Evaluating the indotecan-neutropenia relationship in patients with solid tumors by population pharmacokinetic modeling and sigmoidal Emax regressions.

PURPOSE: This study aimed at characterizing indotecan population pharmacokinetics and explore the indotecan-neutropenia relationship in patients with solid tumors. METHODS: Population pharmacokinetics were assessed using nonlinear mixed-effects modeling of concentration data from two first-in-human phase 1 trials evaluating different dosing schedules of indotecan. Covariates were assessed in a stepwise manner. Final model qualification included bootstrap simulation, visual and quantitative predictive checks, and goodness-of-fit. A sigmoidal Emax model was developed to describe the relationship between average concentration and maximum percent neutrophil reduction. Simulations at fixed doses were conducted to determine the mean predicted decrease in neutrophil count for each schedule. RESULTS: 518 concentrations from 41 patients supported a three-compartment pharmacokinetic model. Body weight and body surface area accounted for inter-individual variability of central/peripheral distribution volume and intercompartmental clearance, respectively. Estimated typical population values were CL 2.75 L/h, Q3 46.0 L/h, and V3 37.9 L. The estimated value of Q2 for a typical patient (BSA = 1.96 m2) was 17.3 L/h, while V1 and V2 for a typical patient (WT = 80 kg) was 33.9 L and 132 L. The final sigmoidal Emax model estimated that half-maximal ANC reduction occurs at an average concentration of 1416 µg/L and 1041 µg/L for the daily and weekly regimens, respectively. Simulations of the weekly regimen demonstrated lower percent reduction in ANC compared to the daily regimen at equivalent cumulative fixed doses. CONCLUSION: The final PK model adequately describes indotecan population pharmacokinetics. Fixed dosing may be justified based on covariate analysis and the weekly dosing regimen may have a reduced neutropenic effect.

Evidence for deleterious effects of immunological history in SARS-CoV-2.

A previous report demonstrated the strong association between the presence of antibodies binding to an epitope region from SARS-CoV-2 nucleocapsid, termed Ep9, and COVID-19 disease severity. Patients with anti-Ep9 antibodies (Abs) had hallmarks of antigenic interference (AIN), including early IgG upregulation and cytokine-associated injury. Thus, the immunological memory of a prior infection was hypothesized to drive formation of suboptimal anti-Ep9 Abs in severe COVID-19 infections. This study identifies a putative primary antigen capable of stimulating production of cross-reactive, anti-Ep9 Abs. Binding assays with patient blood samples directly show cross-reactivity between Abs binding to Ep9 and only one bioinformatics-derived, homologous putative antigen, a sequence derived from the neuraminidase protein of H3N2 influenza A virus. This cross-reactive binding is highly influenza strain specific and sensitive to even single amino acid changes in epitope sequence. The neuraminidase protein is not present in the influenza vaccine, and the anti-Ep9 Abs likely resulted from the widespread influenza infection in 2014. Therefore, AIN from a previous infection could underlie some cases of COVID-19 disease severity.

Evidence for Deleterious Antigenic Imprinting in SARS-CoV-2 Immune Response.

