Whole Body PBPK Modeling of Remdesivir and Its Metabolites to Aid in Estimating Active Metabolite Exposure in the Lung and Liver in Patients With Organ Dysfunction.

Remdesivir (RDV) is the first drug approved by the US Food and Drug Administration (FDA) for the treatment of coronavirus disease 2019 (COVID-19) in certain patients requiring hospitalization. As a nucleoside analogue prodrug, RDV undergoes intracellular multistep activation to form its pharmacologically active species, GS-443902, which is not detectable in the plasma. A question arises that whether the observed plasma exposure of RDV and its metabolites would correlate with or be informative about the exposure of GS-443902 in tissues. A whole body physiologically-based pharmacokinetic (PBPK) modeling and simulation approach was utilized to elucidate the disposition mechanism of RDV and its metabolites in the lungs and liver and explore the relationship between plasma and tissue pharmacokinetics (PK) of RDV and its metabolites in healthy subjects. In addition, the potential alteration of plasma and tissue PK of RDV and its metabolites in patients with organ dysfunction was explored. Our simulation results indicated that intracellular exposure of GS-443902 was decreased in the liver and increased in the lungs in subjects with hepatic impairment relative to the subjects with normal liver function. In subjects with severe renal impairment, the exposure of GS-443902 in the liver was slightly increased, whereas the lung exposure of GS-443902 was not impacted. These predictions along with the organ impairment study results may be used to support decision making regarding the RDV dosage adjustment in these patient subgroups. The modeling exercise illustrated the potential of whole body PBPK modeling to aid in decision making for nucleotide analogue prodrugs, particularly when the active metabolite exposure in the target tissues is not available.

Plasma concentrations of branched-chain amino acids differ with Holstein genetic strain in pasture-based dairy systems.

In pasture-based systems, there are nutritional and climatic challenges exacerbated across lactation; thus, dairy cows require an enhanced adaptive capacity compared with cows in confined systems. We aimed to evaluate the effect of lactation stage (21 vs. 180 days in milk, DIM) and Holstein genetic strain (North American Holstein, NAH, n = 8; New Zealand Holstein, NZH, n = 8) on metabolic adaptations of grazing dairy cows through plasma metabolomic profiling and its association with classical metabolites. Although 67 metabolites were affected (FDR < 0.05) by DIM, no metabolite was observed to differ between genetic strains while only alanine was affected (FDR = 0.02) by the interaction between genetic strain and DIM. However, complementary tools for time-series analysis (ASCA analysis, MEBA ranking) indicated that alanine and the branched-chain amino acids (BCAA) differed between genetic strains in a lactation-stage dependent manner. Indeed, NZH cows had lower (P-Tukey < 0.05) plasma concentrations of leucine, isoleucine and valine than NAH cows at 21 DIM, probably signaling for greater insulin sensitivity. Metabolic pathway analysis also revealed that, independently of genetic strains, AA metabolism might be structurally involved in homeorhetic changes as 40% (19/46) of metabolic pathways differentially expressed (FDR < 0.05) between 21 and 180 DIM belonged to AA metabolism.

Metabolite Biomarkers of CKD Progression in Children.

BACKGROUND AND OBJECTIVES: Metabolomics facilitates the discovery of biomarkers and potential therapeutic targets for CKD progression. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We evaluated an untargeted metabolomics quantification of stored plasma samples from 645 Chronic Kidney Disease in Children (CKiD) participants. Metabolites were standardized and logarithmically transformed. Cox proportional hazards regression examined the association between 825 nondrug metabolites and progression to the composite outcome of KRT or 50% reduction of eGFR, adjusting for age, sex, race, body mass index, hypertension, glomerular versus nonglomerular diagnosis, proteinuria, and baseline eGFR. Stratified analyses were performed within subgroups of glomerular/nonglomerular diagnosis and baseline eGFR. RESULTS: Baseline characteristics were 391 (61%) male; median age 12 years; median eGFR 54 ml/min per 1.73 m2; 448 (69%) nonglomerular diagnosis. Over a median follow-up of 4.8 years, 209 (32%) participants developed the composite outcome. Unique association signals were identified in subgroups of baseline eGFR. Among participants with baseline eGFR ≥60 ml/min per 1.73 m2, two-fold higher levels of seven metabolites were significantly associated with higher hazards of KRT/halving of eGFR events: three involved in purine and pyrimidine metabolism (N6-carbamoylthreonyladenosine, hazard ratio, 16; 95% confidence interval, 4 to 60; 5,6-dihydrouridine, hazard ratio, 17; 95% confidence interval, 5 to 55; pseudouridine, hazard ratio, 39; 95% confidence interval, 8 to 200); two amino acids, C-glycosyltryptophan, hazard ratio, 24; 95% confidence interval 6 to 95 and lanthionine, hazard ratio, 3; 95% confidence interval, 2 to 5; the tricarboxylic acid cycle intermediate 2-methylcitrate/homocitrate, hazard ratio, 4; 95% confidence interval, 2 to 7; and gulonate, hazard ratio, 10; 95% confidence interval, 3 to 29. Among those with baseline eGFR <60 ml/min per 1.73 m2, a higher level of tetrahydrocortisol sulfate was associated with lower risk of progression (hazard ratio, 0.8; 95% confidence interval, 0.7 to 0.9). CONCLUSIONS: Untargeted plasma metabolomic profiling facilitated discovery of novel metabolite associations with CKD progression in children that were independent of established clinical predictors and highlight the role of select biologic pathways.

