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Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used in infants, children, and adolescents worldwide; however, despite sufficient evidence of the beneficial effects of NSAIDs in children and adolescents, there is a lack of comprehensive data in infants. The present review summarizes the current knowledge on the safety and efficacy of various NSAIDs used in infants for which data are available, and includes ibuprofen, dexibuprofen, ketoprofen, flurbiprofen, naproxen, diclofenac, ketorolac, indomethacin, niflumic acid, meloxicam, celecoxib, parecoxib, rofecoxib, acetylsalicylic acid, and nimesulide. The efficacy of NSAIDs has been documented for a variety of conditions, such as fever and pain. NSAIDs are also the main pillars of anti-inflammatory treatment, such as in pediatric inflammatory rheumatic diseases. Limited data are available on the safety of most NSAIDs in infants. Adverse drug reactions may be renal, gastrointestinal, hematological, or immunologic. Since NSAIDs are among the most frequently used drugs in the pediatric population, safety and efficacy studies can be performed as part of normal clinical routine, even in young infants. Available data sources, such as (electronic) medical records, should be used for safety and efficacy analyses. On a larger scale, existing data sources, e.g. adverse drug reaction programs/networks, spontaneous national reporting systems, and electronic medical records should be assessed with child-specific methods in order to detect safety signals pertinent to certain pediatric age groups or disease entities. To improve the safety of NSAIDs in infants, treatment needs to be initiated with the lowest age-appropriate or weight-based dose. Duration of treatment and amount of drug used should be regularly evaluated and maximum dose limits and other recommendations by the manufacturer or expert committees should be followed. Treatment for non-chronic conditions such as fever and acute (postoperative) pain should be kept as short as possible. Patients with chronic conditions should be regularly monitored for possible adverse effects of NSAIDs.

PURPOSE The introduction of COVID-19 therapies containing ritonavir has markedly expanded the scope of use for this medicine. As a strong cytochrome P450 3A4 inhibitor, the use of ritonavir is associated with a high drug interaction risk. There are currently no data to inform clinician regarding the likely magnitude and duration of interaction between ritonavir-containing COVID-19 therapies and small-molecule kinase inhibitors (KIs) in patients with cancer. METHODS Physiologically based pharmacokinetic modeling was used to conduct virtual clinical trials with a parallel group study design in the presence and absence of ritonavir (100 mg twice daily for 5 days). The magnitude and time course of changes in KI exposure when coadministered with ritonavir was evaluated as the primary outcome. RESULTS Dosing of ritonavir resulted in a > 2-fold increase in steady-state area under the plasma concentration-time curve and maximal concentration for six of the 10 KIs. When the KI was coadministered with ritonavir, dose reductions to between 10% and 75% of the original dose were required to achieve an area under the plasma concentration-time curve within 1.25-fold of the value in the absence of ritonavir. CONCLUSION To our knowledge, this study provides the first data to assist clinicians' understanding of the drug interaction risk associated with administering ritonavir-containing COVID-19 therapies to patients with cancer who are currently being treated with KIs. These data may support clinicians to make more informed dosing decisions for patients with cancer undergoing treatment with KIs who require treatment with ritonavir-containing COVID-19 antiviral therapies.

