Area Under The Concentration-time Curve Values Research Articles

Flowchart for predicting achieving the target area under the concentration-time curve of vancomycin in critically ill Japanese patients: A multicenter retrospective study

IntroductionIn therapeutic drug monitoring (TDM) of vancomycin (VCM), the area under the concentration-time curve (AUC) is related to the clinical efficacy and toxicity. Therefore, herein, we examined the factors associated with achieving the target AUC at follow-up and developed a decision flowchart for achieving the target AUC in critically ill patients. MethodsThis multicenter retrospective observational study was conducted at eight hospitals. We retrospectively analyzed data from patients who had received VCM in the intensive care unit from January 2020 to December 2022. Decision-tree (DT) analysis was performed using factors with p < 0.1 in univariate analysis as the independent variables. Case data were split up to two times, and four subgroups were included. The primary endpoint was achieving the target AUC at the follow-up TDM (AUCfollow-up) and target AUCfollow-up achievement was defined as an AUC of 400–600 μg‧h/mL. The initial AUC values were calculated with the 2-point concentrations (peak and trough) using the Bayesian estimation software Practical AUC-guided TDM (PAT). ResultsAmong 70 patients (median age [interquartile range], 66 [56, 79] years; 50 % women), the AUCfollow-up was achieved in 70 % (49/70). Three factors were selected for the decision flow chart: predicted AUCfollow-up of 400–600 μg‧h/mL, dosing at 12-h intervals, and CCr of 130 mL/min/1.73 m2 or higher; the accuracy was adequate (92 %, R2 0.52). ConclusionWe successfully identified the factors associated with achieving the target AUC of VCM at follow-up TDM and developed a simple-to-use DT model. However, the validity of the findings needs to be evaluated.

Bioequivalue of two mycophenolate sodium enteric-coated tablets and the drug monitoring based on limited sampling strategy: A single-center, randomized, open-label, three-period, reference-replicated, crossover study

ObjectiveA mycophenolate sodium enteric-coated tablet has shown a satisfying anti-rejection effect in patients receiving solid organ transplantation. The current study evaluated the bioequivalence between the test (Ruiyirong®) vs. reference (Myfortic®) formulations by exploring equations for predicting their area under the concentration-time curve (AUC) using a limited sampling strategy in healthy subjects. MethodsForty-eight healthy Chinese subjects were randomized into three administration sequences (test-reference-reference, reference-reference-test, and reference-test-reference) to receive the Ruiyirong or Myfortic treatment on days 1, 8, and 15. ResultsThe 90% confidential interval (CI) of the geometric mean ratios (test/reference) of maximum plasma concentration (Cmax), the AUC from time 0 to the last timepoint (AUC0–t), and the AUC from 0 to infinity (AUC0–∞) was 92.90%–110.57%, 96.91%- 101.80%, and 96.71%–101.84%, respectively. All these values fell into the bioequivalence criteria of 80.00%–125.00% (based on the criteria of the Food and Drug Administration). The adverse events were 10.4% in Ruiyirong test group and 14.6% in Myfortic reference group. Eight equations for estimating the AUC of the Ruiyirong test and Myfortic reference formulations were evaluated; most of them worked well with the R-value >0.8. Among the four chosen equations, the intragroup verification exhibited a high agreement with the R-value ranging from 0.857 to 0.971 and with the low predictive error (PE > 5% with absolute PE > 15%). Meanwhile, the intergroup verification indicated a high inter-agreement with the R-value ranging from 0.896 to 0.974 (all P < 0.001). ConclusionThe Ruiyirong test vs. Myfortic reference formulations meet the bioequivalent criteria and are well tolerated. The further linear regression analysis explores eight equations predicting the AUC value and the chosen four equations for the Ruiyirong test and Mayfortic reference formulations are interchangeable.

Liver and Plasma Concentrations of Food Chemicals after Virtual Oral Doses Extrapolated Using in silico Estimated Input Pharmacokinetic Parameters to Confirm Reported Liver Toxicity in Rats.

The estimation of health risks of chemical substances was historically investigated using animal studies; however, current research focuses on reducing the number of animal experiments. The toxicity of chemicals in fish screening systems is reportedly correlated with their hydrophobicity. The inverse relationship between absorption rates (intestinal cell permeability) and virtual hepatic/plasma pharmacokinetics of diverse chemicals has been previously evaluated by modeling oral administration in rats. In the current study, internal exposures, i.e., virtual maximum plasma concentrations (Cmax) and areas under the concentration-time curves (AUC), of 56 food chemicals with reported hepatic lowest-observed-effect levels (LOELs) of ≤1000 mg/kg/day in rats were pharmacokinetically modeled using in silico estimated input pharmacokinetic parameters. After a virtual single oral dose of 1.0 mg/kg of 56 food chemicals, the output Cmax and AUC values in rat plasma generated by modeling using the corresponding in silico estimated input parameters were not significantly correlated with the reported hepatic LOEL values. However, significant inverse relationships between hepatic/plasma concentrations of selected lipophilic food chemicals (i.e., octanol-water partition coefficient logP >1) using forward dosimetry and reported LOEL values (≤300 mg/kg/day) were observed (n = 14, r = -0.52-0.66, p ≤ 0.05). This simple modeling approach, which uses no experimental pharmacokinetic data, has the potential to play a significant role in reducing the use of animals to estimate toxicokinetics or internal exposures of lipophilic food components after oral doses. Therefore, these methods are valuable for estimating hepatic toxicity by using forward dosimetry in animal toxicity experiments.

