OAR@UM Community:

Clinical applications and use of medicinal cannabis

2026-03-04T13:55:59Z

Title: Clinical applications and use of medicinal cannabis Abstract: Over the years, cannabis has been utilized for its medicinal properties to address a myriad of complaints including muscular spasms, insomnia, depression, pain and nausea. The dopamine-mediated euphoric effect, which was later attributed to the ability of the tetrahydrocannabinol component of cannabis to activate the CB1 receptor in the human body, has led Western countries to criminalize use of cannabis in the first half of the twentieth century. In recent years, numerous studies have heightened awareness about cannabis's potential medicinal benefits, demonstrating its efficacy in such clinical contexts as chemotherapy-induced nausea, epilepsy and multiple sclerosis spasticity. In Malta, the 2014 Drugs Dependence (Treatment Not Imprisonment) Act was amended in 2018 to allow for clinical use of authorized medicinal cannabis products. This was followed shortly after by the enactment of the Production of Cannabis for Medicinal And Research Purposes Act which delivers a legal framework for the possibility of producing cannabis in Malta for medicinal and research purposes. The developing potential of medicinal cannabis in patient care demarcates a shift in attitude towards cannabis from a legislative perspective that will however also require a clear and measurable change in perception by healthcare professionals in order to translate into benefits in delivery of medical care to patients. This research aimed to explore the therapeutic potential of medicinal cannabis by analyzing current international literature on its indications, contraindications, and administration modalities. This data was also intended to assist in proposing a simplified stepwise framework for clinical trials in this field. Through dissemination of a 25-item questionnaire that was validated by an expert panel ahead of distribution., the study also assessed the perceptions and concerns of the Maltese healthcare professionals on the use of medicinal cannabis, extracting pertinent considerations and uncertainties, and noting attitudes to help evaluate critical issues that ought to be addressed when reviewing the potential clinical use of medicinal cannabis within the Maltese healthcare context. Statistical analyses identified a weak positive correlation between the age of doctors and their propensity to favour prescribing medicinal cannabis (r= 0.20, p= 0.040), mostly among males (r= 0.34, p= 0.009). Both pharmacists (r=0.41, p< 0.001) who had higher knowledge of medicinal cannabis evidenced a more favourable approach to its clinical use, believing that patients could derive benefit from medicinal cannabis and feeling more comfortable in discussing its integration as potential therapy with patients. In doctors this proved to be a stronger predictor of prescription attitude than knowledge and education categories assessed in a hierarchical regression analysis (β= 0.71, p< 0.001, t=6.84). Comparison of results reflected similar statistical patterns for both doctors and pharmacists in terms of attitudes, beliefs and knowledge of medicinal cannabis. A systematic review was conducted following PRISMA guidelines. Searches were performed in PubMed, Ovid, Web of Science, and Cochrane databases using predefined terms related to medicinal cannabis and its clinical applications for a variety of conditions. Eligible studies mostly included randomized controlled trials, cohort studies, and case-control studies evaluating the therapeutic efficacy of medicinal cannabis across various conditions. Data on clinical outcomes, administration modalities, and adverse effects were extracted and analyzed. The clinical trials and studies assessed were also considered in the clinical trial framework proposition, ensuring its compliance with current compliance regulations for clinical trials in the European Union. Questionnaire dissemination to Maltese doctors and pharmacists returned 200 responses, which were utilized for the development of a series of educational initiatives including a lecture series and a patient information brochure. These were validated via feedback from an expert panel. Survey results were in line with those recorded in multiple other regions and, in general, suggested acknowledgment of potential benefits for patients but also hesitancy in engaging with clinical use of medicinal cannabis. The main concerns expressed by healthcare professionals were poor formal education on the subject, unclear evidence-based clinical guidelines and limited training opportunities. It transpires that there is need for vigorous interventions in order to prepare a workforce of healthcare professionals in dealing effectively with discussing with and dispensing medicinal cannabis to eligible patients. Requirements include a significant investment of time and resources, as well as a willingness on the part of healthcare professionals to engage with the latest research and to learn about the various ways in which cannabis can be used as a therapeutic alternative in some clinical contexts. Description: Ph.D.(Melit.)

