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Ramat Gan, Israel

Ribba B.,Ecole Normale Superieure de Lyon | Holford N.H.,Uppsala University | Magni P.,University of Pavia | Troconiz I.,University of Navarra | And 6 more authors.
CPT: Pharmacometrics and Systems Pharmacology | Year: 2014

Population modeling of tumor size dynamics has recently emerged as an important tool in pharmacometric research. A series of new mixed-effects models have been reported recently, and we present herein a synthetic view of models with published mathematical equations aimed at describing the dynamics of tumor size in cancer patients following anticancer drug treatment. This selection of models will constitute the basis for the Drug Disease Model Resources (DDMoRe) repository for models on oncology. © 2014 ASCPT All rights reserved.

Jager E.,Institute for Medical BioMathematics | van der Velden V.H.J.,Rotterdam University | te Marvelde J.G.,Rotterdam University | Walter R.B.,Fred Hutchinson Cancer Research Center | And 4 more authors.
PLoS ONE | Year: 2011

Gemtuzumab ozogamicin (GO) is a chemotherapy-conjugated anti-CD33 monoclonal antibody effective in some patients with acute myeloid leukemia (AML). The optimal treatment schedule and optimal timing of GO administration relative to other agents remains unknown. Conventional pharmacokinetic analysis has been of limited insight for the schedule optimization. We developed a mechanism-based mathematical model and employed it to analyze the time-course of free and GO-bound CD33 molecules on the lekemic blasts in individual AML patients treated with GO. We calculated expected intravascular drug exposure (I-AUC) as a surrogate marker for the response to the drug. A high CD33 production rate and low drug efflux were the most important determinants of high I-AUC, characterizing patients with favorable pharmacokinetic profile and, hence, improved response. I-AUC was insensitive to other studied parameters within biologically relevant ranges, including internalization rate and dissociation constant. Our computations suggested that even moderate blast burden reduction prior to drug administration enables lowering of GO doses without significantly compromising intracellular drug exposure. These findings indicate that GO may optimally be used after cyto-reductive chemotherapy, rather than before, or concomitantly with it, and that GO efficacy can be maintained by dose reduction to 6 mg/m 2 and a dosing interval of 7 days. Model predictions are validated by comparison with the results of EORTC-GIMEMA AML19 clinical trial, where two different GO schedules were administered. We suggest that incorporation of our results in clinical practice can serve identification of the subpopulation of elderly patients who can benefit most of the GO treatment and enable return of the currently suspended drug to clinic. © 2011 Jager et al.

Elishmereni M.,Institute for Medical BioMathematics IMBM | Kheifetz Y.,Institute for Medical BioMathematics IMBM | Sondergaard H.,Novo Nordisk AS | Overgaard R.V.,Novo Nordisk AS | And 2 more authors.
PLoS Computational Biology | Year: 2011

Interleukin (IL)-21 is an attractive antitumor agent with potent immunomodulatory functions. Yet thus far, the cytokine has yielded only partial responses in solid cancer patients, and conditions for beneficial IL-21 immunotherapy remain elusive. The current work aims to identify clinically-relevant IL-21 regimens with enhanced efficacy, based on mathematical modeling of long-term antitumor responses. For this purpose, pharmacokinetic (PK) and pharmacodynamic (PD) data were acquired from a preclinical study applying systemic IL-21 therapy in murine solid cancers. We developed an integrated disease/PK/PD model for the IL-21 anticancer response, and calibrated it using selected "training" data. The accuracy of the model was verified retrospectively under diverse IL-21 treatment settings, by comparing its predictions to independent "validation" data in melanoma and renal cell carcinoma-challenged mice (R 2&0.90). Simulations of the verified model surfaced important therapeutic insights: (1) Fractionating the standard daily regimen (50 μg/dose) into a twice daily schedule (25 μg/dose) is advantageous, yielding a significantly lower tumor mass (45% decrease); (2) A low-dose (12 μg/day) regimen exerts a response similar to that obtained under the 50 μg/day treatment, suggestive of an equally efficacious dose with potentially reduced toxicity. Subsequent experiments in melanoma-bearing mice corroborated both of these predictions with high precision (R 2&0.89), thus validating the model also prospectively in vivo. Thus, the confirmed PK/PD model rationalizes IL-21 therapy, and pinpoints improved clinically-feasible treatment schedules. Our analysis demonstrates the value of employing mathematical modeling and in silico-guided design of solid tumor immunotherapy in the clinic. © 2011 Elishmereni et al.

Agency: Cordis | Branch: H2020 | Program: MSCA-ITN-ETN | Phase: MSCA-ITN-2014-ETN | Award Amount: 3.61M | Year: 2014

Novel treatment options and associated personalised, patient-tailored therapies need to be explored and developed for highly heterogeneous and chemotherapy resistant cancers, such as malignant melanoma. This can only be achieved by industry-academia collaborations in newly emerging, innovative research disciplines such as translational cancer systems biology and systems medicine. These disciplines and the associated European training needs provide the foundation for the MEL-PLEX ETN. MEL-PLEX aims to understand the network-level and multi-scale regulation of disease-relevant signalling in melanoma through a combination of quantitative biomedical and computational research approaches that go significantly beyond the current state-of-the-art. Coordinated by the RCSI Centre for Systems Medicine, MEL-PLEX will train 15 early stage researchers through a highly interdisciplinary and intersectoral research training programme. MEL-PLEX comprises 11 beneficiaries and 7 partner organisations from 11 countries, including European and international leaders in personalised melanoma therapy, melanoma systems biology and cancer systems medicine. MEL-PLEX aims to (i) achieve an unmatched depth of molecular and mechanistic disease understanding, (ii) will exploit this knowledge to develop and validate predictive models for disease progression, prognosis and responsiveness to current and novel (co-)treatment options, and (iii) will provide superior and clinically relevant tools and biomarker signatures for personalising and optimising melanoma treatment. The MEL-PLEX ETN addresses current needs in academia and the private sector for researchers that have been trained in an environment that spans across biology, medicine and mathematics, that can navigate confidently between clinical, academic and private sector research environments, and that have developed an innovative and creative mindset to progress research findings towards applications.

Optimata | Date: 2007-03-20

Computer software and workstations comprised of software modules that model a patient and the behavior of the patient in response to drugs for various diseases for generating an optimal treatment protocol for treating the diseases and for use in studying drug/patient interactions, decision analysis and acceleration of drug development programs. Scientific research and consultations services for the pharmaceutical, biotechnology and health care industries; technical consultation and research in the field of pharmaceuticals and biotechnology; research and development of new medicinal drugs for others; scientific research in the fields of computational physiology and pathology, and dynamic simulation services, including, designing computer software for others within the pharmaceutical, biotechnology and health care industries for use in drug-patient interactions analyses.

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