Gaps and paths forward in cancer pharmacology and translational research

Area of Science:

• Clinical pharmacology and drug development
• Preclinical oncology research
• Pharmacokinetic-pharmacodynamic (PK-PD) modeling

Background:

• Rising drug development costs necessitate improved preclinical efficacy evaluation to minimize false positives.
• The "valley of death" highlights the significant gap between preclinical research and clinical translation, particularly for oncology chemotherapies.
• Despite advances, certain cancers and patient groups still face poor prognoses, underscoring the need for more effective drug candidates.

Purpose of the Study:

• To propose a reframed approach to drug efficacy evaluation in preclinical models.
• To emphasize the role of pharmacokinetic-pharmacodynamic (PK-PD) modeling in enhancing drug translation.
• To advocate for viewing drug development as a dynamic, iterative process rather than a linear one.

Main Methods:

• Review of traditional pharmacodynamic (PD) and pharmacokinetic (PK) evaluation methods.
• Discussion of pharmacokinetic-pharmacodynamic (PK-PD) models applied to tumor growth inhibition.
• Analysis of strategies to bridge the gap between bench research and clinical application.

Main Results:

• Traditional methods may not fully capture drug efficacy, contributing to high failure rates.
• PK-PD modeling provides a more accurate assessment of drug efficacy in cellular models.
• A dynamic, continually refined approach to drug development can yield more efficacious candidates.

Conclusions:

• Rethinking preclinical drug efficacy assessment is essential to reduce the high failure rate of oncology drugs.
• Pharmacokinetic-pharmacodynamic modeling is instrumental for accurate evaluation of drug efficacy and clinical translation potential.
• Adopting a dynamic perspective in drug development is key to improving therapeutic outcomes and aiding underserved patient populations.