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Predictive Models of Cancer Xenograft Models Of Childhood Solid Tumors Solid Malignancies Group St. Jude Children’s Research Hospital.

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Presentation on theme: "Predictive Models of Cancer Xenograft Models Of Childhood Solid Tumors Solid Malignancies Group St. Jude Children’s Research Hospital."— Presentation transcript:

1 Predictive Models of Cancer Xenograft Models Of Childhood Solid Tumors Solid Malignancies Group St. Jude Children’s Research Hospital

2 Drug Development For Children Has To Be Different Drug acquired NCI/Industry/Academia Phase I UnacceptableToxicity Active Inactive Phase III Virtually no drugs are developed specifically to treat childhood solid tumors. Aim: Develop and validate tumor models to identify potentially important new drugs. Phase II Discard Discard Does phase II testing reveal any insight as to why this drug succeeds or fails? Aim: Develop predictive models. How do phase I trials help to prioritize drugs for phase II evaluation? Aim:Develop a process allowing more rational prioritization.

3 Human Tumor Xenografts Human cancers grown in immune- incompetent mice/rats.Human cancers grown in immune- incompetent mice/rats. Models of most childhood solid tumors.Models of most childhood solid tumors. Models of childhood ALL established.Models of childhood ALL established.

4 Xenograft Model Validation (Rhabdomyosarcoma) Model tumors respond qualitatively and quantitatively to drugs known to be active in the respective clinical disease:Model tumors respond qualitatively and quantitatively to drugs known to be active in the respective clinical disease: Diagnosis models: highly sensitive.Diagnosis models: highly sensitive. Relapse models: significantly less responsiveRelapse models: significantly less responsive Models prospectively identify effective agents.Models prospectively identify effective agents. √ √ √

5 Retrospective and Prospective Use of Rhabdomyosarcoma Xenografts

6 SENSITIVITY OF WILMS TUMOR XENOGRAFTS Entering into a collaboration with GSK who identified a potential Wilms target through a genomics/proteomics screen

7 Where do Xenograft Models Fit? Drug acquired NCI/Industry/Academia Phase I Identification of novel agentsIdentification of novel agents Mechanisms- molecular targetsMechanisms- molecular targets Broad spectrum activityBroad spectrum activity Lack of cross-resistanceLack of cross-resistance Optimizing schedules of administrationOptimizing schedules of administration Developing relationships betweenDeveloping relationships between response and systemic exposures Phase II

8 Optimizing schedules of administration Schedule-Dependency of Camptothecins that Target Topoisomerase I

9 Importance of Scheduling Emerging Clinical Data Topotecan Response Rate Solid Tumors Schedule Sample Size Investigatorqdx5 (qdx5)2 8% 25% 40 20 Tubergen et al. Santana et al. Leukemiaqdx5 (qdx5)2 5% 50% 21 14 Furman et al. Irinotecan Solid Tumors Schedule Sample Size Investigator qdx5 (qdx5)2 6% 25% 35 23 Blaney et al. Furman et al. (qdx5)228%25 Cosetti et al. Response Rate Furman et al.

10 Developing Relationships Between Response and Drug Systemic Exposures Allows comparison of AUC @MTD (patients) with AUC causing model tumor regressionsAllows comparison of AUC @MTD (patients) with AUC causing model tumor regressions

11 Developing Relationships Between Response and Drug Systemic Exposures

12 Evaluation of MGI-114 (Phase II in COG?) Systemic exposure is still > 10-fold higher than in children @MTD

13 Neuroblastoma: Preclinical Prediction Topotecan: daily x 5 x 2Topotecan: daily x 5 x 2 Preclinical: 4 of 6 objective responses @ 100 ng.hr/ml.Preclinical: 4 of 6 objective responses @ 100 ng.hr/ml. Phase II targeted systemic exposure (AUC) 100 ng.hr/ml: Clinical: Stage IV Neuroblastoma 16/28 responses (57%)Phase II targeted systemic exposure (AUC) 100 ng.hr/ml: Clinical: Stage IV Neuroblastoma 16/28 responses (57%)

14 Where Do Xenograft Models Fit in Drug Development for Childhood Cancer? Drug acquired NCI/Industry/Academia Phase I Phase II Prospective identification of active agents Optimization of administration schedules Prioritization of agents for phase I Rational decisions to advance/stop development Potential to focus phase II trials Include pediatric tumor models

15 Conclusions Valid models of childhood cancers exist.Valid models of childhood cancers exist. Models reflect clinical drug sensitivity.Models reflect clinical drug sensitivity. Species differences in drug disposition, metabolism and tolerance are the major problems in accurately translating results.Species differences in drug disposition, metabolism and tolerance are the major problems in accurately translating results. Models accurately identify clinically active agents when systemic exposure is normalized.Models accurately identify clinically active agents when systemic exposure is normalized.

16 Practical Considerations Access to drugs at an early stageAccess to drugs at an early stage Establishment of national consortium to encompass most childhood tumorsEstablishment of national consortium to encompass most childhood tumors Develop predictive pharmacokinetic modelsDevelop predictive pharmacokinetic models Characterize available models (genomic/proteomic screens)Characterize available models (genomic/proteomic screens) Develop a funding mechanism to support experimentalists involved in preclinical to clinical transitional science.Develop a funding mechanism to support experimentalists involved in preclinical to clinical transitional science.

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