Evaluation of Vancomycin Area Under the Concentration-Time Curve Predictive Performance Using Bayesian Modeling Software With and Without Peak Concentration: An Academic Hospital Experience for Adult Patients Without Renal Impairment.

The revised U.S. consensus guidelines on vancomycin therapeutic drug monitoring (TDM) recommend obtaining trough and peak samples to estimate the area under the concentration-time curve (AUC) using the Bayesian approach; however, the benefit of such two-point measurements has not been demonstrated in a clinical setting. We evaluated Bayesian predictive performance with and without peak concentration data using clinical TDM data. We retrospectively analyzed 54 adult patients without renal impairment who had two serial peak and trough concentration measurements in a ≤1-week interval. The concentration and AUC values were estimated and predicted using Bayesian software (MwPharm++; Mediware, Prague, Czech Republic). The median prediction error (MDPE) for bias and median absolute prediction error (MDAPE) for imprecision were calculated based on the estimated AUC and measured trough concentration. AUC predictions using the trough concentration had an MDPE of -1.6% and an MDAPE of 12.4%, whereas those using both peak and trough concentrations had an MDPE of -6.2% and an MDAPE of 16.9%. Trough concentration predictions using the trough concentration had an MDPE of -8.7% and an MDAPE of 18.0%, whereas those using peak and trough concentrations had an MDPE of -13.2% and an MDAPE of 21.0%. The usefulness of the peak concentration for predicting the AUC on the next occasion by Bayesian modeling was not demonstrated; therefore, the practical value of peak sampling for AUC-guided dosing can be questioned. As this study was conducted in a specific setting and generalization is limited, results should be interpreted cautiously.

Development and Evaluation of a Novel Software Program, SAKURA-TDM, for Area Under the Concentration-Time Curve-Guided Vancomycin Dosing: A Short Communication.

The area under the concentration-time curve (AUC)-guided dosing of vancomycin has been introduced in Japan; however, the optimal dosing method remains controversial. Here, a novel software program was developed for AUC-guided vancomycin dosing and to estimate the theoretical threshold of the steady-state AUC 24 that could reduce the risk of renal injury. A single-center, retrospective, observational study was conducted to develop a novel software program (SAKURA-TDM ver.1.0) for AUC-guided dosing. The estimation accuracy of pharmacokinetic parameters determined using SAKURA-TDM was compared with that of clinically available software programs and assessed with Bland-Altman analysis. In addition, theoretical cutoff points of the steady-state AUC 24 and the predicted trough values were estimated using Youden J statistic approach. The estimation accuracy of pharmacokinetic parameters and AUC determined using SAKURA-TDM was comparable to that of other TDM software programs. Of note, despite a good relationship between the predicted AUC 24 and trough values, the correlation between the predicted AUC 24 and measured trough values was not strong. The cutoff values of the steady-state AUC 24 and the predicted trough value for reducing the probability of a measured trough value of >20 mcg/mL were 513.1 mg·h/L and 15.6 mcg/mL, respectively. We demonstrated the equivalence of the estimated PK parameters between SAKURA-TDM and other TDM software programs available in Japan. Considering the threshold of both trough values and the steady-state AUC and monitoring of the AUC in a non-steady state, it would be possible to reduce the risk of vancomycin-associated renal injury.

Mycophenolate Mofetil Dose Adjustment in Pediatric Kidney Transplant Recipients.

The Immunosuppressant Bayesian Dose Adjustment web site aids clinicians and pharmacologists involved in the care of transplant recipients; it proposes dose adjustments based on the estimated area under the concentration-time curve (AUCs). Three concentrations (T 20 min , T 1 h , and T 3 h ) are sufficient to estimate mycophenolic acid (MPA) AUC 0-12 h in pediatric kidney transplant recipients. This study investigates mycophenolate mofetil (MMF) doses and MPA AUC values in pediatric kidney transplant recipients, and target exposure attainment when the proposed doses were followed, through a large-scale analysis of the data set collated since the inception of the Immunosuppressant Bayesian Dose Adjustment web site. In this study, 4051 MMF dose adjustment requests, corresponding to 1051 patients aged 0-18 years, were retrospectively analyzed. AUC calculations were performed in the back office of the Immunosuppressant Bayesian Dose Adjustment using published Bayesian and population pharmacokinetic models. The first AUC request was posted >12 months posttransplantation for 41% of patients. Overall, only 50% had the first MPA AUC 0-12 h within the recommended 30-60 mg.h/L range. When the proposed dose was not followed, the proportion of patients with an AUC in the therapeutic range for MMF with cyclosporine or tacrolimus at the subsequent request was lower (40% and 45%, respectively) than when it was followed (58% and 60%, respectively): P = 0.08 and 0.006, respectively. Furthermore, 3 months posttransplantation, the dispersion of AUC values was often lower at the second visit when the proposed doses were followed, namely, P = 0.03, 0.003, and 0.07 in the 4 months-1 year, and beyond 1 year with <6-month or >6-month periods between both visits, respectively. Owing to extreme interindividual variability in MPA exposure, MMF dose adjustment is necessary; it is efficient at reducing such variability when based on MPA AUC.