Purpose This review provides an overview of the current challenges in oral targeted antineoplastic drug (OAD) dosing and outlines the unexploited value of therapeutic drug monitoring (TDM). Factors influencing the pharmacokinetic exposure in OAD therapy are depicted together with an overview of different TDM approaches. Finally, current evidence for TDM for all approved OADs is reviewed. Methods A comprehensive literature search (covering literature published until April 2020), including primary and secondary scientific literature on pharmacokinetics and dose individualisation strategies for OADs, together with US FDA Clinical Pharmacology and Biopharmaceutics Reviews and the Committee for Medicinal Products for Human Use European Public Assessment Reports was conducted. Results OADs are highly potent drugs, which have substantially changed treatment options for cancer patients. Nevertheless, high pharmacokinetic variability and low treatment adherence are risk factors for treatment failure. TDM is a powerful tool to individualise drug dosing, ensure drug concentrations within the therapeutic window and increase treatment success rates. After reviewing the literature for 71 approved OADs, we show that exposure-response and/or exposure-toxicity relationships have been established for the majority. Moreover, TDM has been proven to be feasible for individualised dosing of abiraterone, everolimus, imatinib, pazopanib, sunitinib and tamoxifen in prospective studies. There is a lack of experience in how to best implement TDM as part of clinical routine in OAD cancer therapy. Conclusion Sub-therapeutic concentrations and severe adverse events are current challenges in OAD treatment, which can both be addressed by the application of TDM-guided dosing, ensuring concentrations within the therapeutic window.

IntroductionChildhood leukaemia is the most common type of cancer in children and represents among 25% of the diagnoses in children Methods and analysisSystematic review methodology will be applied to identify, select and extract data from published plasma guided dosing studies conducted in a paediatric leukaemia cohort. Databases (eg, Ovid Embase, Ovid MEDLINE, Ovid Cochrane) and clinical trial registries (CENTRAL, ClinicalTrials.gov and ISRCTN) will be used to perform the systematic literature search (up until February 2021). Only full empirical studies will be included, with primary clinical outcomes (progression-free survival, toxicities, minimal residual disease status, complete cytogenetic response, partial cytogenetic response and major molecular response) being used to decide whether the study will be included. The quality of included studies will be undertaken, with a subgroup analysis where appropriate.Ethics and disseminationThis systematic review will not require ethics approval as there will not be collection of primary data. Findings of this review will be made available through publications in peer-reviewed journals and conference presentations. Gaps will be identified in current literature to inform future-related research.PROSPERO registration numberCRD42021225045.

Tamoxifen is used worldwide to treat estrogen receptor-positive breast cancer. It is extensively metabolized, and minimum steady-state concentrations of its metabolite endoxifen (CSS,min ENDX) &gt, 5.97 ng/mL have been associated with favorable outcome. Endoxifen formation is mediated by the enzyme CYP2D6, and impaired CYP2D6 function has been associated with lower CSS,min&nbsp, ENDX. In the Women’s Healthy Eating and Living (WHEL) study proposing the target concentration, 20% of patients showed subtarget CSS,min ENDX at tamoxifen standard dosing. CYP2D6 allele frequencies vary largely between populations, and as 87% of the patients in the WHEL study were White, little is known about the risk for subtarget CSS,min ENDX in other populations. Applying pharmacokinetic simulations, this study investigated the risk for subtarget CSS,min ENDX at tamoxifen standard dosing and the need for dose individualization in nine different biogeographical groups with distinct CYP2D6 allele frequencies. The high variability in CYP2D6 allele frequencies amongst the biogeographical groups resulted in an up to three-fold difference in the percentages of patients with subtarget CSS,min ENDX. Based on their CYP2D6 allele frequencies, East Asian breast cancer patients were identified as the population for which personalized, model-informed precision dosing would be most beneficial (28% of patients with subtarget CSS,min ENDX).

Drug approval is based on exposure, response, and variability of studied populations, typically excluding comorbidities/medications and very ill patients, thus not representing real‐world populations. This results in wide variability in therapeutic outcome for individual patients. Model‐informed precision dosing (MIPD) can characterize/quantify this variability, support optimal dose selection, and enable individualized therapy. The aim of this perspective is to raise awareness for MIPD, identify challenges hindering its implementation in clinical practice, provide recommendations, and highlight opportunities.

