Toward Project Optimus for Oncology Precision Medicine: <scp>Multi‐Dimensional</scp> Dose Optimization Enabled by Quantitative Clinical Pharmacology

Venkatakrishnan, Karthik; Graaf, Piet H. van der

doi:10.1002/cpt.2742

Cited by 23 publications

(15 citation statements)

References 31 publications

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“…Moreover, the simulation step provides insight into the “learning” of the dose–response relationship, which is not a statistical testing problem, but rather a quantification of the probability of achieving better outcomes with one dose versus another based on integration of all available data 38 . Together with clinical safety data and associated exposure‐safety relationships, the framework described here can be powerful as a component of a Totality of Evidence approach to dose optimization for oncology therapies that is based on a robust characterization of dose/exposure‐response relationships 38‐40 . Furthermore, integration of covariates (e.g., tumor genomics) into these models can present opportunities for informing patient selection hypotheses in precision medicine development.…”

Section: Discussionmentioning

confidence: 99%

“…38 Together with clinical safety data and associated exposure-safety relationships, the framework described here can be powerful as a component of a Totality of Evidence approach to dose optimization for oncology therapies that is based on a robust characterization of dose/exposure-response relationships. [38][39][40] Furthermore, integration of covariates (e.g., tumor genomics) into these models can present opportunities for informing patient selection hypotheses in precision medicine development. Taken together, we view the approach described here as an important component of the pharmacometrics toolkit in oncology drug development and encourage our readers to reflect on potential opportunities for future applications across cancer indications to inform cross-endpoint bridging, patient selection, and dose optimization.…”

Section: F I G U R Ementioning

confidence: 99%

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A multistate modeling and simulation framework to learn dose–response of oncology drugs: Application to bintrafusp alfa in non‐small cell lung cancer

Liu

Grisic

Krishnan

et al. 2023

CPT Pharmacom & Syst Pharma

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The dose/exposure‐efficacy analyses are often conducted separately for oncology end points like best overall response, progression‐free survival (PFS) and overall survival (OS). Multistate models offer to bridge these dose‐end point relationships by describing transitions and transition times from enrollment to response, progression, and death, and evaluating transition‐specific dose effects. This study aims to apply the multistate pharmacometric modeling and simulation framework in a dose optimization setting of bintrafusp alfa, a fusion protein targeting TGF‐β and PD‐L1. A multistate model with six states (stable disease [SD], response, progression, unknown, dropout, and death) was developed to describe the totality of endpoints data (time to response, PFS, and OS) of 80 patients with non‐small cell lung cancer receiving 500 or 1200 mg of bintrafusp alfa. Besides dose, evaluated predictor of transitions include time, demographics, premedication, disease factors, individual clearance derived from a pharmacokinetic model, and tumor dynamic metrics observed or derived from tumor size model. We found that probabilities of progression and death upon progression decreased over time since enrollment. Patients with metastasis at baseline had a higher probability to progress than patients without metastasis had. Despite dose failed to be statistically significant for any individual transition, the combined effect quantified through a model with dose‐specific transition estimates was still informative. Simulations predicted a 69.2% probability of at least 1 month longer, and, 55.6% probability of at least 2‐months longer median OS from the 1200 mg compared to the 500 mg dose, supporting the selection of 1200 mg for future studies.

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Section: Discussionmentioning

confidence: 99%

Section: F I G U R Ementioning

confidence: 99%

A multistate modeling and simulation framework to learn dose–response of oncology drugs: Application to bintrafusp alfa in non‐small cell lung cancer

Liu

Grisic

Krishnan

et al. 2023

CPT Pharmacom & Syst Pharma

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“…Model-based approaches are planned to confirm the selected xevinapant dose/regimen once data from these phase III studies become available (Figure 1). Viewed from a broader perspective and in the context of the growing recognition of the importance of dose optimization in oncology drug development, 33,[37][38][39][40] these analyses illustrate the value of quantitative clinical pharmacological contextualization for dose and regimen selection. Importantly, they illustrate the value of a holistic integration of preclinical and clinical PK, PD, safety, and efficacy data and associated E-R relationships, with a totality of evidence approach, 41 in which confidence can be gained from consistency across multiple approaches and data sources integrated in a mechanism-informed manner through modeling and simulation.…”

Section: Discussionmentioning

confidence: 99%

Model‐Informed Selection of the Recommended Phase III Dose of the Inhibitor of Apoptosis Protein Inhibitor, Xevinapant, in Combination with Cisplatin and Concurrent Radiotherapy in Patients with Locally Advanced Squamous Cell Carcinoma of the Head and Neck