Lanthionine, a Novel Uremic Toxin, in the Vascular Calcification of Chronic Kidney Disease: The Role of Proinflammatory Cytokines.

Vascular calcification (VC) is a risk factor for cardiovascular events and mortality in chronic kidney disease (CKD). Several components influence the occurrence of VC, among which inflammation. A novel uremic toxin, lanthionine, was shown to increase intracellular calcium in endothelial cells and may have a role in VC. A group of CKD patients was selected and divided into patients with a glomerular filtration rate (GFR) of <45 mL/min/1.73 m2 and ≥45 mL/min/1.73 m2. Total Calcium Score (TCS), based on the Agatston score, was assessed as circulating lanthionine and a panel of different cytokines. A hemodialysis patient group was also considered. Lanthionine was elevated in CKD patients, and levels increased significantly in hemodialysis patients with respect to the two CKD groups; in addition, lanthionine increased along with the increase in TCS, starting from one up to three. Interleukin IL-6, IL-8, and Eotaxin were significantly increased in patients with GFR < 45 mL/min/1.73 m2 with respect to those with GFR ≥ 45 mL/min/1.73 m2. IL-1b, IL-7, IL-8, IL-12, Eotaxin, and VEGF increased in calcified patients with respect to the non-calcified. IL-8 and Eotaxin were elevated both in the low GFR group and in the calcified group. We propose that lanthionine, but also IL-8 and Eotaxin, in particular, are a key feature of VC of CKD, with possible marker significance.

Integration of metabolomics, genomics, and immune phenotypes reveals the causal roles of metabolites in disease.

BACKGROUND: Recent studies highlight the role of metabolites in immune diseases, but it remains unknown how much of this effect is driven by genetic and non-genetic host factors. RESULT: We systematically investigate circulating metabolites in a cohort of 500 healthy subjects (500FG) in whom immune function and activity are deeply measured and whose genetics are profiled. Our data reveal that several major metabolic pathways, including the alanine/glutamate pathway and the arachidonic acid pathway, have a strong impact on cytokine production in response to ex vivo stimulation. We also examine the genetic regulation of metabolites associated with immune phenotypes through genome-wide association analysis and identify 29 significant loci, including eight novel independent loci. Of these, one locus (rs174584-FADS2) associated with arachidonic acid metabolism is causally associated with Crohn's disease, suggesting it is a potential therapeutic target. CONCLUSION: This study provides a comprehensive map of the integration between the blood metabolome and immune phenotypes, reveals novel genetic factors that regulate blood metabolite concentrations, and proposes an integrative approach for identifying new disease treatment targets.

Quantitative HPLC-MS/MS determination of Nuc, the active metabolite of remdesivir, and its pharmacokinetics in rat.

Remdesivir is a nucleotide analog prodrug that has received much attention since the outbreak of the COVID-19 pandemic in December 2019. GS-441524 (Nuc) is the active metabolite of remdesivir and plays a pivotal role in the clinical treatment of COVID-19. Here, a robust HPLC-MS/MS method was developed to determine Nuc concentrations in rat plasma samples after a one-step protein precipitation process. Chromatographic separation was accomplished on Waters XBrige C18 column (50 × 2.1 mm, 3.5 µm) under gradient elution conditions. Multiple reaction monitoring transitions in electrospray positive ion mode were m/z 292.2 → 163.2 for Nuc and 237.1 → 194.1 for the internal standard (carbamazepine). The quantitative analysis method was fully validated in line with the United States Food and Drug Administration guidelines. The linearity, accuracy and precision, matrix effect, recovery, and stability results met the requirements of the guidelines. Uncertainty of measurement and incurred sample reanalysis were analyzed to further ensure the robustness and reproducibility of the method. This optimized method was successfully applied in a rat pharmacokinetics study of remdesivir (intravenously administration, 5 mg kg-1). The method can act as a basis for further pharmacokinetic and clinical efficacy investigations in patients with COVID-19. Graphical abstract.