Liver-derived small extracellular vesicles (sEVs), prepared from small sets of banked serum samples using a novel two-step protocol, were deployed as liquid biopsy to study the induction of cytochromes P450 (CYP3A4, CYP3A5, and CYP2D6) and organic anion transporting polypeptides (OATP1B1 and OATP1B3) during pregnancy (nonpregnant (T0), first, second, and third (T3) trimester women; N = 3 each) and after administration of rifampicin (RIF) to healthy male subjects. Proteomic analysis revealed induction (mean fold-increase, 90% confidence interval) of sEV CYP3A4 after RIF 300 mg × 7 days (3.5, 95% CI = 2.5-4.5, N = 4, P = 0.029) and 600 mg × 14 days (3.7, 95% CI = 2.1-6.0, N = 5, P = 0.018) consistent with the mean oral midazolam area under the plasma concentration time curve (AUC) ratio in the same subjects (0.28, 95% CI = 0.22-0.34, P

Aim To evaluate the capacity for modafinil to be a perpetrator of metabolic drug–drug interactions by altering cytochrome P450 activity following a single dose and dosing to steady state. Methods A single centre, open label, single sequence cocktail drug interaction trial. On days 0, 2 and 8 participants were administered an oral drug cocktail comprising 100 mg caffeine, 30 mg dextromethorphan, 25 mg losartan, 1 mg midazolam and 20 mg enteric-coated omeprazole. Timed blood samples were collected prior to and for up to 6 h post cocktail dosing. Between days 2 and 8 participants orally self-administered 200 mg modafinil each morning. Results Following a single 200 mg dose of modafinil mean (± 95% CI) AUC ratios for caffeine, dextromethorphan, losartan, midazolam and omeprazole were 0.95 (± 0.08), 1.01 (± 0.35), 0.97 (± 0.10), 0.98 (± 0.10) and 1.36 (± 0.06), respectively. Following dosing of modafinil to steady state (200 mg for 7 days), AUC ratios for caffeine, dextromethorphan, losartan, midazolam and omeprazole were 0.90 (± 0.16), 0.79 (± 0.09), 0.98 (± 0.11), 0.66 (± 0.12) and 1.90 (± 0.53), respectively. Conclusions These data support consideration of the risk of clinically relevant metabolic drug–drug interactions perpetrated by modafinil when this drug is co-administered with drugs that are primarily cleared by CYP2C19 (single modafinil dose or steady state modafinil dosing) or CYP3A4 (steady state modafinil dosing only) catalysed metabolic pathways.

Background: Epidermal growth factor receptor (EGFR) kinase inhibitors (KIs) have shown promising results in the treatment of non-small cell lung cancer (NSCLC). However, inter-individual variability in exposure results in a large proportion of patients experience either a lack of efficacy due to sub-therapeutic dosing or toxicity as a result of excessive dosing. Physiologically-based pharmacokinetic (PBPK) modeling, is a mechanistic “bottom up” approach, whereby the concentration-time profile for a drug in a patient cohort is simulated based on the physiochemical and in vitro kinetics of the drug and the physiological characteristics of the patient cohort. In this study, PBPK profiles for afatinib, erlotinib and gefitinib were developed and validated using data from healthy volunteer trials. The capacity of the profiles to account for the impact of covariates such as age, gender, and ethnicity, and the impact of co-administration with strong cytochromes P450 (CYP) 3A4 inhibitors and inducers on in vivo clearance was assessed. Methods: The rate of microsomal KI metabolism was quantified in the presence and absence of CYP and uridine diphosphate (UDP)-glucuronosyltransferase (UGT) cofactors as well as a selective CYP3A4 inhibitor (CYP3Cide). Microsomal clearance was assessed on the basis of the substrate depletion at an initial KI concentration of 1 μM over the course of a 3-hour incubation. CYP and UGT clearances were calculated based on the depletion half-life for incubations performed in the presence of the associated cofactors. CYP3A4 mediated clearance was assessed by subtracting the clearance in the presence of CYP3Cide from total CYP clearance. PBPK profiles for each compound were created based on reported physicochemical and distribution characteristics and in vitro microsomal CL int data. All simulations were conducted utilising the Simcyp Simulator ® (version 15.1) and the advanced dissolution, absorption and metabolism (ADAM) sub-model was used in conjunction with the whole body “full-PBPK” model for profile development. Results: The EGFR KI compound profiles were validated by comparing simulated pharmacokinetic parameters [area under the curve (AUC), C max and t max ] describing exposure with those observed in clinical studies that were not used in the development of the compound profiles. With the exception of the AUC ratio describing the impact of induction on erlotinib exposure (0.64), the ratio of observed to simulated parameters describing exposure, or parameter ratios describing the impact of induction on exposure were contained within the range 0.8 to 1.2. Conclusions: Robust mechanistic models with the capacity to describe EGFR KI exposure and the impact of covariates on exposure were developed and validated. These models may be applied to inform the impact of different dosing regimens on EGFR KI exposure, the potential impact of poor compliance on EGFR KI efficacy, the need to perform bridging studies when introducing EGFR KIs to new international markets, and the potential impact of DDIs on EFGR KI exposure.

