CPT: Pharmacometrics & Systems Pharmacology最新文献

Adebrelimab, a novel anti-PD-L1 antibody, has been approved by the National Medical Products Administration of China as an intravenous infusion for use in combination with carboplatin and etoposide as first-line treatment for extensive-stage small-cell lung cancer in 2023. A two-compartment model with empirical time-varying CL for adebrelimab was established based on data from 263 patients receiving body weight-based doses from two clinical studies. Significant covariate effects of baseline body weight, albumin levels, tumor size, neutrophil counts, and presence of anti-drug antibodies were identified on CL of debrelimab, none of which were clinically significant or warranted dose adjustment. The degree of decrease in CL was higher in patients who responded to treatment with adebrelimab than in non-responders. Adebrelimab exposures (AUC, C_trough, or C_max) were not identified as a statistically significant factor related to efficacy or safety endpoint in the exposure–response analysis. Distribution of simulated exposure metrics from the flat dose regimen (1200 mg q3w) was similar to the marketed weight-based dosing regimen (20 mg/kg q3w), supporting the alternative flat dose regimen in the clinic.

Mavacamten is the first cardiac myosin inhibitor approved by the US Food and Drug Administration for the treatment of adults with symptomatic obstructive hypertrophic cardiomyopathy (HCM). The phase III EXPLORER-HCM (NCT03470545) study used a dose-titration scheme based on mavacamten exposure and echocardiographic assessment of Valsalva left ventricular outflow tract gradient (VLVOTg) and left ventricular ejection fraction (LVEF). Using population pharmacokinetic/exposure-response modeling and simulations of virtual patients, this in silico study evaluated alternative dose-titration regimens for mavacamten, including regimens that were guided by echocardiographic measures only. Mavacamten exposure-response models for VLVOTg (efficacy) and LVEF (safety) were developed using patient data from five clinical studies and characterized using nonlinear mixed-effects models. Simulations of five echocardiography-guided regimens were performed in virtual cohorts constructed based on either expected or equal population distributions of cytochrome P450 2C19 (CYP2C19) metabolizer phenotypes. Each regimen aimed to maximize the proportions of patients who achieved a VLVOTg below 30 mm Hg while maintaining LVEF above 50% over 40 weeks and 104 weeks, respectively. The exposure-response models successfully characterized mavacamten efficacy and safety parameters. Overall, the simulated regimen with the optimal benefit–risk profile across CYP2C19 phenotypes had steps for down-titration at weeks 4 and 8 (for VLVOTg <20 mm Hg), and up-titration at week 12 (for VLVOTg ≥30 mm Hg and LVEF ≥55%), and every 12 weeks thereafter. This simulation-optimized regimen is recommended in the mavacamten US prescribing information.

Dasatinib, a second-generation tyrosine kinase inhibitor, is approved for treating chronic myeloid and acute lymphoblastic leukemia. As a sensitive cytochrome P450 (CYP) 3A4 substrate and weak base with strong pH-sensitive solubility, dasatinib is susceptible to enzyme-mediated drug–drug interactions (DDIs) with CYP3A4 perpetrators and pH-dependent DDIs with acid-reducing agents. This work aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) model of dasatinib to describe and predict enzyme-mediated and pH-dependent DDIs, to evaluate the impact of strong and moderate CYP3A4 inhibitors and inducers on dasatinib exposure and to support optimized dasatinib dosing. Overall, 63 plasma profiles from perorally administered dasatinib in healthy volunteers and cancer patients were used for model development. The model accurately described and predicted plasma profiles with geometric mean fold errors (GMFEs) for area under the concentration–time curve from the first to the last timepoint of measurement (AUC_last) and maximum plasma concentration (C_max) of 1.27 and 1.29, respectively. Regarding the DDI studies used for model development, all (8/8) predicted AUC_last and C_max ratios were within twofold of observed ratios. Application of the PBPK model for dose adaptations within various DDIs revealed dasatinib dose reductions of 50%–80% for strong and 0%–70% for moderate CYP3A4 inhibitors and a 2.3–3.1-fold increase of the daily dasatinib dose for CYP3A4 inducers to match the exposure of dasatinib administered alone. The developed model can be further employed to personalize dasatinib therapy, thereby help coping with clinical challenges resulting from DDIs and patient-related factors, such as elevated gastric pH.

