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The safety of COVID-19 pharmacotherapy is a relevant issue, first of all, because of the current lack of experience with using particular medicinal products and with off-label prescribing. The aim of the study was to analyse information on potential adverse drug reactions (ADRs) and their predictors in etiology- and pathogenesis-oriented COVID-19 therapy. According to literature data, the main clinically significant risk factors for COVID-19 patients to develop an ADR are the duration of their hospital stay, combined use of antivirals, polypharmacy, and their history of drug allergies. The most common adverse reactions to antivirals, to virus-neutralising antibodies, and to human anti-COVID-19 immunoglobulin and convalescent plasma are, respectively, gastrointestinal and hepatobiliary disorders;gastrointestinal disorders, neurological disorders, and allergic reactions;and transfusion reactions (fever, chills, etc.). For pathogenesis-oriented therapy with systemic glucocorticosteroids, the most characteristic ADR is hyperglycaemia. Janus kinase inhibitors and interleukin inhibitors are most often associated with gastrointestinal disorders and hypertransaminasemia;neutropenia is also characteristic of a number of interleukin inhibitors. Haemostatic adverse reactions to anticoagulants depend on the patient's dosing regimen and condition. Drug-drug interactions are a common problem in COVID-19 treatment, with the combination of nirmatrelvir and ritonavir showing the largest number of significant interactions attributed to their pharmacokinetics. Currently, there is data on the role of pharmacogenetic biomarkers in the safety and clinical outcomes of COVID-19 therapy. Thus, to improve the safety of COVID-19 therapy, an integrated approach is needed that will take into account both the clinical, demographic, and pharmacogenetic predictors of ADRs and the risk of drug-drug interactions.Copyright © 2023 Safety and Risk of Pharmacotherapy. All rights reserved.
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Objective: The COVID-19 pandemic, which started in Wuhan, China and affected the whole world, still represents a unique global challenge with its contagiousness and lethality. The symptoms of COVID-19 patients may differ depending on the severity of the disease. According to the report published by the Ministry of Health Coronavirus Research Advisory Board on the diagnosis, treatment and control of COVID-19, drug combination therapy (hydroxychloroquine, lopinavir / ritonavir and favipiravir) is recommended by health authorities. Drug-drug interaction is a possible situation as a result of simultaneous use of these drugs, which are metabolized by cytochrome P 450 enzymes (CYP), which are mostly found in the liver, with some other drugs. In this review, we aimed to show the pharmacokinetic drug-drug interactions of the drugs used in the treatment of COVID-19, especially by indicating the metabolism pathways. Result and Discussion: The COVID-19 pandemic adversely affects social life, economic and financial markets worldwide. Appropriate treatment protocols are of great importance but taking drug-drug interactions into account in treatment practices prevents unwanted results in patient treatment.Copyright © 2021 University of Ankara. All rights reserved.
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COVID-19 creates unique challenges for medical monitors The clinical research community is experiencing unprecedented challenges when it comes to treating COVID-19 and its associated symptoms, particularly tracking the impact of offlabel use of existing medicines, repurposed drugs, new standard of care protocols, and new therapies under investigation. To protect patients' safety throughout the course of a study in this environment, the role of medical monitoring should be redefined from an analog process perspective that heavily relies on reviewing spreadsheets, to utilizing modern review methodologies that focus on data science. To adapt to this need, medical monitoring needs to move from data handling in silos using old-school methods to new methods that enable the synchronous interaction of data monitors with stakeholders who handle data.
