services worldwide, and Ireland is no exception. Over the past decade, the integration of digital health technologies-such as electronic health records (EHRs), telemedicine, mobile health applications, wearable devices, and artificial intelligence (AI)-has gained significant momentum within the Irish healthcare system. This thesis critically evaluates the impact of these digital health tools on patient outcomes and healthcare delivery in Ireland, within the context of national policy initiatives like the “Digital for Care” framework. This thesis investigates the impact of digital health tools on patient outcomes and healthcare delivery efficiency in Ireland, with a particular focus on personalized medication management in home care and nursing home settings. Adopting a quantitative, cross-sectional research design, the study surveyed 102 healthcare professionals, including home care nurses, care assistants, and nursing home staff-using a structured online questionnaire comprising 18 questions (16 closed-ended and 2 open-ended). The survey explored usage patterns, perceived effectiveness, and the barriers and facilitators influencing the adoption of digital health technologies such as wearable devices, electronic prescribing, and remote patient monitoring. Descriptive statistical analysis revealed that digital health tools are widely utilized among respondents, with electronic prescribing and remote patient monitoring being the most frequently adopted technologies. Respondents reported significant improvements in medication adherence and patient monitoring, with 78% indicating enhanced accuracy in medication management and 65% noting improved patient outcomes. However, barriers such as digital literacy gaps, concerns about data privacy, and integration challenges with existing systems were frequently cited. Inferential analysis, including chi-square testing, identified statistically significant associations between professional role and perceived effectiveness of digital tools (p < 0.05), as well as between years of experience and likelihood of technology adoption. Thematic analysis of open-ended responses underscored the need for targeted training, improved interoperability, and robust data protection measures to facilitate broader adoption. Overall, the findings demonstrate that digital health tools have a positive impact on patient outcomes and operational efficiency in Irish care settings, but addressing implementation barriers is crucial for maximizing their potential. The study provides evidence-based recommendations for policymakers and healthcare leaders to support the sustainable integration of digital innovations in Ireland’s healthcare system.
Evaluating the Impact of Electronic Prescription Services on Workflow Efficiencies in Community Pharmacies of Dublin, Ireland.
(2024) Vattamkandathil Tomy, Ardra
The integration of Electronic Prescription Services (EPS) represents a significant advancement in the healthcare sector, designed to enhance the accuracy and efficiency of prescription management. By enabling the electronic transmission of prescriptions from healthcare providers to pharmacies, EPS aims to reduce the errors associated with traditional paper-based prescriptions and streamline pharmacy operations. Despite its potential benefits, the implementation of EPS presents various challenges, including technical integration and the need for comprehensive staff training. This research investigates the impact of Electronic Prescription Services (EPS) on community pharmacies in Dublin, Ireland, examining areas such as prescription accuracy, workflow efficiency, pharmacist satisfaction, and implementation challenges. EPS, an advancement in healthcare, facilitates the electronic transmission of prescriptions from healthcare providers to pharmacies, aiming to enhance patient safety, streamline operations, and reduce errors compared to traditional paper prescriptions. Despite EPS’s potential benefits, including improved prescription accuracy and operational efficiency, community pharmacies face challenges such as technical integration issues and the need for effective staff training. This study employs a quantitative methodology, using surveys distributed to pharmacists and pharmacy staff, to evaluate these impacts comprehensively. Adopting a pragmatic research philosophy and an inductive approach, the study collects and analyzes primary data to understand the operational changes brought about by EPS. Data analysis, performed using JASP software, involved descriptive and inferential statistical techniques, including Chi-square and Kendall’s Tau tests, to assess relationships between EPS implementation and various performance metrics. The findings reveal significant associations: improved communication with prescribers correlates moderately with reduced prescription errors, and overall pharmacist satisfaction is strongly associated with the ease of EPS use and improvements in medication inventory management. Workflow efficiency showed notable improvements in prescription processing time, daily volume, patient waiting time, and counselling ability, though increased processing time was linked to reduced efficiency. Confidence in EPS is high, particularly regarding its role in identifying potential medication interactions. The study concludes that EPS positively impacts several facets of pharmacy operations, enhancing prescription accuracy, workflow efficiency, and pharmacist satisfaction, while increasing confidence in the system. Nonetheless, further attention is needed to address training and technical challenges associated with EPS implementation.