It is critical to understand the impact of significant physiological changes during pregnancy on the extent of maternal and fetal drug exposure. Fostemsavir (FTR) is a prodrug of temsavir (TMR) and is approved in combination with other antiretrovirals for multi-drug-resistant human immunodeficiency virus (HIV) infections. This physiologically based pharmacokinetic model (PBPK) study was used to estimate TMR PK in pregnant populations during each trimester of pregnancy to inform FTR dosing. A PBPK model was developed and validated for TMR using PK data collected following intravenous TMR and oral FTR dosing (immediate-release and extended-release tablets) in healthy volunteers. Predicted TMR concentration-time profiles accurately predicted the reported clinical data and variability in healthy (dense data) and pregnant (sparse data) populations. Predicted versus observed TMR geometric mean (CV%) clearance following intravenous administration was 18.01 (29) versus 17 (21) (L/h). Predicted versus observed TMR AUC_0-inf (ng.h/mL) in healthy volunteers following FTR administration of the extended-release tablet were 9542 (66) versus 7339 (33). The validated TMR PBPK model was then applied to predict TMR PK in a population of pregnant individuals during each trimester. Simulations showed TMR AUC in pregnant individuals receiving FTR 600 mg twice daily was decreased by 25% and 38% in the second and third trimesters, respectively. However, TMR exposure remained within the range observed in nonpregnant adults with no need for dose adjustment. The current PBPK model can also be applied for the prediction of local tissue concentrations and drug-drug interactions in pregnancy.

Changes in physiological factors may result in large pharmacokinetic variability of vancomycin in pediatric patients, thereby leading to either supratherapeutic or subtherapeutic exposure and potentially affecting clinical outcomes. This study set out to characterize the disposition of vancomycin, quantify the exposure target and establish an optimal dosage regimen among the Southern Chinese pediatric population. Routine therapeutic drug monitoring data of 453 patients were available. We performed a retrospective population pharmacokinetic analysis of hospitalized children prescribed intravenous vancomycin using NONMEM® software. A one-compartment PPK model of vancomycin with body weight and renal functions as covariates based on a cutoff of 2 years old children was proposed in this study. Both internal and external validation showing acceptable and robust predictive performance of the model to estimate PK parameters. The value of area under the curve over 24 h to minimum inhibitory concentration ratio (AUC_0-24/MIC) ≥ 260 was a significant predictor for therapeutic efficacy. Monte Carlo simulations served as a model-informed precision dosing approach and suggested that different optimal dose regimens in various scenarios should be considered rather than flat dosing. The evaluation of vancomycin exposure-efficacy relationship indicated that lower target level of AUC_0-24/MIC may be needed to achieve clinical effectiveness in children, which was used to derive the recommended dosing regimen. Further prospective studies will be needed to corroborate and elucidate these results.

While randomized, placebo-controlled, double-blinded clinical studies are the gold standard for evaluating the efficacy of investigational drugs, the use of placebo in children with achondroplasia should be limited because it provides no clinical benefit while exhausting study participants' treatment window. Recifercept is an investigational drug for treating children with achondroplasia aged 2–10 years. An alternative efficacy evaluation method, instead of a placebo control arm, was employed in the phase II study. Prior to participating in the phase II study, participants completed a natural history (NH) study. Based on the NH data, a multi-variate linear mixed effects natural disease course model of three anthropometric end points (standing height, sitting height, and arm span) was developed. The model was validated using published growth charts of children with achondroplasia. Subsequently, the model was used to simulate the natural growth trajectories (without any treatment) of the three anthropometric end points for the individuals enrolled in the phase II study. To quantify the efficacy of recifercept, the simulations were compared with the observations post-recifercept treatment in the phase II study. For all the tested doses of recifercept, at the individual level, the observations were comparable to the simulations at 6 and 12 months post-recifercept treatment, suggesting no treatment effect. The results contributed to the decision of terminating recifercept clinical development. This work delivers a framework that could eliminate the need for placebo in clinical trials yet provide sufficient evidence for evaluating the efficacy of an investigational drug.

Regulatory T cells (T_regs) are essential for maintaining immune homeostasis by serving as negative regulators of adaptive immune system effector cell responses. Reduced production or function of T_regs has been implicated in several human autoimmune diseases. The cytokine interleukin 2 plays a central role in promoting T_reg differentiation, survival, and function in vivo and may therefore have therapeutic benefits for autoimmune diseases. mRNA-6231 is an investigational, lipid nanoparticle-encapsulated, mRNA-based therapy that encodes a modified human interleukin 2 mutein fused to human serum albumin (HSA-IL2m). Herein, we report the development of a semi-mechanistic kinetic-pharmacodynamic model to quantify the relationship between subcutaneous dose(s) of mRNA-6231, HSA-IL2m protein expression, and T_reg expansion in nonhuman primates. The nonclinical kinetic-pharmacodynamic model was extrapolated to humans using allometric scaling principles and the physiological basis of pharmacological mechanisms to predict the clinical response to therapy a priori. Model-based simulations were used to inform the dose selection and design of the first-in-human clinical study (NCT04916431). The modeling approach used to predict human responses was validated when data became available from the phase I clinical study. This validation indicates that the approach is valuable in informing clinical decision-making.

