Christina R. Chow

Posaconazole is an effective broad-spectrum triazole antifungal used as prophylaxis or to treat invasive Aspergillus and Candida infections in adults and pediatric patients. Posaconazole is a known strong inhibitor of cytochrome P4503A4 (CYP3A4) and substrate of P-glycoprotein (P-gp), which may lead to drug-drug interactions (DDIs) when co-administered with CYP3A4-sensitive substrates and warrants modified dosing of sensitive drugs when administered concomitantly with posaconazole. Given the long elimination half-life of posaconazole (26-35 h), there is the potential for DDIs caused by posaconazole after discontinuing the antifungal. Our clinical studies revealed that the half-life of posaconazole is significantly prolonged in subjects with a body mass index (BMI) ≥ 35 kg/m², which may put this population at an increased risk of DDIs after stopping posaconazole. This manuscript describes the development, verification, and validation of a whole-body, physiologically-based pharmacokinetic (PBPK) model which describes the concomitant use and washout DDIs of posaconazole delayed-release tablet (DRT) with victim drugs ranolazine and lurasidone in healthy volunteers of normal weight and with obesity. The key findings of this model are 1) the half-life of posaconazole is significantly prolonged in patients with BMI ≥ 35 kg/m² and 2) the mechanism of inhibition of CYP3A4 by posaconazole appears to be irreversible in vivo. This model may be used moving forward to assess the potential for washout DDIs with CYP3A4-sensitive substrates during concomitant use with, and after discontinuing posaconazole in subjects with normal weight and obesity.

Purpose of Review: To provide examples of knowledge gaps in current pharmaceutical treatments for people with obesity and call for changes to regulatory and pharmaceutical clinical research requirements during the drug discovery and development process. Recent Findings: Treatment of obesity and its comorbidities often require the use of prescription drugs, many of which have not been fully evaluated in people with obesity. Despite a growing body of research on this topic, the impact of obesity on the pharmacokinetics and pharmacodynamics of drugs is often under-studied by drug sponsors and regulators, and subsequently underappreciated by clinicians and caretakers. There are currently multiple opportunities for pharmaceuticals to include dosing information specifically for patients with obesity in order to ensure safety and efficacy of drugs in this population. Additionally, there are serious gaps between what is known about the effects of obesity on drug disposition and the current use of drugs according to drug prescribing information and clinical practice. Summary: There is currently no requirement to test drugs in people with obesity during the drug approval process, even when preliminary data suggests there may be altered kinetics in this population. The lack of information on the safe and effective use of drugs in people with obesity may be contributing to poorer health outcomes in this population.

Dual‐energy x‐ray absorptiometry (DXA) scanning is used for objective determination of body composition, but instrumentation is expensive and not generally available in customary clinical practice. Anthropometric surrogates are often substituted as anticipated correlates of absolute and relative body fat content in the clinical management of obesity and its associated medical risks. DXA and anthropometric data from a cohort of 9230 randomly selected American subjects, available through the ongoing National Health and Nutrition Examination Survey, was used to evaluate combinations of surrogates (age, height, total weight, waist circumference) as predictors of DXA‐determined absolute and relative body fat content. Multiple regression analysis yielded linear combinations of the 4 surrogates that were closely predictive of DXA‐determinedabsolutefat content (R² = 0.93 and 0.96 for male and female subjects). Accuracy of the new algorithm was improved over customary surrogate‐based predictors such as body mass index. However prediction ofrelativebody fat was less robust (R² less than 0.75), probably due to the nonlinear relation between degree of obesity (based on body mass index) and relative body fat. The paradigm was validated using an independent cohort from the National Health and Nutrition Examination Survey, as well as two independent external subject groups. The described regression‐based algorithm is likely to be a sufficiently accurate predictor of absolute body fat (but not relative body fat) to substitute for DXA scanning in many clinical situations. Further work is needed to assess algorithm validity for subgroups of individuals with “atypical” body construction.

