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Translation of anticancer efficacy from nonclinical models to the clinic.

Stroh M, Duda DG, Takimoto CH, Yamazaki S, Vicini P - CPT Pharmacometrics Syst Pharmacol (2014)

Bottom Line: Mouse cancer models have provided critical insights into tumor biology; however, clinical translation of these findings has been challenging.This perspective posits that factors impacting on successful translation start with limitations in capturing human cancer pathophysiology and end with challenges in generating robust translatable preclinical end points.A comprehensive approach that considers clinically relevant mouse models with both an integrated biomarker strategy and a complementary modeling and simulation effort will strengthen the current oncology drug development paradigm.

View Article: PubMed Central - PubMed

Affiliation: Clinical Pharmacology, Genentech, South San Francisco, California, USA.

ABSTRACT
Mouse cancer models have provided critical insights into tumor biology; however, clinical translation of these findings has been challenging. This perspective posits that factors impacting on successful translation start with limitations in capturing human cancer pathophysiology and end with challenges in generating robust translatable preclinical end points. A comprehensive approach that considers clinically relevant mouse models with both an integrated biomarker strategy and a complementary modeling and simulation effort will strengthen the current oncology drug development paradigm.

No MeSH data available.


Related in: MedlinePlus

Translational phase I study with biomarker-defined end points. Phase I oncology studies classically treat advanced cancer patients in cohorts of three at progressively increasing starting dose levels until drug-related toxicities are observed. When the incidence and severity of these toxicities exceed levels predefined as dose limiting in the study protocol, dose escalation is halted. Additional patients are then treated at a lower dose to determine the maximum tolerated dose level. In a modern translational phase I study design, these classical phase I end points are augmented by pharmacodynamic biomarker monitoring to define the minimum exposures associated with biological activity. At the end of dose escalation, patient expansion cohorts are often added to collect additional biomarker, safety, and pharmacokinetic data. Thus, these early clinical studies mimic the comprehensive preclinical studies used to define pharmacologically active drug exposures. Modeling and simulation can be used at every step along the sequence to integrate exposure, biomarker, and other data collected during the trials. BED, biologically effective dose; DLT, dose-limiting toxicity; MTD, maximum tolerated dose.
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fig2: Translational phase I study with biomarker-defined end points. Phase I oncology studies classically treat advanced cancer patients in cohorts of three at progressively increasing starting dose levels until drug-related toxicities are observed. When the incidence and severity of these toxicities exceed levels predefined as dose limiting in the study protocol, dose escalation is halted. Additional patients are then treated at a lower dose to determine the maximum tolerated dose level. In a modern translational phase I study design, these classical phase I end points are augmented by pharmacodynamic biomarker monitoring to define the minimum exposures associated with biological activity. At the end of dose escalation, patient expansion cohorts are often added to collect additional biomarker, safety, and pharmacokinetic data. Thus, these early clinical studies mimic the comprehensive preclinical studies used to define pharmacologically active drug exposures. Modeling and simulation can be used at every step along the sequence to integrate exposure, biomarker, and other data collected during the trials. BED, biologically effective dose; DLT, dose-limiting toxicity; MTD, maximum tolerated dose.

Mentions: To increase the impact of biomarkers in oncology, it is important to have a robust framework for biomarker implementation into clinical development. The pharmacological audit trail (PhAT) can be especially useful.6 The PhAT partitions the determinants of drug action into a series of multilevel connected questions, progressing from target molecule to clinical response. Measurements at each of these levels permit a more holistic understanding of the drug's performance and provide context both for interpretation of biomarker readout and for broader use in dose selection. The emphasis upon interconnectivity between drug and effect enables identification of a biologically effective dose; this is in contrast to the more common selection of maximally tolerated dose that in turn focuses only on one aspect of the PhAT (i.e., tolerability). Accordingly, the PhAT naturally lends itself to defense of biologically effective dose as an alternative to dose selection based upon maximally tolerated dose. Figure 2 provides an example of how we can incorporate this approach into early development clinical designs. Examples of studies using biologically effective dose as a primary end point include trials with agents such as PARP inhibitors and antiangiogenic agents.7,8


Translation of anticancer efficacy from nonclinical models to the clinic.

