Safety of Pharmacotherapy in COVID-19 Patients: A Literature Review.

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.

Pharmacokinetic evaluation of drug-drug interactions in the treatment of COVID-19.

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.

Evaluation of Drug-Drug Interactions of Ensitrelvir, a SARS-CoV-2 3CL Protease Inhibitor, With Transporter Substrates Based on In Vitro and Clinical Studies.

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.

Safety of Pharmacotherapy in COVID-19 Patients: A Literature Review.

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.

Pharmacokinetic evaluation of drug-drug interactions in the treatment of COVID-19.

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.

Pharmacokinetic evaluation of drug-drug interactions in the treatment of COVID-19.

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.

Paxlovid-Induced Tacrolimus Toxicity in the Treatment of COVID-19: A Case Report.

PaxlovidTM (nirmaltrelvir/ritonavir) received emergency use authorization from the Food and Drug Administration (FDA) in December 2021 to treat coronavirus disease 2019 (COVID-19). Given the actions of Paxlovid on cytochrome P450-3A4 (CYP3A4) enzymes, it is imperative to check for potential drug-drug interactions before prescribing. We describe a case in which the common emergency department presentation of generalized weakness was found to be caused by interactions between Paxlovid and a patient's home medications resulting in tacrolimus toxicity.

Pharmacokinetics under the COVID-19 storm.

AIMS: The storm-like nature of the health crises caused by COVID-19 has led to unconventional clinical trial practices such as the relaxation of exclusion criteria. The question remains: how can we conduct diverse trials without exposing subgroups of populations to potentially harmful drug exposure levels? The aim of this study was to build a knowledge base of the effect of intrinsic/extrinsic factors on the disposition of several repurposed COVID-19 drugs. METHODS: Physiologically based pharmacokinetic (PBPK) models were used to study the change in the pharmacokinetics (PK) of drugs repurposed for COVID-19 in geriatric patients, different race groups, organ impairment and drug-drug interactions (DDIs) risks. These models were also used to predict epithelial lining fluid (ELF) exposure, which is relevant for COVID-19 patients under elevated cytokine levels. RESULTS: The simulated PK profiles suggest no dose adjustments are required based on age and race for COVID-19 drugs, but dose adjustments may be warranted for COVID-19 patients also exhibiting hepatic/renal impairment. PBPK model simulations suggest ELF exposure to attain a target concentration was adequate for most drugs, except for hydroxychloroquine, azithromycin, atazanavir and lopinavir/ritonavir. CONCLUSION: We demonstrate that systematically collated data on absorption, distribution, metabolism and excretion, human PK parameters, DDIs and organ impairment can be used to verify simulated plasma and lung tissue exposure for drugs repurposed for COVID-19, justifying broader patient recruitment criteria. In addition, the PBPK model developed was used to study the effect of age and ethnicity on the PK of repurposed drugs, and to assess the correlation between lung exposure and relevant potency values from in vitro studies for SARS-CoV-2.

Drug-Drug Interactions among Patients Hospitalized with COVID-19 in Greece.

The modulation of the pharmacological action of drugs due to drug-drug interactions (DDIs) is a critical issue in healthcare. The aim of this study was to evaluate the prevalence and the clinical significance of potential DDIs in patients admitted to the University Hospital of Heraklion in Greece with coronavirus disease 2019 (COVID-19). Cardiovascular disorders (58.4%) and diabetes (types I and II) (29.6%) were the most common comorbidities. A high occurrence of DDIs was observed, and clinically significant DDIs that may hamper response to treatment represented 40.3% of cases on admission, 21% during hospitalization, and 40.7% upon discharge. Polypharmacy and comorbidities were associated with a higher prevalence of DDIs in a statistically significant way (p < 0.05, 95% CI). Clinically significant DDIs and increased C-reactive protein values upon admission were associated with prolonged hospitalization. The results reveal that patients admitted due to COVID-19 in Greece often have an additional burden of DDIs that healthcare teams should approach and resolve.

Knowledge4COVID-19: A semantic-based approach for constructing a COVID-19 related knowledge graph from various sources and analyzing treatments' toxicities.