Model-based tumor growth inhibition (TGI) metrics are increasingly used to predict overall survival (OS) data in Phase III immunotherapy clinical trials. However, there is still a lack of understanding regarding the differences between two-stage or joint modeling methods to leverage Phase I/II trial data and help early decision-making. A recent study showed that TGI metrics such as the tumor growth rate constant K_G may have good operating characteristics as early endpoints. This previous study used a two-stage approach that is easy to implement and intuitive but prone to bias as it does not account for the relationship between the longitudinal and time-to-event processes. A relevant alternative is to use a joint modeling approach. In the present article, we evaluated the operating characteristics of TGI metrics using joint modeling, assuming an OS model previously developed using historical data. To that end, we used TGI and OS data from IMpower150—a study investigating atezolizumab in over 750 patients suffering from non-small cell lung cancer—to mimic randomized Phase Ib/II trials varying in terms of number of patients included (40 to 15 patients per arm) and follow-up duration (24 to 6 weeks after the last patient included). In this context, joint modeling did not outperform the two-stage approach and provided similar operating characteristics in all the investigated scenarios. Our results suggest that K_G geometric mean ratio could be used to support early decision-making provided that 30 or more patients per arm are included and followed for at least 12 weeks.

Peritoneal metastases (PM) are common in patients with colorectal cancer. Patients with PM have a poor prognosis, and for those who are not eligible for cytoreductive surgery (CRS) with or without hyperthermic intraperitoneal chemotherapy (HIPEC), palliative chemotherapy is currently the only option. Recently, we conducted a phase I trial (INTERACT) in which irinotecan was administered intraperitoneally (IP) to 18 patients ineligible for CRS-HIPEC. The primary objective was to evaluate covariates influencing the PK profile of irinotecan and SN-38 after IP administration. Secondly, a population PK model was developed to support the further development of IP irinotecan by improving dosing in patients with PM. Patients were treated with IP irinotecan every 2 weeks in combination with systemic FOLFOX-bevacizumab. Irinotecan and SN-38 were measured in plasma (588 samples) and SN-38 was measured in peritoneal fluid (267 samples). Concentration-Time data were log-transformed and analyzed using NONMEM version 7.5 using FOCE+I estimation. An additive error model described the residual error, with inter-individual variability in PK parameters modeled exponentially. The final structural model consisted of five compartments. Weight was identified as a covariate influencing the SN-38 plasma volume of distribution and GGT was found to influence the SN-38 plasma clearance. This population PK model adequately described the irinotecan and SN-38 in plasma after IP administration, with weight and GGT as predictive factors. Irinotecan is converted intraperitoneal to SN-38 by carboxylesterases and the plasma bioavailability of irinotecan is low. This model will be used for the further clinical development of IP irinotecan by providing dosing strategies.

Polatuzumab vedotin is a CD79b-directed antibody–drug conjugate that targets B cells and delivers the cytotoxic payload monomethyl auristatin E (MMAE). The phase III POLARIX study (NCT03274492) evaluated polatuzumab vedotin in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone (R-CHP) as first-line treatment of diffuse large B-cell lymphoma (DLBCL). To examine dosing decisions for this regimen, population pharmacokinetic (popPK) analysis, using a previously developed popPK model, and exposure–response (ER) analysis, were performed. The popPK analysis showed no clinically meaningful relationship between cycle 6 (C6) antibody-conjugated (acMMAE)/unconjugated MMAE area under the concentration–time curve (AUC) or maximum concentration, and weight, sex, ethnicity, region, mild or moderate renal impairment, mild hepatic impairment, or other patient and disease characteristics. In the ER analysis, C6 acMMAE AUC was significantly associated with longer progression-free and event-free survival (both p = 0.01). An increase of <50% in acMMAE/unconjugated MMAE exposure did not lead to a clinically meaningful increase in adverse events of special interest. ER data and the benefit–risk profile support the use of polatuzumab vedotin 1.8 mg/kg once every 3 weeks with R-CHP for six cycles in patients with previously untreated DLBCL.