Vugmeyster,

Ravula,

Rouits

et al. 2023

Clin Pharma and Therapeutics

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Xevinapant, an oral inhibitor of apoptosis protein (IAP) inhibitor, demonstrated efficacy in combination with chemoradiotherapy in a randomized phase 2 study (NCT02022098) in patients with locally advanced squamous cell carcinoma of the head and neck at 200 mg/day on days 1‐14 of a 3‐week cycle. To confirm 200 mg/day as the recommended phase 3 dose (RP3D), we integrated preclinical, clinical, pharmacokinetic/pharmacodynamic (PK/PD), and exposure‐response modeling results. Population PK/PD modeling of IAP inhibition in peripheral blood mononuclear cells in 21 patients suggested the pharmacologically active dose range was 100‐200 mg/day, with a trend for more robust inhibition at the end of the dosing interval at 200 mg/day based on an indirect response model. Additionally, the unbound average plasma concentration at 200 mg/day was similar to that associated with efficacy in preclinical xenograft models. Logistic regression exposure‐response analyses of data from 62 patients in the phase 2 study showed exposure‐related increases in probabilities of locoregional control at 18 months (primary endpoint), overall response, complete response, and the radiosensitization mechanism‐related composite safety endpoint “mucositis and/or dysphagia” (p<0.05). Exposure‐response relationships were not discernible for 12 of 13 evaluated safety endpoints, incidence of dose reductions, and time to first dose reduction. Quantitative integration of all available data, including model‐derived target inhibition profiles, positive exposure‐efficacy relationships, and lack of discernible exposure‐safety relationships for most safety endpoints, supports selection of xevinapant 200 mg/day on days 1‐14 of a 3‐week cycle as the RP3D, allowing for successive dose reductions to 150 and 100 mg/day to manage adverse events.

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“…23 In line with the exposure-response analysis results, efficacy was maintained after dose reduction from ponatinib 45 mg or 30 mg to 15 mg with a consistent toxicity profile. 24,25 The consistency in findings from OPTIC, associated exposure-response modeling and simulation, and emerging real-world clinical experience support an assessment based on "totality-of-evidence" principles 26,27 that the responsebased updated posology for ponatinib has a superior benefit-risk profile compared with continuous fixed dosing for the treatment of patients with CP-CML.…”

Section: Articlementioning

confidence: 92%

Response‐Based Dosing for Ponatinib: Model‐Based Analyses of the Dose‐Ranging OPTIC Study

Hanley

Diderichsen

Rich

et al. 2023

Clin Pharma and Therapeutics

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Optimizing Ponatinib Treatment in CP‐CML (OPTIC) was a randomized, phase II dose‐optimization trial of ponatinib in chronic phase‐chronic myeloid leukemia (CP‐CML) resistant to ≥ 2 tyrosine kinase inhibitors or with T315I mutation. Patients were randomized to starting doses of 45‐, 30‐, or 15‐mg ponatinib once daily. Patients receiving 45‐ or 30‐mg reduced to 15‐mg upon achievement of ≤ 1% BCR::ABL1IS (≥ molecular response with 2‐log reduction (MR2)). The exposure‐molecular response relationship was described using a four‐state, discrete‐time Markov model. Time‐to‐event models were used to characterize the relationship between exposure and arterial occlusive events (AOEs), grade ≥ 3 neutropenia, and thrombocytopenia. Increasing systemic exposures were associated with increasing probability of transitioning from no response to ≥ MR1, and from MR1 to ≥ MR1, with odds ratios of 1.63 (95% confidence interval (CI), 1.06–2.73) and 2.05 (95% CI, 1.53–2.89) for a 15‐mg dose increase, respectively. Ponatinib exposure was a significant predictor of AOEs (hazard ratio (HR) 2.05, 95% CI, 1.43–2.93, for a 15‐mg dose increase). In the exposure‐safety models for neutropenia and thrombocytopenia, exposure was a significant predictor of grade ≥ 3 thrombocytopenia (HR 1.31, 95% CI, 1.05–1.64, for a 15‐mg dose increase). Model‐based simulations predicted a clinically meaningful higher rate of ≥ MR2 response at 12 months for the 45‐mg starting dose (40.4%) vs. 30‐mg (34%) and 15‐mg (25.2%). The exposure–response analyses supported a ponatinib starting dose of 45 mg with reduction to 15 mg at response for patients with CP‐CML.

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Toward Project Optimus for Oncology Precision Medicine: Multi‐Dimensional Dose Optimization Enabled by Quantitative Clinical Pharmacology

Cited by 23 publications

References 31 publications

A multistate modeling and simulation framework to learn dose–response of oncology drugs: Application to bintrafusp alfa in non‐small cell lung cancer

A multistate modeling and simulation framework to learn dose–response of oncology drugs: Application to bintrafusp alfa in non‐small cell lung cancer

Model‐Informed Selection of the Recommended Phase III Dose of the Inhibitor of Apoptosis Protein Inhibitor, Xevinapant, in Combination with Cisplatin and Concurrent Radiotherapy in Patients with Locally Advanced Squamous Cell Carcinoma of the Head and Neck

Response‐Based Dosing for Ponatinib: Model‐Based Analyses of the Dose‐Ranging OPTIC Study

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