Model‐Informed Development and Registration of a Once‐Daily Regimen of Extended‐Release Tofacitinib

Lamba, Manisha; Hutmacher, Matthew M.; Fürst, Daniel E.; Dikranian, Ara; Dowty, Martin E.; Conrado, Daniela J.; Stock, Thomas; Nduaka, Chudy I.; Cook, Jack; Krishnaswami, Sriram

doi:10.1002/cpt.576

Cited by 33 publications

(45 citation statements)

References 38 publications

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“…The fenebrutinib effect on response was modeled as an E max function driven by fenebrutinib exposure as measured by C max , C min , or AUC, and the statistical significance of incorporating each exposure metric into the E-R model was similar in terms of p-values. Steady state AUC was chosen as the driver for efficacy, based on exploratory results, and prior E-R modeling knowledge in RA (33,34). Separate E max functions to describe the E-R relationship for each of ACR20, ACR50, and ACR70 probability were tested, but it was seen that a single E max term for all three ACR thresholds adequately captured the data.…”

Section: Acr20 Acr50 and Acr70mentioning

confidence: 99%

Population Pharmacokinetics, Efficacy Exposure-response Analysis, and Model-based Meta-analysis of Fenebrutinib in Subjects with Rheumatoid Arthritis

Chan¹,

Yu²,

Chinn³

et al. 2020

Pharm Res

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Purpose Fenebrutinib (GDC-0853), a Bruton's tyrosine kinase (BTK) inhibitor was investigated in a Phase 2 clinical trial in patients with rheumatoid arthritis (RA). Our aim was to apply a model-informed drug development (MIDD) approach to examine the totality of available clinical efficacy data. Methods Population pharmacokinetics (popPK) modeling, exposure-response (E-R) analysis, and model-based metaanalysis (MBMA) of fenebrutinib were performed based on the Phase 2 data. Results PopPK of fenebrutinib after oral administration was described using a 3-compartment model with linear elimination and a flexible absorption transit compartment model. Healthy subjects had a 52% higher apparent clearance than patients. E-R analyses based on longitudinal ACR20, ACR50, and ACR70 and DAS28 (CRP) data modeled fenebrutinib effect with an E max function, and an efficacy plateau was achieved within the exposure range obtained in the Phase 2 clinical trial. Based on literature data, a summary-level clinical efficacy database was constructed, and MBMA determined ACR20, ACR50, and ACR70 responder rates in the placebo and adalimumab arms of the Phase 2 clinical trial were found to be consistent with historical data for these treatments. Conclusions Our multi-pronged approach applied MIDD to maximize knowledge extraction of efficacy data and enabled robust interpretation from a Phase 2 clinical trial. KEY WORDS Bruton's tyrosine kinase (BTK) inhibitor. exposure-response. model-based meta-analysis. population pharmacokinetics. rheumatoid arthritis ABBREVIATIONS AUC Area under the concentration-time curve BTK Bruton's tyrosine kinase CL/F Apparent clearance C max Maximum concentration C min Trough concentration CRP C-reactive protein DAS28 Disease Activity Score with 28-joint counts EBE Empirical Bayes estimates E-R Exposure-response F1 Relative extent of absorption FOCE-I First order conditional estimation with interaction MBMA Model-based meta-analysis MIDD Model-informed drug development MTT Mean transit time MTX Methotrexate NLME Non-linear mixed effects NTR Number of transit compartments pcVPC Prediction-corrected visual predictive check PD Pharmacodynamic The original version of this article was revised: The article was published with an incomplete title. The complete title is "Population Pharmacokinetics, Efficacy Exposure-response Analysis, and Model-based Meta-analysis of Fenebrutinib in Subjects with Rheumatoid Arthritis".

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Section: Acr20 Acr50 and Acr70mentioning

confidence: 99%

Population Pharmacokinetics, Efficacy Exposure-response Analysis, and Model-based Meta-analysis of Fenebrutinib in Subjects with Rheumatoid Arthritis

Chan¹,

Yu²,

Chinn³

et al. 2020

Pharm Res

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“…The minimum concentration in plasma at steady state (C trough ) of the once‐daily MR formulation was approximately 30% lower than that of the twice‐daily IR formulation. The applicant subsequently conducted additional exposure‐response analysis to evaluate the effect of differences in PK parameters on efficacy 7 …”

