Beaucoup d’arguments militent en faveur du in silico en complément et en renforcement mais non en remplacement des recherches in vitro et in vivo.
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François-Henri BOISSEL est invité lors du Totem HealthTech de BpifranceHub aux côtés de @therapixel et du Dr Jean Sébastien Hulot
It is now important for the European Medicines Agency to recognize and integrate into its regulatory processes these new methods of in silico simulation and prediction.
François-Henri BOISSEL introducing NOVA at Labiotech Refresh 2017, Berlin.
Specify the optimal duration which helps to obtain the target effect, the dose that has to be used to maximize this effect. In other words, it’s to help us do the operations that are done today by a rather theoretical approach.
With the help of in silico models we can integrate the right patients in clinical trials and reduce the size of these trials.
The Effect Model enables us -according to the indicators that you have, either clinical, genetic, imaging or biomarkers, – to go down to the patient and to go much further in an individual prescription.
François-Henri BOISSEL introducing NOVA at 17th Biotech in Europe Forum – Sachs Associates
The human body contains 10 000 potential targets. that means that we are just at the begining and there is a huge of fields to be explored with the right tools to investigate in a capital efficient maner.
Our work is to really get to the bottom of these mechanisms. To identify step-by-step the sequences that lead to the disease and to the treatment that can be given.
In itself, the virtual population, irrespective of its important role in the use of models, has other qualities. The first quality is to be able to collect data that are today stored in various dispersed databases…
Let’s think the human body as a machine and start to look at it as engineers look at machines. In a normal state and at time of dysfunction.
Anything that will contribute upstream to better mechanistic knowledge and to improved selection of responder patients will be welcome. I think that there is a whole avenue opening up for in silico modeling in oncology today.
In silico is truly a new method of medical research investigation. Digital technology is used to be able to reduce as much as possible the experiments to be performed: animal testing and of course trials in patients.
There was a fundamental stage that we weren’t expecting, that is the integration by the FDA then by the EMA of the potential importance of in silico in the clinical research of new therapies.
The result demonstrated that with the molecule we were using, the way that finally proved to be promising, it was not effective, even deleterious. This result was important as it allowed this molecule to not be used.
Clearly the model enables us to learn more about the mechanism of action of the therapy and this is unprecedented compared with «small aspects» that we were concerned about through in vitro and in vivo trials.
We started working with Nova in 2011. At that time, Nova was one of the first companies to structure a service offer to address a need of tomorrow: the integration of data, this explosion of data for personalized medicine.
In this European project called SysClad, Novadiscovery was instructed to explore in-silico the
efficacy of a partial blocking of the signaling pathway mTor for the prevention of lung transplant rejection.
In reality, we face two problems when we develop our models. The first one is that we are in the limit of knowledge.