Safety Profile of Molnupiravir with Significant Effect on COVID-19: A Review

Background: As the COVID era unfolds, researchers reveal that rapid changes in viral genetic material allow viruses to circumvent challenges triggered by the host immune system and resist anti-viral drugs, potentially leading to persistent viral manifestations in host cells. Molnupiravir (RNA-dependent RNA polymerase inhibitor) is a novel anti-viral medicine promising a vital role in coming setbacks.Objectives: This review aims to clarify the safety and efficacy of the molnupiravir molecule in light of existing case studies. As a result, it is intended to explore and discuss the molecular structure, mechanism of action, discovery and development process, preclinical research, clinical investigations, and other subtopics.Methods: A total of 75 publications were searched using multiple engines, such as Google Scholar, PubMed, Web of Science, Embase, Cochrane Library, ClinicalTrials.gov, and others, with a constraint applied to exclude publications published over 11 years ago. Molnupiravir, safety, efficacy, COVID- 19, RdRp, PK-PD, and clinical study were utilized as keywords.Results: Clinical results on molnupiravir are supported by investigations that were recently disclosed in a study on both sex volunteers (male and female) with an age restriction of 19 to 60 years, followed by a Phase-3 Clinical Trial (NCT04575584) with 775 randomly assigned participants and no fatalities reported due to treatment.Conclusion: Molnupiravir proved a high level of safety, allowing it to be tested further. This review supports the safety and efficacy of this molecule based on the established evidence, which claims the most anticipated employment of molnupiravir in COVID protocol.

All Roads Lead to Rome: Enhancing the Probability of Target Attainment with Different Pharmacokinetic/Pharmacodynamic Modelling Approaches.

In light of rising antimicrobial resistance and a decreasing number of antibiotics with novel modes of action, it is of utmost importance to accelerate development of novel treatment options. One aspect of acceleration is to understand pharmacokinetics (PK) and pharmacodynamics (PD) of drugs and to assess the probability of target attainment (PTA). Several in vitro and in vivo methods are deployed to determine these parameters, such as time-kill-curves, hollow-fiber infection models or animal models. However, to date the use of in silico methods to predict PK/PD and PTA is increasing. Since there is not just one way to perform the in silico analysis, we embarked on reviewing for which indications and how PK and PK/PD models as well as PTA analysis has been used to contribute to the understanding of the PK and PD of a drug. Therefore, we examined four recent examples in more detail, namely ceftazidime-avibactam, omadacycline, gepotidacin and zoliflodacin as well as cefiderocol. Whereas the first two compound classes mainly relied on the 'classical' development path and PK/PD was only deployed after approval, cefiderocol highly profited from in silico techniques that led to its approval. Finally, this review shall highlight current developments and possibilities to accelerate drug development, especially for anti-infectives.

Target attainment and population pharmacokinetics of flucloxacillin in critically ill patients: a multicenter study.

PURPOSE: Insufficient antimicrobial exposure has been associated with worse clinical outcomes. Reportedly, flucloxacillin target attainment in critically ill patients was heterogeneous considering the study population selection and reported target attainment percentages. Therefore, we assessed flucloxacillin population pharmacokinetics (PK) and target attainment in critically ill patients. METHODS: This prospective, multicenter, observational study was conducted from May 2017 to October 2019 and included adult, critically ill patients administered flucloxacillin intravenously. Patients with renal replacement therapy or liver cirrhosis were excluded. We developed and qualified an integrated PK model for total and unbound serum flucloxacillin concentrations. Monte Carlo dosing simulations were performed to assess target attainment. The unbound target serum concentration was four times the minimum inhibitory concentration (MIC) for ≥ 50% of the dosing interval (ƒT>4xMIC ≥ 50%). RESULTS: We analyzed 163 blood samples from 31 patients. A one-compartment model with linear plasma protein binding was selected as most appropriate. Dosing simulations revealed 26% ƒT>2 mg/L ≥ 50% following continuous infusion of 12 g flucloxacillin and 51% ƒT>2 mg/L ≥ 50% for 24 g. CONCLUSION: Based on our dosing simulations, standard flucloxacillin daily doses of up to 12 g may substantially enhance the risk of underdosing in critically ill patients. Prospective validation of these model predictions is needed.