Section: Resultsmentioning

confidence: 99%

Application of Clinical Pharmacology Principles in Drug Development of Modified‐Release Products: Leveraging Exposure‐Response Information to Support Approval

Abuasal

Hamed

Ahmed

et al. 2020

The Journal of Clinical Pharma

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The development of modified-release (MR) drug products aims to address a clinical need such as improving patient compliance. There are multiple pathways and development strategies for the registration and approval of MR products.The development strategy of an MR product is usually dependent on the availability and pharmacokinetic/pharmacodynamics (PK/PD) characteristics of the reference drug product, that is, an immediate-release (IR) product or a reference MR. Compared with a reference IR product, an MR product is likely to have a different PK profile over the least common dosing time due to unequal dosing intervals. In case of differences in PK profiles between the MR product and the reference product, confirmatory efficacy and safety studies may be needed to support registration. In some cases, however, a thorough clinical PK/PD characterization may provide sufficient basis to support the approval of the proposed MR product without the need for additional safety and efficacy studies. This article summarizes the US Food and Drug Administration experience and the regulatory considerations supporting the approval of MR products in the past 6 years and discusses cases in which clinical pharmacology and PK/PD information were leveraged to support approval without the need for additional clinical studies. Details of all these cases are available in the public domain. In 2 cases a well-characterized exposure-response relationship provided sufficient justification that differences in the shape of the PK profiles were not clinically relevant. In the remaining 3 cases a thorough characterization of the PK profile along with a risk-based approach provided bases for approval.

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“…Therefore, the unbound TOF concentrations in the SPT space were assigned as the driving force for the alleviation of paw edema. An indirect response model was used to characterize the effects of DEX and TOF on paw swelling because the drugs interfere with pro-inflammatory cytokine production and disrupt responses such as recruitment of immune effector cells (39). The maximal concentration of TOF in the SPT compartment occurs at 0.75 h after SC dosing, while the peak paw edema suppression was seen around 10 h. Similar time delays between peak concentration and peak drug effect were also seen in DEX-treated CIA rats, which presumably reflects the time needed for cytokine dissipation (k out ).…”

Section: Discussionmentioning

confidence: 99%

Modeling Combined Anti-Inflammatory Effects of Dexamethasone and Tofacitinib in Arthritic Rats

Song

DuBois

et al. 2019

AAPS J

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Tofacitinib (TOF), a Janus kinase (JAK) inhibitor, which was approved in 2012, has been recommended for the treatment of clinically active rheumatoid arthritis (RA). Dexamethasone (DEX), a potent corticosteroid, is also used in RA therapy but with limited usefulness due to doseand time-dependent adverse effects. This pilot study examines the single and combined effects of DEX and TOF in order to explore the steroid-sparing potential of TOF. Collagen-induced arthritic (CIA) rats were subcutaneously (SC) dosed with vehicle, 1.5 mg/kg TOF, 5 mg/kg TOF, 0.225 mg/kg DEX, or a combination of 1.5 mg/kg TOF and 0.225 mg/kg DEX. Paw sizes were measured as an index of disease and drug efficacy and dynamically depicted using a logistic function for natural paw growth, a turnover model for disease progression, an indirect response model for inhibitory effects of TOF and DEX and a non-competitive interaction model for the combined effect of DEX and TOF. TOF alone exerted only a slight inhibitory effect on RA paw edema compared to DEX, which reduced edema by 40%. In combination, TOF and DEX had additive effects with an interaction factor of 0.76. Using model simulations, a single SC dose of TOF does not have a visible steroid-sparing potential, although BID oral dosing has such potential. The current study suggests an additive effect of TOF and DEX and simulations indicate that further exploration of TOF and DEX administration timing may produce desirable drug efficacy with lower DEX doses.

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Model‐Informed Development and Registration of a Once‐Daily Regimen of Extended‐Release Tofacitinib

Cited by 33 publications

References 38 publications

Population Pharmacokinetics, Efficacy Exposure-response Analysis, and Model-based Meta-analysis of Fenebrutinib in Subjects with Rheumatoid Arthritis

Population Pharmacokinetics, Efficacy Exposure-response Analysis, and Model-based Meta-analysis of Fenebrutinib in Subjects with Rheumatoid Arthritis

Application of Clinical Pharmacology Principles in Drug Development of Modified‐Release Products: Leveraging Exposure‐Response Information to Support Approval

Modeling Combined Anti-Inflammatory Effects of Dexamethasone and Tofacitinib in Arthritic Rats

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