Physiologically-Based Pharmacokinetic Modeling of PAXLOVID™ with First-Order Absorption Kinetics.

PURPOSE: PAXLOVID™ is nirmatrelvir tablets co-packaged with ritonavir tablets. Ritonavir is used as a pharmacokinetics (PK) enhancer to reduce metabolism and increase exposure of nirmatrelvir. This is the first disclosure of Paxlovid physiologically-based pharmacokinetic (PBPK) model. METHODS: Nirmatrelvir PBPK model with first-order absorption kinetics was developed using in vitro, preclinical, and clinical data of nirmatrelvir in the presence and absence of ritonavir. Clearance and volume of distribution were derived from nirmatrelvir PK obtained using a spray-dried dispersion (SDD) formulation where it is considered to be dosed as an oral solution, and absorption is near complete. The fraction of nirmatrelvir metabolized by CYP3A was estimated based on in vitro and clinical ritonavir drug-drug interaction (DDI) data. First-order absorption parameters were established for both SDD and tablet formulation using clinical data. Nirmatrelvir PBPK model was verified with both single and multiple dose human PK data, as well as DDI studies. Simcyp® first-order ritonavir compound file was also verified with additional clinical data. RESULTS: The nirmatrelvir PBPK model described the observed PK profiles of nirmatrelvir well with predicted AUC and Cmax values within ± 20% of the observed. The ritonavir model performed well resulting in predicted values within twofold of observed. CONCLUSIONS: Paxlovid PBPK model developed in this study can be applied to predict PK changes in special populations, as well as model the effect of victim and perpetrator DDI. PBPK modeling continues to play a critical role in accelerating drug discovery and development of potential treatments for devastating diseases such as COVID-19. NCT05263895, NCT05129475, NCT05032950 and NCT05064800.

Species differences in plasma protein binding of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease inhibitor nirmatrelvir.

Plasma protein binding (PPB) studies on the SARS-CoV-2 main protease inhibitor nirmatrelvir revealed considerable species differences primarily in dog and rabbit, which prompted further investigations into the biochemical basis for these differences.The unbound fraction (fu) of nirmatrelvir in dog and rabbit plasma was concentration (2-200 µM)-dependent (dog fu,p 0.024-0.69, rabbit fu,p 0.010-0.82). Concentration (0.1-100 µM)-dependent binding in serum albumin (SA) (fu,SA 0.040-0.82) and alpha-1-acid glycoprotein (AAG) (fu,AAG 0.050-0.64) was observed in dogs. Nirmatrelvir showed minimal binding to rabbit SA (1-100 µM: fu,SA 0.70-0.79), while binding to rabbit AAG was concentration-dependent (0.1-100 µM: fu,AAG 0.024-0.66). In contrast, nirmatrelvir (2 µM) revealed minimal binding (fu,AAG 0.79-0.88) to AAG from rat and monkeys. Nirmatrelvir showed minimal-to-moderate binding to SA (1-100 µM; fu,SA 0.70-1.0) and AAG (0.1-100 µM; fu,AAG 0.48-0.58) from humans across tested concentrations.Nirmatrelvir molecular docking studies using published crystal structures and homology models of human and preclinical species SA and AAG were used to rationalise the species differences to plasma proteins. This suggested that species differences in PPB are primarily driven by molecular differences in albumin and AAG resulting in differences in binding affinity.

Disposition of Nirmatrelvir, an Orally Bioavailable Inhibitor of SARS-CoV-2 3C-Like Protease, across Animals and Humans.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3C-like protease inhibitor PF-07321332 (nirmatrelvir), in combination with ritonavir (Paxlovid), was recently granted emergency use authorization by multiple regulatory agencies for the treatment of coronavirus disease 2019 (COVID-19) in adults and pediatric patients. Disposition studies on nirmatrelvir in animals and in human reagents, which were used to support clinical studies, are described herein. Plasma clearance was moderate in rats (27.2 ml/min per kg) and monkeys (17.1 ml/min per kg), resulting in half-lives of 5.1 and 0.8 hours, respectively. The corresponding oral bioavailability was moderate in rats (34%-50%) and low in monkeys (8.5%), primarily due to oxidative metabolism along the gastrointestinal tract in this species. Nirmatrelvir demonstrated moderate plasma protein binding in rats, monkeys, and humans with mean unbound fractions ranging from 0.310 to 0.478. The metabolism of nirmatrelvir was qualitatively similar in liver microsomes and hepatocytes from rats, monkeys, and humans; prominent metabolites arose via cytochrome P450 (CYP450)-mediated oxidations on the P1 pyrrolidinone ring, P2 6,6-dimethyl-3-azabicyclo[3.1.0]hexane, and the tertiary-butyl group at the P3 position. Reaction phenotyping studies in human liver microsomes revealed that CYP3A4 was primarily responsible (fraction metabolized = 0.99) for the oxidative metabolism of nirmatrelvir. Minor clearance mechanisms involving renal and biliary excretion of unchanged nirmatrelvir were also noted in animals and in sandwich-cultured human hepatocytes. Nirmatrelvir was a reversible and time-dependent inhibitor as well as inducer of CYP3A activity in vitro. First-in-human pharmacokinetic studies have demonstrated a considerable boost in the oral systemic exposure of nirmatrelvir upon coadministration with the CYP3A4 inhibitor ritonavir, consistent with the predominant role of CYP3A4 in nirmatrelvir metabolism. SIGNIFICANCE STATEMENT: The manuscript describes the preclinical disposition, metabolism, and drug-drug interaction potential of PF-07321332 (nirmatrelvir), an orally active peptidomimetic-based inhibitor of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3CL protease, which has been granted emergency use authorization by multiple regulatory agencies around the globe for the treatment of coronavirus disease 2019 (COVID-19) in COVID-19-positive adults and pediatric patients who are at high risk for progression to severe COVID-19, including hospitalization or death.