Vancomycin AUC values estimated with trough-only data: Accuracy in an adult academic medical center population.

Vancomycin area under the concentration-time curve (AUC) can be calculated using steady-state serum peak and trough concentrations; however, compared to traditional trough-only monitoring, this approach requires an additional blood sample. Recently published data demonstrated vancomycin AUC estimations using trough-only data with a volume of distribution (Vd) model incorporating age and actual body weight were reasonably accurate and precise in a veteran population. This study sought to extend these methods to a Mayo Clinic adult population. A retrospective, observational cohort of adult patients with documented steady-state vancomycin peak and trough concentrations was evaluated. Vancomycin AUCs were estimated using trough-only data, and 4 Vd models were assessed for accuracy and precision. Estimated AUCs were compared to AUCs calculated using 1-compartment intermittent infusion equations and steady-state peak and trough ("peak-trough") data. The study population (N = 95) was 46% female, with a median age of 59 years and a median weight of 97 kg. Using the VancoPK equation Vd = 0.29 (age in y) + 0.33 (actual weight in kg) + 11, the mean peak-trough and estimated trough-only AUC were 533 and 534, respectively, with a correlation of 0.936. The root mean square error was 47.7, meaning about 95% of AUCs were within 95 mg · h/L of peak-trough AUCs. Accuracy and precision of Vancomycin AUC estimations using trough-only data and the described Vd model were demonstrated in a Mayo Clinic cohort. Targeting an estimated AUC of 500 mg · h/L using the VancoPK model would likely result in an actual AUC within 400 to 600 mg · h/L.

Prediction Accuracy of Area under the Concentration-Time Curve of Vancomycin by Bayesian Approach Using Creatinine-Based Equations of Estimated Kidney Function in Bedridden Elderly Japanese Patients.

An administration plan for vancomycin (VCM) in bedridden elderly patients has not been established. This retrospective study aimed to evaluate the prediction accuracy of the area under the concentration-time curve (AUC) of VCM by the Bayesian approach using creatinine-based equations of estimated kidney function in such patients. Kidney function was estimated using the Japanese equation of estimated glomerular filtration rate (eGFR) and the Cockcroft-Gault equation of estimated creatinine clearance (eCCr). eCCr (serum creatinine (SCr) + 0.2) was calculated by substituting the SCr level +0.2 mg/dL into the Cockcroft-Gault equation. For eGFR/0.789, eGFR, eCCr, and eCCr (SCr + 0.2), the AUC values were calculated by the Bayesian approach using the therapeutic drug monitoring (TDM) software, BMs-Pod (ver 8.06) and denoted as AUCeGFR/0.789, AUCeGFR, AUCeCCr, and AUCeCCr (SCr + 0.2) respectively. The reference AUC (AUCREF) was calculated by applying VCM's peak and trough steady-state concentrations to first-order pharmacokinetic equations. The medians (range) of AUCeGFR/0.789/AUCREF, AUCeGFR/AUCREF, AUCeCCr/AUCREF, and AUCeCCr (SCr + 0.2)/AUCREF were 0.88 (0.74-0.93), 0.90 (0.79-1.04), 0.92 (0.81-1.07), and 1.00 (0.88-1.11), respectively. Moreover, the percentage of patients within 10% of the AUCREF, defined as |Bayesian-estimated AUC - AUCREF| < AUCREF × 0.1, was the highest (86%) in AUCeCCr (SCr + 0.2). These results suggest that the Bayesian approach using eCCr (SCr + 0.2) has the highest prediction accuracy for the AUCREF in bedridden elderly patients. Although further studies are required with more accurate determination methods of the CCr and AUC, our findings highlight the potential of eCCr (SCr + 0.2) for estimating VCM's AUC by the Bayesian approach in such patients.

Correlation between pharmacokinetic parameters of 5-fluorouracil and related metabolites and adverse reactions in East-Asian patients with advanced colorectal cancer.

