A phase I trial of SON-1010, a tumor-targeted, interleukin-12-linked, albumin-binding cytokine, shows favorable pharmacokinetics, pharmacodynamics, and safety in healthy volunteers.

Background: The benefits of recombinant interleukin-12 (rIL-12) as a multifunctional cytokine and potential immunotherapy for cancer have been sought for decades based on its efficacy in multiple mouse models. Unexpected toxicity in the first phase 2 study required careful attention to revised dosing strategies. Despite some signs of efficacy since then, most rIL-12 clinical trials have encountered hurdles such as short terminal elimination half-life (T½), limited tumor microenvironment targeting, and substantial systemic toxicity. We developed a strategy to extend the rIL-12 T½ that depends on binding albumin in vivo to target tumor tissue, using single-chain rIL-12 linked to a fully human albumin binding (FHAB) domain (SON-1010). After initiating a dose-escalation trial in patients with cancer (SB101), a randomized, double-blind, placebo-controlled, single-ascending dose (SAD) phase 1 trial in healthy volunteers (SB102) was conducted. Methods: SB102 (NCT05408572) focused on safety, tolerability, pharmacokinetic (PK), and pharmacodynamic (PD) endpoints. SON-1010 at 50-300 ng/kg or placebo administered subcutaneously on day 1 was studied at a ratio of 6:2, starting with two sentinels; participants were followed through day 29. Safety was reviewed after day 22, before enrolling the next cohort. A non-compartmental analysis of PK was performed and correlations with the PD results were explored, along with a comparison of the SON-1010 PK profile in SB101. Results: Participants receiving SON-1010 at 100 ng/kg or higher tolerated the injection but generally experienced more treatment-emergent adverse effects (TEAEs) than those receiving the lowest dose. All TEAEs were transient and no other dose relationship was noted. As expected with rIL-12, initial decreases in neutrophils and lymphocytes returned to baseline by days 9-11. PK analysis showed two-compartment elimination in SB102 with mean T½ of 104 h, compared with one-compartment elimination in SB101, which correlated with prolonged but controlled and dose-related increases in interferon-gamma (IFNγ). There was no evidence of cytokine release syndrome based on minimal participant symptoms and responses observed with other cytokines. Conclusion: SON-1010, a novel presentation for rIL-12, was safe and well-tolerated in healthy volunteers up to 300 ng/kg. Its extended half-life leads to a prolonged but controlled IFNγ response, which may be important for tumor control in patients. Clinical trial registration: https://clinicaltrials.gov/study/NCT05408572, identifier NCT05408572.

Delineating gene-environment effects using virtual twins of patients treated with clozapine.

Studies that focus on individual covariates, while ignoring their interactions, may not be adequate for model-informed precision dosing (MIPD) in any given patient. Genetic variations that influence protein synthesis should be studied in conjunction with environmental covariates, such as cigarette smoking. The aim of this study was to build virtual twins (VTs) of real patients receiving clozapine with interacting covariates related to genetics and environment and to delineate the impact of interacting covariates on predicted clozapine plasma concentrations. Clozapine-treated patients with schizophrenia (N = 42) with observed clozapine plasma concentrations, demographic, environmental, and genotype data were used to construct VTs in Simcyp. The effect of increased covariate virtualization was assessed by performing simulations under three conditions: "low" (demographic), "medium" (demographic and environmental interaction), and "high" (demographic and environmental/genotype interaction) covariate virtualization. Increasing covariate virtualization with interaction improved the coefficient of variation (R2 ) from 0.07 in the low model to 0.391 and 0.368 in the medium and high models, respectively. Whereas R2 was similar between the medium and high models, the high covariate virtualization model had improved accuracy, with systematic bias of predicted clozapine plasma concentration improving from -138.48 ng/ml to -74.65 ng/ml. A high level of covariate virtualization (demographic, environmental, and genotype) may be required for MIPD using VTs.

Liquid Biopsy for Patient Characterization in Cardiovascular Disease: Verification against Markers of Cytochrome P450 and P-Glycoprotein Activities.