Background: Drug probe phenotyping is used extensively in academic and industry research to evaluate cytochrome P450 (CYP) phenotype in order to account for sources of between- and within- subject variability in metabolic clearance. In terms of application, CYP3A is the most important drug metabolizing enzyme the most frequently studied. Currently, phenotyping studies for CYP3A involve the administration of midazolam and collection of timed blood samples up to 24-48 hours in order to determine an area under the plasma concentration time curve (AUC). The key challenge that limits the use of midazolam-based phenotyping for CYP3A in academic research settings and preclude the use of this approach in a clinical setting is the logistical burden of collecting frequent blood samples for up to 48 h post dose following the administration of a probe drug ± an interacting drug. Aim: The current study sought to validate if a reduced sampling interval could be used to accurately define both between-subject variability in CYP3A phenotype and the magnitude of changes in CYP3A activity due to either induction or mechanism-based inhibition. Methods: The area under the curve (AUC) for midazolam was assessed under baseline, induction (7 days rifampin, 300 mg daily) and, following a washout period of 4 days, mechanism based inhibition (3 days clarithromycin, 250 mg daily) conditions in a cohort of 30 health males. The capacity of normalized reduced sampling interval AUCs measured over 0 to 1, 0 to 2, 0 to 3, and 0 to 4 h to accurately define the AUC0-6 was evaluated with respect to precision (R2 for correlation), bias (slope of normalized correlation), agreement (Bland Altman analysis) and proportional bias (linear regression of Bland Altman parameters). Results: Robust concordance was observed between the AUC calculated from PK collection intervals of 0 to 3 and 0 to 6 h in terms of both the measurement of between-subject variability in midazolam AUC and changes in midazolam AUC due to induction and mechanism-based inhibition of CYP3A4. Conclusion: On this basis, it is proposed that a 3-h assessment of midazolam AUC (AUC0-3) represents a viable strategy to reduce the logistical burden associated with the assessment of CYP3A phenotype.

This review provides an overview of the current challenges in oral targeted antineoplastic drug (OAD) dosing and outlines the unexploited value of therapeutic drug monitoring (TDM). Factors influencing the pharmacokinetic exposure in OAD therapy are depicted together with an overview of different TDM approaches. Finally, current evidence for TDM for all approved OADs is reviewed.A comprehensive literature search (covering literature published until April 2020), including primary and secondary scientific literature on pharmacokinetics and dose individualisation strategies for OADs, together with US FDA Clinical Pharmacology and Biopharmaceutics Reviews and the Committee for Medicinal Products for Human Use European Public Assessment Reports was conducted.OADs are highly potent drugs, which have substantially changed treatment options for cancer patients. Nevertheless, high pharmacokinetic variability and low treatment adherence are risk factors for treatment failure. TDM is a powerful tool to individualise drug dosing, ensure drug concentrations within the therapeutic window and increase treatment success rates. After reviewing the literature for 71 approved OADs, we show that exposure-response and/or exposure-toxicity relationships have been established for the majority. Moreover, TDM has been proven to be feasible for individualised dosing of abiraterone, everolimus, imatinib, pazopanib, sunitinib and tamoxifen in prospective studies. There is a lack of experience in how to best implement TDM as part of clinical routine in OAD cancer therapy.Sub-therapeutic concentrations and severe adverse events are current challenges in OAD treatment, which can both be addressed by the application of TDM-guided dosing, ensuring concentrations within the therapeutic window.

