The pharmacists' interventions after a Drug and Therapeutics Committee (DTC) establishment during the COVID-19 pandemic.

Introduction: Healthcare systems in developing countries faced significant challenges during COVID-19, grappling with limited resources and staffing shortages. Assessment of the impact of pharmaceutical care expertise, particularly in critical care units during the pandemics, in developing countries remains poorly explored. The principal aim of our study was to assess the impact of the Drug and Therapeutics Committee (DTC), comprising clinical pharmacists, on the incidence, types, and severity of medication errors and associated costs in using COVID-19 medications, especially antibiotics. Methods: An interventional pre-post study was carried out at a public isolation hospital in Egypt over 6 months. Results: Out of 499 medication orders, 238 (47.7%) had medication errors, averaging 2.38 errors per patient. The most frequent were prescribing errors (44.9%), specifically incorrect drug choice (57.9%), excessive dosage (29.9%), treatment duplication (4.5%), inadequate dosage (4.5%), and overlooked indications (3.6%). Linezolid and Remdesivir were the most common medications associated with prescribing errors. Pharmacists intervened 315 times, primarily discontinuing medications, reducing doses, introducing new medications, and increasing doses. These actions led to statistically significant cost reductions (p < 0.05) and better clinical outcomes; improved oxygen saturation, decreased fever, stabilised respiratory rates, and normalised white blood cell counts. So, clinical pharmacist interventions made a notable clinical and economic difference (66.34% reduction of the expenses) in antibiotics usage specifically and other medications used in COVID-19 management during the pandemic. Conclusion: Crucially, educational initiatives targeting clinical pharmacists can foster judicious prescribing habits.

Bridging the gap: The future of biosimilars regulations.

Biosimilar vaccines and immunotherapeutic are innovative approaches in medical research. This commentary addresses the current disparities in regulations of biosimilar vaccines and immunotherapeutic products across different nations. It also navigates the benefits of global regulatory alignment and challenges that may be encountered. The current discrepancies in regulations across different countries, which pose significant challenges for the development and approval of biosimilar vaccines and immunotherapeutic products. These disparities often lead to delayed market access, increased development costs, and hindered innovation. The commentary stresses that such obstacles could be mitigated through harmonized regulations, resulting in faster approvals, reduced healthcare costs, and improved patient outcomes. Moreover, the commentary explores the specific complexities associated with biosimilar vaccines and immunotherapeutic, such as the intricate evaluation of biosimilarity due to their molecular composition and immunogenic properties. In conclusion, the editorial advocates for collaborative efforts to overcome the challenges in achieving global regulatory harmonization for biosimilars. This includes establishing uniform standards, fostering international cooperation among regulatory agencies, and promoting educational initiatives for healthcare providers and regulators. The ultimate goal is to ensure that patients worldwide have timely access to safe, effective, and affordable biosimilar treatments.

Machine learning in infectious diseases: potential applications and limitations.

Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learning and Big Data analytics have emerged as a potential solution to analyse diverse datasets and face challenges posed by infectious diseases. In this commentary we explore the potential applications and limitations of ML to management of infectious disease. It explores challenges in key areas such as outbreak prediction, pathogen identification, drug discovery, and personalized medicine. We propose potential solutions to mitigate these hurdles and applications of ML to identify biomolecules for effective treatment and prevention of infectious diseases. In addition to use of ML for management of infectious diseases, potential applications are based on catastrophic evolution events for the identification of biomolecular targets to reduce risks for infectious diseases and vaccinomics for discovery and characterization of vaccine protective antigens using intelligent Big Data analytics techniques. These considerations set a foundation for developing effective strategies for managing infectious diseases in the future.

Infectious diseases are a major challenge worldwideArtificial Intelligence (AI) combined algorithms have emerged as a potential solution to analyse diverse datasets and face challenges posed by infectious diseasesFuture directions include applications of ML to identify biomolecules for effective treatment and prevention of infectious diseases.