Development and validation of a simple, selective, and sensitive LC-MS/MS assay for the quantification of remdesivir in human plasma.

Remdesivir, formerly GS-5734, has recently become the first antiviral drug approved by the U.S. Food and Drug Administration (FDA) to treat COVID-19, the disease caused by SARS-CoV-2. Therapeutic dosing and pharmacokinetic studies require a simple, sensitive, and selective validated assay to quantify drug concentrations in clinical samples. Therefore, we developed a rapid and sensitive LC-MS/MS assay for the quantification of remdesivir in human plasma with its deuterium-labeled analog, remdesivir-2H5, as the internal standard. Chromatographic separation was achieved on a Phenomenex® Synergi™ HPLC Fusion-RP (100 × 2 mm, 4 µm) column by gradient elution. Excellent accuracy and precision (<5.2% within-run variations and. <9.8% between-run variations) were obtained over the range of 0.5-5000 ng/mL. The assay met the FDA Bioanalytical Guidelines for selectivity and specificity, and low inter-matrix lot variability (<2.7%) was observed for extraction efficiency (77%) and matrix effect (123%) studies. Further, stability tests showed that the analyte does not degrade under working conditions, nor during freezing and thawing processes.

Liver alanine catabolism promotes skeletal muscle atrophy and hyperglycaemia in type 2 diabetes.

Both obesity and sarcopenia are frequently associated in ageing, and together may promote the progression of related conditions such as diabetes and frailty. However, little is known about the pathophysiological mechanisms underpinning this association. Here we show that systemic alanine metabolism is linked to glycaemic control. We find that expression of alanine aminotransferases is increased in the liver in mice with obesity and diabetes, as well as in humans with type 2 diabetes. Hepatocyte-selective silencing of both alanine aminotransferase enzymes in mice with obesity and diabetes retards hyperglycaemia and reverses skeletal muscle atrophy through restoration of skeletal muscle protein synthesis. Mechanistically, liver alanine catabolism driven by chronic glucocorticoid and glucagon signalling promotes hyperglycaemia and skeletal muscle wasting. We further provide evidence for amino acid-induced metabolic cross-talk between the liver and skeletal muscle in ex vivo experiments. Taken together, we reveal a metabolic inter-tissue cross-talk that links skeletal muscle atrophy and hyperglycaemia in type 2 diabetes.

Hemoadsorption eliminates remdesivir from the circulation: Implications for the treatment of COVID-19.

Both antiviral treatment with remdesivir and hemoadsorption using a CytoSorb® adsorption device are applied in the treatment of severe COVID-19. The CytoSorb® adsorber consists of porous polymer beads that adsorb a broad range of molecules, including cytokines but also several therapeutic drugs. In this study, we evaluated whether remdesivir and its main active metabolite GS-441524 would be adsorbed by CytoSorb® . Serum containing remdesivir or GS-441524 was circulated in a custom-made system containing a CytoSorb® device. Concentrations of remdesivir and GS-441524 before and after the adsorber were analyzed by liquid chromatography-tandem mass spectrometry. Measurements of remdesivir in the outgoing tube after the adsorber indicated almost complete removal of remdesivir by the device. In the reservoir, concentration of remdesivir showed an exponential decay and was not longer detectable after 60 mins. GS-441524 showed a similar exponential decay but, unlike remdesivir, it reached an adsorption-desorption equilibrium at ~48 µg/L. Remdesivir and its main active metabolite GS-441524 are rapidly eliminated from the perfusate by the CytoSorb® adsorber device in vitro. This should be considered in patients for whom both therapies are indicated, and simultaneous application should be avoided. In general, plasma levels of therapeutic drugs should be closely monitored under concurrent CytoSorb® therapy.

Simultaneous quantification of seven repurposed COVID-19 drugs remdesivir (plus metabolite GS-441524), chloroquine, hydroxychloroquine, lopinavir, ritonavir, favipiravir and azithromycin by a two-dimensional isotope dilution LC-MS/MS method in human serum.