Precision dosing strategies require accounting for between-patient variability in pharmacokinetics together with subsequent pharmacodynamic differences. Liquid biopsy is a valuable new approach to diagnose disease prior to the appearance of clinical signs and symptoms, potentially circumventing invasive tissue biopsies. However, the possibility of quantitative grading of biomarkers, as opposed to simply confirming their presence or absence, is relatively new. In this study, we aimed to verify expression measurements of cytochrome P450 (CYP) enzymes and the transporter P-glycoprotein (P-gp) in liquid biopsy against genotype and activity phenotype (assessed by the Geneva cocktail approach) in 30 acutely ill patients with cardiovascular disease in a hospital setting. After accounting for exosomal shedding, expression in liquid biopsy correlated with activity phenotype for CYP1A2, CYP2B6, CYP2C9, CYP3A, and P-gp (r = 0.44-0.70, P ≤ 0.05). Although genotype offered a degree of stratification, large variability (coefficient of variation (CV)) in activity (up to 157%) and expression in liquid biopsy (up to 117%) was observed within each genotype, indicating a mismatch between genotype and phenotype. Further, exosome screening revealed expression of 497 targets relevant to drug metabolism and disposition (159 enzymes and 336 transporters), as well as 20 molecular drug targets. Although there were no functional data available to correlate against these large-scale measurements, assessment of disease perturbation from healthy baseline was possible. Verification of liquid biopsy against activity phenotype is important to further individualize modeling approaches that aspire to achieve precision dosing from the start of drug treatment without the need for multiple rounds of dose optimization.

Quantifying the Impact of Phenoconversion on Medications With Actionable Pharmacogenomic Guideline Recommendations in an Acute Aged Persons Mental Health Setting.

Introduction: Polypharmacy and genetic variants that strongly influence medication response (pharmacogenomics, PGx) are two well-described risk factors for adverse drug reactions. Complexities arise in interpreting PGx results in the presence of co-administered medications that can cause cytochrome P450 enzyme phenoconversion. Aim: To quantify phenoconversion in a cohort of acute aged persons mental health patients and evaluate its impact on the reporting of medications with actionable PGx guideline recommendations (APRs). Methods: Acute aged persons mental health patients (N = 137) with PGx and medication data at admission and discharge were selected to describe phenoconversion frequencies for CYP2D6, CYP2C19 and CYP2C9 enzymes. The expected impact of phenoconversion was then assessed on the reporting of medications with APRs. Results: Post-phenoconversion, the predicted frequency at admission and discharge increased for CYP2D6 intermediate metabolisers (IMs) by 11.7 and 16.1%, respectively. Similarly, for CYP2C19 IMs, the predicted frequency at admission and discharge increased by 13.1 and 11.7%, respectively. Nineteen medications with APRs were prescribed 120 times at admission, of which 50 (42%) had APRs pre-phenoconversion, increasing to 60 prescriptions (50%) post-phenoconversion. At discharge, 18 medications with APRs were prescribed 122 times, of which 48 (39%) had APRs pre-phenoconversion, increasing to 57 prescriptions (47%) post-phenoconversion. Discussion: Aged persons mental health patients are commonly prescribed medications with APRs, but interpretation of these recommendations must consider the effects of phenoconversion. Adopting a collaborative care model between prescribers and clinical pharmacists should be considered to address phenoconversion and ensure the potential benefits of PGx are maximised.

Combining Therapeutic Drug Monitoring and Pharmacokinetic Modelling Deconvolutes Physiological and Environmental Sources of Variability in Clozapine Exposure.

