Pharmacokinetic/pharmacodynamic data extrapolation models for improved pediatric efficacy and toxicity estimation, with application to secondary hyperparathyroidism.

In most drug development settings, the regulatory approval process is accompanied by extensive studies performed to understand the drug's pharmacokinetic (PK) and pharmacodynamic (PD) properties. In this article, we attempt to utilize the rich PK/PD data to inform the borrowing of information from adults during pediatric drug development. In pediatric settings, it is especially crucial that we are parsimonious with the patients recruited for experimentation. We illustrate our approaches in the context of clinical trials of cinacalcet for treating secondary hyperparathyroidism in pediatric and adult patients with chronic kidney disease, where we model both parathyroid hormone (efficacy endpoint) and corrected calcium levels (safety endpoint). We use population PK/PD modeling of the cinacalcet data to quantitatively assess the similarity between adults and children, and use this information in various hierarchical Bayesian adult borrowing rules whose statistical properties can then be evaluated. In particular, we simulate the bias and mean square error performance of our approaches in settings where borrowing is and is not warranted to inform guidelines for the future use of our methods.

Statistical modeling for Bayesian extrapolation of adult clinical trial information in pediatric drug evaluation.

Children represent a large underserved population of "therapeutic orphans," as an estimated 80% of children are treated off-label. However, pediatric drug development often faces substantial challenges, including economic, logistical, technical, and ethical barriers, among others. Among many efforts trying to remove these barriers, increased recent attention has been paid to extrapolation; that is, the leveraging of available data from adults or older age groups to draw conclusions for the pediatric population. The Bayesian statistical paradigm is natural in this setting, as it permits the combining (or "borrowing") of information across disparate sources, such as the adult and pediatric data. In this paper, authored by the pediatric subteam of the Drug Information Association Bayesian Scientific Working Group and Adaptive Design Working Group, we develop, illustrate, and provide suggestions on Bayesian statistical methods that could be used to design improved pediatric development programs that use all available information in the most efficient manner. A variety of relevant Bayesian approaches are described, several of which are illustrated through 2 case studies: extrapolating adult efficacy data to expand the labeling for Remicade to include pediatric ulcerative colitis and extrapolating adult exposure-response information for antiepileptic drugs to pediatrics.

A model-based approach to assess the exposure-response relationship of Lorenzo's oil in adrenoleukodystrophy.

AIMS: X-linked adrenoleukodystrophy (X-ALD) is a peroxisomal disorder, most commonly affecting boys, associated with increased very long chain fatty acids (C26:0) in all tissues, causing cerebral demyelination and adrenocortical insufficiency. Certain monounsaturated long chain fatty acids including oleic and erucic acids, known as Lorenzo's oil (LO), lower plasma C26:0 levels. The aims of this study were to characterize the effect of LO administration on plasma C26:0 concentrations and to determine whether there is an association between plasma concentrations of erucic acid or C26:0 and the likelihood of developing brain MRI abnormalities in asymptomatic boys. METHODS: Non-linear mixed effects modelling was performed on 2384 samples collected during an open label single arm trial. The subjects (n = 104) were administered LO daily at ~2-3 mg kg(-1) with a mean follow-up of 4.88 ± 2.76 years. The effect of erucic acid exposure on plasma C26:0 concentrations was characterized by an inhibitory fractional Emax model. A Weibull model was used to characterize the time-to-developing MRI abnormality. RESULTS: The population estimate for the fractional maximum reduction of C26:0 plasma concentrations was 0.76 (bootstrap 95% CI 0.73, 0.793). Our time-to-event analyses showed that every mg l(-1) increase in time-weighted average of erucic acid and C26:0 plasma concentrations was, respectively, associated with a 3.7% reduction and a 753% increase in the hazard of developing MRI abnormality. However, the results were not significant (P = 0.5344, 0.1509, respectively). CONCLUSIONS: LO administration significantly reduces the abnormally high plasma C26:0 concentrations in X-ALD patients. Further studies to evaluate the effect of LO on the likelihood of developing brain MRI abnormality are warranted.

A hierarchical Bayesian approach for combining pharmacokinetic/pharmacodynamic modeling and Phase IIa trial design in orphan drugs: Treating adrenoleukodystrophy with Lorenzo's oil.