Stroh M, Duda DG, Takimoto CH, Yamazaki S, Vicini P - CPT Pharmacometrics Syst Pharmacol (2014)

Translational phase I study with biomarker-defined end points. Phase I oncology studies classically treat advanced cancer patients in cohorts of three at progressively increasing starting dose levels until drug-related toxicities are observed. When the incidence and severity of these toxicities exceed levels predefined as dose limiting in the study protocol, dose escalation is halted. Additional patients are then treated at a lower dose to determine the maximum tolerated dose level. In a modern translational phase I study design, these classical phase I end points are augmented by pharmacodynamic biomarker monitoring to define the minimum exposures associated with biological activity. At the end of dose escalation, patient expansion cohorts are often added to collect additional biomarker, safety, and pharmacokinetic data. Thus, these early clinical studies mimic the comprehensive preclinical studies used to define pharmacologically active drug exposures. Modeling and simulation can be used at every step along the sequence to integrate exposure, biomarker, and other data collected during the trials. BED, biologically effective dose; DLT, dose-limiting toxicity; MTD, maximum tolerated dose.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4150926&req=5

fig2: Translational phase I study with biomarker-defined end points. Phase I oncology studies classically treat advanced cancer patients in cohorts of three at progressively increasing starting dose levels until drug-related toxicities are observed. When the incidence and severity of these toxicities exceed levels predefined as dose limiting in the study protocol, dose escalation is halted. Additional patients are then treated at a lower dose to determine the maximum tolerated dose level. In a modern translational phase I study design, these classical phase I end points are augmented by pharmacodynamic biomarker monitoring to define the minimum exposures associated with biological activity. At the end of dose escalation, patient expansion cohorts are often added to collect additional biomarker, safety, and pharmacokinetic data. Thus, these early clinical studies mimic the comprehensive preclinical studies used to define pharmacologically active drug exposures. Modeling and simulation can be used at every step along the sequence to integrate exposure, biomarker, and other data collected during the trials. BED, biologically effective dose; DLT, dose-limiting toxicity; MTD, maximum tolerated dose.
Mentions: To increase the impact of biomarkers in oncology, it is important to have a robust framework for biomarker implementation into clinical development. The pharmacological audit trail (PhAT) can be especially useful.6 The PhAT partitions the determinants of drug action into a series of multilevel connected questions, progressing from target molecule to clinical response. Measurements at each of these levels permit a more holistic understanding of the drug's performance and provide context both for interpretation of biomarker readout and for broader use in dose selection. The emphasis upon interconnectivity between drug and effect enables identification of a biologically effective dose; this is in contrast to the more common selection of maximally tolerated dose that in turn focuses only on one aspect of the PhAT (i.e., tolerability). Accordingly, the PhAT naturally lends itself to defense of biologically effective dose as an alternative to dose selection based upon maximally tolerated dose. Figure 2 provides an example of how we can incorporate this approach into early development clinical designs. Examples of studies using biologically effective dose as a primary end point include trials with agents such as PARP inhibitors and antiangiogenic agents.7,8

Bottom Line: Mouse cancer models have provided critical insights into tumor biology; however, clinical translation of these findings has been challenging.This perspective posits that factors impacting on successful translation start with limitations in capturing human cancer pathophysiology and end with challenges in generating robust translatable preclinical end points.A comprehensive approach that considers clinically relevant mouse models with both an integrated biomarker strategy and a complementary modeling and simulation effort will strengthen the current oncology drug development paradigm.

View Article: PubMed Central - PubMed

Affiliation: Clinical Pharmacology, Genentech, South San Francisco, California, USA.

ABSTRACT
Mouse cancer models have provided critical insights into tumor biology; however, clinical translation of these findings has been challenging. This perspective posits that factors impacting on successful translation start with limitations in capturing human cancer pathophysiology and end with challenges in generating robust translatable preclinical end points. A comprehensive approach that considers clinically relevant mouse models with both an integrated biomarker strategy and a complementary modeling and simulation effort will strengthen the current oncology drug development paradigm.

No MeSH data available.


Related in: MedlinePlus