Background: Clozapine is a key antipsychotic drug for treatment-resistant schizophrenia but exhibits highly variable pharmacokinetics and a propensity for serious adverse effects. Currently, these challenges are addressed using therapeutic drug monitoring (TDM). This study primarily sought to (i) verify the importance of covariates identified in a prior clozapine population pharmacokinetic (popPK) model in the absence of environmental covariates using physiologically based pharmacokinetic (PBPK) modelling, and then to (ii) evaluate the performance of the popPK model as an adjunct or alternative to TDM-guided dosing in an active TDM population. Methods: A popPK model incorporating age, metabolic activity, sex, smoking status and weight was applied to predict clozapine trough concentrations (Cmin) in a PBPK-simulated population and an active TDM population comprising 142 patients dosed to steady state at Flinders Medical Centre in Adelaide, South Australia. Post hoc analyses were performed to deconvolute the impact of physiological and environmental covariates in the TDM population. Results: Analysis of PBPK simulations confirmed age, cytochrome P450 1A2 activity, sex and weight as physiological covariates associated with variability in clozapine Cmin (R2 = 0.7698; p = 0.0002). Prediction of clozapine Cmin using a popPK model based on these covariates accounted for <5% of inter-individual variability in the TDM population. Post hoc analyses confirmed that environmental covariates accounted for a greater proportion of the variability in clozapine Cmin in the TDM population. Conclusions: Variability in clozapine exposure was primarily driven by environmental covariates in an active TDM population. Pharmacokinetic modelling can be used as an adjunct to TDM to deconvolute sources of variability in clozapine exposure.

Use of Physiologically Based Pharmacokinetic Modeling to Identify Physiological and Molecular Characteristics Driving Variability in Axitinib Exposure: A Fresh Approach to Precision Dosing in Oncology.

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.

Physiologically Based Pharmacokinetic Modeling to Identify Physiological and Molecular Characteristics Driving Variability in Drug Exposure.

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.

Prediction of olanzapine exposure in individual patients using physiologically based pharmacokinetic modelling and simulation.

AIM: The aim of the present study was to predict olanzapine (OLZ) exposure in individual patients using physiologically based pharmacokinetic modelling and simulation (PBPK M&S). METHODS: A 'bottom-up' PBPK model for OLZ was constructed in Simcyp® (V14.1) and validated against pharmacokinetic studies and data from therapeutic drug monitoring (TDM). The physiological, demographic and genetic attributes of the 'healthy volunteer population' file in Simcyp® were then individualized to create 'virtual twins' of 14 patients. The predicted systemic exposure of OLZ in virtual twins was compared with measured concentration in corresponding patients. Predicted exposures were used to calculate a hypothetical decrease in exposure variability after OLZ dose adjustment. RESULTS: The pharmacokinetic parameters of OLZ from single-dose studies were accurately predicted in healthy Caucasians [mean-fold errors (MFEs) ranged from 0.68 to 1.14], healthy Chinese (MFEs 0.82 to 1.18) and geriatric Caucasians (MFEs 0.55 to 1.30). Cumulative frequency plots of trough OLZ concentration were comparable between the virtual population and patients in a TDM database. After creating virtual twins in Simcyp®, the R2 values for predicted vs. observed trough OLZ concentrations were 0.833 for the full cohort of 14 patients and 0.884 for the 7 patients who had additional cytochrome P450 2C8 genotyping. The variability in OLZ exposure following hypothetical dose adjustment guided by PBPK M&S was twofold lower compared with a fixed-dose regimen - coefficient of variation values were 0.18 and 0.37, respectively. CONCLUSIONS: Olanzapine exposure in individual patients was predicted using PBPK M&S. Repurposing of available PBPK M&S platforms is an option for model-informed precision dosing and requires further study to examine clinical potential.

Potential drug-drug interactions with direct oral anticoagulants in elderly hospitalized patients.