A previous report demonstrated the strong association between the presence of antibodies binding to an epitope region from SARS-CoV-2 nucleocapsid, termed Ep9, and COVID-19 disease severity. Patients with anti-Ep9 antibodies (Abs) had hallmarks of antigenic imprinting (AIM), including early IgG upregulation and cytokine-associated injury. Thus, the immunological memory of a previous infection was hypothesized to drive formation of suboptimal anti-Ep9 Abs in severe COVID-19 infections. This study identifies a putative primary antigen capable of stimulating production of cross-reactive, anti-Ep9 Abs. Binding assays with patient blood samples directly show cross-reactivity between Abs binding to Ep9 and only one bioinformatics-derived, homologous potential antigen, a sequence derived from the neuraminidase protein of H3N2 Influenza A virus. This cross-reactive binding is highly influenza strain specific and sensitive to even single amino acid changes in epitope sequence. The neuraminidase protein is not present in the influenza vaccine, and the anti-Ep9 Abs likely resulted from the widespread influenza infection in 2014. Therefore, AIM from a previous infection could underlie some cases of COVID-19 disease severity. IMPORTANCE: Infections with SARS-COV-2 result in diverse disease outcomes, ranging from asymptomatic to fatal. The mechanisms underlying different disease outcomes remain largely unexplained. Previously, our laboratory identified a strong association between the presence of an antibody and increased disease severity in a subset of COVID-19 patients. Here, we report that this severity-associated antibody cross-reacts with viral proteins from an influenza A viral strain from 2014. Therefore, we speculate that antibodies generated against previous infections, like the 2014 influenza A, play a significant role in directing some peoples’ immune responses against SARS-COV-2. Such understanding of the sources and drivers of COVID-19 disease severity can help early identification and pre-emptive treatment.

Predicting COVID-19 Severity with a Specific Nucleocapsid Antibody plus Disease Risk Factor Score.

Effective methods for predicting COVID-19 disease trajectories are urgently needed. Here, enzyme-linked immunosorbent assay (ELISA) and coronavirus antigen microarray (COVAM) analysis mapped antibody epitopes in the plasma of COVID-19 patients (n = 86) experiencing a wide range of disease states. The experiments identified antibodies to a 21-residue epitope from nucleocapsid (termed Ep9) associated with severe disease, including admission to the intensive care unit (ICU), requirement for ventilators, or death. Importantly, anti-Ep9 antibodies can be detected within 6 days post-symptom onset and sometimes within 1 day. Furthermore, anti-Ep9 antibodies correlate with various comorbidities and hallmarks of immune hyperactivity. We introduce a simple-to-calculate, disease risk factor score to quantitate each patient's comorbidities and age. For patients with anti-Ep9 antibodies, scores above 3.0 predict more severe disease outcomes with a 13.42 likelihood ratio (96.7% specificity). The results lay the groundwork for a new type of COVID-19 prognostic to allow early identification and triage of high-risk patients. Such information could guide more effective therapeutic intervention.IMPORTANCE The COVID-19 pandemic has resulted in over two million deaths worldwide. Despite efforts to fight the virus, the disease continues to overwhelm hospitals with severely ill patients. Diagnosis of COVID-19 is readily accomplished through a multitude of reliable testing platforms; however, prognostic prediction remains elusive. To this end, we identified a short epitope from the SARS-CoV-2 nucleocapsid protein and also a disease risk factor score based upon comorbidities and age. The presence of antibodies specifically binding to this epitope plus a score cutoff can predict severe COVID-19 outcomes with 96.7% specificity.

Predicting COVID-19 Severity with a Specific Nucleocapsid Antibody plus Disease Risk Factor Score.

Effective methods for predicting COVID-19 disease trajectories are urgently needed. Here, ELISA and coronavirus antigen microarray (COVAM) analysis mapped antibody epitopes in the plasma of COVID-19 patients (n = 86) experiencing a wide-range of disease states. The experiments identified antibodies to a 21-residue epitope from nucleocapsid (termed Ep9) associated with severe disease, including admission to the ICU, requirement for ventilators, or death. Importantly, anti-Ep9 antibodies can be detected within six days post-symptom onset and sometimes within one day. Furthermore, anti-Ep9 antibodies correlate with various comorbidities and hallmarks of immune hyperactivity. We introduce a simple-to-calculate, disease risk factor score to quantitate each patients comorbidities and age. For patients with anti-Ep9 antibodies, scores above 3.0 predict more severe disease outcomes with a 13.42 Likelihood Ratio (96.7% specificity). The results lay the groundwork for a new type of COVID-19 prognostic to allow early identification and triage of high-risk patients. Such information could guide more effective therapeutic intervention.

Evaluation of the pharmacokinetic drug-drug interaction potential of iohexol, a renal filtration marker.