To examine the range of the area under the concentration-time curve (AUC) calculated using plasma 5-FU concentration at steady-state plasma concentration-time of 5-fluorouracil (5-FU) and correlation between 5-FU metabolites (5,6-dihydro-5-fluorouracil, 5-FUH2 and α-fluoro-β-Alanine, FBAL) plasma concentration and adverse reactions when patients with advanced colorectal cancer (CRC) received 5-FU-based chemotherapy. 74 patients with advanced CRC receiving 5-FU-based chemotherapy from Aug. 2017 to Nov. 2020 in Harbin Medical University Cancer Hospital were involved in this study, the dosage of 5-FU being determined according to the patient's body surface area (BSA). Using an ultra-high performance liquid chromatography-tandem mass spectrum (UPLC-MS/MS) to determine the 5-FU steady-state plasma concentration (CSS) and plasma concentration of 5-FUH2 and FBAL in CRC patients receiving 5-FU in continuous intravenous infusion for 18-30h, the start time and end time of 5-FU infusion in patients were accurately recorded and the continuous infusion time (TCI) was calculated. The AUC value was calculated according to AUC = CSS × TCI. At the same time, the treatment effects and adverse drug reactions of patients were evaluated, to analyze the relationship between 5-FU AUC, 5-FUH2 and FBAL plasma concentration and clinical efficacy and adverse reactions in CRC patients, and explore the ideal AUC range of 5-FU in the treatment of colorectal cancer. The AUC of 5-FU was not normally distributed and ranged from 3.13 to 41.12mgh/L, with an average value of 14.81 ± 8.62mg·h /L, and the AUC values had obvious inter-individual differences up to 13 times. 5-FUH2 ranged from 131.98 to 987.93ng/mL, with an average of 550.58 ± 260.60ng/mL; FBAL ranged from 23.58 to 262.48ng/mL, with an average of 89.79 ± 58.47ng/mL. Correlation analysis results revealed a significant correlation between 5-FU AUC, 5-FUH2 and FABL plasma concentration and adverse reactions, 5-FU AUC and clinical efficacy. There are obvious individual differences in AUC values in CRC patients receiving different dosages of 5-FU based on BSA. The ideal AUC range of 5-FU is 18.23-29.17mg·h/L. There was a significant correlation between 5-FUH2 and FABL plasma concentration and adverse reactions.

Therapeutic drug monitoring of intravenous busulfan in Thai children undergoing hematopoietic stem cell transplantation: A pilot study

Busulfan (Bu) is commonly used in myeloablative conditioning regimens for children undergoing hematopoietic stem cell transplantation. The standard target area under the concentration-time curve (AUC) of Bu is approximately 900–1500 µM min. In previous studies using five fixed doses (0.8–1.2 mg/kg) for Bu without dose adjustment, 75% patients achieved the target AUC. The aim of this pilot study was to determine the percentage of target AUC for intravenous (IV) Bu in Thai children. IV Bu was administered every 6 h over 16 doses. Blood samples were collected for pharmacokinetic (PK) analysis after the first, ninth, and thirteenth doses of Bu. Seven patients (2–14 years; median 6 years) were diagnosed with thalassemia (n = 4), acute myeloid leukemia (n = 2), and pure red cell aplasia. Three, two, and two patients received Bu at 1.1, 1.2, and 0.8 mg/kg, respectively. The AUC of Bu varied from 292–1714 µM min (median = 804). Nine (42.86%), eleven (52.38%), and one (4.76%) AUC values were within, below, and above the target, respectively. The median (range) Bu clearance was 5.93 (1.91–14.65) mL/min/kg. In this study, 42.86% AUC value achieved the target, which was lower than that in previous studies. Therapeutic drug monitoring (TDM) of Bu should be considered in Thai children receiving five fixed doses of IV Bu, and dose adjustment should be performed as necessary. Further PK studies for Bu with a larger sample size are warranted for confirming the necessity of TDM in every step dose of Bu. (Trial registration numbers; TCTR20190528003)

Estimation of the area under concentration-time curve of polymyxin B based on limited sampling concentrations in Chinese patients with severe pneumonia.

The efficacy and toxicity of polymyxin B (PB) are closely related to its pharmacokinetic/pharmacodynamic (PK/PD) index area under the concentration-time curve (AUC) to minimum inhibitory concentration (MIC) ratio. The purpose of this study was to obtain PK data for PB in Chinese severe pneumonia patients and establish appropriate blood sampling time points for the PB therapeutic drug monitoring (TDM). After treatment with at least four doses of PB (50 IU, q12h), the blood samples were collected immediately after the end of infusion (C0) and 1.5, 2, 4, 6, 8, and 12 h (C1.5, C2, C4, C6, C8, C12) after PB administration. The PB blood plasma concentrations were determined using an ultra-performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS). All 42 patients were randomly divided into modeling (n = 24) and validation (n = 18) groups. The relationship between AUCss,24h and PB plasma concentration at each time point in modeling group was analyzed using limited sampling strategy and a PK method based on one-compartment with correction model. C6 scheme was found to provide the most accurate prediction of AUCss,24h values (r2 = 0.984) with the target value of 1.9-4.2 μg/ml at steady state to reach the 50-100 μg h/ml criteria of AUCss,24h. C0 with target value of 1.0-2.8 μg/ml can be considered an alternative sampling scheme (r2 = 0.900) but prediction deviation may exist. C0 and Cmax sampling scheme also demonstrated good predicting ability of AUC values using PK model. This study provides a clear plan for the implementation of TDM of PB, which is useful for optimizing the dosing regimen and individualizing treatment in severe pneumonia patients.