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.

Control-based drug tailoring schemes towards personalized influenza treatment

Influenza infections continue to be a global threat. This chapter provides a current overall view of the influenza infection pathogenesis, historical landmarks with pandemic events, features of the viral particle – the virion – and treatment regimes with neuraminidase inhibitors. In addition, treatment optimization schemes are introduced integrating host infection modeling, drug dynamics under the PK/PD approach, and control-based methods. Combining inverse optimal and impulsive control, the chapter hypothesizes schemes of dose tailoring towards personalized treatment, where the dose dynamically adapts according to the viral load evolution. The proposed control-based treatment is compared with the current fixed-dose framework in terms of treatment efficacy and reduction of the total amount of drug. The chapter closes by highlighting the implications of the control-based schemes not only to tackle influenza infections but also to combat similar acute infectious diseases such as COVID-19. © 2022 Elsevier Inc. All rights reserved.

Relationship between Pharmacokinetic/Pharmacodynamic Target Attainment and Microbiological Outcome in Critically Ill COVID-19 Patients with Documented Gram-Negative Superinfections Treated with TDM-Guided Continuous-Infusion Meropenem.

OBJECTIVES: The objective of this study was to explore the relationship between pharmacokinetic/pharmacodynamic (PK/PD) target attainment of continuous-infusion (CI) meropenem and microbiological outcome in critical COVID-19 patients with documented Gram-negative superinfections. METHODS: Patients receiving CI meropenem for documented Gram-negative infections at the COVID ICU of the IRCCS Azienda Ospedaliero-Universitaria di Bologna and undergoing therapeutic drug monitoring from January 2021 to February 2022 were retrospectively assessed. Average steady-state meropenem concentrations (Css) were calculated and the Css/MIC ratio was selected as a pharmacodynamic parameter of meropenem efficacy. The Css/MIC ratio was defined as optimal if ≥4, quasi-optimal if between 1 and 4, and suboptimal if <1. The relationship between Css/MIC and microbiological outcome was assessed. RESULTS: Overall, 43 critical COVID-19 patients with documented Gram-negative infections were retrieved. Combination therapy was implemented in 26 cases. Css/MIC ratios were optimal in 27 (62.8%), quasi-optimal in 7 (16.3%), and suboptimal in 9 cases (20.9%). Microbiological failure occurred in 21 patients (48.8%), with no difference between monotherapy and combination therapy (43.8% vs. 53.8%; p = 0.53). The microbiological failure rate was significantly lower in patients with an optimal Css/MIC ratio compared to those with a quasi-optimal or suboptimal Css/MIC ratio (33.3% vs. 75.0%; p = 0.01). CONCLUSION: Suboptimal attainment of meropenem PK/PD targets may be a major determinant impacting on microbiological failure in critical COVID-19 patients with Gram-negative superinfections.

Population Pharmacokinetics of Hydroxychloroquine and 3 Metabolites in COVID-19 Patients and Pharmacokinetic/Pharmacodynamic Application.

We develop a population pharmacokinetic model for hydroxychloroquine (HCQ) and three of its metabolites (desethylhydroxychloroquine, Des HCQ; desethylchloroquine, DesCQ; and didesethylchloroquine, didesCQ) in COVID-19 patients in order to determine whether a pharmacokinetic (PK)/pharmacodynamic (PD) relationship was present. The population PK of HCQ was described using non-linear mixed effects modelling. The duration of hospitalization, the number of deaths, and poor clinical outcomes (death, transfer to ICU, or hospitalization ≥ 10 d) were evaluated as PD parameters. From 100 hospitalized patients (age = 60.7 ± 16 y), 333 BHCQ and M were available for analysis. The data for BHCQ were best described by a four-compartment model with a first-order input (KA) and a first-order output. For M, the better model of the data used one compartment for each metabolite with a first-order input from HCQ and a first-order output. The fraction of HCQ converted to the metabolites was 75%. A significant relationship was observed between the duration of hospitalization and BHCQ at 48 h (r2 = 0.12; p = 0.0052) or 72 h (r2 = 0.16; p = 0.0012). At 48 h or 72 h, 87% or 91% of patients vs. 63% or 62% had a duration < 25 d with a BHCQ higher or below 200 µg/L, respectively. Clinical outcome was significantly related to BHCQ at 48 h (good outcome 369 +/- 181 µg/L vs. poor 285 +/- 144 µg/L; p = 0.0441) but not at 72 h (407 +/- 207 µg/L vs. 311 +/- 174 µg/L; p = 0.0502). The number of deaths was not significantly different according to the trough concentration (p = 0.972 and 0.836 for 48 h and 72 h, respectively).