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The decision to use voriconazole for suspected COVID-19-associated pulmonary aspergillosis (CAPA) is based on clinical judgement weighed against concerns about its potential toxicity. We assessed the safety profile of voriconazole for patients with suspected CAPA by conducting a retrospective study of patients across two intensive care units. We compared changes in any liver enzymes or bilirubin and any new or increasing corrected QT interval (QTc) prolongation following voriconazole use to patient baseline to indicate possible drug effect. In total, 48 patients with presumed CAPA treated with voriconazole were identified. Voriconazole therapy was administered for a median of 8 days (interquartile range [IQR] 5-22) and the median level was 1.86 mg/L (IQR 1.22-2.94). At baseline, 2% of patients had a hepatocellular injury profile, 54% had a cholestatic injury profile, and 21% had a mixed injury profile. There were no statistically significant changes in liver function tests over the first 7 days after voriconazole initiation. At day 28, there was a significant increase in alkaline phospahte only (81-122 U/L, P = 0.006), driven by changes in patients with baseline cholestatic injury. In contrast, patients with baseline hepatocellular or mixed injury had a significant decrease in alanine transaminase and aspartate transaminase. Baseline QTc was 437 ms and remained unchanged after 7 days of voriconazole therapy even after sensitivity analysis for concomitantly administered QT prolonging agents. Therefore, at the doses used in this study, we did not detect evidence of significant liver or cardiac toxicity related to voriconazole use. Such information can be used to assist clinicians in the decision to initiate such treatment.
Our study did not show significant voriconazole-related liver or cardiac side effects in a critically ill cohort of patients with suspected COVID-19-associated pulmonary aspergillosis. These findings may allay specific clinician concerns when commencing therapy for such patients.
Subject(s)
COVID-19 , Pulmonary Aspergillosis , Animals , Voriconazole/adverse effects , Antifungal Agents/adverse effects , Retrospective Studies , Triazoles/adverse effects , COVID-19/veterinary , Pulmonary Aspergillosis/drug therapy , Pulmonary Aspergillosis/veterinaryABSTRACT
Background: Anticipating the correlation between SARS-CoV-2 infection and ‘triplenegative breast cancer (TNBC)' remains challenging. It has been reported that people currently diagnosed with cancer have a higher risk of severe complications if they are affected by the viral infection. Cancer treatments, including chemotherapy, targeted therapies, and immunotherapy, may weaken the immune system and possibly cause critical lung damage and breathing problems. Special attention must be paid to the ‘comorbidity condition' while estimating the risk of severe SARSCoV- 2 infection in TNBC patients. Hence the work aims to study the correlation between triplenegative breast cancer (TNBC) and SARS-CoV-2 using biomolecular networking.Methods: The genes associated with SARS CoV-2 have been collected from curated data in Bio- GRID. TNBC-related genes have been collected from expression profiles. Molecular networking has generated a Protein-Protein Interaction (PPI) network and a Protein-Drug Interaction (PDI) network. The network results were further evaluated through molecular docking studies followed by molecular dynamic simulation.Results: The genetic correlation of TNBC and SARS-Cov-2 has been observed from the combined PPI of their proteins. The drugs interacting with the disease's closely associated genes have been identified. The docking and simulation study showed that anti-TNBC and anti-viral drugs interact with these associated targets, suggesting their influence in inhibiting both the disease mutations.Conclusion: The study suggests a slight influence of SARS-CoV-2 viral infection on Triple Negative Breast Cancer. Few anticancer drugs such as Lapatinib, Docetaxel and Paclitaxel are found to inhibit both TNBC and viral mutations. The computational studies suggest these molecules are also useful for TNBC patients to control SARS-CoV-2 infection.
