IntroductionEfforts to improve medication access in low-and middle-income countries, particularly in Sub-Saharan Africa, have made progress, especially in the fight against infectious diseases such as tuberculosis. However, challenges exist in establishing effective pharmacovigilance systems. The PhArmacoVIgilance Africa (PAVIA) project was committed to enhancing pharmacovigilance in Tanzania, Eswatini, Nigeria, and Ethiopia, with an emphasis on anti-tuberculosis drugs, utilizing various methods, including training. This study evaluates the PAVIA training program’s effectiveness and its adaptation during the COVID-19 pandemic.MethodsA blended e-learning program, incorporating two courses and a platform for educational materials, was developed. This program, designed to train healthcare professionals in pharmacovigilance, was incorporated into a Training of Trainers model. To evaluate the program effectiveness, we used multiple measures such as assessing knowledge gain through pre-and post-test scores, assessing learners’ satisfaction and attitudes via questionnaires, and analyzing Individual Case Safety Reports (ICSRs) in VigiBase to determine the impact on spontaneous reporting systems in the PAVIA countries.Results121 learners enrolled in the pilot trainings, including 36 from Tanzania, 34 from Eswatini, 25 from Nigeria, and 26 from Ethiopia. Notably, post-test scores were significantly higher than pre-test scores in all four countries. Following the pilot trainings, multiple step-down training sessions were held in Tanzania, Eswatini, and Nigeria, with a total of 827 learners registering and 421 successfully completing the program. Learners’ scores on the post-tests were significantly higher than on the pre-tests for both courses in all three countries. Learners’ feedback on the training was overwhelmingly positive. Additionally, a qualitative analysis of ICSRs revealed a substantial increase in reports after the training in Tanzania, Eswatini, and Nigeria.DiscussionAn innovative e-learning program trained healthcare professionals in pharmacovigilance and anti-tuberculosis drug safety over 3 years in four PAVIA countries. The program effectively improved participants’ knowledge, received positive feedback, and likely had an impact on reporting rates in Tanzania, Eswatini, and Nigeria, although a direct causal link could not be definitively established due to data limitations and other factors, such as the heightened reporting rates associated with COVID-19 vaccines, that could have contributed to the notable increase in ICSRs.

Abstract Introduction Under-reporting of adverse drug reactions is a major challenge in Tanzania. It is important to educate the health care providers about pharmacovigilance in order to improve the reporting rate. Objectives: We conducted a study with the objective of evaluating the impact of an educational intervention based on the knowledge on pharmacovigilance among healthcare providers in Tanzania. Methods: A pharmacovigilance e-blended learning method was used. Pre and post-test, courses were the basic concepts in Pharmacovigilance and the safety of Anti-Tuberculosis Drugs. Descriptive analyses were run to determine the proportions of the correct and wrong answers for pre and post training. Results A total of 118 (72%) completed the pre-and post-test for both the first and the second courses. There was an increase in the correct answers in the post-test to every question. The median score of pre-intervention for knowledge about basic pharmacovigilance increased from 5 (range 4–7) in pre-test to 8 (range 7–9) in post-test. The median score for anti-TB drug safety issues monitoring and management increased from 4 (range 4–6) in pre-test to 7 (range 7–9) in post-test. Conclusion The findings of this study showed that knowledge scores and correct answers were increased following an educational intervention among HCP.

Evidence on treatments for early-stage COVID-19 in outpatient setting is sparse. We explored the pattern of use of drugs prescribed for COVID-19 outpatients’ management in Southern Italy in the period February 2020–January 2021. This population-based cohort study was conducted using COVID-19 surveillance registry from Caserta Local Health Unit, which was linked to claims databases from the same catchment area. The date of SARS-CoV-2 infection diagnosis was the index date (ID). We evaluated demographic and clinical characteristics of the study drug users and the pattern of use of drugs prescribed for outpatient COVID-19 management. Overall, 40,030 patients were included in the analyses, with a median (IQR) age of 44 (27–58) years. More than half of the included patients were asymptomatic at the ID. Overall, during the study period, 720 (1.8%) patients died due to COVID-19. Azithromycin and glucocorticoids were the most frequently prescribed drugs, while oxygen was the less frequently prescribed therapy. The cumulative rate of recovery from COVID-19 was 84.2% at 30 days from ID and it was lower among older patients. In this study we documented that the drug prescribing patterns for COVID-19 treatment in an outpatient setting from Southern Italy was not supported from current evidence on beneficial therapies for early treatment of COVID-19, thus highlighting the need to implement strategies for improving appropriate drug prescribing in general practice.