Intrinsic risk factors of falls in older patients

2026-02-06T07:42:44Z

Title: Intrinsic risk factors of falls in older patients Abstract: Falls in older adults pose a major public health challenge, with intrinsic factors such as co-morbidities, polypharmacy and fall-risk-increasing drugs (FRIDs) contributing to increased risk and healthcare burden. The aim of this study is to identify key intrinsic risk factors for falls in older patients and to propose systems for healthcare professionals (HCP) to reduce falls risk and improve patient outcomes. In a retrospective analytical cross-sectional study, within a rehabilitation hospital, patient profiles compiled by clinical pharmacists were reviewed for patients 65 years and over and discharged between January and December 2023. Participants who met the inclusion criteria and were admitted with falls were classified as the faller group, while the remaining participants were assigned to the control group. Falls in the faller group were identified as non-mechanical (intrinsic). A data collection sheet was compiled to record data on demographic characteristics, co-morbidities, FRIDs and the number of chronic medications prescribed. For each category under investigation, statistical analysis was conducted to analyse associations between the faller group and the control group. From the findings of this study a fall risk assessment tool (SAFE-R), to identify intrinsic risk factors for falls, was developed. Of 782 participants meeting the inclusion criteria, 355 (45%) experienced a non-mechanical fall. The results of the study revealed that the risk of experiencing falls increases with increasing age (p < 0.05) and female gender (p < 0.001). Binary logistic regression analysis was used to relate risk of a fall to co-morbidities and FRIDs. Seven significant co-morbidity predictors for falls were identified, namely cognitive impairment, visual impairment, syncope, postural instability, history of falls, present fracture and osteoporosis (p < 0.05). The greater the number of co-morbidities present, the greater the risk of experiencing a fall (p < 0.001). The more chronic medications taken, the greater was the likelihood of experiencing a fall (p < 0.001). Benzodiazepine receptor agonists (p = 0.022) and opioids (p < 0.001) were identified as significant fall predictors. This study highlights the need to assess intrinsic fall risk factors and identifies strategies to enhance the intervention of clinical pharmacists in treatment optimisation. It further emphasizes that fall risk assessment tools support HCPs in identifying high-risk patients, thereby reducing fall risk and improving outcomes. Description: M.Sc.(Melit.)

Artificial intelligence in pharmacy

2025-12-12T13:05:16Z

Title: Artificial intelligence in pharmacy Abstract: Artificial intelligence (AI) has emerged as a transformative technology within the pharmaceutical sciences, offering innovative solutions across drug discovery, personalised medicine, clinical trials, and pharmacy operations. The increasing complexity of healthcare demands more efficient, accurate, and patient-centred approaches, and AI provides tools capable of analysing vast datasets, predicting therapeutic outcomes, and optimizing decision-making processes. This thesis explores the application of AI in pharmacy, with a specific focus on its roles in drug discovery and development, personalised medicine predictive analytics, patient centred care, pharmaceutical operations and pharmacy practice. It also examines the challenges surrounding AI adoption, including regulatory, ethical, and data-related concerns. This research used a literature review to gather relevant studies on AI application in pharmacy. The search included articles published between 2015 and 2024, sourced from databases such as PubMed, Scopus and Google scholar. Keywords included Artificial intelligence in pharmacy, AI in drug discovery, personalised medicine. AI has shown measurable benefits in accelerating drug target identification, optimizing clinical trials, and tailoring therapies using genomic data. Notable tools such as DeepMind’s AlphaFold and IBM Watson for Oncology exemplify AI’s potential in reducing development time and supporting personalized treatment. In pharmacy practice, AI-enabled clinical decision support systems (CDSS), chatbots, and computerized prescriber order entry (CPOE) have reduced medication errors and improved patient counselling. Nevertheless, concerns persist around data privacy, algorithmic bias, model interpretability, and cost of implementation. AI presents substantial opportunities for enhancing efficiency, safety, and innovation within pharmacy practice. By addressing current challenges through interdisciplinary collaboration and regulatory advancements, AI can further revolutionize pharmaceutical research, development, and patient care, ultimately improving health outcomes and operational efficiency across the sector. Description: M.Pharm.(Melit.)

Opportunities for telepharmacy

2025-12-12T13:01:49Z

Title: Opportunities for telepharmacy Abstract: Telepharmacy, the provision of pharmaceutical care through telecommunications to patients in locations where they may not have direct contact with a pharmacist, is gaining momentum globally. This dissertation investigates the opportunities, challenges, and policy implications of telepharmacy implementation across five countries India, China, Spain, Germany, and Sweden representing diverse healthcare systems, income levels, and digital readiness. Through a literature review of over 36 peer reviewed studies, government policy documents, and global health reports, this research examines key themes including access to pharmaceutical care, medication safety, cost-effectiveness, digital infrastructure, and regulatory frameworks. The findings indicate that telepharmacy enhances medication access and continuity of care, particularly in underserved rural regions, and contributes significantly to improving medication adherence and safety. Spain, Germany, and Sweden demonstrate mature telepharmacy systems integrated within national e-health strategies, while India and China exhibit innovative yet fragmented adoption patterns, with rural infrastructure and policy gaps acting as major barriers. A thematic analysis reveals that regulatory clarity, digital infrastructure, pharmacist training, and patient digital literacy are central to successful implementation. The study also finds that telepharmacy aligns well with global health targets such as Universal Health Coverage and the WHO's digital health strategies. It underscores the need for formal policy development, public-private collaboration, and national training frameworks to ensure sustainable integration. By presenting a comparative analysis supported by country specific data and international best practices, this dissertation provides strategic insights for policymakers, healthcare professionals, and academic stakeholders. It advocates for mainstreaming telepharmacy as a core health service delivery model to bridge access gaps, improve pharmaceutical care, and build resilient healthcare systems in a digitally transforming world. Description: M.Pharm.(Melit.)