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The Brownian dynamics method can give insight into the initial stages of the interaction of antiviral drug molecules with the structural components of bacteria or viruses. RAM of conventional personal computer allows calculation of Brownian dynamics of interaction of antiviral drugs with individual coronavirus S protein. However, scaling up this approach for modeling the interaction of antiviral drugs with the whole virion consisting of thousands of proteins and lipids is difficult due to high requirements for computing resources. In the case of the Brownian dynamics method, the main amount of RAM in the calculations is occupied by an array of values of the virion electrostatic potential field. When the system is increased from one S protein to the whole virion, the volume of data increases significantly. The standard protocol for calculating Brownian dynamics uses a three-dimensional grid with a spatial step of 1°A to calculate the electrostatic potential field. In this work, we consider the possibility of increasing the grid spacing parameter for calculating the electrostatic potential field of individual coronavirus S proteins. In this case, the amount of RAM occupied by the electrostatic potential field is reduced, which makes it possible to use personal computers for calculations. We performed Brownian dynamics simulations of interaction of an antiviral photosensitizer molecule with S proteins of three coronaviruses SARS-CoV, MERS-CoV, and SARS-CoV-2, and demonstrated that reduction of detalization of electrostatic potential field does not influence the results of Brownian dynamics much © The Authors 2022. This paper is published with open access at SuperFri.org
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Background and ImportancePaxlovid® is indicated for the treatment of COVID-19 in adults who do not require supplemental oxygen and who are at increased risk for progressing to severe COVID-19. The Spanish Drug Agency published prioritisation criteria for it access. Paxlovid® has significant drug interactions, mainly due to ritonavir. Hospital pharmacists must validate the prescription, carrying out a thorough review of the patient‘s medical history to check its suitability, as well as the concomitant medication to avoid interactions.Aim and ObjectivesAnalyse the use of Paxlovid® in Huesca and Sector-1 of Zaragoza (Aragon, Spain) in early months post-authorisation.Material and MethodsAll Paxlovid's prescriptions from April to September 2022 were reviewed. The following variables were collected: gender, age, vaccination schedule, prioritised high-risk criteria and renal function. All concomitant medication was reviewed for drug interactions using a protocol created by Coordination Unit for the Rational Drug Use of Aragon. The observations made to the prescribing physician by the hospital pharmacist were recorded.Results40 requests were received. 5 were prescription errors. 29 (82.9%) were accepted and 6 (17.1%) rejected. Median age (years, interquartile-range q1-q3) was 52.2 (45.6–65.3), 57.1% were male. Vaccination status was complete primary vaccination with booster-dose (62.8%) followed by complete vaccination (25.7%) and incomplete vaccination (11.5%). As high-risk criteria prioritised, 91.4% belonged to group composed by immunocompromised persons. 91.4% had renal function >60ml/min. Only in 3 cases (8.6%) the prescribing physician indicated the patient had potential drug interactions.All patients had concomitant medication, median of 8 drugs (4–10). 60% had any potential interaction, with serious drug interactions in 42.9% of them. Drugs with potential serious interactions were statins (5/11);benzodiazepines (2/11) and antithrombotic agents (2/11).44.8% prescriptions were accepted with recommendations to modify or temporary stop some of the patient‘s usual treatment. 80% of the rejected cases were due to serious drug interactions.Conclusion and RelevanceIn the use of Paxlovid®, the role of hospital pharmacists was crucial, as drug interactions were detected in 60% of patients and were serious in 42.9% of them, leading to recommendations for adjustments in patients‘ drug therapy in almost half of the cases, with potentially serious drug interactions being the main reason to not dispense Paxlovid®.References and/or AcknowledgementsConflict of InterestNo conflict of interest
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Tacrolimus is commonly used for immunosuppression in patients following solid organ transplantation. For transplant patients with COVID-19 infection, early treatment is indicated due to the risk of progression to severe disease. However, the first line agent, nirmatrelvir/ritonavir, has multiple drug-drug interactions. We report a case of tacrolimus toxicity in a patient with a history of renal transplant due to enzyme inhibition related to nirmatrelvir/ritonavir. An 85-year-old woman with a history of multiple comorbidities presented to the emergency department (ED) with weakness, increasing confusion, poor oral intake, and inability to walk. She had been recently diagnosed with COVID-19 infection and was prescribed nirmatrelvir/ritonavir due to her underlying comorbidities and immune suppression. In the ED, she was dehydrated and had an acute kidney injury (creatinine 2.1 mg/dL, up from a baseline of 0.8 mg/dL). The tacrolimus concentration on initial labs was 143 ng/mL (5-20 ng/mL) and it continued to rise despite being held, to a peak of 189 ng/mL on hospital day 3. The patient was treated with phenytoin for enzyme induction and the tacrolimus concentration began to fall. She was discharged to a rehabilitation facility after a 17 day hospitalization. ED physicians must be cognizant of drug-drug interactions when prescribing nirmatrelvir/ritonavir and evaluating patients recently treated with the drug to identify toxicity due to these interactions.