Biological drugs have improved the management of immune-mediated inflammatory diseases (IMIDs) despite being associated with important safety issues such as immunogenicity, infections, and malignancies in real-world settings. The aim of this study was to explore the potential of a large Italian multi-database distributed network for use in the postmarketing surveillance of biological drugs, including biosimilars, in patients with IMID. A retrospective cohort study was conducted using 13 Italian regional claims databases during 2010–2019. A tailor-made R-based tool developed for distributed analysis of claims data using a study-specific common data model was customized for this study. We measured the yearly prevalence of biological drug users and the frequency of switches between originator and biosimilars for infliximab, etanercept, and adalimumab separately and stratified them by calendar year and region. We then calculated the cumulative number of users and person-years (PYs) of exposure to individual biological drugs approved for IMIDs. For a number of safety outcomes (e.g., severe acute respiratory syndrome coronavirus 2 [SARS-COV-2] infection), we conducted a sample power calculation to estimate the PYs of exposure required to investigate their association with individual biological drugs approved for IMIDs, considering different strengths of association. From a total underlying population of almost 50 million inhabitants from 13 Italian regions, we identified 143,602 (0.3%) biological drug users, with a cumulative exposure of 507,745 PYs during the entire follow-up. The mean age ± standard deviation of biological drug users was 49.3 ± 16.3, with a female-to-male ratio of 1.2. The age-adjusted yearly prevalence of biological drug users increased threefold from 0.7 per 1000 in 2010 to 2.1 per 1000 in 2019. Overall, we identified 40,996 users of biosimilars of tumor necrosis factor (TNF)-α inhibitors (i.e., etanercept, adalimumab, and infliximab) in the years 2015–2019. Of these, 46% (N = 18,845) switched at any time between originator and biosimilars or vice versa. To investigate a moderate association (incidence rate ratio 2) between biological drugs approved for IMIDs and safety events of interest, such as optic neuritis (lowest background incidence rate 10.4/100,000 PYs) or severe infection (highest background incidence rate 4312/100,000 PYs), a total of 43,311 PYs and 104 PYs of exposure to individual biological drugs, respectively, would be required. As such, using this network, of 15 individual biological drugs approved for IMIDs, the association with those adverse events could be investigated for four (27%) and 14 (93%), respectively. The VALORE project multi-database network has access to data on more than 140,000 biological drug users (and > 0.5 million PYs) from 13 Italian regions during the years 2010–2019, which will be further expanded with the inclusion of data from other regions and more recent calendar years. Overall, the cumulated amount of person-time of exposure to biological drugs approved for IMIDs provides enough statistical power to investigate weak/moderate associations of almost all individual compounds and the most relevant safety outcomes. Moreover, this network may offer the opportunity to investigate the interchangeability of originator and biosimilars of several TNFα inhibitors in different therapeutic areas in real-world settings.

Pharmacovigilance is the field of science devoted to the collection, analysis, and prevention of Adverse Drug Reactions (ADRs). Efficient strategies for the extraction of information about ADRs from free text sources are essential to support the important task of detecting and classifying unexpected pathologies, possibly related to (therapy-related) drug use. Narrative ADR descriptions may be collected in different ways, e.g., either by monitoring social networks or through the so called "spontaneous reporting, the main method pharmacovigilance adopts in order to identify ADRs. The encoding of free-text ADR descriptions according to MedDRA standard terminology is central for report analysis. It is a complex work, which has to be manually implemented by the pharmacovigilance experts. The manual encoding is expensive (in terms of time). Moreover, a problem about the accuracy of the encoding may occur, since the number of reports is growing up day by day. In this paper, we propose MagiCoder, an efficient Natural Language Processing algorithm able to automatically derive MedDRA terminologies from free-text ADR descriptions. MagiCoder is part of VigiWork, a web application for online ADR reporting and analysis. From a practical point of view, MagiCoder reduces the encoding time of ADR reports. Pharmacologists have simply to review and validate the MedDRA terms proposed by MagiCoder, instead of choosing the right terms among the 70K terms of MedDRA. Such improvement in the efficiency of pharmacologists' work has a relevant impact also on the quality of the following data analysis.Our proposal is based on a general approach, not depending on the considered language. Indeed, we developed MagiCoder for the Italian pharmacovigilance language, but preliminarily analyses show that it is robust to language and dictionary changes.

Adding patients to the range of potential reporters of adverse drug reactions (ADRs) may increase spontaneous reporting and contribute to the detection of signals, one of the primary aims of spontaneous reporting systems. Community pharmacies could have an important role in this context as a service for promoting patient reporting of ADRs.

Pharmacovigilance is the activity related to the collection, analysis, and prevention of adverse reactions induced by drugs. The spontaneous reporting of adverse drug reactions is a system for identifying and sending reports about unexpected reactions to the regulatory authority. In Italy the information needed for properly carrying out the pharmacovigilance activities is scattered in different databases, which often contain the same information but encoded in different and temporally evolving ways. The data contained in the mentioned archives need to be integrated with information contained in other databases. In this paper we describe the construction of a data warehousing system, called VigiSegn, for the national center of pharmacovigilance; in particular, we focus on the data sources analysis and the design of the reconciled database. The (temporal) schema of reconciled data has been designed by using the TimeER conceptual data model.