Population pharmacokinetic (PK) and exposure-response analyses from the pivotal ALTA-1L study: Model-based analyses supporting the brigatinib dose in patients with anaplastic lymphoma kinase (ALK)–positive non–small cell lung cancer (NSCLC).

e21725 Background: Brigatinib is a next-generation ALK tyrosine kinase inhibitor (TKI) with differential activity by dose (90 mg vs 180 mg [with a 7-day lead-in at 90 mg] qd) in the phase 2 post-crizotinib ALTA trial (NCT02094573). Herein, we describe results from population PK and exposure-response analyses of the efficacy and safety of brigatinib 180 mg qd (with a 7-day lead-in at 90 mg) from data in the first-line phase 3 ALTA-1L study (NCT02737501). Methods: Brigatinib plasma concentration-time data were described by a 3-compartment model with transit compartment absorption. Post hoc individual apparent clearance estimates for brigatinib were obtained using Bayesian re-estimation and used to calculate time-averaged area under the concentration-time curve (AUC) values for logistic regression analyses of relationships to response endpoints (confirmed objective response rate [ORR], intracranial ORR) and time-varying AUC values for parametric time-to-event models of relationships to progression-free survival (PFS). Population PK modeling, covariate analysis, and simulations were performed using NONMEM (version 7.3 or higher), running under PsN (Perl-speaks-NONMEM, version 4.6 or higher), while exposure–efficacy and safety analyses were performed using R (version 3.5.2 or higher). Results: Brigatinib PK parameters and estimated systemic exposures for patients in ALTA-1L (ALK TKI–naive setting) were similar to those in the 180 mg qd arm of ALTA. Patient covariates including weight, sex, age, race, and renal function (CrCL ≥30 mL/min) were not found to impact brigatinib exposure, suggesting no dose adjustment based on these covariates. In the exposure-response analyses, brigatinib exposure was not a significant predictor of response (≥partial response) or PFS. This suggests that the efficacy benefit was consistent across the range of exposures achieved with the 180 mg dosing regimen including after dose modifications. There was a significant relationship ( P&lt; 0.05) between exposure and certain laboratory abnormalities (increased amylase and lipase). There was no relationship between exposure and CPK elevation, and brigatinib exposure had no effect on time to first dose reduction. Conclusions: These results support a favorable benefit/risk profile of the proposed 180 mg qd brigatinib dose (with a 7-day lead-in at 90 mg) for the front-line treatment of patients with ALK+ NSCLC. Clinical trial information: NCT02737501.

In vitro and in vivo evaluation of the influences of polysaccharides derived from Glycyrrhiza uralensis on three alkaloids and potential interaction mechanisms

The purpose of this study was to investigate the influences of the polysaccharides derived from Glycyrrhiza uralensis Fisch. (GCPs) on aconitine (AC), hypaconitine (HA), and benzoylmesaconine (BMA) from Aconitum carmichaelii Debx. and to explore potential interaction mechanisms. Biopharmaceutical properties in vitro including stability, aqueous solubility and permeability were determined by UPLC. Pharmacokinetic parameters in vivo were determined using UPLC-MS/MS. Phase solubility analysis, UV–vis spectrophotometry and differential scanning calorimetry (DSC) were used to explore potential interaction mechanisms. The results showed that GCPs could increase the stabilities of three alkaloids and solubilities of AC and HA, significantly decrease permeabilities of three alkaloids. The pharmacokinetic studies demonstrated that, after combination with GCPs, AC exhibited a higher Cmax value, shorter t0.5, higher elimination rate and greater area under the concentration-time curve (AUC) value compared to free AC. GCPs also improved the Cmax, t0.5, AUC(0–tn) and AUC(0–∞) values of HA to play a therapeutic role, and improved the t0.5 and AUC(0–∞) values of BMA to prolong the pharmacological effect and increase bioavailability. In addition, the results for the apparent formation constants and DSC analysis showed that an inclusion complex could be formed between GCPs and AC, GCPs and HA, and GCPs and BMA.