Subject(s)
COVID-19 , Ritonavir , Humans , Female , Aged, 80 and over , Ritonavir/adverse effects , COVID-19 Drug Treatment , Tacrolimus/adverse effects , Antiviral AgentsABSTRACT
Of fundamental importance in biochemical and biomedical research is understanding a molecule's biological properties—its structure, its function(s), and its activity(ies). To this end, computational methods in Artificial Intelligence, in particular Deep Learning (DL), have been applied to further biomolecular understanding—from analysis and prediction of protein–protein and protein–ligand interactions to drug discovery and design. While choosing the most appropriate DL architecture is vitally important to accurately model the task at hand, equally important is choosing the features used as input to represent molecular properties in these DL models. Through hypothesis testing, bioinformaticians have created thousands of engineered features for biomolecules such as proteins and their ligands. Herein we present an organizational taxonomy for biomolecular features extracted from 808 articles from across the scientific literature. This objective view of biomolecular features can reduce various forms of experimental and/or investigator bias and additionally facilitate feature selection in biomolecular analysis and design tasks. The resulting dataset contains 1360 nondeduplicated features, and a sample of these features were classified by their properties, clustered, and used to suggest new features. The complete feature dataset (the Public Repository of Engineered Features for Molecular Deep Learning, PREFMoDeL) is released for collaborative sourcing on the web.
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Evidence is scarce to guide the use of nonsteroidal anti-inflammatory drugs (NSAIDs) to mitigate SARS-CoV-2 vaccine related adverse effects, given the possibility of blunting the desired immune response. In this pilot study, we deeply phenotyped a small number of volunteers who did or did not take NSAIDs concomitant with SARS-CoV-2 immunizations to seek initial information on the immune response. A SARS-CoV-2 vaccine specific RBD-IgG antibody response and efficacy in the evoked neutralization titers were evident irrespective of concomitant NSAID consumption. Given the sample size, only a large and consistent signal of immunomodulation would have been detectable, and this was not apparent. However, the information gathered may inform the design of a definitive clinical trial. Here, we report a series of divergent omics signals that invite additional hypotheses testing. Significance Statement A SARS-CoV-2 vaccine specific immune response was evident irrespective of concomitant NSAID consumption in a clinical pilot study of small sample size.
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Drug-drug interaction potentials of ensitrelvir, a novel oral inhibitor of 3C-like protease of severe acute respiratory syndrome coronavirus 2, for drug transporters were evaluated by in vitro and clinical studies. The target drug transporters assessed were P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), organic anion transporting polypeptide (OATP) 1B1, OATP1B3, organic anion transporter (OAT) 1, OAT3, organic cation transporter (OCT) 1, OCT2, and multidrug and toxin extrusion 1 and 2K. In vitro study revealed that ensitrelvir is a substrate for P-gp and BCRP and inhibits P-gp, BCRP, OATP1B1, OATP1B3, OCT1, and OAT3. Based on these results, a clinical drug-drug interaction study to evaluate the effect of ensitrelvir on the pharmacokinetics of P-gp, BCRP, OATP1B1, OATP1B3, and OCT1 substrates was conducted with a cocktail approach using digoxin (P-gp substrate), rosuvastatin (BCRP, OATP1B1, and OATP1B3 substrate), and metformin (OCT1 substrate). The cocktail was administered first, and after the washout period, the cocktail was coadministered with 500 mg of ensitrelvir. No treatment-emergent adverse events were observed. Pharmacokinetic analyses demonstrated that the ratios (90% confidence intervals) of "cocktail with ensitrelvir" to "cocktail without ensitrelvir" for maximum plasma concentration and area under the plasma concentration-time curve were, respectively, 2.17 (1.72-2.73) and 1.31 (1.13-1.52) for digoxin, 1.97 (1.73-2.25) and 1.65 (1.47-1.84) for rosuvastatin, and 1.03 (0.91-1.16) and 1.02 (0.94-1.11) for metformin. The results indicate that the exposure levels of digoxin and rosuvastatin increased when coadministered with ensitrelvir, but those of metformin were not changed. In conclusion, ensitrelvir has an impact on the exposure levels of P-gp, BCRP, OATP1B1, and OATP1B3 substrates.