BACKGROUND: The present COVID-19 pandemic has prompted worldwide repurposing of drugs. The aim of the present work was to develop and validate a two-dimensional isotope-dilution liquid chromatrography tandem mass spectrometry (ID-LC-MS/MS) method for accurate quantification of remdesivir and its active metabolite GS-441524, chloroquine, hydroxychloroquine, lopinavir, ritonavir, favipiravir and azithromycin in serum; drugs that have gained attention for repurposing in the treatment of COVID-19. METHODS: Following protein precipitation, samples were separated with a two-dimensional ultra-high performance liquid chromatography (2D-UHPLC) setup, consisting of an online solid phase extraction (SPE) coupled to an analytical column. For quantification, stable isotope-labelled analogues were used as internal standards for all analytes. The method was validated on the basis of the European Medicines Agency bioanalytical method validation protocol. RESULTS: Detuning of lopinavir and ritonavir allowed simultaneous quantification of all analytes with different concentration ranges and sensitivity with a uniform injection volume of 5 µL. The method provided robust validation results with inaccuracy and imprecision values of ≤ 9.59 % and ≤ 11.1 % for all quality controls. CONCLUSION: The presented method is suitable for accurate and simultaneous quantification of remdesivir, its metabolite GS-441525, chloroquine, hydroxychloroquine, lopinavir, ritonavir, favipiravir and azithromycin in human serum. The quantitative assay may be an efficient tool for the therapeutic drug monitoring of these potential drug candidates in COVID-19 patients in order to increase treatment efficacy and safety.

Circulating markers of NADH-reductive stress correlate with mitochondrial disease severity.

Mitochondrial disorders represent a large collection of rare syndromes that are difficult to manage both because we do not fully understand biochemical pathogenesis and because we currently lack facile markers of severity. The m.3243A>G variant is the most common heteroplasmic mitochondrial DNA mutation and underlies a spectrum of diseases, notably mitochondrial encephalomyopathy lactic acidosis and stroke-like episodes (MELAS). To identify robust circulating markers of m.3243A>G disease, we first performed discovery proteomics, targeted metabolomics, and untargeted metabolomics on plasma from a deeply phenotyped cohort (102 patients, 32 controls). In a validation phase, we measured concentrations of prioritized metabolites in an independent cohort using distinct methods. We validated 20 analytes (1 protein, 19 metabolites) that distinguish patients with MELAS from controls. The collection includes classic (lactate, alanine) and more recently identified (GDF-15, α-hydroxybutyrate) mitochondrial markers. By mining untargeted mass-spectra we uncovered 3 less well-studied metabolite families: N-lactoyl-amino acids, ß-hydroxy acylcarnitines, and ß-hydroxy fatty acids. Many of these 20 analytes correlate strongly with established measures of severity, including Karnofsky status, and mechanistically, nearly all markers are attributable to an elevated NADH/NAD+ ratio, or NADH-reductive stress. Our work defines a panel of organelle function tests related to NADH-reductive stress that should enable classification and monitoring of mitochondrial disease.

Validation of LC-MS/MS methods for determination of remdesivir and its metabolites GS-441524 and GS-704277 in acidified human plasma and their application in COVID-19 related clinical studies.

Remdesivir (RDV) is a phosphoramidate prodrug designed to have activity against a broad spectrum of viruses. Following IV administration, RDV is rapidly distributed into cells and tissues and simultaneously metabolized into GS-441524 and GS-704277 in plasma. LC-MS/MS methods were validated for determination of the 3 analytes in human plasma that involved two key aspects to guarantee their precision, accuracy and robustness. First, instability issues of the analytes were overcome by diluted formic acid (FA) treatment of the plasma samples. Secondly, a separate injection for each analyte was performed with different ESI modes and organic gradients to achieve sensitivity and minimize carryover. Chromatographic separation was achieved on an Acquity UPLC HSS T3 column (2.1 × 50 mm, 1.8 µm) with a run time of 3.4 min. The calibration ranges were 4-4000, 2-2000, and 2-2000 ng/mL, respectively for RDV, GS-441524 and GS-704277. The intraday and interday precision (%CV) across validation runs at 3 QC levels for all 3 analytes was less than 6.6%, and the accuracy was within ±11.5%. The long-term storage stability in FA-treated plasma was established to be 392, 392 and 257 days at -70 °C, respectively for RDV, GS-441524 and GS-704277. The validated method was successfully applied in COVID-19 related clinical studies.