Real-World Use of Dalbavancin in the Era of Empowerment of Outpatient Antimicrobial Treatment: A Careful Appraisal Beyond Approved Indications Focusing on Unmet Clinical Needs.

Dalbavancin is a novel, long-acting lipoglycopeptide characterized by a long elimination half-life coupled with excellent in vitro activity against multidrug-resistant Gram-positives. Although it is currently approved only for the treatment of acute bacterial skin and skin structure infections, an ever-growing amount of evidence supports the efficacy of dalbavancin as a long-term therapy in osteomyelitis, prosthetic joint infections, endocarditis, and bloodstream infections. This article provides a critical reappraisal of real-world use of dalbavancin for off-label indications. A search strategy using specific keywords (dalbavancin, osteomyelitis, endocarditis, long-term suppressive therapy, bloodstream infection, pharmacokinetic/pharmacodynamic profile) until April 2021 was performed on the PubMed-MEDLINE database. As for other novel antibiotics, a conundrum between approved indications and potential innovative therapeutic uses has emerged for dalbavancin as well. The promising efficacy in challenging scenarios (i.e., osteomyelitis, endocarditis, prosthetic joint infections), coupled with the unique pharmacokinetic/pharmacodynamic properties, makes dalbavancin a valuable alternative to daily in-hospital intravenous or outpatient antimicrobial regimens in the treatment of long-term Gram-positive infections. This makes dalbavancin valuable in the current COVID-19 scenario, in which hospitalization and territorial medicine empowerment are unavoidable.

Mathematical Modeling of Remdesivir to Treat COVID-19: Can Dosing Be Optimized?

The antiviral remdesivir has been approved by regulatory bodies such as the European Medicines Agency (EMA) and the US Food and Drug administration (FDA) for the treatment of COVID-19. However, its efficacy is debated and toxicity concerns might limit the therapeutic range of this drug. Computational models that aid in balancing efficacy and toxicity would be of great help. Parametrizing models is difficult because the prodrug remdesivir is metabolized to its active form (RDV-TP) upon cell entry, which complicates dose-activity relationships. Here, we employ a computational model that allows drug efficacy predictions based on the binding affinity of RDV-TP for its target polymerase in SARS-CoV-2. We identify an optimal infusion rate to maximize remdesivir efficacy. We also assess drug efficacy in suppressing both wild-type and resistant strains, and thereby describe a drug regimen that may select for resistance. Our results differ from predictions using prodrug dose-response curves (pseudo-EC50s). We expect that reaching 90% inhibition (EC90) is insufficient to suppress SARS-CoV-2 in the lungs. While standard dosing mildly inhibits viral polymerase and therefore likely reduces morbidity, we also expect selection for resistant mutants for most realistic parameter ranges. To increase efficacy and safeguard against resistance, we recommend more clinical trials with dosing regimens that substantially increase the levels of RDV-TP and/or pair remdesivir with companion antivirals.

Using mixed-effects modeling to estimate decay kinetics of response to SARS-CoV-2 infection.

The duration of natural immunity in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a matter of some debate in the literature at present. For example, in a recent publication characterizing SARS-CoV-2 immunity over time, the authors fit pooled longitudinal data, using fitted slopes to infer the duration of SARS-CoV-2 immunity. In fact, such approaches can lead to misleading conclusions as a result of statistical model-fitting artifacts. To exemplify this phenomenon, we reanalyzed one of the markers (pseudovirus neutralizing titer) in the publication, using mixed-effects modeling, a methodology better suited to longitudinal datasets like these. Our findings showed that the half-life was both longer and more variable than reported by the authors. The example selected by us here illustrates the utility of mixed-effects modeling in provide more accurate estimates of the duration and heterogeneity of half-lives of molecular and cellular biomarkers of SARS-CoV-2 immunity.

