7 research outputs found

    Pharmacokinetics and pharmacodynamics of topotecan administered daily for 5 days every 3 weeks

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    Topotecan is a novel semisynthetic derivative of the anticancer agent camptothecin and inhibits the intranuclear enzyme topoisomerase I. The lactone structure of topotecan, which is in equilibrium with the inactive ringopened hydroxy acid, is essential for this activity. The open form predominates at physiological pH. We performed a pharmacokinetic, study as part of a phase I study in patients with various types of soli

    Predictive ability of a semi-mechanistic model for neutropenia in the development of novel anti-cancer agents: two case studies

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    Abstract In cancer chemotherapy neutropenia is a common dose-limiting toxicity. An ability to predict the neutropenic effects of cytotoxic agents based on proposed trial designs and models conditioned on previous studies would be valuable. The aim of this study was to evaluate the ability of a semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model for myelosuppression to predict the neutropenia observed in Phase I clinical studies, based on parameter estimates obtained from prior trials. Pharmacokinetic and neutropenia data from 5 clinical trials for diflomotecan and from 4 clinical trials for indisulam were used. Data were analyzed and simulations were performed using the population approach with NONMEM VI. Parameter sets were estimated under the following scenarios: (a) data from each trial independently, (b) pooled data from all clinical trials and (c) pooled data from trials performed before the tested trial. Model performance in each of the scenarios was evaluated by means of predictive (visual and numerical) checks. The semi-mechanistic PK/PD model for neutropenia showed adequate predictive ability for both anti-cancer agents. For diflomotecan, similar predictions were obtained for the three scenarios. For indisulam predictions were better when based on data from the specific study, however when the model parameters were conditioned on data from trials performed prior to a specific study, similar predictions of the drug related-neutropenia profiles and descriptors were obtained as when all data were used. This work provides further indication that modeling and simulation tools can be applied in the early stages of drug development to optimize future trials

    Vemurafenib plus cobimetinib in unresectable stage IIIc or stage IV melanoma

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    Background: In patients with BRAFV600 mutated unresectable stage IIIc or metastatic melanoma, molecular targeted therapy with combined BRAF/MEK-inhibitor vemurafenib plus cobimetinib has shown a significantly improved progression-free survival and overall survival compared to treatment with vemurafenib alone. Nevertheless, the majority of BRAFV600 mutation-positive melanoma patients will eventually develop resistance to treatment. Molecular imaging with 18F-Fluorodeoxyglucose (18F-FDG) PET has been used to monitor response to vemurafenib in some BRAFV600 mutated metastatic melanoma patients, showing a rapid decline of 18F-FDG uptake within 2 weeks following treatment. Furthermore, preliminary results suggest that metabolic alterations might predict the development of resistance to treatment. 18F-Fluoro-3'-deoxy-3'L-fluorothymidine (18F-FLT), a PET-tracer visualizing proliferation, might be more suitable to predict response or resistance to therapy than 18F-FDG. Methods: This phase II, open-label, multicenter study evaluates whether metabolic response to treatment with vemurafenib plus cobimetinib in the first 7 weeks as assessed by 18F-FDG/18F-FLT PET can predict progression-free survival and whether early changes in 18F-FDG/18F-FLT can be used for early detection of treatment response compared to standard response assessment with RECISTv1.1 ceCT at 7 weeks. Ninety patients with BRAFV600E/K mutated unresectable stage IIIc/IV melanoma will be included. Prior to and during treatment all patients will undergo 18F-FDG PET/CT and in 25 patients additional 18F-FLT PET/CT is performed. Histopathological tumor characterization is assessed in a subset of 40 patients to unravel mechanisms of resistance. Furthermore, in all patients, blood samples are taken for pharmacokinetic analysis of vemurafenib/cobimetinib. Outcomes are correlated with PET/CT-imaging and therapy response.

    Predictive ability of a semi-mechanistic model for neutropenia in the development of novel anti-cancer agents: two case studies

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    Abstract In cancer chemotherapy neutropenia is a common dose-limiting toxicity. An ability to predict the neutropenic effects of cytotoxic agents based on proposed trial designs and models conditioned on previous studies would be valuable. The aim of this study was to evaluate the ability of a semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model for myelosuppression to predict the neutropenia observed in Phase I clinical studies, based on parameter estimates obtained from prior trials. Pharmacokinetic and neutropenia data from 5 clinical trials for diflomotecan and from 4 clinical trials for indisulam were used. Data were analyzed and simulations were performed using the population approach with NONMEM VI. Parameter sets were estimated under the following scenarios: (a) data from each trial independently, (b) pooled data from all clinical trials and (c) pooled data from trials performed before the tested trial. Model performance in each of the scenarios was evaluated by means of predictive (visual and numerical) checks. The semi-mechanistic PK/PD model for neutropenia showed adequate predictive ability for both anti-cancer agents. For diflomotecan, similar predictions were obtained for the three scenarios. For indisulam predictions were better when based on data from the specific study, however when the model parameters were conditioned on data from trials performed prior to a specific study, similar predictions of the drug related-neutropenia profiles and descriptors were obtained as when all data were used. This work provides further indication that modeling and simulation tools can be applied in the early stages of drug development to optimize future trials
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