Improvement in the Prediction of Neonatal Hypoxic-Ischemic Encephalopathy with the Integration of Umbilical Cord Metabolites and Current Clinical Makers.

OBJECTIVE: To validate our previously identified candidate metabolites, and to assess the ability of these metabolites to predict hypoxic-ischemic encephalopathy (HIE) both individually and combined with clinical data. STUDY DESIGN: Term neonates with signs of perinatal asphyxia, with and without HIE, and matched controls were recruited prospectively at birth from 2 large maternity units. Umbilical cord blood was collected for later batch metabolomic analysis by mass spectroscopy along with clinical details. The optimum selection of clinical and metabolites features with the ability to predict the development of HIE was determined using logistic regression modelling and machine learning techniques. Outcome of HIE was determined by clinical Sarnat grading and confirmed by electroencephalogram grade at 24 hours. RESULTS: Fifteen of 27 candidate metabolites showed significant alteration in infants with perinatal asphyxia or HIE when compared with matched controls. Metabolomic data predicted the development of HIE with an area under the curve of 0.67 (95% CI, 0.62-0.71). Lactic acid and alanine were the primary metabolite predictors for the development of HIE, and when combined with clinical data, gave an area under the curve of 0.96 (95% CI, 0.92-0.95). CONCLUSIONS: By combining clinical and metabolic data, accurate identification of infants who will develop HIE is possible shortly after birth, allowing early initiation of therapeutic hypothermia.

The liver-alpha cell axis associates with liver fat and insulin resistance: a validation study in women with non-steatotic liver fat levels.

AIMS/HYPOTHESIS: Many individuals who develop type 2 diabetes also display increased glucagon levels (hyperglucagonaemia), which we have previously found to be associated with the metabolic syndrome. The concept of a liver-alpha cell axis provides a possible link between hyperglucagonaemia and elevated liver fat content, a typical finding in the metabolic syndrome. However, this association has only been studied in individuals with non-alcoholic fatty liver disease. Hence, we searched for a link between the liver and the alpha cells in individuals with non-steatotic levels of liver fat content. We hypothesised that the glucagon-alanine index, an indicator of the functional integrity of the liver-alpha cell axis, would associate with liver fat and insulin resistance in our cohort of women with low levels of liver fat. METHODS: We analysed data from 79 individuals participating in the Prediction, Prevention and Subclassification of Type 2 Diabetes (PPSDiab) study, a prospective observational study of young women at low to high risk for the development of type 2 diabetes. Liver fat content was determined by MRI. Insulin resistance was calculated as HOMA-IR. We conducted Spearman correlation analyses of liver fat content and HOMA-IR with the glucagon-alanine index (the product of fasting plasma levels of glucagon and alanine). The prediction of the glucagon-alanine index by liver fat or HOMA-IR was tested in multivariate linear regression analyses in the whole cohort as well as after stratification for liver fat content ≤0.5% (n = 39) or >0.5% (n = 40). RESULTS: The glucagon-alanine index significantly correlated with liver fat and HOMA-IR in the entire cohort (ρ = 0.484, p < 0.001 and ρ = 0.417, p < 0.001, respectively). These associations resulted from significant correlations in participants with a liver fat content >0.5% (liver fat, ρ = 0.550, p < 0.001; HOMA-IR, ρ = 0.429, p = 0.006). In linear regression analyses, the association of the glucagon-alanine index with liver fat remained significant after adjustment for age and HOMA-IR in all participants and in those with liver fat >0.5% (ß = 0.246, p = 0.0.23 and ß = 0.430, p = 0.007, respectively) but not in participants with liver fat ≤0.5% (ß = -0.184, p = 0.286). CONCLUSIONS/INTERPRETATION: We reproduced the previously reported association of liver fat content and HOMA-IR with the glucagon-alanine index in an independent study cohort of young women with low to high risk for type 2 diabetes. Furthermore, our data indicates an insulin-resistance-independent association of liver fat content with the glucagon-alanine index. In summary, our study supports the concept that even lower levels of liver fat (from 0.5%) are connected to relative hyperglucagonaemia, reflecting an imminent impairment of the liver-alpha cell axis.

Pre-diagnostic biomarkers of type 2 diabetes identified in the UAE's obese national population using targeted metabolomics.