Obesity is a serious condition with many known comorbid conditions and other health risks. Despite the rising global rates of obesity, drug disposition in this population is typically understudied, which results in limited information guiding the use of drugs in patients with obesity. Presently, dosing adjustments for patients with obesity typically focus on addressing altered drug clearance with body size and are therefore limited to chronic dosing recommendations. These instructions are variable and rarely based on dedicated studies in people with obesity. This review briefly discusses the current clinical use of body measurements to guide chronic dosing instructions and highlights the need for obesity‐specific dosing instructions when the half‐life of a drug is prolonged (typically through increased volume of distribution) in people with obesity. Examples of drugs with apparent opportunities for either ramp‐up, loading, or washout instructions for patients based on body mass index are identified, specifically for vortioxetine, posaconazole, and brexpiprazole. We call for inclusion of people with obesity in clinical studies as a special subpopulation during drug development and propose the use of body mass index to guide dosing decisions among these patients.

In 1979, the late Dr. Darrell R. Abernethy and colleagues began a series of clinical studies aimed at understanding the pertinent determinants of drug distribution, elimination, and clearance in obesity, and how those variables are interconnected. The studies confirmed that volume of distribution (V_d) and clearance are the principal independent biological variables, which conjointly determine elimination of half‐life as a dependent variable. For drugs distributed by passive diffusion, their pharmacokinetic V_d — after correcting for plasma protein binding — was increased in obesity, depending in part on the physicochemical lipophilicity of the individual drugs, and the quantitative extent of obesity in overweight individuals. Across all studies, the ratio of mean clearance in obese divided by control groups had an overall median value of 1.21 (range, 0.75‐3.11), indicating a small and variable effect of obesity on clearance, without clear directionality. Since drug clearance was not clearly related to lipophilicity or degree of obesity, the prolonged half‐life of lipophilic drugs in patients with obesity was largely explained by the increased V_d. Dr. Abernethy further identified delayed attainment of steady state after initiation of multiple‐dose treatment, and delayed washout after termination of dosage, as potential clinical consequences of the extended half‐life in people with obesity. These consequences for specific drugs have been recently emphasized in contemporary studies of chronic dosage in subjects with obesity. Without data identifying an obesity‐related change in clearance for a specific drug, maintenance doses (in milligrams) should be based on ideal weight rather than adjusted upward on the basis of total weight.

Brexpiprazole is an oral antipsychotic agent indicated for use in patients with schizophrenia or as adjunctive treatment for major depressive disorder. As obesity (body mass index ≥35 kg/m²) has the potential to affect drug pharmacokinetics and is a common comorbidity of both schizophrenia and major depressive disorder, it is important to understand changes in brexpiprazole disposition in this population. This study uses a whole‐body physiologically based pharmacokinetic model to compare the pharmacokinetics of brexpiprazole in obese and normal‐weight (body mass index 18‐25 kg/m²) individuals known to be cytochrome P450 2D6 extensive metabolizers (EMs) and poor metabolizers (PMs). The physiologically based pharmacokinetic simulations demonstrated significant differences in the time to effective concentrations between obese and normal‐weight individuals within metabolizer groups according to the label‐recommended titration. Simulations using an alternative dosing strategy of 1 week of twice‐daily dosing in obese EMs or 2 weeks of twice‐daily dosing in obese poor metabolizers, followed by a return to once‐daily dosing, yielded more consistent plasma concentrations between normal‐weight and obese patients without exceeding the area under the plasma concentration–time curve observed in the normal‐weight EMs. These alternative dosing strategies reduce the time to effective concentrations in obese patients and may improve clinical response to brexpiprazole.

Brexpiprazole is an oral antipsychotic agent indicated for use in patients with schizophrenia, or as adjunctive treatment for major depressive disorder (MDD). As CYP2D6 contributes significantly to brexpiprazole metabolism, there is a label-recommended 50% reduction in dose among patients with the CYP2D6 poor metabolizer phenotype. This study uses a whole-body physiologically-based pharmacokinetic (PBPK) model to compare the pharmacokinetics of brexpiprazole in patients known to be extensive (EM) and poor metabolizers (PMs). A PBPK model was constructed, verified, and validated against brexpiprazole clinical data, and simulations of 500 subjects were performed to establish the median time-to-effective concentrations in EMs and PMs. The PBPK simulations captured brexpiprazole PK well and demonstrated significant differences in the time to effective concentrations between EMs and PMs according to the label-recommended titration. Additionally, these simulations suggest that CYP2D6 PMs consistently achieve lower C_trough concentrations than CYP2D6 EMs. Simulations using an alternative dosing strategy of BID dosing (as opposed to QD) in PMs during the first week of brexpiprazole dosing yielded more consistent plasma concentrations between EMs and PMs, without exceeding the AUC observed in the EMs. Taken together, the results of these PBPK simulations suggest that product labeling for brexpiprazole titration in CYP2D6 PMs likely overcompensates for the decreased clearance seen in this population. We propose an alternative dosing strategy that decreases the time to effective concentrations and recommend a re-evaluation of steady-state PK in this population to potentially allow for higher daily doses in CYP2D6 PMs. This article is protected by copyright. All rights reserved