Modulation of CYP3A Activity to Increase the Oral Bioavailability of Ibrutinib

BackgroundIbrutinib (Imbruvica; PCI‐32765), an orally administered inhibitor of Bruton’s tyrosine kinase, is considered a breakthrough targeted therapy that is approved as frontline therapy in chronic lymphocytic leukemia (CLL). Ibrutinib has an average oral bioavailability in humans of &lt;4% with substantial variability in exposure, which predisposes patients to unpredictable and potentially harmful adverse events such as bleeding and atrial fibrillation. As ibrutinib is subject to extensive first‐pass metabolism by CYP3A following oral administration, inhibition of CYP3A activity may be a promising strategy to increase the bioavailability and decrease inter‐individual pharmacokinetic (PK) variability of ibrutinib. The objective of this study was to characterize the impact of CYP3A on the PK of ibrutinib and its main active metabolite, PCI‐45227, in mice.MethodsTo characterize the impact of CYP3A on ibrutinib disposition, in vivo PK studies were performed in wild‐type (WT) male and female FVB mice treated with CYP3A inhibitors including ketoconazole (50 mg/kg p.o.) and cobicistat (30 mg/kg; p.o.) or the respective vehicle controls (PEG400 or corn oil p.o.) thirty minutes prior to dosing with ibrutinib (10 mg/kg p.o.). Based on these results, CYP3A(−/−) female FVB mice were treated with ibrutinib (10 mg/kg p.o. or 1 mg/kg i.v.) alone or thirty minutes after administration of cobicistat (30 mg/kg; p.o.). Concentrations of ibrutinib and PCI‐45227 in plasma were determined by a validated method based on liquid chromatography‐tandem mass spectrometry, and PK parameter estimates were calculated with the software package Phoenix WinNonlin (Version 8.1). Student t‐tests comparing mean AUC values between groups were used to determine significance.ResultsThe peak plasma concentration (Cmax) and area under the concentration‐time curve (AUC) of ibrutinib were ~10‐fold higher in mice administered pharmacologic CYP3A inhibitors prior to ibrutinib (P &lt; 0.0001) with a substantial decrease in the PCI‐45227 to ibrutinib AUC ratio. As expected, when ibrutinib was administered orally to CYP3A(−/−) mice, the AUC of ibrutinib in CYP3A(−/−) mice was increased ~10‐fold (P &lt; 0.0001) with almost no formation of the PCI‐45227 metabolite compared with WT mice. Cobicistat did not impact ibrutinib AUC in CYP3A(−/−) mice (P &gt; 0.9), which suggests that CYP3A inhibition is the major mechanism for cobicistat‐induced increases in ibrutinib exposure.ConclusionsPreviously obtained data with other kinase inhibitors indicate that patients with high CYP3A4 activity may benefit from an increased dose to achieve drug concentrations required to interact with kinase targets; a strategy by which enzyme activity is inhibited could achieve similar results. In view of the established inverse‐correlation between absolute bioavailability and inter‐individual PK variability, the current data provide a rationale for the development of exploratory clinical studies aimed at decreasing the variability in ibrutinib exposure by concomitant administration of CYP3A4 inhibitors. Future preclinical efficacy studies will determine the impact of this strategy on survival in mouse models of B‐cell malignancies.

Chemical and Physical Stability of an Admixture Containing Cefepime and Vancomycin in Lactated Ringer Solution.

Purpose: To evaluate the chemical and physical stability of an admixture containing cefepime and vancomycin in a single volume of lactated Ringer solution at refrigerated temperatures. Methods: Cefepime 2000 mg and vancomycin 1000 mg were, respectively, reconstituted with 10 and 20 mL of sterile water for injection (SWFI) per manufacturer instructions. This resulted in cefepime and vancomycin concentrations of 200 and 50 mg/mL, respectively. The resulting cefepime and vancomycin solutions at 10 and 20 mL, respectively, were drawn up and injected into 1000 mL lactated Ringer solution. Aliquot samples were obtained on days 0 to 9, visually inspected for gross incompatibility, and then stored at -80°C. Samples were thawed on the day of the analysis and run through ultraperformance liquid chromatography. Area under the concentration-time curve (AUC) on each day was compared with baseline AUC values. Chemical stability was defined as an AUC more than 93% of the baseline value. Results: No evidence of gross physical incompatibility was observed by visual inspection. Cefepime and vancomycin replicants were more than 94.5% and 98% of baseline AUC values. Therefore, all sample replicants were found to be more than 93% of their baseline AUC value. Conclusion: An admixture containing cefepime 2000 mg and vancomycin 1000 mg in 1000 mL lactated Ringer solution appears to be chemically and physically stable at refrigerated temperatures for up to 9 days.