PURPOSE: Carboplatin dose is calculated based on kidney function, commonly estimated with imperfect creatinine-based formulae. Iohexol is used to measure glomerular filtration rate (GFR) and allows calculation of a more appropriate carboplatin dose. To address potential concerns that iohexol administered during a course of chemotherapy impacts that therapy, we performed in vitro and in vivo pharmacokinetic drug-drug interaction evaluations of iohexol. METHODS: Carboplatin was administered IV to female mice at 60 mg/kg with or without iohexol at 300 mg/kg. Plasma ultrafiltrate, kidney and bone marrow platinum was quantitated by atomic absorption spectrophotometry. Paclitaxel microsomal and gemcitabine cytosolic metabolism as well as metabolism of CYP and UGT probes was assessed with and without iohexol at 300 µg/mL by LC-MS/MS. RESULTS: In vivo carboplatin exposure was not significantly affected by iohexol co-administration (platinum AUC combination vs alone: plasma ultrafiltrate 1,791 vs 1920 µg/mL min; kidney 8367 vs 9757 µg/g min; bone marrow 12.7 vs 12.7 µg/mg-protein min). Paclitaxel microsomal metabolism was not impacted (combination vs alone: 6-α-OH-paclitaxel 38.3 versus 39.4 ng/mL/60 min; 3-p-OH-paclitaxel 26.2 versus 27.7 ng/mL/60 min). Gemcitabine human cytosolic elimination was not impacted (AUC combination vs gemcitabine alone: dFdU 24.1 versus 23.7 µg/mL/30 min). Iohexol displayed no relevant inhibition of the CYP and UGT enzymes in human liver microsomes. CONCLUSIONS: Iohexol is unlikely to affect the clinical pharmacokinetics of carboplatin, paclitaxel, gemcitabine, or other agents used in combination with carboplatin treatment. Measuring GFR with iohexol to better dose carboplatin is unlikely to alter the safety or efficacy of chemotherapy through pharmacokinetic drug-drug interactions.

Calcium carbonate does not affect imatinib pharmacokinetics in healthy volunteers.

PURPOSE: Imatinib mesylate (Gleevec(®)/Glivec(®)) has revolutionized the treatment of chronic myeloid leukemias and gastrointestinal stromal tumors, and there is evidence for an exposure response relationship. Calcium carbonate is increasingly used as a calcium supplement and in the setting of gastric upset associated with imatinib therapy. Calcium carbonate could conceivably elevate gastric pH and complex imatinib, thereby influencing imatinib absorption and exposure. We aimed to evaluate whether use of calcium carbonate has a significant effect on imatinib pharmacokinetics. METHODS: Eleven healthy subjects were enrolled in a 2-period, open-label, single-institution, randomized crossover, fixed-schedule study. In one period, each subject received 400 mg of imatinib p.o. In the other period, 4,000 mg calcium carbonate (Tums Ultra(®)) was administered p.o. 15 min before 400 mg of imatinib. Plasma concentrations of imatinib and its active N-desmethyl metabolite CGP74588 were assayed by LC-MS; data were analyzed non-compartmentally and compared after log transformation. RESULTS: Calcium carbonate administration did not significantly affect the imatinib area under the plasma concentration versus time curve (AUC) (41.2 µg/mL h alone vs. 40.8 µg/mL h with calcium carbonate, P = 0.99), maximum plasma concentration (C(max)) (2.35 µg/mL alone vs. 2.39 µg/mL with calcium carbonate, P = 0.89). CONCLUSIONS: Our results indicate that the use of calcium carbonate does not significantly affect imatinib pharmacokinetics.