Progressive multifocal leukoencephalopathy (PML) is a rare demyelinating disorder of the brain caused by reactivation of the JC virus (JCV), a polyomavirus that infects at least 60% of the population but is asymptomatic or results in benign symptoms in most people. PML occurs as a secondary disease in a variety of disorders or as a serious adverse event from immunosuppressant agents, but is mainly found in three groups: HIV-infected patients, patients with hematological malignancies, or multiple sclerosis (MS) patients on the immunosuppressant therapy natalizumab. It is severely debilitating and is deadly in ~50% HIV cases, ~90% of hematological malignancy cases, and ~24% of MS-natalizumab cases. A PML risk prediction test would have clinical utility in all at risk patient groups but would be particularly beneficial in patients considering therapy with immunosuppressant agents known to cause PML, such as natalizumab, rituximab, and others. While a JC antibody test is currently used in the clinical decision process for natalizumab, it is suboptimal because of its low specificity and requirement to periodically retest patients for seroconversion or to assess if a patient's JCV index has increased. Whereas a high specificity genetic risk prediction test comprising host genetic risk variants (i.e., germline variants occurring at higher frequency in PML patients compared to the general population) could be administered one time to provide clinicians with additional risk prediction information that is independent of JCV serostatus. Prior PML case reports support the hypothesis that PML risk is greater in patients with a genetically caused immunodeficiency disorder. To identify germline PML risk variants, we performed exome sequencing on 185 PML cases (70 in a discovery cohort and 115 in a replication cohort) and used the gnomAD variant database for interpretation. Our study yielded 19 rare variants (maximum allele frequency of 0.02 in gnomAD ethnically matched populations) that impact 17 immune function genes (10 are known to cause inborn errors of immunity). Modeling of these variants in a PML genetic risk test for MS patients considering natalizumab treatment indicates that at least a quarter of PML cases may be preventable.

Biomarkers that are able to identify patients at risk of drug-induced liver injury (DILI) after treatment with infliximab could be important in increasing the safety of infliximab use. We performed a genetic analysis to identify possible human leukocyte antigen (HLA) associations with DILI in European Caucasian users of infliximab in a retrospective study of 16 infliximab-DILI patients and 60 matched controls. In infliximab-associated liver injury, multiple potentially causal individual HLA associations were observed, as well as possible haplotypes. The strongest associated HLA allele was HLA-B*39:01 (P = 0.001; odds ratio [OR] 43.6; 95% confidence interval [CI] 2.8-infinity), which always appeared with another associated allele C*12:03 (P = 0.032; OR 6.1; 95% CI 0.9–47.4). Other associations were observed with HLAs DQB1*02:01 (P = 0.007; OR 5.7; 95% CI 1.4–24.8), DRB1*03:01 (P = 0.012; OR 4.9; 95% CI 1.2–20.5), and B*08:01 (P = 0.048; OR 3.4; 95% CI 0.9–13.2), which also appeared together whenever present in cases. Additional associations were found with HLA-DPB1*10:01 (P = 0.042; OR 20.9; 95% CI 0.7–infinity) and HLA-DRB1*04:04 (P = 0.042; OR 20.9; 95% CI 0.7–infinity). A strong association with HLA-B*39:01 was identified as a potentially causal risk factor for infliximab-induced DILI. Future work should aim to validate this finding and explore possible mechanisms through which the biologic interacts with this particular allele.

Since many tumors are associated with a pronounced collagen-rich stromal reaction, there is increasing interest in understanding mechanisms by which cancer cells invade through the collagen barrier. Here we describe a quantitative method to track cell invasion in 3D collagen I gels. We analyze invasion by quantifying proteolytic tracks generated by invading cancer cells through a 3D collagen microenvironment. We provide a detailed protocol for this quantitative assay, which can be used to characterize signaling pathways that regulate invasion in the 3D microenvironment.