BACKGROUND: To determine the prevalence and nature of potential drug-drug interactions (DDIs) with direct oral anticoagulants (DOACs) in elderly hospitalized patients. METHODS: This was a retrospective observational study. Inclusion criteria were: aged over 65 years; taking apixaban, rivaroxaban or dabigatran; and admitted to the Repatriation General Hospital between April 2014 and July 2015. A list of clinically relevant 'perpetrator' drugs was compiled from product information, the Australian Medicines Handbook, the Australian National Prescribing Service resources, and local health network guidelines. The prevalence and nature of potential DDIs with DOACs was determined by comparing inpatient drug charts with the list of perpetrator drugs. RESULTS: There were 122 patients in the study with a mean age of 82 years. Most patients had nonvalvular atrial fibrillation and were taking DOACs to prevent thrombotic stroke (83%). Overall, 45 patients (37%) had a total of 54 potential DDIs. Thirty-five patients had potential pharmacodynamic DDIs with antidepressants, nonsteroidal anti-inflammatory drugs and antiplatelets (35/122, 29%). Nineteen patients had potential pharmacokinetic DDIs (19/122, 16%). Of these, 68% (13/19) were taking drugs that increase DOAC plasma concentrations (amiodarone, erythromycin, diltiazem or verapamil) and 32% (6/19) were taking drugs that decrease DOAC plasma concentrations (carbamazepine, primidone or phenytoin). There were no cases of patients taking contraindicated interacting drugs. DISCUSSION: Potential DDIs with DOACs in elderly hospital inpatients are relatively common, particularly interactions that may increase the risk of bleeding. The risk-benefit ratio of DOACs in elderly patients on polypharmacy should always be carefully considered.

Targeted pharmacotherapy after somatic cancer mutation screening.

Many patients with solid tumours are treated with targeted pharmacotherapy based on the results of genetic testing ('precision medicine'). This study investigated the use of targeted drugs after OncoFOCUS™+ KIT screening in patients with malignant melanoma, non-small cell lung cancer and metastatic colorectal cancer, and then audited the results against the National Comprehensive Cancer Network (NCCN) guidelines. Patients who were not indicated for targeted pharmacotherapy did not receive such treatment (99%, 100/101). Of the patients indicated for targeted drugs, 79% (33/42) received treatment according to NCCN guidelines. In 48% (20/42) of these patients the results from OncoFOCUS™+ KIT screening were required for targeted drug selection. This study highlights the growing importance of precision medicine approaches in directing pharmacotherapy in medical oncology.

In vitro-in vivo extrapolation of CYP2C8-catalyzed paclitaxel 6α-hydroxylation: effects of albumin on in vitro kinetic parameters and assessment of interindividual variability in predicted clearance.

OBJECTIVES: This study aimed to characterize the effects of bovine serum albumin (BSA) on the kinetics of CYP2C8-catalyzed paclitaxel 6α-hydroxylation in vitro; determine whether the addition of BSA to incubations improves the prediction of paclitaxel hepatic clearance via this pathway in vivo; and assess interindividual variability in predicted clearance. METHODS: The kinetics of paclitaxel 6α-hydroxlation by human liver microsomes (HLM) and recombinant CYP2C8 were characterized in incubations performed with and without BSA (2% w/v) supplementation, and the in vitro kinetic data were extrapolated to provide estimates of in vivo clearances. The Simcyp population-based ADME simulator was used to determine interindividual variability in the predicted clearances. RESULTS: Supplementation of incubations of HLM with BSA resulted in a 3.6-fold increase in the microsomal intrinsic clearance for paclitaxel 6α-hydroxylation, due mainly to a reduction in K(m) (7.08 ± 2.50 to 2.26 ± 0.39 µM), while addition of BSA to incubations of recombinant CYP2C8 resulted in an approximate doubling of intrinsic clearance. Mean values of predicted in vivo hepatic clearance were in good agreement with clinical data when in vitro data obtained in the presence of BSA were used for IV-IVE. Simcyp predicted 20- to 30-fold interindividual variability in in vivo paclitaxel hepatic clearance via the 6α-hydroxylation pathway. CONCLUSIONS: Human liver microsomal K(m) and intrinsic clearance values are over- and underpredicted, respectively, when incubations of the CYP2C8 substrate paclitaxel are performed without BSA supplementation. IV-IVE based on kinetic parameters generated in the presence of BSA improves the accuracy of predicted paclitaxel hepatic clearance.

