Aim: We hypothesize that the efficacy of COVID-19 therapeutic candidates will be better predicted by understanding their effects at various points on a viral cell cycle, in particular, the specific rate constants, and that drugs acting independently of these specific discrete sites may not yield expected efficacy. We hypothesize that drugs, or combinations of drugs that act at specific multiple sites on the viral life cycle have the highest probability of success in the treatment of early infection phase in COVID-19 patients. Methods: Using a target cell limited model structure that had been used to characterize viral load dynamics from COVID-19 patients, we performed simulations to show that combinations of therapeutics targeting specific rate constants have greater probability of efficacy and supportive rationale for clinical trial evaluation. Results: Based on the known kinetics of the SARS-CoV-2 life cycle, we rank ordered potential targeted approaches involving repurposed, low-potency agents. We suggest that targeting multiple points central to viral replication within infected host cells or release from those cells is a viable strategy for reducing both viral load and host cell infection. In addition, we observed that the time-window opportunity for a therapeutic intervention to effect duration of viral shedding exceeds the effect on sparing epithelial cells from infection or impact on viral load AUC. Furthermore, the impact on reduction on duration of shedding may extend further in patients who exhibit a prolonged shedder phenotype. Conclusions: Our work highlights the use of model-informed tools to better rationalize effective treatments for COVID-19.
Aim To assess clinical outcomes and adverse drug events in patients hospitalised with COVID -19 treated with off- label hydroxychloroquine and azithromycin. Methods We performed a retrospective analysis of hospitalised COVID-19+ patients who received hydroxychloroquine plus azithromycin over a 2 week period. The primary end point was clinical improvement on day 7 defined as either hospital discharge or an improvement of two points on a six-category ordinal scale. Secondary outcomes evaluated included mortality at day 28, ICU admission, requirement for mechanical ventilation and incidence of adverse drug events. Results Data from a total of 82 patients with laboratory confirmed SARS-CoV-2 infection was evaluated. Clinical improvement was seen in 26.8% of patients at Day 7. 31% of patients were admitted to ICU, 16 (19.5%) underwent mechanical ventilation and Day 28 mortality was 28%. Age over 70, history of cardiovascular disease and 3 or more comorbidities were risk factors for mortality. The incidence of adverse drug events was 42%. No patient experienced a Grade 4 or 5 toxicity. Over a fifth of patients (23) had raised LFTs (65% had raised LFTs at baseline), 11 patients experienced prolonged QT and 1 patient experienced grade 1 hypoglycaemia. Treatment was stopped early in 6(7.3%) patients due to prolonged QT interval or LFT elevations. Conclusion This descriptive study details the clinical outcomes of COVID-19 positive patients treated with these agents and highlights the importance of monitoring all repurposed agents for adverse drug events.
AIM: The main objective was to determine the prevalence of prescribing issues in HIV-infected subjects ≥65 years according to the Beers and STOPP/START criteria and drug-drug interactions (Liverpool website). Secondary objectives were to assess the concordance between Beers and STOPP/START criteria in our population, and to identify the drugs most frequently involved in the prescribing issues. METHODS: Cross-sectional cohort study based on a systematic review of the electronic drug prescriptions of 91 HIV-infected patients aged ≥65 years. Discrepancies between prescription criteria were assessed using crosstabs and compared using the Chi-square test or Fisher exact test. RESULTS: The mean age was 72.1 (5.6) years, 75.8% had ≥3 comorbidities, and 59.3% polypharmacy. Prescribing issues were identified in 87.9%; 71.4% by STOPP/START and 45.1% by Beers. Comparing both criteria, 56.9% of prescribing issues by STOPP/START were detected by Beers, while 92.5% of those detected by the Beers criteria were detected by STOPP/START (p<0.001). Orange/red flag interactions were found in 45.1%: 3 severe (red) in 2 patients (2.2%). The most frequent drugs involved in prescribing issues were benzodiazepines (>30%). Cobicistat was the drug most frequently involved in interactions (42.9%). CONCLUSIONS: The prevalence of prescribing issues among older HIV-infected persons gives cause for concern, as it is almost 90%. Optimization strategies, including a critical review of the treatment plan, should be implemented in clinical routine by a multidisciplinary team, in particular in patients with multiple comorbidities and polypharmacy. The STOPP/START criteria should be recommended for European populations, since they seem to better detect prescribing issues.