Implementing Virtual Wards: A Case Study on Doccla’s Acute Hospital Care Transformation
(2025-05) Mullaney, John
This research study demonstrated that successful implementation of virtual wards in Ireland requires addressing a combination of factors. These factors span across technical, organisational, individual and process related considerations. Virtual wards were designed to deliver hospital level care to suitable patients in the comfort of their own homes, enabled through remote monitoring and digital technologies. It explored how virtual wards could be introduced effectively into the Irish healthcare system, including what lessons could be drawn from existing models of delivery elsewhere. This was enabled through a comprehensive literature review. Doccla was chosen as the focus of the case study, as they are the current supplier of the virtual ward service being piloted in Ireland. The research employed a qualitative case study methodology, situated within an interpretivist paradigm. Data collection involved semi-structured interviews with five strategically selected healthcare professionals, representing diverse clinical and technical roles. Two participants had direct experience with virtual wards, while three offered perspectives from adjacent areas. Purposive sampling ensured participants possessed relevant expertise and insight. To identify patterns and relationships across responses, data was systematically analysed using Braun and Clarke’s six-phase thematic analysis framework. Eight key themes were identified, Patient Experience and Access, Resource Allocation, Staffing and Training, Technology and Infrastructure, Communication and Engagement, Clinical Governance, Integration of Care, and Implementation Strategy. Participants highlighted benefits such as high patient satisfaction, earlier discharge, and reduced hospital pressure. However, they also identified key challenges, including digital literacy gaps, poor internet connectivity, limited staff capacity, and the need for clear governance procedures and training for both staff and patients. Based on these findings, seven recommendations were developed to support healthcare providers and decision makers, in planning and delivering a successful virtual ward implementation in Ireland. The research offered practical guidance for expanding digital models of care, with the aim of improving system capacity while maintaining patient safety and quality of care.
Leveraging AI And Genomics In Drug Discovery And Identification In India
(2025-05) Krishna, Abhirami
Drug development and personalized treatment are changing as a result of the combination of genomics and artificial intelligence (AI), which holds promise for resolving India's complicated healthcare system. Given that more than 60% of deaths in India are caused by chronic diseases including diabetes, cancer, and cardiovascular ailments, the country urgently needs accurate and affordable medical treatments. This study investigates how AI may be used to drive population-specific drug development and targeted therapy by leveraging India's enormous genetic diversity, as demonstrated by programs like the IndiGen program. Important phases of the drug development pipeline are being accelerated by AI technologies, such as generative models, deep learning, and machine learning. These include of lead optimization, virtual screening, target discovery, and drug toxicity and efficacy prediction. In order to find new biomarkers, disease pathways, and drug resistance mechanisms, AI also makes it easier to analyze complicated genomic, transcriptomic, and proteomic information. Therefore, by providing individualized treatment based on a person's genetic composition, AI facilitates the shift from generic to precision medicine. Even with the quick developments, AI is still not widely used in the biotech and pharmaceutical industries in India. Widespread optimism over AI's revolutionary potential was emphasized by a national survey of 207 stakeholders, but it also identified obstacles such a lack of technical competence, fragmented data ecosystems, high implementation costs, and inadequate infrastructure. Concerns over ethical justice, data privacy, and the opaque "black-box" character of many AI models were also mentioned by respondents as issues that impede clinical trust and regulatory acceptance. The study highlights the necessity of making strategic investments in infrastructure, education, and interdisciplinary cooperation in order to fully reap the benefits of AI-driven genomics. To guarantee fair access and responsible innovation, it also urges the implementation of flexible legal frameworks, standardized data standards, and moral protections. AI's impact can be further increased through public-private partnerships, targeted rare disease research, and the incorporation of digital health tools. By tackling these issues, India can fully utilize AI and genomics to transform drug discovery, enhance diagnostics, and provide individualized, reasonably priced treatments that are suited to its heterogeneous populace. The study emphasizes that India is in a strong position to lead the world in precision medicine and AIpowered pharmaceutical development with focused efforts.
Pharmacogenomic Methods Driven by AI for Tailored Antidepressant Therapy: Increasing Treatment Effectiveness and Mitigating Side Effects
(2025-05) Kanath Sudeer Kumar, Soorya
Artificial intelligence (AI) is rapidly revolutionizing mental health by improving pharmacogenomic techniques to provide more personalized antidepressant medication. This dissertation looks at how AI-driven pharmacogenomics is observed, accepted, and applied in healthcare settings in India and Europe. The study's goal is to analyze the present state of knowledge, preparedness, and ethical issues around AI-guided prescription, as well as identify hurdles and facilitators that impact its clinical acceptance. The study used a concurrent mixed-method approach, combining quantitative data from 105 verified survey replies with qualitative insights from six expert interviews. The survey results, which were collected from healthcare professionals, researchers, and regulatory stakeholders, were analyzed using, while thematic analysis of the interviews was conducted using NVivo. The findings provide significant evidence for AI in improving antidepressant medication by minimizing trial-and-error prescription and improving treatment outcomes. 73% of all participants recognized AI's role in boosting accuracy, and 68% agreed pharmacogenomics might personalize therapy. However, geographical differences emerged: European professionals shown more knowledge and system preparedness, whereas Indian respondents raised worries about insufficient infrastructure, a lack of specialist training, and unclear legal frameworks. Data privacy concerns, ethical uncertainty, and inadequate integration into healthcare operations were recognized as common problems across both areas. Notably, the study found that increasing familiarity with AI corresponds higher trust in its application, emphasizing the importance of focused teaching initiatives. Furthermore, the readiness of healthcare professionals-particularly early adopters in both regions-indicates that stakeholder involvement, legislative reform, and technological investment are critical for wider adoption. In conclusion, the work highlights AI-driven pharmacogenomics as a possible tool for changing antidepressant prescribing habits. Healthcare systems may speed up the adoption of personalized medicine by solving regional disparities through training, ethical measures, and infrastructure development. These findings add to global conversations about digital health transformation and highlight the importance of locally appropriate policies that combine innovation with accountability.