1561. Omadacycline Pharmacokinetics: Influence of Mortality Risk Score Among Patients with Community-Acquired Bacterial Pneumonia

BackgroundOmadacycline is a novel aminomethylcycline with activity against Gram-positive and -negative organisms, including tetracycline-resistant pathogens. Omadacycline was recently approved in the United States for treatment of adult patients with community-acquired bacterial pneumonia (CABP) and acute bacterial skin and skin structure infections. Analyses were undertaken to determine whether PORT risk class and CURB-65 score influence the pharmacokinetics of omadacycline in patients with CABP.MethodsOmadacycline pharmacokinetic data were available from omadacycline-treated patients with CABP enrolled in the Phase 3 OPTIC Study. Patients received omadacycline 100 mg IV q12h on Day 1 followed by 100 mg IV q24h. After Day 3, patients could be switched to 300 mg PO q24h if predefined clinical stability criteria were met. Four pharmacokinetic samples per patient were collected between Days 2 and 5. These data were previously utilized in the development of a population pharmacokinetic model describing the disposition of omadacycline [Microbe 2018; Abstr SAT-628]. Individual post-hoc parameter estimates for patients enrolled in the OPTIC study were utilized to compute Day 1 total-drug plasma area under the concentration-time curve (AUC) values following administration of omadacycline 100 mg IV q12h. Differences among these AUC values by PORT risk class and CURB-65 score were assessed using a one-way ANOVA.ResultsA total of 187 pharmacokinetic samples were available from 50 patients. Among the patients classified as PORT risk class II, III, and IV (n = 12, 28, and 10, respectively), mean Day 1 omadacycline AUC values were 10.2, 11.0, and 12.0 mg L/h, respectively. Among patients with CURB-65 scores of 0, 1, and 2 (n = 23, 23, and 4, respectively), mean Day 1 omadacycline AUC values were 10.6, 11.6, and 9.7 mg L/h, respectively. The differences in mean AUC values were not statistically significant among patients by PORT risk class (P = 0.248) and CURB-65 score groups (P = 0.745). Moreover, variability was similar across these groups as displayed in Figure 1.ConclusionOmadacycline exposures were similar across PORT risk class and CURB-65 score groups; thus, omadacycline dose adjustments based on these classifications are likely not warranted. Disclosures All authors: No reported disclosures.

In Vitro and In Vivo Assessment of the Potential of Supersaturation to Enhance the Absorption of Poorly Soluble Basic Drugs

Delaying precipitation of weakly basic drugs in supersaturated state following their transition from the acidic gastric environment to the near-neutral proximal small intestinal fluid is emerging as a promising tactic for achieving higher transitional solubility and improving bioavailability of such drugs. The aim of this study was to assess the effect of supersaturation on drug dissolution and permeation in vitro, and to evaluate the in vitro-in vivo correlation of the supersaturation effect for the poorly soluble basic drug ketoconazole. We monitored dissolution of drugs in simulated gastric fluid followed by drug dissolution in simulated intestinal fluid and simultaneous permeation across Caco-2 cell monolayers using the IDAS2 experimental procedure. The pH shift from pH 1.6 to pH 6.5 (mimicking in vivo gastric to intestinal transition) was used to induce transient in vitro supersaturation of the tested weakly basic poorly soluble drugs. Polymeric precipitation inhibitor, hydroxypropyl methylcellulose acetate succinate (HPMCAS), was added to dissolution medium in order to increase the amplitude and duration of the pH-driven supersaturation of the weakly basic drug ketoconazole in the in vitro IDAS2 setting. The effect of HPMCAS on oral bioavailability of ketoconazole was demonstrated in the rat pharmacokinetic model. Drug supersaturation induced by pH shift was assessed in vitro by comparing drug dissolution and permeation under the 2-stage (pH shift from gastric pH 1.6 to intestinal pH 6.5) conditions vs. 1-stage (constant intestinal pH 6.5) conditions. Compared to the 1-stage conditions, 2-stage procedure increased in vitro dissolution AUC (area under the concentration-time curve) of the weakly basic drugs dipyridamole, ketoconazole, and itraconazole by 393%, 161%, and 71%, respectively, accompanied by corresponding 543%, 264%, and 46% increase in in vitro permeation. In contrast, the BCS 2 acidic drug warfarin exhibited 9% decrease in dissolution under 2-stage conditions, which was associated with a 21% decrease in permeation. None of the tested BCS 1 drugs (minoxidil and metoprolol) exhibited supersaturation after the gastric to intestinal pH shift; consistent with the absence of supersaturation, and the permeation of these drugs was not affected by the transition from simulated gastric to simulated intestinal environments. The polymeric precipitation inhibitor, HPMCAS, increased the in vitro dissolution and permeation AUC values of ketoconazole by 187% and 119%, respectively, and ketoconazole plasma AUC0-24h and Cmax by 54% and 49% following oral administration in rats. This study has shown that the novel in vitro dissolution-absorption methodology simulating the in vivo gastrointestinal environments that influence drug release and absorption of orally administered drugs constitutes a sensitive and physiologically relevant approach for investigating the potential utility of formulation excipients for exploiting supersaturation as a means to improve systemic drug absorption.

Conversion from Vancomycin Trough Concentration-Guided Dosing to Area Under the Curve-Guided Dosing Using Two Sample Measurements in Adults: Implementation at an Academic Medical Center.