In this paper, we present Knowledge4COVID-19, a framework that aims to showcase the power of integrating disparate sources of knowledge to discover adverse drug effects caused by drug-drug interactions among COVID-19 treatments and pre-existing condition drugs. Initially, we focus on constructing the Knowledge4COVID-19 knowledge graph (KG) from the declarative definition of mapping rules using the RDF Mapping Language. Since valuable information about drug treatments, drug-drug interactions, and side effects is present in textual descriptions in scientific databases (e.g., DrugBank) or in scientific literature (e.g., the CORD-19, the Covid-19 Open Research Dataset), the Knowledge4COVID-19 framework implements Natural Language Processing. The Knowledge4COVID-19 framework extracts relevant entities and predicates that enable the fine-grained description of COVID-19 treatments and the potential adverse events that may occur when these treatments are combined with treatments of common comorbidities, e.g., hypertension, diabetes, or asthma. Moreover, on top of the KG, several techniques for the discovery and prediction of interactions and potential adverse effects of drugs have been developed with the aim of suggesting more accurate treatments for treating the virus. We provide services to traverse the KG and visualize the effects that a group of drugs may have on a treatment outcome. Knowledge4COVID-19 was part of the Pan-European hackathon#EUvsVirus in April 2020 and is publicly available as a resource through a GitHub repository and a DOI.

Cardiovascular Drug Interactions With Nirmatrelvir/Ritonavir in Patients With COVID-19: JACC Review Topic of the Week.

Nirmatrelvir-ritonavir (NMVr) is used to treat symptomatic, nonhospitalized patients with coronavirus disease-2019 (COVID-19) who are at high risk of progression to severe disease. Patients with cardiovascular risk factors and cardiovascular disease are at a high risk of developing adverse events from COVID-19 and as a result have a higher likelihood of receiving NMVr. Ritonavir, the pharmaceutical enhancer used in NMVr, is an inhibitor of the enzymes of CYP450 pathway, particularly CYP3A4 and to a lesser degree CYP2D6, and affects the P-glycoprotein pump. Co-administration of NMVr with medications commonly used to manage cardiovascular conditions can potentially cause significant drug-drug interactions and may lead to severe adverse effects. It is crucial to be aware of such interactions and take appropriate measures to avoid them. In this review, we discuss potential drug-drug interactions between NMVr and commonly used cardiovascular medications based on their pharmacokinetics and pharmacodynamic properties.

Detecting drug-drug interactions between therapies for COVID-19 and concomitant medications through the FDA adverse event reporting system.

Background: COVID-19 patients with underlying medical conditions are vulnerable to drug-drug interactions (DDI) due to the use of multiple medications. We conducted a discovery-driven data analysis to identify potential DDIs and associated adverse events (AEs) in COVID-19 patients from the FDA Adverse Event Reporting System (FAERS), a source of post-market drug safety. Materials and Methods: We investigated 18,589 COVID-19 AEs reported in the FAERS database between 2020 and 2021. We applied multivariate logistic regression to account for potential confounding factors, including age, gender, and the number of unique drug exposures. The significance of the DDIs was determined using both additive and multiplicative measures of interaction. We compared our findings with the Liverpool database and conducted a Monte Carlo simulation to validate the identified DDIs. Results: Out of 11,337 COVID-19 drug-Co-medication-AE combinations investigated, our methods identified 424 signals statistically significant, covering 176 drug-drug pairs, composed of 13 COVID-19 drugs and 60 co-medications. Out of the 176 drug-drug pairs, 20 were found to exist in the Liverpool database. The empirical p-value obtained based on 1,000 Monte Carlo simulations was less than 0.001. Remdesivir was discovered to interact with the largest number of concomitant drugs (41). Hydroxychloroquine was detected to be associated with most AEs (39). Furthermore, we identified 323 gender- and 254 age-specific DDI signals. Conclusion: The results, particularly those not found in the Liverpool database, suggest a subsequent need for further pharmacoepidemiology and/or pharmacology studies.

A biomedical knowledge graph-based method for drug-drug interactions prediction through combining local and global features with deep neural networks.

Drug-drug interactions (DDIs) prediction is a challenging task in drug development and clinical application. Due to the extremely large complete set of all possible DDIs, computer-aided DDIs prediction methods are getting lots of attention in the pharmaceutical industry and academia. However, most existing computational methods only use single perspective information and few of them conduct the task based on the biomedical knowledge graph (BKG), which can provide more detailed and comprehensive drug lateral side information flow. To this end, a deep learning framework, namely DeepLGF, is proposed to fully exploit BKG fusing local-global information to improve the performance of DDIs prediction. More specifically, DeepLGF first obtains chemical local information on drug sequence semantics through a natural language processing algorithm. Then a model of BFGNN based on graph neural network is proposed to extract biological local information on drug through learning embedding vector from different biological functional spaces. The global feature information is extracted from the BKG by our knowledge graph embedding method. In DeepLGF, for fusing local-global features well, we designed four aggregating methods to explore the most suitable ones. Finally, the advanced fusing feature vectors are fed into deep neural network to train and predict. To evaluate the prediction performance of DeepLGF, we tested our method in three prediction tasks and compared it with state-of-the-art models. In addition, case studies of three cancer-related and COVID-19-related drugs further demonstrated DeepLGF's superior ability for potential DDIs prediction. The webserver of the DeepLGF predictor is freely available at http://120.77.11.78/DeepLGF/.