Pharmacy in the Digital Age: Exploring Adults' Trust, Awareness, and Adoption of Technology-Driven Services
(2025-05) Monohan, Priya
This quantitative study examines the determinants of awareness and trust of digital pharmacy services and adoption by adults, with the goal of understanding how demographic, behavioural and technological variables shape consumers’ engagement with technology-based pharmaceutical care. The research had three major objectives to focus on. In order to study the factors that affect the awareness of digital pharmacy services, the role of trust in the adoption of these services and the barriers and facilitators that affect the uptake of these services. Data on a sample size of 143 people of different age groups and educational backgrounds, with a significant concentration in the 18–34 age group, was collected using a structured survey distributed online. The study used descriptive and regression analysis to determine the extent to which digital literacy, internet access, health literacy, and demographic traits influence awareness and adoption behaviours. Based on the findings, trust is the highest determinant of adoption whereby adoption is likely to occur when users believe in high levels of data privacy, security, and service reliability. Awareness also surfaced as a significant factor, though secondary to trust, better-informed users were shown to be more engaged. Those who are younger and more digitally as well as health literate were more likely to use digital pharmacy services, while the older adults and those with fewer digital skills were more resistant as a result of the concerns about usability and security. Lack of information, digital inaccessibility, and preference for traditional in person interactions were impediments more common in low income and elderly groups. While hypotheses on digital literacy and trust were directly strengthened by statistical evidence, health literacy and age relations were mostly inferred from descriptive insights. Overall, the study finds that digital pharmacy services can only be successfully implemented if user trust is improved, public awareness increased, and digital inequalities addressed, especially among the underserved populations. These results have essential implications for policymakers, healthcare providers and developers of digital health to expand reach and equity of digital pharmacy solutions.
The Impact of AI (Machine Learning and Automation) on Biopharmaceutical Manufacturing Industry
(2024-05) Sayal, Ruchi
This research investigates the transformative effects of artificial intelligence (AI), machine learning (ML), and automation on the biopharmaceutical manufacturing industry. The study provides a comprehensive analysis of how these advanced technologies are revolutionizing manufacturing processes. Through an extensive literature review and detailed survey analysis, the research examines how these technologies address challenges such as data quality and complex biological systems, emphasizing their role in overcoming regulatory hurdles and improving manufacturing efficiency. The study explores key trends and drivers behind the escalating adoption of AI, including the need for process optimization, advancements in drug discovery, and enhanced quality control. Furthermore, the research assesses the impact of AI on traditional biopharmaceutical manufacturing models. It illustrates how AI disrupts conventional processes by enabling real-time issue identification, enhancing quality control, and boosting productivity. The introduction of new methodologies such as personalized medication production, AI-powered robotics, and AI-assisted drug discovery showcases the transformative potential of these technologies. In conclusion, the study reveals that AI adoption in the biopharmaceutical industry is rapidly advancing, driven by its transformative potential in enhancing efficiency, innovation, and competitiveness. Addressing challenges and ensuring responsible adoption will be pivotal in realizing the full benefits of AI-enabled technologies in biopharmaceutical manufacturing. The research provides valuable insights for industry stakeholders, guiding strategic decision-making and fostering a more informed approach to integrating AI technologies, ultimately contributing to the growth and advancement of the biopharmaceutical sector.
The impact of Smart Manufacturing on the Digital Maturity of Medical Device Industry
(2024-05) Dattaram Solkar, Ankita
The study explores the impact of smart manufacturing on the digital maturity of the medical device industry. The research aims to assess smart manufacturing technologies contributions to digital maturity, focusing on technological advancements, connectivity features, and overall industry improvements. The literature review highlights the importance of operational efficiency, quality improvement, product customization, and regulatory compliance as primary drivers for adopting digital technologies in the medical device industry. Additionally, the study emphasizes the significance of a robust data strategy, seamless digital integration, and smart manufacturing practices. The study adopts a mixed-methods approach, combining qualitative and quantitative data to understand the impact of smart manufacturing on digital maturity, involving a comprehensive literature review and a survey of industry professionals from India and Ireland. Findings suggest that digital maturity positively impacts operational efficiency and product quality, with potential benefits including enhanced quality, efficiency, and innovation through advanced technologies like AI, IoT, and big data analytics. However, challenges such as data security and system interoperability need to be addressed. The research recommends a supportive organizational culture, leadership commitment, and continuous employee training to drive digital maturity, ultimately fostering innovation and competitiveness.