Aims: The investigation regarding the clinical significance of programmed cell death protein-1 (PD-1)-targeted immunotherapy in Chinese patients is rare. This study evaluated safety and efficacy of PD-1 with Toripalimab, Camrelizumab or Sintilimab for Chinese Hepatocellular carcinoma (HCC) patients in a real-life cohort. Methods: We retrospectively analyzed HBV associated HCC patients treated with Toripalimab, Camrelizumab or Sintilimab in a retrospective cohort from Nov 2018 to Dec 2019. Efficacy was evaluated with objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), time to tumor progression (TTP) and overall survival (OS). Results: Seventy eight patients were finally included in the analysis: 26 for Toripalimab, 36 for Camrelizumab, and 16 for Sintilimab. Mean duration of follow-up was 22.7 ± 12.6 weeks and the mean Cycles of PD-1 at cut-off were 4.8 ± 2.7 for all patients. The ORR and DCR for the whole cohort were 17.9% and 73.1%, respectively. Overall, 21 (26.9%) patients had radiological disease progression and 6 (7.7%) patients died during follow-up. Median PFS was 40.7 (95% CI, 34.7-46.7) weeks, median TTP was 45.7 (95% CI, 40.5-60.0) weeks, and median OS was 51.1 (95% CI, 46.4-55.9) weeks. Most frequent drug-related AEs were Rash (19.2%), Hypertension (15.4%), Fatigue (12.8%), Paraesthesia (12.8%), and Diarrhoea (10.3%). Conclusions: Our findings suggest that: 1. PD-1-targeted immunotherapy with Toripalimab, Camrelizumab or Sintilimab yielded a promising outcome in Chinese HBV patients with HCC; 2. Immunotherapy was well tolerated generally and had manageable side effects, which is worth of popularization and application in clinical practice.
Quantitative systems pharmacology (QSP) is a relatively new discipline within modelling and simulation that has gained wide attention over the past few years. The application of QSP models spans drug-target identification and validation, through all drug development phases as well as clinical applications. Due to their detailed mechanistic nature, QSP models are capable of extrapolating knowledge to predict outcomes in scenarios that have not been tested experimentally making them an important resource in experimental and clinical pharmacology. However, these models are complicated to work with due to their size and inherent complexity. This makes many applications of QSP models for simulation, parameter estimation and trial design computationally intractable. A number of techniques have been developed to simplify QSP models into smaller models that are more amenable to further analyses while retaining their accurate predictive capabilities. Different simplification techniques have different strengths and weaknesses and hence different utilities. Understanding the utilities of different methods is essential for selection of the best method for a particular situation. In this paper, we have created an overall framework for model simplification techniques that allows a natural categorisation of methods based on their utility. We provide a brief description of the concept underpinning the different methods and example applications. A summary of the utilities of methods is intended provide a guide to modellers in their model endeavours to simplify these complicated models.
In a recent issue of Br J Clin Pharmacol Smith et al1 published an outstanding commentary titled ‘Dosing will be a key success factor in repurposing antivirals for Covid-19’. They highlighted that the success in our repurposing efforts will be dependent on ‘getting the dose right’ for drugs which have been developed for different indications and stressed some of the unique challenges of treating this particular disease. They pointed the reader to lopinavir/ritonavir (LPV/r) as an example of a repurposed antiviral and the limited experience of this drug regimen (and other treatments) in the elderly population with comorbidities – ie those most at risk from Covid-19. It is on the issue of comorbidities, polypharmacy and drug-drug interactions (DDIs) that we wish to comment.
Hundreds of researchers are working to develop a vaccine and are evaluating drugs to mitigate the adverse health and economic consequences of COVID-19 (Coronavirus disease 19) worldwide. If novel compounds are found, geopolitical and economic variables will determine their introduction to communities. Therefore, finding low-cost and widely accessible drugs for prevention or treatment of COVID-19 would be ideal.A recent study found that ivermectin, an FDA-approved anti-parasitic drug, has inhibitory effects on replication of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1. Ivermectin has broad anti-viral activity through inhibition of viral proteins including importin α/β1 heterodimer and integrase protein2. Caly and colleagues reported that the addition of ivermectin at a concentration of 5 micromolar (μM) (twice the reported IC50) to Vero-hSLAM cells, 2 hours post infection with SARS-CoV-2, resulted in a reduction in the viral RNA load by 99.98% at 48 hours1. The authors suggested that this drug could reduce the viral load in infected patients, with potential effect on disease progression and spread.While the findings by Caly and colleagues provide some promise, there is no evidence that the 5 μM concentration of ivermectin used by Caly and colleagues in their in vitro SARS-CoV-2 experiment, can be achieved in vivo . The pharmacokinetics of ivermectin in humans is well described (Figure 1)3-5, and even with the highest reported dose of approximately 1700 µg/kg (i.e. 8.5 times the FDA-approved dose of 200 μg/kg), the maximum plasma concentration was only 0.28 µM5. This is 18 times lower than the concentration required to reduce viral replication of SARS-CoV-2in vitro . Ivermectin accumulation in tissues is mild and would not be sufficient to achieve the antiviral effect with conventional doses6. Although high doses of ivermectin in adults or children are well tolerated5,7, the clinical effects of ivermectin at a concentration of 5 μM range are unknown and may be associated with toxicity. Consequently, ivermectin has in vitroactivity against SARS-CoV-2 but this effect is unlikely to be observedin vivo using current dosing.Amidst fear of the pandemic, the public and some physicians are now using ivermectin off-label for prophylaxis or as adjuvant therapy for COVID-19. Because ivermectin is only commercially available as a 3 or 6 mg tablets or a 6 mg/ml oral suspension, in order to administer a high dose, some people may experiment with more concentrated veterinary formulations. These actions are not based on clinical trials and have motivated cautionary statements from institutions such as the FDA against the use of pharmaceutical formulations of ivermectin intended for animals as therapeutics in humans 8.Potential avenues for further investigation into repurposing ivermectin for SARS-CoV-2 may be to: (i) develop an inhaled formulation to efficiently deliver a high local concentration in the lung, whilst minimizing systemic exposure; and (ii) evaluate more potent ivermectin analogs (e.g. doramectin) which may also inhibit SARS-CoV-2. These are areas for research – clearly, further studies are needed before ivermectin can be used for the prevention and treatment of COVID-19. As recently discussed in BJCP, this highlights the critical need to consider pharmacological principles to guide in vitro testing when repurposing old drugs for therapeutic use against COVID-199.