Calcium carbonate does not affect nilotinib pharmacokinetics in healthy volunteers.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: Gastric upset is a common side effect of nilotinib therapy, and calcium carbonate is frequently used concomitantly, either as antacid or as calcium supplementation. With the increasing number of oral agents in cancer therapy, oral drug-drug interactions are becoming more relevant. Nilotinib has already been shown to be absorbed to a much lesser extent when co-administered with proton pump inhibitors. Because exposure to sub-therapeutic concentrations of anticancer drugs such as nilotinib may result in selection of resistant clones and ultimately relapse, we studied the effect of a calcium carbonate supplement (Tums Ultra 1000®) on nilotinib pharmacokinetics. WHAT THIS STUDY ADDS: Calcium carbonate may be co-administered with nilotinib without significantly affecting the pharmacokinetics of nilotinib and potentially impacting efficacy. PURPOSE: Nilotinib is a second-generation oral tyrosine kinase inhibitor with superior efficacy compared with imatinib mesylate in the treatment for chronic phase chronic myelogenous leukemia. Calcium carbonate is commonly used as a source of calcium supplementation or as antacid to ameliorate the gastrointestinal side effects associated with nilotinib, which could have unknown effects on nilotinib absorption. The purpose of this study was to provide information on the effect of calcium carbonate on the PK of nilotinib in healthy volunteers. METHODS: Healthy subjects were enrolled in a two-period, open-label, single-institution, randomized, cross-over, fixed-schedule study. In one period, each subject received 400 mg of nilotinib p.o. In the other period, 4,000 mg of calcium carbonate (4 X Tums Ultra 1000®) was administered p.o. 15 min prior to the nilotinib dose. Plasma samples were collected at specified timepoints, concentrations of nilotinib were quantitated by LC-MS, and data were analyzed non-compartmentally. RESULTS: Eleven subjects were evaluable. Calcium supplementation did not significantly affect nilotinib pharmacokinetic parameters including area under the plasma concentration versus time curve (18.4 µg/mL h alone vs. 16.9 µg/mL h with calcium carbonate, p = 0.83; 80 % power); maximum plasma concentration (C(max)) (0.670 µg/mL alone vs. 6.18 µg/mL with calcium carbonate, p = 0.97); or half-life (18.9 h alone vs. 17.2 h with calcium carbonate, p = 0.18). CONCLUSIONS: Our results indicate that the use of calcium carbonate does not significantly affect nilotinib pharmacokinetics.

Effect of a proton pump inhibitor on the pharmacokinetics of imatinib.

AIMS: Imatinib mesylate (Gleevec/Glivec), which has revolutionized the treatment of chronic myeloid leukemias (CML) and gastrointestinal stromal tumours (GIST), has been reported to cause gastric upset. Consequently, proton pump inhibitors (PPI) are frequently co-administered with imatinib. Because PPI can elevate gastric pH and delay gastric emptying or antagonize ATP-binding-cassette transporters, they could influence imatinib absorption and pharmacokinetics. We aimed to evaluate whether use of omeprazole has a significant effect on imatinib pharmacokinetics. METHODS: Twelve healthy subjects were enrolled in a two-period, open-label, single-institution, randomized cross-over, fixed-schedule study. In one period, each subject received 400 mg imatinib orally. In the other period, 40 mg omeprazole (Prilosec) was administered orally for 5 days, and on day 5 it was administered 15 min before 400 mg imatinib. Plasma concentrations of imatinib and its active N-desmethyl metabolite CGP74588 were assayed by LC-MS, and data were analyzed non-compartmentally. RESULTS: PPI administration did not significantly affect the imatinib area under the plasma concentration vs time curve (AUC) (34.1 microg ml(-1) h alone vs 33.1 microg ml(-1) h with omeprazole, P= 0.64; 80% power), maximum plasma concentration (C(max)) (2.04 microg ml(-1) alone vs 2.02 microg ml(-1) with omeprazole, P= 0.97), or half-life (13.4 h alone vs 14.1 h with omeprazole, P= 0.13). CONCLUSIONS: Our results indicate that the use of omeprazole does not significantly affect the pharmacokinetics of imatinib, as opposed to, for example, dasatinib where PPI decreased AUC and C(max) two-fold.