Subject(s)
COVID-19 , Metformin , Organic Anion Transporters , Humans , ATP Binding Cassette Transporter, Subfamily G, Member 2/metabolism , SARS-CoV-2 , Rosuvastatin Calcium/pharmacokinetics , Protease Inhibitors , Neoplasm Proteins/metabolism , Membrane Transport Proteins/metabolism , Drug Interactions , ATP Binding Cassette Transporter, Subfamily B, Member 1/metabolism , Digoxin/pharmacokinetics , Enzyme Inhibitors , Organic Cation Transporter 1 , Metformin/pharmacokinetics , Biological Transport , Solute Carrier Organic Anion Transporter Family Member 1B3/metabolismABSTRACT
Background: Direct oral anticoagulants (DOACs) are widely used in patients with atrial fibrillation and venous thromboembolism. However, DOACs have important potential drug-drug interactions (DDIs) with several classes of drugs. In particular, antiepileptic (AE) drugs may induce cytochrome P450 3A4 or P-glycoprotein. Co-administration of DOACs and AE drugs may result in lower DOAC drug levels and reduced DOAC efficacy. However, the clinical significance of such DDIs is uncertain. Objectives: The aim of this systematic review was to generate an updated review of these DDIs and their clinical relevance, given the rapidly evolving knowledge relating to DOAC and AE DDIs. Methods: We searched the MEDLINE and Embase databases for studies reporting clinical adverse outcomes (thrombotic events, bleeding events, and all-cause mortality) in patients concomitantly taking DOACs and AE drugs. Results: We retrieved 874 studies of which 15 were deemed eligible for this review, including 4 congress abstracts, 3 case reports, 2 letters to the editor, 5 retrospective cohorts, and 1 prospective cohort study. No randomized clinical trials were found. Most of the included studies reported thrombotic events, 3 studies reported major bleeding, and one study reported all-cause mortality associated with DOAC and AE drug administration. Substantial differences in the study designs did not allow for a meta-analysis to be performed. Conclusion: The current literature assessing these adverse clinical outcomes from DOAC and AE drug co-administration is limited. Although the available data point to a possible increased risk of thrombotic events, they are insufficient to draw definitive conclusions. Well-designed clinical studies are of utmost importance.
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Introduction:Coronavirus disease 2019 (COVID-19) has become a pandemic with 1771514 cases identified in the world and 70029 cases in Iran until April 12, 2020. The co-prescription of psychotropics with COVID-19 medication is not uncommon. Healthcare providers should be familiar with many Potential Drug-Drug Interactions (DDIs) between COVID-19 therapeutic agents and psychotropic drugs based on cytochrome P450 metabolism. This review comprehensively summarizes the current literature on DDIs between antiretroviral drugs and chloroquine/hydroxychloroquine, and psychotropics, including antidepressants, antipsychotics, mood stabilizers, and anxiolytics.Methods:Medical databases, including Google Scholar, PubMed, Web of Science, and Scopus were searched to identify studies in English with keywords related to psychiatric disorders, medications used in the treatment of psychiatric disorders and COVID-19 medications.Results:There is a great potential for DDIs between psychiatric and COVID-19 medications ranging from interactions that are not clinically apparent (minor) to those that produce life-threatening adverse drug reactions, or loss of treatment efficacy. The majority of interactions are pharmacokinetic interactions via the cytochrome P450 enzyme system.Conclusion:DDIs are a major concern in the comorbidity of psychiatric disorders and COVID-19 infection resulting in the alteration of expected therapeutic outcomes. The risk of toxicity or lack of efficacy may occur due to a higher or lower plasma concentration of medications. However, psychiatric medication can be safely used in combination with COVID-19 pharmacotherapy with either a wise selection of medication with the least possibility of interaction or careful patient monitoring and management.
