UNASSIGNED: Trastuzumab improves outcomes in patients with HER2-overexpressing malignancies but is associated with decreases in left ventricular ejection fraction. Heart failure (HF) risks from other anti-HER2 therapies are less clear.
UNASSIGNED: Using World Health Organization pharmacovigilance data, the authors compared HF odds across anti-HER2 regimens.
UNASSIGNED: In VigiBase, 41,976 patients had adverse drug reactions (ADRs) with anti-HER2 monoclonal antibodies (trastuzumab, n = 16,900; pertuzumab, n = 1,856), antibody-drug conjugates (trastuzumab emtansine [T-DM1], n = 3,983; trastuzumab deruxtecan, n = 947), and tyrosine kinase inhibitors (afatinib, n = 10,424; lapatinib, n = 5,704; neratinib, n = 1,507; tucatinib, n = 655); additionally, 36,052 patients had ADRs with anti-HER2-based combination regimens. Most patients had breast cancer (monotherapies, n = 17,281; combinations, n = 24,095). Outcomes included comparison of HF odds with each monotherapy relative to trastuzumab, within each therapeutic class, and among combination regimens.
UNASSIGNED: Of 16,900 patients with trastuzumab-associated ADRs, 2,034 (12.04%) had HF reports (median time to onset 5.67 months; IQR: 2.85-9.32 months) compared with 1% to 2% with antibody-drug conjugates. Trastuzumab had higher odds of HF reporting relative to other anti-HER2 therapies collectively in the overall cohort (reporting OR [ROR]: 17.37; 99% CI: 14.30-21.10) and breast cancer subgroup (ROR: 17.10; 99% CI: 13.12-22.27). Pertuzumab/T-DM1 had 3.4 times higher odds of HF reporting than T-DM1 monotherapy; tucatinib/trastuzumab/capecitabine had similar odds as tucatinib. Among metastatic breast cancer regimens, HF odds were highest with trastuzumab/pertuzumab/docetaxel (ROR: 1.42; 99% CI: 1.17-1.72) and lowest with lapatinib/capecitabine (ROR: 0.09; 99% CI: 0.04-0.23).
UNASSIGNED: Trastuzumab and pertuzumab/T-DM1 had higher odds of HF reporting than other anti-HER2 therapies. These data provide large-scale, real-world insight into which HER2-targeted regimens would benefit from left ventricular ejection fraction monitoring.

Antimicrobial susceptibility testing is an essential task for selecting appropriate antimicrobial agents to treat infectious diseases. Constant evolution has been observed in methods used in the diagnostic microbiology laboratories. Disc diffusion or broth microdilution are classical and conventional phenotypic methods with long turnaround time and labour-intensive but still widely practiced as gold-standard. Scientists are striving to develop innovative, novel and faster methods of antimicrobial susceptibility testing to be applicable for routine microbiological laboratory practice and research. To meet the requirements, there is an increasing trend towards automation, genotypic and micro/nano technology-based innovations. Automation in detection systems and integration of computers for online data analysis and data sharing are giant leaps towards versatile nature of automated methods currently in use. Genotypic methods detect a specific genetic marker associated with resistant phenotypes using molecular amplification techniques and genome sequencing. Microfluidics and microdroplets are recent addition in the continuous advancement of methods that show great promises with regards to safety and speed and have the prospect to identify and monitor resistance mechanisms. Although genotypic and microfluidics methods have many exciting features, however, their applications into routine clinical laboratory practice warrant extensive validation. The main impetus behind the evolution of methods in antimicrobial susceptibility testing is to shorten the overall turnaround time in obtaining the results and to enhance the ease of sample processing. This comprehensive narrative review summarises major conventional phenotypic methods and automated systems currently in use, and highlights principles of some of the emerging genotypic and micro/nanotechnology-based methods in antimicrobial susceptibility testing.

UNASSIGNED: Coronavirus disease(COVID-19) outbroke towards the end of December 2019 in China, soon it started spreading rapidly to various countries leading to an outburst of pandemic. Due to the restrictions imposed to control the spread of the infection, globally the manufacturing, import and export of medicine and the healthcare services to patients with chronic illness had been affected. This study aimed to explore the perspectives of the pharmacists on the medicine supply chain for patients with chronic diseases during COVID-19 pandemic in India.
UNASSIGNED: This study is a prospective, qualitative research involving telephonic, semi-structured in-depth interviews. An interview guide for pharmacists was prepared and validated using \"Interview Protocol Refinement\" method. Purposive sampling method was used to recruit the pharmacists; a telephonic oral consent was obtained. The interview session was audio recorded and the recordings were transcribed verbatim. Further, transcripts were validated and later analysed using NVivo software.
UNASSIGNED: A total of 8 participants were interviewed during our study. Thematic analysis of the transcripts resulted in seven main themes. The study showed that there was deficiency in medicine supply during the COVID-19 pandemic and the pharmacists faced several challenges in procuring and storing the medication, arranging for unavailable medicines, medication dispensing and provision of the services such as medicine delivery, patient counselling. There was also scarcity of manpower leading to extra workload and working overtime.
UNASSIGNED: Uninterrupted supply of essential medicine is the backbone of health care system. An effective plan and appropriate strategies are vital to combat such future emergencies.