X-linked adrenoleukodystrophy (X-ALD) is a rare, progressive, and typically fatal neurodegenerative disease. Lorenzo's oil (LO) is one of the few X-ALD treatments available, but little has been done to establish its clinical efficacy or indications for its use. In this article, we analyze data on 116 male asymptomatic pediatric patients who were administered LO. We offer a hierarchical Bayesian statistical approach to understand LO pharmacokinetics (PK) and pharmacodynamics (PD) resulting from an accumulation of very long-chain fatty acids. We experiment with individual- and observational-level errors and various choices of prior distributions and deal with the limitation of having just one observation per administration of the drug, as opposed to the more usual multiple observations per administration. We link LO dose to the plasma erucic acid concentrations by PK modeling, and then link this concentration to a biomarker (C26, a very long-chain fatty acid) by PD modeling. Next, we design a Bayesian Phase IIa study to estimate precisely what improvements in the biomarker can arise from various LO doses while simultaneously modeling a binary toxicity endpoint. Our Bayesian adaptive algorithm emerges as reasonably robust and efficient while still retaining good classical (frequentist) operating characteristics. Future work looks toward using the results of this trial to design a Phase III study linking LO dose to actual improvements in health status, as measured by the appearance of brain lesions observed via magnetic resonance imaging.

Elranatamab in relapsed or refractory multiple myeloma: the MagnetisMM-1 phase 1 trial.

Multiple myeloma (MM) is a plasma cell malignancy expressing B cell maturation antigen (BCMA). Elranatamab, a bispecific antibody, engages BCMA on MM and CD3 on T cells. The MagnetisMM-1 trial evaluated its safety, pharmacokinetics and efficacy. Primary endpoints, including the incidence of dose-limiting toxicities as well as objective response rate (ORR) and duration of response (DOR), were met. Secondary efficacy endpoints included progression-free survival (PFS) and overall survival (OS). Eighty-eight patients with relapsed or refractory MM received elranatamab monotherapy, and 55 patients received elranatamab at efficacious doses. Patients had received a median of five prior regimens; 90.9% were triple-class refractory, 29.1% had high cytogenetic risk and 23.6% received prior BCMA-directed therapy. No dose-limiting toxicities were observed during dose escalation. Adverse events included cytopenias and cytokine release syndrome. Exposure was dose proportional. With a median follow-up of 12.0 months, the ORR was 63.6% and 38.2% of patients achieving complete response or better. For responders, the median DOR was 17.1 months. All 13 patients evaluable for minimal residual disease achieved negativity. Even after prior BCMA-directed therapy, 53.8% achieved response. For all 55 patients, median PFS was 11.8 months, and median OS was 21.2 months. Elranatamab achieved durable responses, manageable safety and promising survival for patients with MM. ClinicalTrials.gov Identifier: NCT03269136 .

A Phase 1 Dose-Escalation Study of PF-06671008, a Bispecific T-Cell-Engaging Therapy Targeting P-Cadherin in Patients With Advanced Solid Tumors.

P-cadherin is a cell-cell adhesion molecule that is overexpressed in several solid tumors. PF-06671008 is a T-cell-redirecting bispecific antibody that engages both P-cadherin on tumors and CD3ϵ on T cells and induces antitumor activity in preclinical models. We conducted a phase 1, open-label, first-in-human, dose-escalation study to characterize the safety and tolerability of PF-06671008, towards determining the recommended phase 2 dose. Adult patients with treatment-refractory solid tumors received PF-06671008 (1.5-400 ng/kg) as a weekly intravenous (IV) infusion on a 21-day/3-week cycle. Parallel cohorts evaluated dosing via subcutaneous injection (SC) or an IV-prime dose. Of the 27 patients enrolled in the study, 24 received PF-06671008 IV in escalating doses, two received SC, and one IV-prime. A dose-limiting toxicity of cytokine release syndrome (CRS) occurred in the 400-ng/kg IV group, prompting evaluation of SC and IV-prime schedules. In all, 25/27 patients who received PF-06671008 reported at least one treatment-related adverse event (TRAE); the most common were CRS (21/27), decreased lymphocyte count (9/27), and hypophosphatemia (8/27). Seven patients permanently discontinued treatment due to adverse events and no treatment-related deaths occurred. Cytokine peak concentrations and CRS grade appeared to positively correlate with Cmax. Although the study was terminated due to limited antitumor activity, it provides important insights into understanding and managing immune-related adverse events resulting from this class of molecules. Clinical Trial Registration: URL: https://clinicaltrials.gov/ct2/show/NCT02659631, ClinicalTrials.gov Identifier: NCT02659631.