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4CPS-043 Table 1DDI category, n(%) C: monitor therapy D: consider therapy modification X: avoid concomitant use 24(46.2) 16(30.8) 12(23.1) ATC of DDI, n (%) N-nervous system C-cardiovascular system B-blood and blood forming organs G-genito urinary system H-systemic hormonal preparations L-antineoplastic and immunomodulating agents A-alimentary tract and metabolism M-musculo-skeletal system R-respiratory system 21(40.4) 13(25) 5(9.6) 4(7.7) 3(5.8) 2(3.8) 2(3.8) 1(1.9) 1(1.9) Medical department with DDI, n(%) Haematology Oncology Nephrology Pneumology Emergency room 6(23.1) 4(15.4) 3(11.5) 3(11.5) 3(11.5) Pharmacy intervention on concomitant drugs, n(%) Discontinuation Adverse events monitoring Dose reduction Substitution Efficacy monitoring 23(44.2) 15(28.8) 7(13.5) 5(9.6) 2(3.8) Statistical significant differences were found with ATC and DDI category (p<0.001): cardiovascular system drugs had more X-category DDI (41.7%) and nervous system drugs had more C-category DDI (60.8%).Haematology department had more patients presenting any DDI (23.1%, p=0.047).No DDI provoked any adverse event during treatment with nirmatrelvir/ritonavir.Conclusion and RelevanceA high risk for DDI with nirmatrelvir/ritonavir was found, although most of them were mild and none provoked any adverse event. Cardiovascular system drugs showed the most severe DDI.Haematology patients and those receiving nervous system drugs had higher prevalence for DDI.Almost half of pharmacy recommendations were to discontinue the drug presenting the DDI. None of the pharmaceutical interventions induced any adverse event derived from the modification of concomitant treatment during nirmatrelvir/ritonavir administration.References and/or AcknowledgementsConflict of InterestNo conflict of interest
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Background and ImportanceNirmatrelvir/ritonavir (Paxlovid®) has been recently authorised for treating coronavirus disease 2019 (COVID-19) in adults who do not require supplemental oxygen and who are at increased risk for progressing to severe disease. Due to multiple drugs metabolised by CYP3A may have significant interactions with ritonavir, physicians and pharmacists should work together for the safe and effective use of paxlovid.Aim and ObjectivesTo describe the pharmacist interventions (PIs) in the emergency department (ED) regarding optimisation of paxlovid prescriptions in non-hospitalised COVID-19 patients.Material and MethodsAn observational prospective study was conducted from 1 April 2022 to 31 August 2022 in a 1000-bed university hospital. Clinical variables were obtained using electronic medical records. We registered demographic data (sex, age), vaccination status and comorbidities, hospitalisation and prescription with other therapies (such as remdesivir and baricitinib) after paxlovid treatment, posology, potential drug interactions and contraindications. PIs were classified into the following types: (1) dose adjustment, (2) contraindication, (3) potential interaction, (4) non-compliance with the indication. We also identified primary non-adherence to paxlovid.ResultsWe included 77 patients, 56% female, median age of 67 years (IQR 52-81). Most patients (87%) were fully vaccinated (including booster dose), 12% required subsequent hospitalisation for COVID-19, none of them died and only one patient required remdesivir as other therapies. In relation to comorbidities, 86% of patients had respiratory diseases, 33% hypertension, 30% cancer treated with chemotherapy, 21% autoimmune diseases, 17% renal disease, 16% diabetes mellitus, 9% liver disease. The percentage of patients with PIs was 70%. The total of PIs carried out was 87:(1) 31%, (2) 13%, (3) 33%, (4) 23%. Forty-six potential interactions were detected being the most frequent: statins (33%), antihypertensives (11%), anticoagulants (6%), immunosuppressants (6%), among other drugs, as well as, 14 contraindications, in which statins again stood out. Primary non-adherence was detected in 10% of patients. 100% of PI were accepted.Conclusion and RelevanceHospital pharmacists are key in the optimisation of paxlovid prescriptions in the ED. This includes assessing for potential drug interactions, as well as contraindications, among other PIs. Due to the recent conditional marketing authorisation of paxlovid, it is important to encourage multidisciplinary work to reduce potential dosing errors and adverse reactions, increasing patient safety.References and/or AcknowledgementsConflict of InterestNo conflict of interest
ABSTRACT
The safety of COVID-19 pharmacotherapy is a relevant issue, first of all, because of the current lack of experience with using particular medicinal products and with off-label prescribing. The aim of the study was to analyse information on potential adverse drug reactions (ADRs) and their predictors in etiology- and pathogenesis-oriented COVID-19 therapy. According to literature data, the main clinically significant risk factors for COVID-19 patients to develop an ADR are the duration of their hospital stay, combined use of antivirals, polypharmacy, and their history of drug allergies. The most common adverse reactions to antivirals, to virus-neutralising antibodies, and to human anti-COVID-19 immunoglobulin and convalescent plasma are, respectively, gastrointestinal and hepatobiliary disorders;gastrointestinal disorders, neurological disorders, and allergic reactions;and transfusion reactions (fever, chills, etc.). For pathogenesis-oriented therapy with systemic glucocorticosteroids, the most characteristic ADR is hyperglycaemia. Janus kinase inhibitors and interleukin inhibitors are most often associated with gastrointestinal disorders and hypertransaminasemia;neutropenia is also characteristic of a number of interleukin inhibitors. Haemostatic adverse reactions to anticoagulants depend on the patient's dosing regimen and condition. Drug-drug interactions are a common problem in COVID-19 treatment, with the combination of nirmatrelvir and ritonavir showing the largest number of significant interactions attributed to their pharmacokinetics. Currently, there is data on the role of pharmacogenetic biomarkers in the safety and clinical outcomes of COVID-19 therapy. Thus, to improve the safety of COVID-19 therapy, an integrated approach is needed that will take into account both the clinical, demographic, and pharmacogenetic predictors of ADRs and the risk of drug-drug interactions.Copyright © 2023 Safety and Risk of Pharmacotherapy. All rights reserved.