UNASSIGNED: High COVID-19 vaccine coverage is essential. Patients who are considered high risk for hypersensitivity reactions and have had an allergic reaction to the COVID-19 vaccine are usually referred to an allergist for assessment of vaccination. Administration of a vaccine graded challenge (also known as a provocation test) is an option that can be considered in this population. This primary objective of this study is to describe the outcome of the COVID-19 vaccine provocation test and to understand the predicting factors associated with hypersensitivity reaction after the provocation test as the secondary objective.
UNASSIGNED: Adult patients with a history of hypersensitivity reaction to the first COVID-19 vaccine and high-allergic patients who underwent COVID-19 vaccine provocation test up until May 2022 were included. A protocol using skin prick test (SPT), intradermal test (IDT), followed by graded challenge was developed for the determined vaccine used.
UNASSIGNED: A total of 232 patients were included in the analysis. Twenty-eight had hypersensitivity to their first COVID-19 vaccine dose and 204 were high risk for allergic reaction. Hypersensitivity reactions occurred in 20 patients (8.6%, 95% CI: 5-12.2%), consisting of 4 reactions after SPT, 9 after IDT, 7 during or after titrated challenge. Half of the reactions were mild; however, 3 patients developed severe reactions. Patients with history of anaphylaxis were more likely to experience hypersensitivity reaction after provocation test (aRR = 2.79, 95% CI: 1.05-7.42).
UNASSIGNED: Provocation test in COVID-19 vaccination has a high success rate in patients with a history of hypersensitivity to the first COVID-19 vaccine and in high allergic patients. History of anaphylaxis is associated with hypersensitivity reaction after a COVID-19 vaccine provocation test.

UNASSIGNED: This study aimed to assess the type, severity, seriousness, reasons, and outcomes of adverse drug reactions (ADRs) in the reports submitted to the regional spontaneous ADR database.
UNASSIGNED: A retrospective observational study was conducted to analyze all the Tabuk Health Affairs hospitals in Saudi Arabia submitted to SFDA from January 2020 to December 2020. The database was structured according to the Saudi ADR form\'s fields. The Naranjo algorithm was used to assess the causes of the ADRs (sFDA, 2022).
UNASSIGNED: For 1 year, 2,349 ADR reports, along with 242 suspected drugs for 4,114 reactions, were submitted to SFDA. We found more males than females had ADRs (56.1% vs. 43.8%, P < 0.05).Antimicrobial drugs (26.9%), hematologic drugs (19.7%), and neuropsychiatric drugs (12.9%) were responsible for most ADRs. Most of the reactions were associated with the use of ciprofloxacin (7.7%), followed by the combination of lopinavir and ritonavir (4.1%). Two deaths resulted from salbutamol and cefazolin use. Based on the results of the Naranjo assessment of causality, cardiovascular events (9.9%) exhibited the highest score (≥9) for a causal relationship with the suspected drugs, followed by dermatological events (9.5%).
UNASSIGNED: The spontaneous report database is an important and valuable source of aftermarket authorization safety information. In our study, most drugs used as antimicrobial, cardiovascular, and hematologic therapies were associated with a higher risk of developing severe and serious events. We recommend monitoring and using medications optimally to ensure patient safety.

Linezolid is an oxazolidinone antibiotic. Linezolid-associated lactic acidosis has been reported in 6.8% of linezolid-treated patients. Lactic acidosis is associated with poor clinical outcomes, with high blood lactate levels resulting in organ dysfunction and mortality. This case report describes the development of lactic acidosis in a 64-year-old Chinese woman who had received 33 days of treatment with antituberculosis drugs and 28 days of treatment with oral linezolid for tuberculous meningitis. Severe lactic acidosis was reversed by withdrawing antituberculosis drugs and using continuous venovenous hemodiafiltration (CVVH). When the patient\'s condition was stable, she was transferred to the infectious disease department, and antituberculosis drugs, with the exception of linezolid, were reintroduced. This did not result in recurrence of lactic acidosis. The causal relationship between lactic acidosis and linezolid was categorized as \'probable\' on the Adverse Drug Reaction Probability Scale. This case demonstrates that CVVH has potential as an alternative to discontinuation of linezolid alone for rapid reversal of linezolid-associated severe lactic acidosis.