An oral SARS-CoV-2 Mpro inhibitor clinical candidate for the treatment of COVID-19.

The worldwide outbreak of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global pandemic. Alongside vaccines, antiviral therapeutics are an important part of the healthcare response to countering the ongoing threat presented by COVID-19. Here, we report the discovery and characterization of PF-07321332, an orally bioavailable SARS-CoV-2 main protease inhibitor with in vitro pan-human coronavirus antiviral activity and excellent off-target selectivity and in vivo safety profiles. PF-07321332 has demonstrated oral activity in a mouse-adapted SARS-CoV-2 model and has achieved oral plasma concentrations exceeding the in vitro antiviral cell potency in a phase 1 clinical trial in healthy human participants.

From impossible to possible: the lessons from the control of recent COVID-19 outbreaks in China.

The COVID-19 pandemic has catastrophically impacted the world. Before the success in vaccination, this virus shows no sign of stop spreading. Nearly all the countries have implemented stringent approaches to slow down the transmission of the virus, but the virus still caused over 2 million deaths and the number is increasing. Therefore, preventing the virus spreading is still necessary to protect most people, especially the ones with pre-conditions. Mainland China has successfully eradicated the COVID-19 virus infection in Wuhan in 2020. After that, several small-scale outbreaks occurred in many cities in China, but none of these COVID-19 virus infections caused the widespread. In this review, we would like to give a detailed presentation of the approaches that were implemented by the China government to suppress the virus spreading by considering the unique characteristics of this virus and the paths of the virus transmission. Both the pros and cons of these strategies will also be analyzed. The experiences and lessons learned during the virus-fighting in China, expectedly, will be a useful source of reference for other regions in overcoming the threat caused by the COVID-19 virus.

Applications of the CRISPR-Cas system for infectious disease diagnostics.

INTRODUCTION: Rapid and accurate diagnostic approaches are essential for impeding the spread of infectious diseases. This review aims to summarize current progress of clustered regularly interspaced short palindromic repeats (CRISPR)-associated (Cas) systems in the applications for diagnostics of infectious diseases including the ongoing COVID-19 epidemic. AREAS COVERED: In this review, we discuss class 2 CRISPR-Cas biosensing systems-based diagnostics in various emerging and reemerging infectious diseases, CRISPR-Cas systems have created a new era for early diagnostics of infectious diseases, especially with the discovery of the collateral cleavage activity of Cas12 and Cas13. We mainly focus on different CRISPR-Cas effectors for the detection of pathogenic microorganisms as well as provide a detailed explanation of the pros and cons of CRISPR-Cas biosensing systems. In addition, we also introduce future research perspectives. EXPERT COMMENTARY: However, further improvement of newly discovered systems and engineering existing ones should be developed to increase the specificity, sensitivity or stability of the diagnostic tools. It may be a long journey to finish the clinical transition from research use. CRISPR-Cas approaches will emerge as more promising and robust tools for infectious disease diagnosis in the future.

CT-based radiomics for predicting the rapid progression of coronavirus disease 2019 (COVID-19) pneumonia lesions.

OBJECTIVES: To develop and validate a radiomic model to predict the rapid progression (defined as volume growth of pneumonia lesions > 50% within seven days) in patients with coronavirus disease 2019 (COVID-19). METHODS: Patients with laboratory-confirmed COVID-19 who underwent longitudinal chest CT between January 01 and February 18, 2020 were included. A total of 1316 radiomic features were extracted from the lung parenchyma window for each CT. The least absolute shrinkage and selection operator (LASSO), Relief, Las Vegas Wrapper (LVW), L1-norm-Support Vector Machine (L1-norm-SVM), and recursive feature elimination (RFE) were applied to select the features that associated with rapid progression. Four machine learning classifiers were used for modeling, including Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR), and Decision Tree (DT). Accordingly, 20 radiomic models were developed on the basis of 296 CT scans and validated in 74 CT scans. Model performance was determined by the receiver operating characteristic curve. RESULTS: A total of 107 patients (median age, 49.0 years, interquartile range, 35-54) were evaluated. The patients underwent a total of 370 chest CT scans with a median interval of 4 days (interquartile range, 3-5 days). The combination methods of L1-norm SVM and SVM with 17 radiomic features yielded the highest performance in predicting the likelihood of rapid progression of pneumonia lesions on next CT scan, with an AUC of 0.857 (95% CI: 0.766-0.947), sensitivity of 87.5%, and specificity of 70.7%. CONCLUSIONS: Our radiomic model based on longitudinal chest CT data could predict the rapid progression of pneumonia lesions, which may facilitate the CT follow-up intervals and reduce the radiation. ADVANCES IN KNOWLEDGE: Radiomic features extracted from the current chest CT have potential in predicting the likelihood of rapid progression of pneumonia lesions on the next chest CT, which would improve clinical decision-making regarding timely treatment.