Use of Blockchain Technology in reducing drug supply shortages in the Irish public healthcare system through cross-industry data-sharing of pharmaceutical manufacturing and supply chain data.
(2025-05) Cronin, Donal
The Irish public healthcare system is facing growing challenges due to recurring drug supply shortages, which significantly impact patient care and healthcare operations. This research investigates whether blockchain technology can serve as a viable solution to enhance transparency and data-sharing between pharmaceutical manufacturers and healthcare providers in Ireland, with the ultimate aim of reducing such shortages. The primary research question explores the feasibility of using blockchain to enable timely and secure sharing of manufacturing and supply chain data across public and private stakeholders. Supporting objectives include identifying current barriers in data access, evaluating blockchain’s benefits and technical integration challenges, and gauging stakeholder demand for cross-industry collaboration. A mixed-methods approach was adopted, combining quantitative survey data with qualitative interviews. Surveys were completed by 45 professionals from healthcare, life sciences, supply chain, and regulatory backgrounds, selected through purposive sampling. The survey gathered perceptions on drug shortages, blockchain awareness, trust in datasharing, and governance preferences. Data was analysed using descriptive statistics, t-tests, Analysis of Variance, and Chi-square testing. The qualitative phase consisted of in-depth, semi-structured interviews with six subject matter experts across the life sciences and healthcare domains. Thematic analysis was used to extract insights aligned with the study’s core objectives. Findings revealed broad awareness of drug shortages across all sectors, with manufacturing delays, supply chain fragility and quality, and lack of real-time data identified as critical factors. Participants viewed blockchain as a potentially transformative technology, particularly for improving traceability, trust, and data integrity. However, technical barriers, such as integration complexity, data standardisation, and regulatory compliance, were seen as significant adoption hurdles. Upstream processes, such as provision of quality raw material, and downstream processes, such as Ireland’s market size and drug approval practices, were highlighted and present significant challenges to drug manufacturing organisations. A consistent theme across interviews was the need for secure, permissioned data environments and proof-of-concept pilots to build trust and validate impact. The study concludes that blockchain holds promise in alleviating drug shortages through enhanced data-sharing and visibility, but successful adoption will depend on cross-sector collaboration, regulatory alignment, and demonstrable pilot outcomes. Recommendations include the development of national governance frameworks, implementation of limitedscale blockchain pilots, and the creation of funding models that support public-private partnerships to ensure system-wide scalability and sustainability.
Utilizing Artificial Intelligence (Machine learning algorithms) for Process Optimization in Pharmaceutical Manufacturing Processes
(2024-05) Adelodun Johnson, Arafat
Digital transformation has introduced smart manufacturing, artificial intelligence, IoT, and advanced computerization to the pharmaceutical industry to drive Process Optimization. This plays a crucial role in the pharmaceutical industry as the complexity of manufacturing processes presents multidimensionality of product design, process development and product manufacturing data. While statistical techniques such as multivariate data analysis has made significant contribution to the pharmaceutical sector, its application can only be subjected to one process at a time in terms of providing support for quality-by-design based development and manufacturing of pharmaceuticals, limiting the enormous potential for automation. By leveraging machine learning, manufacturing processes can be streamlined to mitigate challenges associated with variability and complexity through predictive analysis of the large volume of data generated by PAT. This paper aims to provide a critical overview of how ML can be applied during various stages of the manufacturing process through a comprehensive analysis of existing literature from peer-reviewed journals, books, academic papers with illustrative examples applied in the context of pharmaceutical formulation development and related technologies as well as future trends. The study also aims to gain objective insights regarding the use of ML in pharmaceutical dosage manufacturing by exploring the opinions and perspectives of professionals actively involved in pharmaceutical manufacturing processes. With an estimated sample size of 90 participants, the study utilised an online survey-questionnaire that was administered to process managers, operators, industry experts, quality assurance and control officers to gather quantitative data in Ireland. An overall response rate of 69% was obtained and their opinion was evaluated in line with reviewed literature. The outcome of the study demonstrated the potential benefits that ML had to offer the pharmaceutical industry, the current applications, the limitations, and regulatory issues surrounding the adoption of ML in pharmaceutical manufacturing from both primary and secondary data sources.

Browse

Browsing Digital Transformation Dissertations by Title

Results Per Page

Sort Options