Tools supporting polypharmacy management in Italy: Factors determining digital technologies' intention to use in clinical practice.

Background and Aims: INTERCheckWEB is one of the most outstanding digital technologies, that could be implemented at the hospital level, supporting the clinicians in the evaluation of the therapy appropriateness, reducing the potentially inappropriate prescriptions, for the improvement of the clinical decision-making process. The paper aims at investigating the relationship between clinicians' behaviors towards digital decision support system in therapy appropriateness for elderly patients in polytherapy in medical departments, defining the factors that could influence clinicians to use INTERCheckWEB, for supporting drugs' prescription. Methods: A questionnaire was administered to 70 clinicians referring to Internal Medicine wards, of four Italian hospitals. The authors assessed how perceived usefulness, perceived ease of use, image, and output quality, would affect INTERCheckWeb intention to use. Inferential statistics, by means of a regression analysis, were conducted to define the main aspects useful to understand the factors impacting on such digital technology adoption in clinical practice. Results: The regression analysis reported that image, perceived ease of use and perceived usefulness, as well as the moderator effect of the voluntary use between the perceived usefulness and the intention to use, are the factors that most influence the use of INTERCheckWEB (adjusted R 2 = 0.870). Conclusions: Results demonstrated that clinicians would use INTERCheckWEB, when available, to identify all the information on situations that could be dangerous for the patients, thus limiting the drug-drug interactions, optimizing the overall patient's clinical pathway. Furthermore, the implementation of INTERCheckWEB could also contribute to the proper management of COVID-19 patients, since both hospitalized and symptomatic COVID-19 patients are frequently older, with comorbidities.

Detecting Drug-Drug Interactions in COVID-19 Patients.

COVID-19 patients with multiple comorbid illnesses are more likely to be using polypharmacy to treat their COVID-19 disease and comorbid conditions. Previous literature identified several DDIs in COVID-19 patients; however, various DDIs are unrecognized. This study aims to discover novel DDIs by conducting comprehensive research on the FDA Adverse Event Reporting System (FAERS) data from January 2020 to March 2021. We applied seven algorithms to discover DDIs. In addition, the Liverpool database containing DDI confirmed by clinical trials was used as a gold standard to determine novel DDIs in COVID-19 patients. The seven models detected 2,516 drug-drug pairs having adverse events (AEs), 49 out of which were confirmed by the Liverpool database. The remaining 2,467 drug pairs tested to be significant by the seven models can be candidate DDIs for clinical trial hypotheses. Thus, the FAERS database, along with informatics approaches, provides a novel way to select candidate drug-drug pairs to be examined in COVID-19 patients.

Ways to Improve Insights into Clindamycin Pharmacology and Pharmacokinetics Tailored to Practice.

Given the increase in bacterial resistance and the decrease in the development of new antibiotics, the appropriate use of old antimicrobials has become even more compulsory. Clindamycin is a lincosamide antibiotic approved for adults and children as a drug of choice for systemic treatment of staphylococcal, streptococcal, and gram-positive anaerobic bacterial infections. Because of its profile and high bioavailability, it is commonly used as part of an oral multimodal alternative for prolonged parenteral antibiotic regimens, e.g., to treat bone and joint or prosthesis-related infections. Clindamycin is also frequently used for (surgical) prophylaxis in the event of beta-lactam allergy. Special populations (pediatrics, pregnant women) have altered cytochrome P450 (CYP)3A4 activity. As clindamycin is metabolized by the CYP3A4/5 enzymes to bioactive N-demethyl and sulfoxide metabolites, knowledge of the potential relevance of the drug's metabolites and disposition in special populations is of interest. Furthermore, drug-drug interactions derived from CYP3A4 inducers and inhibitors, and the data on the impact of the disease state on the CYP system, are still limited. This narrative review provides a detailed survey of the currently available literature on pharmacology and pharmacokinetics and identifies knowledge gaps (special patient population, drug-drug, and drug-disease interactions) to describe a research strategy for precision medicine.

Assessing the proportion of the Danish population at risk of clinically significant drug-drug interactions with new oral antivirals for early treatment of COVID-19.

