gms | German Medical Science

Rational drug development is nowadays guided by translational research bringing together preclinical data and available clinical data. The aim is to predict the biological effective concentration thus defining together with preclinical toxicology data the anticipated therapeutic window of a therapeutic option as well as identification of the population with the highest chance to benefit from the given treatment.

This translational workflow starts at the concept phase with a biological hypothesis supported by bioinformatic and knowledge management data packages compiling the current knowledge of the target, pathway(s) and relevant disease(s). In the sequence of the different research phases, critical experiments are performed in vitro and in vivo validating the initial hypothesis and delivering translatable evidence directing the clinical development strategy. This translational research approach is dependent on the availability of predictive models for the human setting as well on diagnostic, prognostic, pharmacodynamic and predictive biomarkers as the major tools. Availability of patient derived xenograft models, imaging modalities, and the recent developments biomarker field expedited not only this preclinical translational research process but improved also our understanding of the molecular basis of cancer dramatically.

This improved understanding of the biological characteristics of a drug together with the improved understanding of the molecular basis of cancer impacts the starting dose, the anticipated dose escalation steps, minimizes the number of patients at subtherapeutic doses during dose escalation and the selected exploratory trial design like patient (sub)population(s) for the expansion cohorts and clinical Proof of Concept.

In this presentation an use case is presented how Translational Research guides and accompanies the exploratory clinical trials by predicting the best suited patient subpoulations and delivering pharmacodynamic and predictive biomarkers to increase the probability of success in the transition from the research to the exploratory and ultimately to the pivotal development phase and vice versa.