Doctor: Alexandre Vivot
Title: Personalized medicine in clinical oncology. Transferring genetic biomarker discoveries to clinical use
Supervisor: Raphaël Porcher
Doctoral school: ED 393 Epidemiology and Biomedical Information Sciences, Université Paris Cité
Date of thesis defense: 13/10/2017
Jury: Simone Mathoulin-Pélissier, Xavier Paoletti, Julia Bonastre, Pierre Bougnères, Pierre Laurent-Puig, Raphaël Porcher
Summary:
Personalized medicine represents great expectations and hopes in oncology. This approach aims to adapt treatments to the personal characteristics of the patient, mainly genetic biomarkers.
In our first work, we analyzed all the FDA-approved drugs with a pharmacoge- netic biomarker in their label and showed (1) that oncology represented one-third of the drugs with a biomarker in their label and (2) a significant portion of onco- logy drugs mentioned the biomarker to require a biomarker test, contrary to other therapeutic areas.
Our second work analyzed the clinical trials submitted to the FDA for the ap- proval of targeted therapies for which there was a indication restricted to biomarker- positive patients. We conclude that in two-thirds of the cases, the use of the bio- marker to select the patients to be treated was based on the results of the clinical trials restricted to the biomarker-positive patients. Thus, in these cases, there was no clinical evidence to conclude to a treatment-by-biomarker interaction.
For our third work, we mapped all the trials recorded on the US ClinicalTrials.gov registry for anti-cancer drugs with a biomarker labeling. We found very important variations between drugs in the use of enriched trials and in testing of the drug in several indications or with several predictive biomarkers.
In our last work, we examined the benefit of anti-cancer drugs in a context of very significant price increases and the recent publication of two scales by the European and American oncology societies (ESMO and ASCO). We analyzed the benefit of all anti-cancer drugs approved between 2000 and 2015 for the treatment of a solid tumor. We have shown (1) the low value of recent anti-cancer drugs, (2) the lack of relationship between the price and the value of these drugs, and (3) the lack of difference of benefice between personalized and “classical” medicines.
In conclusion, the presence of predictive biomarkers in the label of drugs — often cited as a criterion of success of personalized medicine — is, at least for now, being restricted in large part to oncology. The level of evidence for clinical utility is often unknown because studies are restricted to the subgroup of biomarker-positive patients from the initial stages of the drug development. Finally, only one third of the anti-cancer drugs approved by the FDA between 2000 and 2015 have meaningful clinical benefit and there is no difference in clinical benefit between drugs with and without biomarkers and no relation between the price and the benefit of anti-cancer drugs.
