Lake Como School, Year 2016

Course on

“Quantitative translational approaches
in oncology drug development”

September 12-16, 2016

In the last years, a rationalization has been attempted to facilitate the smart development of new oncology drugs. For instance, the adoption of the pharmacological audit trail (Workman Mol Cancer Ther 2003) is theorizing that the development can be done via a sequence of questions: (i) Is the drug absorbed in sufficient quantity? (ii) Is the drug remaining in the systemic circulation for the time required to interact with the target? (iii) Is the extent of the target engagement enough to elicit the downstream pharmacological effects? (iv) Are the downstream effects sufficient to allow for a tumor response or a reduction of tumor burden? (v) Is the reduction of tumor burden sufficient to give rise to a significant improvement in the clinically relevant survival endpoint? This theorization is an example of the adoption of a translational approach. An even more useful approach would be to substitute the qualitative terms (sufficient, enough, etc.) with quantitative, model-based attributes and, possibly, to extend the problem to the undesired (adverse) effects. Mechanistic and semi-mechanistic pharmacokinetic (PK) and pharmacokinetic-pharmacodynamic (PK-PD) models, dissecting the system-related parameters from the drug-related ones are the best suited to allow the translation across the different systems. In this school, the various translational aspects mentioned below will be considered in the light of existing modelistic approaches, applied to practical examples: 1- in vitro-in vivo (e.g., Del Bene et al 2009 Cancer Chemother Pharmacol 2009); 2- in vivo preclinical-target modulation (Sardu et al, J Pharmacokin Pharmacodyn 2015); 3- clinical target modulation vs. surrogate clinical endpoint, e.g. response rate, tumor dimension (in this respect, cancer genomics is of paramount importance in the translation, Ramaswamy N Engl J Med 2004); 4- surrogate clinical endpoint vs. regulatory endpoint (Xu et al AACR-GU 2014, Xu et al Clinical Cancer Res 2015; Claret et al JCO 2009; Wang et al CPT 2009), 5- a different approach may be required by the safety/toxicity aspects emerging from off- target interactions, as only on-target effects (exaggerated pharmacological effects) can be treated in a target-mediated mechanistic manner.

During the discussion other, potentially useful approaches (eg, data mining and other multivariate approaches; real data evidence) will be also introduced and evaluated for this purpose.

Course Language: English

Course Directors:

Prof. G. De Nicolao (University of Pavia)

Prof. C. Kloft (Freie Universität Berlin)

Dr. I. Poggesi (Janssen CILAG, Belgium)

Prof. P. Magni (University of Pavia)

Prof. I. Troconiz (University of Navarra)

(to be completed)

Prof. G. De Nicolao (Univ. of Pavia, Italy)

Prof. C. Kloft (Freie Universität Berlin)

Prof. P.Magni (Univ. of Pavia, Italy)

Poggesi (Janssen CILAG, Belgium)

Rocchetti (Italy)

Prof. I. Troconiz (University of Navarra)