3^rd Antibodies and Bio Therapeutics Congress & B2B November 08-09, 2017 Las Vegas, Nevada, USA

Biomarkers Development

The development of cancer therapies is increasingly dependent on our understanding of tumor biology, and biomarkers—especially predictive biomarkers—are crucial tools in the field of personalized medicine and health economics, in particular, as they enable definition of the populations of patients who are most likely to benefit from targeted therapies. More-effective patient selection than is possible at present is mandatory to improve the success rate of new therapies, which are sometimes prohibitively expensive, and thereby increase their cost–utility; thus, delineating reliable predictive biomarkers is essential if we are to achieve this objective. One commonly used definition of a biomarker is a measurable indicator that is used to distinguish precisely, reproducibly and objectively either a normal biological state from a pathological state, or the response to a specific therapeutic intervention. In fact, biomarkers are used for numerous purposes: to predict survival (prognostic biomarkers); to assess drug safety and evaluate target engagement and the immediate consequence on biological processes (pharmacodynamics biomarkers), to identify patients who are more likely to benefit from a treatment (predictive biomarkers; more generally termed companion biomarkers when associated with a specific therapeutic agent); to predict outcome given the response to therapy (surrogate biomarkers); and to monitor disease progression or therapeutic efficacy (monitoring biomarkers). Identification and widespread use of biomarkers will help ensure that patients receive the best possible therapeutic strategies, thereby avoiding unnecessary treatments and associated toxicities, and eventually reducing total health costs.

Even though immunotherapeutic approaches are being studied in many cancer types, correlative studies have thus far been most extensively conducted in melanoma, providing valuable experience and making it a model system for identifying therapeutic biomarkers.

• Turning an Active Compound into a Personalized Medicine
• Evaluation of Biomarker Performance in the Real World
• Predicting Benefit to Therapy: Biomarkers and Molecular Profiles in Oncology Drug Development
• Identification of Fluid Biomarkers of Treatment
• Surrogate endpoints: utilising biomarkers in clinical trials

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