This study aimed to evaluate the impact of early adverse events on overall survival (OS), progression-free survival (PFS) and objective response within a pooled secondary analysis of participants treated with first-line vemurafenib or vemurafenib plus cobimetinib in the clinical trials BRIM3 and coBRIM. The study included 583 participants who received vemurafenib monotherapy and 247 who received vemurafenib plus cobimetinib. Adverse events requiring vemurafenib/cobimetinib dose adjustment within the first 28 days of therapy were significantly associated with OS (hazard ratio (HR) [95% CI]: dose reduced/interrupted = 0.79 [0.65-0.96]; drug withdrawn = 1.18 [0.71-1.96]; p = 0.032), PFS (HR [95% CI]: dose reduced/interrupted = 0.82 [0.67-0.99]; drug withdrawn = 1.58 [0.97-2.58]; p = 0.017) and objective response (odds ratio (OR) [95% CI]: dose reduced/interrupted = 1.35 [0.99-1.85]; drug withdrawn = 0.17 [0.06-0.43]; p =

Axitinib is a second-generation small-molecule vascular endothelial growth factor receptor inhibitor. An axitinib steady-state area under the plasma concentration-time curve (AUCSS ) >300 ng/mL/hr is associated with superior progression-free and overall survival. This study sought to characterize the physiological and molecular characteristics driving variability in axitinib AUCSS using physiologically based pharmacokinetic modeling to identify exposure biomarkers for this drug. The capacity to predict subjects likely to fail to achieve an axitinib AUCSS >300 ng/mL/hr was evaluated as a secondary outcome. A full physiologically based pharmacokinetic model incorporating mechanistic absorption was developed and verified for axitinib in accordance with the US Food and Drug Administration Guidance using Simcyp (Version 17.1). This model was used to simulate axitinib exposure over 7 days with twice-daily dosing (5 mg) in a cohort of 1000 virtual cancer patients. Multiple linear regression modeling was used to identify patient characteristics associated with differences in axitinib exposure. A multivariable linear regression model incorporating hepatic cytochrome P450 (CYP) 3A4 abundance, albumin concentration, hepatic CYP1A2 abundance, hepatic CYP2C19 abundance, and intestinal CYP2C19 abundance provided robust prediction of axitinib AUCSS (R2 = 0.890; P < .001). By accounting for these variables, it was possible to identify subjects who would fail to achieve an effective axitinib AUCSS with a specificity of 88.7% and a sensitivity of 92.6%. Variability in axitinib AUCSS is primarily driven by differences in hepatic CYP3A4 abundance and albumin concentration. Consideration of these 2 characteristic is likely to be sufficient to individualize axitinib dosing.