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This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the following algorithms: (1) an algorithm for constructing the knowledge graph from drug, gene, and disease mentions in the biomedical literature;(2) an algorithm for vetting the knowledge graph from drug combinations that may pose a risk of drug interaction;(3) and two querying algorithms for searching the knowledge graph by a single drug or a combination of drugs. The resulting knowledge graph had 844 drugs, 306 gene/protein features, and 19 disease mentions. The original number of drug combinations generated was 2,001. We queried the knowledge graph to eliminate noise generated from chemicals that are not drugs. This step resulted in 614 drug combinations. When vetting the knowledge graph to eliminate the potentially risky drug combinations, it resulted in predicting 200 combinations. Our domain expert manually eliminated extra 54 combinations which left only 146 combination candidates. Our three-layered knowledge graph, empowered by our algorithms, offered a tool that predicted drug combination therapeutics for scientists who can further investigate from the viewpoint of drug targets and side effects. © 2022 IEEE.
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Objective: The COVID-19 pandemic, which started in Wuhan, China and affected the whole world, still represents a unique global challenge with its contagiousness and lethality. The symptoms of COVID-19 patients may differ depending on the severity of the disease. According to the report published by the Ministry of Health Coronavirus Research Advisory Board on the diagnosis, treatment and control of COVID-19, drug combination therapy (hydroxychloroquine, lopinavir / ritonavir and favipiravir) is recommended by health authorities. Drug-drug interaction is a possible situation as a result of simultaneous use of these drugs, which are metabolized by cytochrome P 450 enzymes (CYP), which are mostly found in the liver, with some other drugs. In this review, we aimed to show the pharmacokinetic drug-drug interactions of the drugs used in the treatment of COVID-19, especially by indicating the metabolism pathways. Result and Discussion: The COVID-19 pandemic adversely affects social life, economic and financial markets worldwide. Appropriate treatment protocols are of great importance but taking drug-drug interactions into account in treatment practices prevents unwanted results in patient treatment.Copyright © 2021 University of Ankara. All rights reserved.
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Objective: The COVID-19 pandemic, which started in Wuhan, China and affected the whole world, still represents a unique global challenge with its contagiousness and lethality. The symptoms of COVID-19 patients may differ depending on the severity of the disease. According to the report published by the Ministry of Health Coronavirus Research Advisory Board on the diagnosis, treatment and control of COVID-19, drug combination therapy (hydroxychloroquine, lopinavir / ritonavir and favipiravir) is recommended by health authorities. Drug-drug interaction is a possible situation as a result of simultaneous use of these drugs, which are metabolized by cytochrome P 450 enzymes (CYP), which are mostly found in the liver, with some other drugs. In this review, we aimed to show the pharmacokinetic drug-drug interactions of the drugs used in the treatment of COVID-19, especially by indicating the metabolism pathways. Result and Discussion: The COVID-19 pandemic adversely affects social life, economic and financial markets worldwide. Appropriate treatment protocols are of great importance but taking drug-drug interactions into account in treatment practices prevents unwanted results in patient treatment.Copyright © 2021 University of Ankara. All rights reserved.