Aims In the absence of a commonly agreed dosing protocol based on pharmacokinetic considerations, the dose and treatment duration for hydroxychloroquine (HCQ) COVID-19 disease currently vary across national guidelines and clinical study protocols. We have used a model-based approach to explore the relative impact of alternative dosing regimens proposed in different dosing protocols for hydroxychloroquine in COVID-19. Methods We compared different PK exposures using Monte Carlo simulations based on a previously published population pharmacokinetic model in patients with rheumatoid arthritis, externally validated using both independent data in lupus erythematous patients and recent data in French COVID-19 patients. Clinical efficacy and safety information from COVID-19 patients treated with HCQ were used to contextualize and assess the actual clinical value of the model predictions. Results Literature and observed clinical data confirm the variability in clinical responses in COVID-19 when treated with the same fixed doses. Confounding factors were identified that should be taken into account for dose recommendation. For 80% of patients, doses higher than 800mg day on D1 followed by 600mg daily on following days might not be needed for being cured. Limited adverse drug reactions have been reported so far for this dosing regimen, most often confounded by co-medications, comorbidities or underlying COVID-19 disease effects. Conclusion Our results were clear indicating the unmet need for characterization of target PK exposures to inform HCQ dosing optimization in COVID-19. Dosing optimization for HCQ in COVID-19 is still an unmet need. Efforts in this sense are a prerequisite for best the benefit/risk balance.
Background: In Italy both the consumption of antibiotics and the prevalence of bacterial resistance are higher than in other European countries. In 2017, the first National Action Plan on Antimicrobial Resistance (PNCAR) was adopted in Italy. In response to the PNCAR two National Reports on Antibiotics’ use in the human setting have been published. The article’s aim is to describe the pattern of antibiotics consumption in the community setting in Italy from 2013 to 2018. Methods: In order to analyse the consumption for reimbursed antibiotics dispensed by community pharmacies different data sources were used. Consumption was measured in terms of Defined Daily Dose (DDD), prescriptions or prevalence of use. Results: In 2018, the consumption of antibiotics in Italy amounted to 16.1 DDD per 1,000 inhabitants per day. The rates of consumption by geographical area were: 12.7 DDD in the North, 16.9 in the Centre and 20.4 in the South. The use was greater in the extreme age groups than in the population aged from 20 to 64 years. The consumption was higher in winter season with high peaks in the incidence of flu syndromes. In the paediatric population, a utilization rate of 1,010 prescriptions per 1,000 children, with a prevalence of use of 40.8%, was found. Conclusion: The study provides useful information on geographical variability of antibiotics’ use in Italy to guide decision makers in the introduction of tailored interventions, as suggested by PNCAR, aimed at promoting a more rational use of antibiotics for humans and reducing antimicrobial resistance.