AIMS: Demonstrate the presence of cytochrome P450 (CYP) and UDP‐glucuronosyltransferase (UGT) proteins and mRNAs in isolated human plasma exosomes and evaluate the capacity for exosome‐derived biomarkers to characterize variability in CYP3A4 activity. METHODS: The presence of CYP and UGT protein and mRNA in exosomes isolated from human plasma and HepaRG cell culture medium was determined by mass spectrometry and reverse transcription–polymerase chain reaction, respectively. The concordance between exosome‐derived CYP3A4 biomarkers and midazolam apparent oral clearance (CL/F) was evaluated in a small proof‐of‐concept study involving six genotyped (CYP3A4 *1/*1 and CYP3A5 *3/*3) Caucasian males. RESULTS: Exosomes isolated from human plasma contained peptides and mRNA originating from CYP 1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 2 J2, 3A4 and 3A5, UGT 1A1, 1A3, 1A4, 1A6, 1A9, 2B4, 2B7, 2B10 and 2B15, and NADPH‐cytochrome P450 reductase. Mean (95% confidence interval) exosome‐derived CYP3A4 protein expression pre‐ and post‐rifampicin dosing was 0.24 (0.2–0.28) and 0.42 (0.21–0.65) ng ml(–1) exosome concentrate. Mean (95% confidence interval) exosome CYP3A4 mRNA expression pre‐ and post‐rifampicin dosing was 6.0 (1.1–32.7) and 48.3 (11.3–104) × 10(–11) 2(‐ΔΔCt), respectively. R(2) values for correlations of exosome‐derived CYP3A4 protein expression, CYP3A4 mRNA expression, and ex vivo CYP3A4 activity with midazolam CL/F were 0.905, 0.787 and 0.832, respectively. CONCLUSIONS: Consistent strong concordance was observed between exosome‐derived CYP3A4 biomarkers and midazolam CL/F. The significance of these results is that CYP3A4 is the drug‐metabolizing enzyme of greatest clinical importance and variability in CYP3A4 activity is poorly described by existing precision dosing strategies.

Prospectively defining the physiological and molecular characteristics most likely driving between-subject variability (BSV) in drug exposure provides the opportunity to inform the assessment of biomarkers to account for this variability. A physiologically based pharmacokinetic (PBPK) model was constructed and verified for dabrafenib. This model was then used to evaluate the physiological and molecular characteristics driving BSV in dabrafenib exposure. The capacity to discriminate a steady-state dabrafenib trough concentration >48 ng/mL was also evaluated. The mean simulated/observed ratios for the parameters describing dabrafenib exposure in single-dose, multiple-dose, and drug-drug interaction studies were between 0.78 and 1.23. Multivariable analysis indicated that consideration of baseline weight, body mass index, and CYP2C8, CYP3A4, and P-gp abundance strongly predicts steady-state dabrafenib trough concentration above 48 ng/mL (ROC AUC = 0.94; accuracy = 86%). This is the first study to use a verified PBPK model to identify baseline physiological and molecular characteristics driving BSV in drug exposure.

Cytochrome P450 (CYP) 3A4 is responsible for the metabolism of more than 30% of clinically used drugs. Inherent between subject variability in clearance of CYP3A4 substrates is substantial; by way of example, midazolam clearance varies by > 10-fold between individuals before considering the impact of extrinsic factors. Relatively little is known about inter-racial variability in the activity of this enzyme. This study assessed inter-racial variability in midazolam exposure in a cohort (n = 30) of CYP3A genotyped, age-matched healthy males of Caucasian and South Asian ancestries. Midazolam exposure was assessed at baseline, following 7 days of rifampicin and following 3 days of clarithromycin. The geometric mean baseline midazolam area under the plasma concentration curve (AUC0–6) in Caucasians (1057 μg/L/min) was 27% greater than South Asians (768 μg/L/min). Similarly, the post-induction midazolam AUC0–6 in Caucasians (308 μg/L/min) was 50% greater than South Asians (154 μg/L/min), while the post-inhibition midazolam AUC0–6 in Caucasians (1834 μg/L/min) was 41% greater than South Asians (1079 μg/L/min). The difference in baseline AUC0–6 between Caucasians and South Asians was statistically significant (p ≤ 0.05), and a trend toward significance (p = 0.067) was observed for the post-induction AUC0–6 ratio, in both unadjusted and genotype adjusted analyses. Significantly higher midazolam clearance was observed in healthy age-matched males of South Asian compared to Caucasian ancestry that was not explained by differences in the frequency of CYP3A genotypes.