BACKGROUND: Saroglitazar-a unique dual peroxisome proliferator-activated receptor agonist was approved marketing authorization in India in 2013 for diabetic dyslipidemia. Postmarketing studies have additionally shown improvement in liver parameters in diabetic dyslipidemia patients with nonalcoholic fatty liver disease (NAFLD) who received saroglitazar.
OBJECTIVE: The aim of this study was to evaluate the effect of saroglitazar on liver function test, liver fibrosis score by FibroScan, lipid profiles, HbA1c in NAFLD patients with diabetic dyslipidemia in southern India.
METHODS: A prospective, interventional, pilot study was performed to study the safety and efficacy of saroglitazar in NAFLD patients having type 2 diabetes mellitus. About 97 patients were screened, of which 85 patients were involved in the study based on the inclusion criteria. The clinical parameters and liver stiffness were measured at the baseline and also after 12 weeks of treatment with administration of saroglitazar 4 mg once daily. The change in the parameters at the baseline and after the end of the treatment was measured and was subjected to statistical analysis using SPSS software.
RESULTS: The recruited patients received saroglitazar and were followed up for a period of 12 weeks. The clinical parameters such as fasting blood sugar, postprandial blood sugar, HbA1c, total cholesterol, triglycerides, SGPT, and liver stiffness showed significant difference after 12 weeks of treatment when compared with the baseline values. No adverse drug reaction was reported in patients receiving saroglitazar during the study.
CONCLUSIONS: Saroglitazar was found to show significant improvement in liver parameters in NAFLD patients with a significant reduction in liver fibrosis and triglycerides level.

Inflammatory bowel disease (IBD) is a chronic intestinal disease with painful clinical manifestations and high risks of cancerization. With no curative therapy for IBD at present, the development of effective therapeutics is highly advocated. Drug delivery systems have been extensively studied to transmit therapeutics to inflamed colon sites through the enhanced permeability and retention (EPR) effect caused by the inflammation. However, the drug still could not achieve effective concentration value that merely utilized on EPR effect and display better therapeutic efficacy in the inflamed region because of nontargeted drug release. Substantial researches have shown that some specific receptors and cell adhesion molecules highly expresses on the surface of colonic endothelial and/or immune cells when IBD occurs, ligand-modified drug delivery systems targeting such receptors and cell adhesion molecules can specifically deliver drug into inflamed sites and obtain great curative effects. This review introduces the overexpressed receptors and cell adhesion molecules in inflamed colon sites and retrospects the drug delivery systems functionalized by related ligands. Finally, challenges and future directions in this field are presented to advance the development of the receptor-mediated targeted drug delivery systems for the therapy of IBD.

Drug discovery aims at finding new compounds with specific chemical properties for the treatment of diseases. In the last years, the approach used in this search presents an important component in computer science with the skyrocketing of machine learning techniques due to its democratization. With the objectives set by the Precision Medicine initiative and the new challenges generated, it is necessary to establish robust, standard and reproducible computational methodologies to achieve the objectives set. Currently, predictive models based on Machine Learning have gained great importance in the step prior to preclinical studies. This stage manages to drastically reduce costs and research times in the discovery of new drugs. This review article focuses on how these new methodologies are being used in recent years of research. Analyzing the state of the art in this field will give us an idea of where cheminformatics will be developed in the short term, the limitations it presents and the positive results it has achieved. This review will focus mainly on the methods used to model the molecular data, as well as the biological problems addressed and the Machine Learning algorithms used for drug discovery in recent years.

Despite of their therapeutic effects, drug\'s exposure may have negative effects on human health such as adverse drug reaction (ADR) and side effects (SE). Adverse drug events (ADEs), that correspond to an event occurring during the drug treatment (i.e. ADR and SE), is not necessarily caused by the drug itself, as this is the case with medical errors and social factors. Due to the complexity of the biological systems, not all ADEs are known for marketed drugs. Therefore, new and effective methods are needed to determine potential risks, including the development of computational strategies. We present an ADE association network based on 90,827 drug-ADE associations between 930 unique drug and 6221 unique ADE, on which we implemented a scoring system based on a pull-down approach for prediction of drug-ADE combination. Based on our network, ADEs proposed for three drugs, safinamide, sonidegib, rufinamide are further discussed. The model was able to identify, already known drug-ADE associations that are supported by the literature and FDA reports, and also to predict uncharacterized associations such as dopamine dysregulation syndrome, or nicotinic acid deficiency for the drugs safinamide and sonidegib respectively, illustrating the power of such integrative toxicological approach.