Biomarker-Driven Early Clinical Trials in Oncology

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Abstract
Early clinical trials represent a crucial bridge between preclinical drug discovery and the especially resource-intense randomized phase III trial-the definitive regulatory hurdle for drug approval. High attrition rates and rising costs, when coupled with the extraordinary opportunities opened up by cancer genomics and the promise of personalized medicine call for new approaches in the conduct and design of phase I/II trials. The key challenge lies in increasing the odds for successful and efficient transition of a compound through the drug development pipeline. The incorporation of scientifically and analytically validated biomarkers into rationally designed hypothesis-testing clinical trials offers a promising way forward to achieving this objective. In this article, we provide an overview of biomarkers in early clinical trials, including examples where they have been particularly successful, and the caveats and pitfalls associated with indiscriminate application. We describe the use of pharmacodynamic end points to demonstrate the proof of modulation of target, pathway, and biologic effect, as well as predictive biomarkers for patient selection and trial enrichment. Establishing the pharmacologic audit trail provides a means to assess and manage risk in a drug development program and thus increases the rationality of the decision-making process. Accurate preclinical models are important for pharmacokinetic-pharmacodynamic-efficacy modeling and biomarker validation. The degree of scientific and analytical validation should ensure that biomarkers are fit-for purpose, according to the stage of development and the impact on the trial; specifically they are either exploratory or used to make decisions within the trial. To be maximally useful at an early stage, these must be in place before the commencement of phase I trials. Validation and qualification of biomarkers then continues through clinical development. We highlight the impact of modern technology platforms, such as genomics, proteomics, circulating tumor cells, and minimally invasive functional and molecular imaging, with respect to their potential role in improving the success rate and speed of drug development and in interrogating the consequences of therapeutic intervention and providing a unique insight into human disease biology. With these technologies already having an impact in the clinic today, we predict that further future advances will come from the application of network analysis to clinical trials, leading to individualized systems-based medicine for cancer.