Introduction: Small molecule protein kinase inhibitors (KIs) are a class of drugs with complex and unconventional physiochemical and pharmacokinetic characteristics. Cytochrome P450 mediated metabolism and transporter-mediated uptake and efflux are important processes that determine KI disposition and exposure. Areas covered: We provide an overview of KI pharmacology, with a comprehensive summary of KI physiochemical and pharmacokinetic properties and description of the major sources of variability in KI pharmacokinetics focusing on common pathways involved in determining exposure. We also consider the strategies proposed to optimize KI dosing, appraise the current evidence for their use and analyze the challenges and knowledge gaps for KI dose optimization. Expert opinion: A number of strategies to optimize KI dosing have been proposed, but evidence underpinning their use is limited. The major challenge for optimized KI dosing is the development of high-quality evidence to demonstrate a significant improvement in therapeutic outcomes and /or reduction in adverse events through appropriately designed trials in a setting where the limited KI prescribing restricts capacity to undertake prospective randomized studies. If precision KI dosing can facilitate a fraction of the reported observational benefits, then substantial gains in patient outcomes will be derived in a cost-effective manner. Refereed/Peer-reviewed

Small molecule kinase inhibitors (KIs) are a rapidly expanding class of narrow therapeutic index antineoplastic drugs that exhibit substantial inter-individual variability in exposure. This manuscript describes a novel approach for the quantification of 18 KIs in plasma, providing a platform that is unparalleled in terms of scope for the assessment of KI therapeutic drug monitoring (TDM) and facilitating pharmacokinetic studies with KIs. Following the addition of a panel of four deuterated internal standards, plasma samples were prepared by solvent precipitation with acidified methanol. Analytes were separated on a Waters ACQUITY™ T3 HSS C18 analytical column (150×2.1mm, 1.8μm particle size) by linear gradient elution, with subsequent detection by time-of-flight mass spectrometry. Time-of-flight data were collected in wide pass mode, with selected ion (pseudo-MRM) spectra extracted at the precursor m/z of analytes in ESI+ mode. The analytical performance of this approach in terms of specificity, linearity, accuracy, precision range, quantification limit and detection limit meet all criteria for an analytical platform for the quantification of drugs. This approach was developed, validated and reported in accordance with the 2015 version of the FDA guidance for industry on 'analytical procedures are methods validation for drugs and biologics' facilitating direct application as a clinical trials platform.

Background Nitric oxide synthase (NOS) mediated conversion of arginine (ARG) to citrulline (CIT) is a key pathway for nitric oxide synthesis. ARG is also metabolised by alternate pathways to ornithine (ORN), homoarginine (HMA), NG-monomethyl-L-arginine (MMA), NG,NG-dimethyl-L-arginine (ADMA) and NG,NG′-dimethyl-L-arginine (SDMA), all of which have the capacity to alter NOS activity. Simultaneous assessment of these analytes, when assessing the impact of arginine metabolism in human disease states, is desirable. Methods Analytes (ARG, ADMA, SDMA, MMA, HMA, CIT and ORN) were isolated from human plasma by solvent extraction, evaporated and reconstituted. Ultra-performance liquid chromatography (UPLC) was performed on a 150 mm × 2.1 mm T3 HSS column using a gradient mobile phase comprising ammonium formate (10 mM, pH 3.8) in methanol (1% to 63%). Analytes were detected by time-of-flight mass spectrometry (Q-ToF-MS) in positive ion mode with electrospray ionisation (ESI +). Data were collected using MSE. Results Solvent extraction provided high recovery (> 95%). UPLC-QToF-MSE facilitated the separation and quantification of the 7 analytes in an analysis time of 6 min. The approach has high sensitivity; LOQ range from 0.005 μM (NMMA) to 0.25 μM (ARG and ORN), and good precision; intra- and inter-day %RSD are Conclusions This approach provides the capacity to quantify 7 key compounds involved in ARG metabolism in a small sample volume, with a short total analysis time. These characteristics make this approach ideal for undertaking a comprehensive characterisation of this pathway in large data sets (e.g. population studies).