Challenging the Norm: A Multidisciplinary Perspective on Intravenous to Subcutaneous Bridging Strategies for Biologics

The transition from intravenous (i.v.) to subcutaneous (s.c.) administration of biologics is a critical strategy in drug development aimed at improving patient convenience, compliance, and therapeutic outcomes. Focusing on the increasing role of model-informed drug development (MIDD) in the acceleration of this transition, an in-depth overview of the essential clinical pharmacology, and regulatory considerations for successful i.v. to s.c. bridging for biologics after the i.v. formulation has been approved are presented. Considerations encompass multiple aspects beginning with adequate pharmacokinetic (PK) and pharmacodynamic (i.e., exposure-response) evaluations which play a vital role in establishing comparability between the i.v. and s.c. routes of administrations. Selected key recommendations and points to consider include: (i) PK characterization of the s.c. formulation, supported by the increasing preclinical understanding of the s.c. absorption, and robust PK study design and analyses in humans; (ii) a thorough characterization of the exposure-response profiles including important metrics of exposure for both efficacy and safety; (iii) comparability studies designed to meet regulatory considerations and support approval of the s.c. formulation, including noninferiority studies with PK and/or efficacy and safety as primary end points; and (iv) comprehensive safety package addressing assessments of immunogenicity and patients' safety profile with the new route of administration. Recommendations for successful bridging strategies are evolving and MIDD approaches have been used successfully to accelerate the transition to s.c. dosing, ultimately leading to improved patient experiences, adherence, and clinical outcomes.

Population pharmacokinetics and exposure-response analyses of daratumumab plus pomalidomide/dexamethasone in relapsed or refractory multiple myeloma

AIM

A population pharmacokinetic (PPK) model was developed to characterize pharmacokinetics (PK) of subcutaneous or intravenous daratumumab administration in a new indication (i.e., combination with pomalidomide and dexamethasone [D-Pd] in patients with relapsed or refractory multiple myeloma [RRMM]). Analyses were conducted to explore exposure-response (E-R) relationships for efficacy and select treatment-emergent adverse events (TEAEs).

METHODS

The PPK analysis included pooled data from the D-Pd cohorts of the phase 3 APOLLO and phase 1b EQUULEUS studies. Covariates were evaluated in the PPK model. Model-predicted exposures to daratumumab were compared between covariate subgroups of interest and used to investigate relationships between daratumumab exposure and efficacy and safety in APOLLO.

RESULTS

The PPK analysis included 1146 daratumumab PK samples from 239 patients (APOLLO, n = 140; EQUULEUS, n = 99). Observed concentration-time data of daratumumab were well described by a two-compartment PPK model with first-order absorption and parallel linear and nonlinear elimination pathways. Treatment with D-Pd provided similar daratumumab PK characteristics versus historical daratumumab monotherapy. The E-R dataset contained data from 290 APOLLO patients (D-Pd, n = 140; Pd, n = 150). The PK-efficacy relationship of daratumumab supported improved progression-free survival for patients in the D-Pd group vs. the Pd group. Additionally, TEAEs did not increase with increasing PK exposure in the D-Pd group.

CONCLUSIONS

The PPK and E-R analyses support the daratumumab subcutaneous 1800 mg dosing regimen in combination with Pd for treatment of patients with RRMM. No dose adjustment is recommended in this indication for any of the investigated factors, none of which had clinically relevant effects on daratumumab PK.

A translational model-based approach to inform the choice of the dose in phase 1 oncology trials: the case study of erdafitinib

PURPOSE

Erdafitinib (JNJ-42756493, BALVERSA) is a tyrosine kinase inhibitor indicated for the treatment of advanced urothelial carcinoma. In this work, a translational model-based approach to inform the choice of the doses in phase 1 trials is illustrated.

METHODS

A pharmacokinetic (PK) model was developed to describe the time course of erdafitinib plasma concentrations in mice and rats. Data from multiple xenograft studies in mice and rats were analyzed using the Simeoni tumor growth inhibition (TGI) model. The model parameters were used to derive a range of erdafitinib exposures that might inform the choice of the doses in oncology phase 1 trials. Conversion of exposures to doses was based on preliminary PK assessments from the first-in human (FIH) study.

RESULTS

A one-compartment PK disposition model, with linear absorption and dose-dependent clearance, adequately described the PK data in both mice and rats via an allometric scaling approach. The TGI model was able to describe tumor growth dynamics, providing quantitative measurements of erdafitinib antitumor potency in mice and rats. Based on these estimates, ranges of efficacious unbound concentration were identified for erdafitinib in mice (0.642-5.364 μg/L) and rats (0.782-2.565 μg/L). Based on the FIH data, it was possible to transpose exposures into doses and doses of above 4 mg/day provided erdafitinib exposures associated with significant TGI in animals. The findings were in agreement with the results of the FIH trial, in which the first hints of clinical activities were observed at 6 mg.

CONCLUSION

The successful modeling exercise of erdafitinib preclinical data showed how translational PK-PD modeling might be a tool to help to inform the choice of the doses in FIH studies.

Population Pharmacokinetics of Total and Free Erdafitinib in Adult Healthy Volunteers and Cancer Patients: Analysis of Phase 1 and Phase 2 Studies

A population pharmacokinetic (PK) model was developed using data pooled from 6 clinical studies (3 in healthy volunteers and 3 in cancer patients) to characterize total and free plasma concentrations of erdafitinib following single- and multiple-dose administration, to understand clinically relevant covariates, and to quantify the inter- and intraindividual variability in erdafitinib PK. An open, linear, 3-compartment disposition model with first-order absorption and a lag time was used to describe the PK profile of total and free erdafitinib plasma concentrations. The PK of erdafitinib were linear and time independent. After oral administration, erdafitinib was rapidly absorbed, with a time to maximum concentration between 2 and 4 hours. In patients, erdafitinib total apparent oral clearance was 0.200 L/h (median free fraction = 0.24%), and the effective terminal half-life of total drug was 76.4 hours. Interindividual variability in PK parameters was moderate for oral clearance and central volume of distribution, and large for absorption rate and peripheral volume of distribution. Sex and renal function were significant covariates on free oral clearance, while weight, sex, and α₁ -acid-glycoprotein were significant on oral central volume of distribution. Age, race, and mild hepatic impairment were not significant covariates of erdafitinib exposure. Given that the magnitude of the covariate effects were within 25% of reference values and that the recommended dosing regimen of erdafitinib comprises individual dose up-titrations and reductions based on presence or absence of toxicities, the clinical relevance of the investigated covariates is expected to be limited, and no dose adjustments are warranted.

Model averaging for robust assessment of QT prolongation by concentration-response analysis

Assessing the QT prolongation potential of a drug is typically done based on pivotal safety studies called thorough QT studies. Model-based estimation of the drug-induced QT prolongation at the estimated mean maximum drug concentration could increase efficiency over the currently used intersection-union test. However, robustness against model misspecification needs to be guaranteed in pivotal settings. The objective of this work was to develop an efficient, fully prespecified model-based inference method for thorough QT studies, which controls the type I error and provides satisfactory test power. This is achieved by model averaging: The proposed estimator of the concentration-response relationship is a weighted average of a parametric (linear) and a nonparametric (monotonic I-splines) estimator, with weights based on mean integrated square error. The desired properties of the method were confirmed in an extensive simulation study, which demonstrated that the proposed method controlled the type I error adequately, and that its power was higher than the power of the nonparametric method alone. The method can be extended from thorough QT studies to the analysis of QT data from pooled phase I studies.