An evaluation of potential mechanism-based inactivation of human drug metabolizing cytochromes P450 by monoamine oxidase inhibitors, including isoniazid.

AIMS: To characterize potential mechanism-based inactivation (MBI) of major human drug-metabolizing cytochromes P450 (CYP) by monoamine oxidase (MAO) inhibitors, including the antitubercular drug isoniazid. METHODS: Human liver microsomal CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A activities were investigated following co- and preincubation with MAO inhibitors. Inactivation kinetic constants (KI and kinact) were determined where a significant preincubation effect was observed. Spectral studies were conducted to elucidate the mechanisms of inactivation. RESULTS: Hydrazine MAO inhibitors generally exhibited greater inhibition of CYP following preincubation, whereas this was less frequent for the propargylamines, and tranylcypromine and moclobemide. Phenelzine and isoniazid inactivated all CYP but were most potent toward CYP3A and CYP2C19. Respective inactivation kinetic constants (KI and kinact) for isoniazid were 48.6 microm and 0.042 min-1 and 79.3 microm and 0.039 min-1. Clorgyline was a selective inactivator of CYP1A2 (6.8 microm and 0.15 min-1). Inactivation of CYP was irreversible, consistent with metabolite-intermediate complexation for isoniazid and clorgyline, and haeme destruction for phenelzine. With the exception of phenelzine-mediated CYP3A inactivation, glutathione and superoxide dismutase failed to protect CYP from inactivation by isoniazid and phenelzine. Glutathione partially slowed (17%) the inactivation of CYP1A2 by clorgyline. Alternate substrates or inhibitors generally protected against CYP inactivation. CONCLUSIONS: These data are consistent with mechanism-based inactivation of human drug-metabolizing CYP enzymes and suggest that impaired metabolic clearance may contribute to clinical drug-drug interactions with some MAO inhibitors.

Mechanism-based inactivation of human cytochrome P4502C8 by drugs in vitro.

Studies were conducted to evaluate the potential mechanism-based inactivation of recombinant and human liver microsomal CYP2C8 by clinically used drugs. Several tricyclic antidepressants, calcium channel blockers, monoamine oxidase inhibitors, and various other known CYP3A4 inhibitors exhibited greater inhibition of CYP2C8 (paclitaxel 6alpha-hydroxylation) following preincubation, consistent with mechanism-based inactivation. Inactivation of recombinant CYP2C8 by phenelzine, amiodarone, verapamil, nortriptyline, fluoxetine, and isoniazid was of the pseudo-first order type and was characterized by respective inactivation kinetic constants (KI and kinact) of 1.2 microM and 0.243 min(-1), 1.5 microM and 0.079 min(-1), 17.5 microM and 0.065 min(-1), 49.9 microM and 0.036 min(-1), 294 microM and 0.083 min(-1), and 374 microM and 0.042 min(-1). Spectral scanning of recombinant CYP2C8 demonstrated the formation of metabolite-intermediate complexes with verapamil, nortriptyline, fluoxetine, and isoniazid, but not amiodarone. In contrast, inactivation by phenelzine resulted from heme destruction by free radicals. Studies with human liver microsomes (HLMs) revealed that nortriptyline, verapamil, and fluoxetine were not mechanism-based inactivators (MBIs) of CYP2C8. Simultaneous inactivation of CYP2C8 and CYP3A4 (paclitaxel 3'-phenyl-hydroxylation) was observed using amiodarone, isoniazid, and phenelzine with the efficiency of inactivation greater for the CYP3A4 pathway. With the exception of phenelzine, glutathione and superoxide dismutase failed to protect CYP2C8 (recombinant and HLMs) or CYP3A4 from inactivation by MBIs. However, the alternate CYP2C8 substrate, torsemide, prevented CYP2C8 inactivation in all cases. These data are consistent with mechanism-based inactivation of CYP2C8 by a range of commonly prescribed drugs, several of which have been implicated in clinically important drug-drug interactions.