Currently, type 2 diabetes mellitus (T2DM) and obesity are major global public health issues, and their prevalence in the United Arab Emirates (UAE) are among the highest in the world. In 2019, The UAE diabetes national prevalence was 15.4%. In recent years there has been a considerable investigation of predictive biomarkers associated with these conditions. This study analysed fasting (8 h) blood samples from an obese, normoglycemic cohort and an obese, T2DM cohort of UAE nationals, employing clinical chemistry analysis, 1D 1H NMR and mass spectroscopy (FIA-MS/MS and LC-MS/MS) techniques. The novel findings reported for the first time in a UAE population revealed significant differences in a number of metabolites in the T2DM cohort. Metabolic fingerprints identified by NMR included BCAAs, trimethylamine N-oxide, ß-hydroxybutyrate, trimethyl uric acid, and alanine. A targeted MS approach showed significant differences in lysophosphatidylcholines, phosphatidylcholines, acylcarnitine, amino acids and sphingomyelins; Lyso.PC.a.C18.0, PC.ae.C34.2, C3.DC..C4.OH, glutamine and SM.C16.1, being the most significant metabolites. Pearson's correlation studies showed associations between these metabolites and the clinical chemistry parameters across both cohorts. This report identified differences in metabolites in response to T2DM in agreement with many published population studies. This contributes to the global search for a bank of metabolite biomarkers that can predict the advent of T2DM and give insight to its pathogenic mechanisms.

Serum metabolomics approach to monitor the changes in metabolite profiles following renal transplantation.

Systemic metabolic changes after renal transplantation reflect the key processes that are related to graft accommodation. In order to describe and better understand these changes, the 1HNMR based metabolomics approach was used. The changes of 47 metabolites in the serum samples of 19 individuals were interpreted over time with respect to their levels prior to transplantation. Considering the specific repeated measures design of the experiments, data analysis was mainly focused on the multiple analyses of variance (ANOVA) methods such as ANOVA simultaneous component analysis and ANOVA-target projection. We also propose here the combined use of ANOVA and classification and regression trees (ANOVA-CART) under the assumption that a small set of metabolites the binary splits on which may better describe the graft accommodation processes over time. This assumption is very important for developing a medical protocol for evaluating a patient's health state. The results showed that besides creatinine, which is routinely used to monitor renal activity, the changes in levels of hippurate, mannitol and alanine may be associated with the changes in renal function during the post-transplantation recovery period. Specifically, the level of hippurate (or histidine) is more sensitive to any short-term changes in renal activity than creatinine.

Quantifying the effect of remdesivir in rhesus macaques infected with SARS-CoV-2.

The world is in the midst of a pandemic caused by a novel coronavirus and is desperately searching for possible treatments. The antiviral remdesivir has shown some effectiveness against SARS-CoV-2 in vitro and in a recent animal study. We use data from a study of remdesivir in rhesus macaques to fit a viral kinetics model in an effort to determine the most appropriate mathematical descripton of the effect of remdesivir. We find statistically significant differences in the viral decay rate and use this to inform a possible mathematical formulation of the effect of remdesivir. Unfortunately, this model formulation suggests that the application of remdesivir will lengthen SARS-CoV-2 infections, putting into question its potential clinical benefit.

New and validated RP-HPLC Method for Quantification of Safinamide Mesylate in Presence of Its Basic Degradate, Levodopa and Ondansetron: Application to Human Plasma.

A simple, precise, rapid and accurate reversed-phase high-performance liquid chromatography (RP-HPLC) method was developed and validated for analysis of safinamide mesylate (SAF) in presence of its basic degradate, and co-administered drugs levodopa and ondansetron. The mobile phase consisted of acetonitrile and 20 mM potassium dihyrogen orthophosphate buffer having pH = 5 (40: 60 v/v). Quantification was achieved with ultraviolet detector at 226 nm. The linear range was 0.5-10 µg/mL with mean recovery ± SD of 99.72 ± 1.59. The peak purity of SAF in pharmaceutical preparation spiked with its degradate and co-administered drugs revealed symmetry factor (999.8) within the calculated threshold (>998.1). The suggested method was validated in compliance with the International Conference on Harmonization (ICH) guidelines and statistically compared with the manufacturer HPLC method with no significant difference in terms of accuracy and precision. The assay method was successfully used to estimate SAF in tablets with good percentage recoveries. The high sensitivity (lower than Cmax of the drug 0.65 µg/mL) of the proposed HPLC method enabled the determination of SAF in presence of its basic degradate and co-administered drug, ondansetron in human plasma with acceptable accuracy. The suggested HPLC method could be used in Quality Control (QC) lab for analysis of the studied drug in pharmaceutical preparation.