OBJECTIVES: The oral antiviral drugs nirmatrelvir/ritonavir (NMV/r) and molnupiravir have been approved for early outpatient treatment of COVID-19 to prevent severe disease. Ritonavir, contained in NMV/r, is known to have significant drug-drug interactions (DDI) with several drugs frequently used by the elderly. This communication puts the problem with DDI with oral antiviral COVID-19 treatment into perspective by assessing the percentage of the elderly population at risk of severe COVID-19, using drugs with significant DDI with oral antivirals. METHODS: We estimated the size of the Danish population at risk of significant DDI with antiviral COVID-19 treatment using the number of claimed prescriptions for drugs predicted to interact with NMV/r in Denmark in 2020. RESULTS: Danish prescription data demonstrate the extensive use of drugs likely to interact with NMV/r. Anticoagulants contraindicated during NMV/r treatment were used by 20% of people ≥65 years and 30% of people ≥80 years. Statins that must be paused during NMV/r treatment were used by 15-18%. More than one in five used either analgesics, calcium channel blockers, or digoxin. CONCLUSION: There is major potential for significant DDI with NMV/r in the elderly population at risk of severe COVID-19 disease. This calls for clear guidance for prescribers to ensure patient safety and treatment success.

Prescription cannabidiol for seizure disorder management: Initial drug-drug interaction management by specialty pharmacists.

PURPOSE: To describe the presence, type, and management of drug-drug interactions (DDIs) at prescription cannabidiol (CBD) therapy initiation. METHODS: We conducted a single-center, retrospective study of patients prescribed CBD from a medical center's neurology clinic for seizure management from January 2019 through April 2020. Patients were excluded if they were enrolled in a CBD clinical trial or the insurance approval or medication fulfillment process was not completed by the center's specialty pharmacy. The primary outcomes were the numbers, types, and management of DDIs identified at the time of CBD prescribing. RESULTS: Of the 136 patients included, 109 (80%) had a DDI identified at baseline. Of the 260 DDIs, 71% (n = 184) were pharmacodynamic and 29% (n = 76) were pharmacokinetic in nature. Management of the 260 DDIs detected included counseling only (89% [n = 232 interactions]), discontinuation of the interacting agent [9% (n = 22 interactions]), and dosage change for the interacting agent [2% (n = 6 interactions]). Clobazam was the most commonly identified interacting medication (n = 63, 24%), while valproic acid accounted for 10% (n = 26) of the DDIs. The population was predominantly white (n = 115, 85%), 18 years of age or younger (n = 92, 68%), and had an indication for prescription CBD treatment of Lennox-Gastaut syndrome (n = 117, 86%). CONCLUSION: This study provides new information on the role that integrated specialty pharmacists can play in identifying and managing initial DDIs in patients starting prescription CBD.

Major revision version 11.0 of the European AIDS Clinical Society Guidelines 2021.

BACKGROUND: The European AIDS Clinical Society (EACS) Guidelines were revised in 2021 for the 17th time with updates on all aspects of HIV care. KEY POINTS OF THE GUIDELINES UPDATE: Version 11.0 of the Guidelines recommend six first-line treatment options for antiretroviral treatment (ART)-naïve adults: tenofovir-based backbone plus an unboosted integrase inhibitor or plus doravirine; abacavir/lamivudine plus dolutegravir; or dual therapy with lamivudine or emtricitabine plus dolutegravir. Recommendations on preferred and alternative first-line combinations from birth to adolescence were included in the new paediatric section made with Penta. Long-acting cabotegravir plus rilpivirine was included as a switch option and, along with fostemsavir, was added to all drug-drug interaction (DDI) tables. Four new DDI tables for anti-tuberculosis drugs, anxiolytics, hormone replacement therapy and COVID-19 therapies were introduced, as well as guidance on screening and management of anxiety disorders, transgender health, sexual health for women and menopause. The sections on frailty, obesity and cancer were expanded, and recommendations for the management of people with diabetes and cardiovascular disease risk were revised extensively. Treatment of recently acquired hepatitis C is recommended with ongoing risk behaviour to reduce transmission. Bulevirtide was included as a treatment option for the hepatitis Delta virus. Drug-resistant tuberculosis guidance was adjusted in accordance with the 2020 World Health Organization recommendations. Finally, there is new guidance on COVID-19 management with a focus on continuance of HIV care. CONCLUSIONS: In 2021, the EACS Guidelines were updated extensively and broadened to include new sections. The recommendations are available as a free app, in interactive web format and as an online pdf.