The Use of Translational Modelling and Simulation to Develop Immunomodulatory Therapy as an Adjunct to Antibiotic Treatment in the Context of Pneumonia.

The treatment of respiratory tract infections is threatened by the emergence of bacterial resistance. Immunomodulatory drugs, which enhance airway innate immune defenses, may improve therapeutic outcome. In this concept paper, we aim to highlight the utility of pharmacometrics and Bayesian inference in the development of immunomodulatory therapeutic agents as an adjunct to antibiotics in the context of pneumonia. For this, two case studies of translational modelling and simulation frameworks are introduced for these types of drugs up to clinical use. First, we evaluate the pharmacokinetic/pharmacodynamic relationship of an experimental combination of amoxicillin and a TLR4 agonist, monophosphoryl lipid A, by developing a pharmacometric model accounting for interaction and potential translation to humans. Capitalizing on this knowledge and associating clinical trial extrapolation and statistical modelling approaches, we then investigate the TLR5 agonist flagellin. The resulting workflow combines expert and prior knowledge on the compound with the in vitro and in vivo data generated during exploratory studies in order to construct high-dimensional models considering the pharmacokinetics and pharmacodynamics of the compound. This workflow can be used to refine preclinical experiments, estimate the best doses for human studies, and create an adaptive knowledge-based design for the next phases of clinical development.

Development of a Minimal Physiologically-Based Pharmacokinetic Model to Simulate Lung Exposure in Humans Following Oral Administration of Ivermectin for COVID-19 Drug Repurposing.

SARS-CoV-2 utilizes the IMPα/ß1 heterodimer to enter host cell nuclei after gaining cellular access through the ACE2 receptor. Ivermectin has shown antiviral activity by inhibiting the formation of the importin-α (IMPα) and IMPß1 subunits as well as dissociating the IMPα/ß1 heterodimer and has in vitro efficacy against SARS-CoV-2. Plasma and lung ivermectin concentrations vs. time profiles in cattle were used to determine the apparent plasma to lung tissue partition coefficient of ivermectin. This coefficient, together with a simulated geometric mean plasma profile of ivermectin from a published population pharmacokinetic model, was utilized to develop a minimal physiologically-based pharmacokinetic (mPBPK) model. The mPBPK model accurately described the simulated ivermectin plasma concentration profile in humans. The mPBPK model was also used to simulate human lung exposure to ivermectin after 12, 30, and 120 mg oral doses. The simulated ivermectin lung exposures reached a maximum concentration of 772 ng/mL, far less than the estimated 1750 ng/mL IC50 reported for ivermectin against SARS-CoV-2 in vitro. Further studies of ivermectin either reformulated for inhaled delivery or in combination with other antivirals with differing mechanisms of action is needed to assess its therapeutic potential.

Concerns about pharmacokinetic (PK) and pharmacokinetic-pharmacodynamic (PK-PD) studies in the new therapeutic area of COVID-19 infection.

In the context of the COVID-19 pandemic, several drugs have been repurposed as potential candidates for the treatment of COVID-19 infection. While preliminary choices were essentially based on in vitro potency, clinical translation into effective therapies may be challenging due to unfavorable in vivo pharmacokinetic properties at the doses chosen for this new indication of COVID-19 infection. However, available pharmacokinetic and pharmacokinetic-pharmacodynamic studies suffer from severe limitations leading to unreliable conclusions, especially in term of dosing optimization. In this paper we propose to highlight these limitations and to identify some of the major requirements that need to be addressed in designing PK and PK-PD studies in this era of COVID. A special attention should be paid to pre-analytical and analytical requirements and to the proper collection of covariates affecting dose-exposure relationships (co-medications, use of specific organ support techniques and other clinical and para-clinical data). We also promote the development of population PK and PK-PD models specifically dedicated to COVID-19 patients since those previously developed for other diseases (SEL, malaria, HIV) and clinical situations (steady-state, non-ICU patients) are not representative of severe patients. Therefore, implementation of well-designed PK and PD studies targeted to COVID-19 patients is urgently needed. For that purpose we call for multi-institutional collaborative work and involvement of clinical pharmacologists in multidisciplinary research consortia.