Analysis of 8 274 cases of new coronavirus nucleic acid detection and co-infection in Wuhan / 中华检验医学杂志

Objective@#To investigate the positive rate for 2019-nCoV tests and co-infections in Wuhan district.@*Methods@#A total of 8 274 cases in Wuhan were enrolled in this cross-sectional study during January 20 to February 9, 2020, and were tested for 2019-nCoV using fluorescence quantitative PCR. Both respiratory tract samples (nasopharynx, oropharynx, sputum and alveolar lavage fluid) and non-respiratory tract samples (urine, feces, anal swabs, blood and conjunctival sac swabs) were collected. If both orf1ab and N genes are positive, they are classified as nucleic acid test positive group; if both orf1ab and N genes are negative, they are classified as negative group; if single gene target is positive, they are classified as suspicious group. Individuals were divided into male group and female group according to sex. At the same time, 316 patients were tested for 13 respiratory pathogens by multiplex PCR.@*Results@#Among the 8 274 subjects, 2 745 (33.2%) were 2019-nCoV infected; 5 277 (63.8%) subjects showed negative results in the 2019-nCoV nucleic acid test; and 252 cases (3.05%) was not definitive (inconclusive result). The age of cases with COVID-19 patients and inconclusive cases was significantly higher than that of cases without 2019-nCoV infection (40 vs 56, t=27.569, P<0.001; 52 vs 56, t=6.774, P<0.001). The positive rate of 13 respiratory pathogens multiple tests was significantly lower in 104 subjects who were positive for 2019-nCoV compared with those in subjects who were negative for 2019-nCoV test (5.77% vs 18.39%, χ2=24.105, P=0.003). Four types of respiratory tract samples and five types of non-respiratory tract samples were found to be positive for 2019-nCoV nucleic acid test.@*Conclusion@#The 2019-nCoV nucleic acid positive rate in male is higher than in female. Co-infections should be pay close attention in COVID-19 patients. 2019-nCoV nucleic acid can be detected in non-respiratory tract samples.

Clinical diagnosis of 8274 samples with 2019-novel coronavirus in Wuhan (preprint)

Background: 2019-Novel coronavirus (2019-nCoV) outbreaks create challenges for hospital laboratories because thousands of samples must be evaluated each day. Sample types, interpretation methods, and corresponding laboratory standards must be established. The possibility of other infections should be assessed to provide a basis for clinical classification, isolation, and treatment. Accordingly, in the present study, we evaluated the testing methods for 2019-nCoV and co-infections. Methods: We used a fluorescence-based quantitative PCR kit urgently distributed by the Chinese CDC to detect 8274 close contacts in the Wuhan region against two loci on the 2019-nCoV genome. We also analyzed 613 patients with fever who underwent multiple tests for 13 respiratory pathogens; 316 subjects were also tested for 2019-nCoV. Findings: Among the 8274 subjects, 2745 (33.2%) had 2019-nCoV infection; 5277 (63.8%) subjects showed negative results in the 2019-nCoV nucleic acid test (non-019-nCoV); and 252 cases (3.0%) because only one target was positive, the diagnosis was not definitive. Sixteen patients who originally had only one positive target were re-examined a few days later; 14 patients (87.5%) were finally defined as 2019-nCoV-positive, and 2 (12.5%) were finally defined as negative. The positive rates of nCoV-NP and nCovORF1ab were 34.7% and 34.7%, respectively. nCoV-NP-positive only and nCovORF1ab-positive cases accounted for 1.5% and 1.5%, respectively. In the 316 patients with multiple respiratory pathogens, 104 were positive for 2019-nCov and 6/104 had co-infection with coronavirus (3/104), influenza A virus (2/104), rhinovirus (2/104), and influenza A H3N2 (1/104); the remaining 212 patients had influenza A virus (11/202), influenza A H3N2 (11/202), rhinovirus (10/202), respiratory syncytial virus (7/202), influenza B virus (6/202), metapneumovirus (4/202), and coronavirus (2/202). Interpretation: Clinical testing methods for 2019-nCoV require improvement. Importantly, 5.8% of 2019-nCoV infected and 18.4% of non-2019-nCoV-infected patients had other pathogen infections. It is important to treat combined infections and perform rapid screening to avoid cross-contamination of patients. A test that quickly and simultaneously screens as many pathogens as possible is needed.