The optimal pharmacodynamic parameter for the prediction of efficacy of vancomycin is the area under the concentration-time curve (AUC), and current published data indicate that dosing based on vancomycin trough concentrations is an inaccurate substitute. In this study, our objective was to compare the achievement of therapeutic target attainment after switching from a trough-based to an AUC-based dosing strategy as a part of our institution's vancomycin-per-pharmacy protocol. Prospective observational quality assurance study. Academic medical center. A total of 296 hospitalized adults who received vancomycin and monitoring under our institution's vancomycin-per-pharmacy protocol were included in the analysis. The preimplementation retrospective comparison group consisted of 179 patients in whom vancomycin was initiated using a trough-based dosing strategy between November 22, 2017, and January 22, 2018. The postimplementation group included 117 patients in whom vancomycin was initiated using an AUC-based dosing strategy using two-point sampling between June 19, 2018, and July 19, 2018, after hospital-wide implementation of this protocol on June 19, 2018. AUC values were calculated from two vancomycin concentrations (peak and trough). The primary outcome was achievement of therapeutic AUC values (400-800mg·hr/L) in the postimplementation group or therapeutic trough level values (10-20mg/L) in the preimplementation group. Only 98 (55%) of 179 initial trough values were therapeutic in the preimplementation group (trough-only dosing method) versus 86 (73.5%) of 117 initial AUC values in the postimplementation group (AUC-based dosing method) (p=0.0014). A lower proportion of supratherapeutic AUC values was observed in the postimplementation group compared with supratherapeutic trough concentrations in the preimplementation group (1.7% vs 18%, p<0.0001). Overall, 62% of patients with initially therapeutic AUC values had subsequent trough value increases of 25% or greater, occurring at a median of 6days of vancomycin therapy. Nephrotoxicity occurred in 11% of patients in the preimplementation versus 9.4% in the postimplementation group (p=0.70). Compared with a trough concentration-based dosing strategy, AUC-based dosing using two-point sampling improved therapeutic target attainment. Implementation is feasible at any hospital that performs vancomycin peak concentration testing and is a workable alternative to using Bayesian software for estimating AUC. This approach should also be directly compared with AUC-based dosing using Bayesian software.

A Comparative Study Between Allometric Scaling and Physiologically Based Pharmacokinetic Modeling for the Prediction of Drug Clearance From Neonates to Adolescents.

The objective of this study was to compare the predictive performance of an allometric model with that of a physiologically based pharmacokinetic (PBPK) model to predict clearance or area under the concentration-time curve (AUC) of drugs in subjects from neonates to adolescents. From the literature, 10 studies were identified in which clearance or AUC of drugs from neonates to adolescents was predicted by PBPK models. In these published studies, drugs were given to children either by intravenous or oral route. The allometric model was an age-dependent exponent (ADE) model for the prediction of clearance across the age groups. The predicted clearance or AUC values from the PBPK and ADE models were compared with the experimental values. The acceptable prediction error was the percentage of subjects within an 0.5- to 2-fold or 0.5- to 1.5-fold prediction error. There were 73 drugs with a total of 372 observations. From PBPK and allometric models, 91.1% and 90.6% of observations were within 0.5- to 2-fold prediction error, respectively. For children ≤2 years old (n = 130), PBPK and allometric models had 89% and 87% of observations within the 0.5- to 2-fold prediction error, respectively. This study indicates that the predictive power of PBPK and allometric models was essentially similar for the prediction of clearance or AUC in pediatric subjects ranging from neonates to adolescents.

Impact of P-Glycoprotein on Intestinal Absorption of an Inhibitor of Apoptosis Protein Antagonist in Rats: Mechanisms of Nonlinear Pharmacokinetics and Food Effects.

This study was designed to investigate the effects of P-glycoprotein (P-gp) expressed in the intestine on the nonlinear pharmacokinetics (PK) of T-3256336, an inhibitor of apoptosis protein inhibitor, and food effects on its bioavailability in rats. To investigate the factors that contribute to nonlinear PK of T-3256336 in the intestine and liver, rats double-cannulated in the portal vein and femoral artery (PS rats) were used. FaFg (Fa, absorption ratio; Fg, intestinal availability) and hepatic availability (Fh) were simultaneously evaluated based on the difference between the portal and systemic blood area under the concentration-time curve (AUC). Elacridar was used as a P-gp inhibitor to assess the impact of P-gp on the intestinal absorption. After oral administration of T-3256336 to PS rats at 3 and 30mg/kg, FaFg value increased with dose escalation, whereas Fh value was nearly constant. Moreover, co-administration of elacridar resulted in a 5-fold increase in the FaFg value at 3mg/kg. The AUC value of T-3256336 under fed conditions was 3-fold lower than that under fasted conditions. This food effect on the oral bioavailability (BA) was reduced by concomitant administration of elacridar. P-gp expressed in the intestine would cause nonlinear PK and a food effect on BA of T-3256336 in rats.