Population pharmacokinetic/pharmacodynamic modeling of drug-induced adverse effects of a novel homocamptothecin analog, elomotecan (BN80927), in a Phase I dose finding study in patients with advanced solid tumors

Trocóniz, Iñaki F.; Cendros, J. M.; Soto, Elena; Pruñonosa, Joan; Perez-Mayoral, Ana; Peraire, Concepción; Principe, Paola; Delavault, Patrick; Cvitkovic, F.; Lesimple, Thierry; Obach, R.

doi:10.1007/s00280-012-1906-y

Cited by 18 publications

(15 citation statements)

References 20 publications

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“…77 The resulting synthetic compounds are known as homocamptothecins. 78 The most promising of these compounds are elomotecan (BN80927) 79,80 and diflomotecan (BN80915), 81,82 which have been tested in clinical trials for colon, breast, prostate, and lung cancer.…”

Section: Figure 716mentioning

confidence: 99%

Other Anticancer Drugs Targeting DNA and DNA-Associated Enzymes

Avendaño

Menéndez²

2015

Medicinal Chemistry of Anticancer Drugs

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Section: Figure 716mentioning

confidence: 99%

Other Anticancer Drugs Targeting DNA and DNA-Associated Enzymes

Avendaño

Menéndez²

2015

Medicinal Chemistry of Anticancer Drugs

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“…These findings are often quantified using grades, because objective direct measurement is not always possible. In these cases, NLME models can use discrete data models, for example, logistic regression/ proportional odds, in which the probability of a certain grade is correlated with a measure of exposure (e.g., diarrhea grades [68] and asthenia, nausea, and vomiting grades [69]). Additionally, Markov models can be used if the toxicity grades between the nearby time points are correlated, which Hénin et al illustrated for hand-and-foot syndrome [70].…”

Section: Adverse Event Modelsmentioning

confidence: 99%

“…Monitored event types that had not Establishing the relationship between PK and BMK and/or TS dynamics (extensively reviewed in [23,29,36,37] Establishing the relationship between different (model-based) predictors and OS and PFS (Table 1) Establishing the relationship between drug exposure and toxicity in Dose optimization [77] PBPK [8][9][10] Hematological toxicities [51][52][53][54][55][56][57][58][59] CT measurement optimization [27] TMDD [12][13][14][15][16] Nonhematological toxicities [65][66][67][68][69][70] Drug selection [17] Abbreviations: BMK, biomarker; CT, computed tomography; OS, overall survival; PFS, progression free survival; PBPK, physiologically based pharmacokinetic model; PK, pharmacokinetics; TMDD, target-mediated drug disposition; TS, tumor size.…”

Section: Data Setsmentioning

confidence: 99%

Bringing Model-Based Prediction to Oncology Clinical Practice: A Review of Pharmacometrics Principles and Applications

et al. 2015

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Despite much investment and progress, oncology is still an area with significant unmet medical needs, with new therapies and more effective use of current therapies needed. The emergent field of pharmacometrics combines principles from pharmacology (pharmacokinetics [PK] and pharmacodynamics [PD]), statistics, and computational modeling to support drug development and optimize the use of already marketed drugs. Although it has gained a role within drug development, its use in clinical practice remains scarce. The aim of the present study was to review the principal pharmacometric concepts and provide some examples of its use in oncology. Integrated population PK/PD/disease progression models as part of the pharmacometrics platform provide a powerful tool to predict outcomes so that the right dose can be given to the right patient to maximize drug efficacy and reduce drug toxicity. Population models often can be developed with routinely collected medical record data; therefore, we encourage the application of such models in the clinical setting by generating close collaborations between physicians and pharmacometricians. The Oncologist 2016;21:220-232Implications for Practice: The present review details how the emerging field of pharmacometrics can integrate medical record data with predictive pharmacological and statistical models of drug response to optimize and individualize therapies. In order to make this routine practice in the clinic, greater awareness of the potential benefits of the field is required among clinicians, together with closer collaboration between pharmacometricians and clinicians to ensure the requisite data are collected in a suitable format for pharmacometrics analysis.

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“…Several examples in the anesthetic (Gambus and Troconiz, 2015) and non-anesthetic (Troconiz et al, 2012) (Sheiner, 1994; Soto et al., 2011) literature have shown the utility of these approaches; the use of the population approach for mathematical modeling extends beyond clinical pharmacology (Owen and Fiedler-Kelly, 2014; Pinheiro and Bates, 2000). …”

Section: Introductionmentioning

confidence: 99%

Relation between acute and long-term cognitive decline after surgery: Influence of metabolic syndrome

Gambús¹,

Trocóniz

Feng

et al. 2015

Brain, Behavior, and Immunity

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Introduction The relationship between persistent postoperative cognitive decline and the more common acute variety remains unknown; using data acquired in preclinical studies of postoperative cognitive decline we attempted to characterize this relationship. Methods Low capacity runner (LCR) rats, which have all the features of the metabolic syndrome, were compared postoperatively with high capacity runner (HCR) rats for memory, assessed by trace fear conditioning (TFC) on the 7th postoperative day, and learning and memory (probe trial [PT]) assessed by the Morris water-maze (MWM) at three months postoperatively. Rate of learning (AL) data from the MWM test, were estimated by non-linear mixed effects modeling. The individual rat's TFC result at postoperative day (POD) 7 was correlated with its AL and PT from the MWM data sets at postoperative day POD 90. Results A single exponential decay model best described AL in the MWM with LCR and surgery (LCR–SURG) being the only significant covariates; first order AL rate constant was 0.07 s−1 in LCR–SURG and 0.16 s−1 in the remaining groups (p<0.05). TFC was significantly correlated with both AL (R = 0.74; p < 0.0001) and PT (R = 0.49; p < 0.01). Conclusion Severity of memory decline at 1 week after surgery presaged long-lasting deteriorations in learning and memory.

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Population pharmacokinetic/pharmacodynamic modeling of drug-induced adverse effects of a novel homocamptothecin analog, elomotecan (BN80927), in a Phase I dose finding study in patients with advanced solid tumors

Abstract: The pharmacokinetic parameters and the toxicity pattern of elomotecan suggest that this novel homocamptothecin analog should be further explored in the clinical setting using a dose of 60 mg administered as a 30-min intravenous infusion, once every 3 weeks.

Cited by 18 publications

References 20 publications

Other Anticancer Drugs Targeting DNA and DNA-Associated Enzymes

Other Anticancer Drugs Targeting DNA and DNA-Associated Enzymes

Bringing Model-Based Prediction to Oncology Clinical Practice: A Review of Pharmacometrics Principles and Applications

Relation between acute and long-term cognitive decline after surgery: Influence of metabolic syndrome

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