Aims: To determine if the combination of exercise and statin could normalize postprandial triglyceridemia (PPTG) in hypercholesteraemic individuals. Mehods: Eight hypercholesteraemic (blood cholesterol 182±38 mg·dL-1; LDL-c 102±32 mg·dL-1) overweight (BMI 30±4 kg·m-2) individuals with metabolic syndrome (i.e., Met Synd) were compared to a group of eight metabolically healthy controls (i.e., MetH, blood cholesterol 149±23 mg·dL-1; LDL-c 77±23 mg·dL-1, and BMI 23±2 kg·m-2). Each group underwent two PPTG tests, either 14-h after a bout of intense exercise (EXER) or without previous exercise (REST). Additionally, Met Synd individuals were tested 96 h after withdrawal of their habitual statin medication (PLAC trials) to study medication effects. Results: A bout of exercise before the test meal did not reduce PPTG in Met Synd (P=0.347), but reduced PPTG by 46% in MetH (224±142 to 413±267 mg·dL-1·for 5 h iAUC; P=0.02). In both trials (i.e., REST and EXER) statin withdrawal in Met Synd greatly increased PPTG (average 65%; P<0.01), mean LDL-c (average 25%; P<0.01), total cholesterol (average 16%; P<0.01) and Apo B48 (24%; P<0.01), without interference from exercise. However, Apo B100 was not affected by statin withdrawal. Conclusions: Hypercholesteraemic Met Synd individuals (compared to metabolically healthy controls) are resistant to the effects of exercise on reducing PPTG. However, chronic statin medication blunts the elevations in TG after a fat meal (i.e., iAUC of PPTG) reducing their cardiovascular risk associated to their atherogenic dyslipidemia. Statin decreases PPTG by reducing the secretion or accelerating the catabolism of intestinal Apo B48.
Personalization of oral small molecule anticancer drug doses based on individual patient blood drug levels, also known as therapeutic drug monitoring or TDM, has the potential to significantly improve the effectiveness of treatment by maximizing drug efficacy and minimize toxicity. However, this option has not yet been widely embraced by the oncology community. Some reasons for this include increased logistical complexity of dose individualization, the lack of clinical laboratories that measure small molecule drug concentrations in support of patient care, and the lack of reimbursement of costs. However, the main obstacle may be the lack of studies clearly demonstrating that monitoring of oral small molecule anticancer drug levels actually improves clinical outcomes. Without unequivocal evidence in support of TDM-guided dose individualization, especially demonstration of improved survival with TDM in randomized controlled trials, wide acceptance of this approach by oncologists and reimbursement by insurance companies is unlikely, and patients may continue to suffer as a result of receiving incorrect drug doses. This article reviews the current status of therapeutic drug monitoring of oral small molecule drugs in oncology and intends to provide strategic insights into the design of studies for evaluating the utility of TDM in this clinical context.
The deployment of artesunate for severe malaria and the artemisinin combination therapies (ACTs) for uncomplicated malaria has been a major advance in antimalarial therapeutics. These drugs have reduced treated mortality, accelerated recovery, and reduced treatment failure rates and transmission from the treated infection. These drugs remain highly effective against falciparum malaria in most malaria endemic areas but significant resistance has emerged in the Greater Mekong subregion of Southeast Asia. Resistance to artemisinin was followed by resistance in the ACT partner drugs, and fit multidrug resistant parasite lineages have now spread widely across the region. ACTs are highly effective against P. vivax and the other malaria species. Recent studies show that radical curative regimens of primaquine (to prevent relapse) can be shortened to seven days, and that the newly introduced single dose tafenoquine is an alternative, although the currently recommended dose is insufficient in Southeast Asia and Oceania. Targeted malaria elimination using focal mass treatments with dihydroartemisinin-piperaquine have proved safe and effective malaria elimination accelerators, but progress overall towards malaria elimination is very slow. Indeed since 2015 overall malaria case numbers globally have risen.
Initiation of statin treatment is suggested to increase the international normalised ratio (INR) among warfarin users. However, available data is limited and conflicting. We conducted a register-based cohort study to evaluate the drug-drug interaction between warfarin and statins. By linking data on INR measurements and filled prescriptions, we identified warfarin users 2000-2015 initiating simvastatin (n=1,363), atorvastatin (n=165), or rosuvastatin (n=23). Simvastatin initiation led to an increase in mean INR from 2.40 to 2.71, with INRs peaking after 4 weeks, corresponding to a mean change of 0.32 (95%CI 0.25-0.38). High-dose and low-dose simvastatin led to comparable changes (mean change 0.33 vs 0.29). Initiation of atorvastatin and rosuvastatin lead to INR increases of 0.27 (95%CI 0.12-0.42) and 0.30 (95%CI -0.09-0.69). In conclusion, initiation of simvastatin, atorvastatin, or rosuvastatin among warfarin users led to a minor increase in INR. The magnitude of this change is for most patients likely of limited clinical relevance.
Tyrosine kinase inhibitors (TKIs) have revolutionized the management of chronic myeloid leukemia (CML), and currently in patients with CML in chronic phase (CML-CP) the first-line treatment is based on BCR-ABL targeted therapy with TKIs . Although generally well tolerated, all BCR-ABL TKIs can be associated with hematologic and non-hematologic toxicities . Most of the patients with CML-CP continue receiving TKIs, unless there is lack of optimal response and/or serious toxicities.