Please can you give a brief introduction to biosimulation?
The need for biosimulation is primarily to do with the very high attrition rate in drug development and especially in the development of drugs for the central nervous system.
Many attempts to develop the drugs have failed and we believe that this may be due to the complexity of the biological systems involved, especially those of the brain, which are not necessarily always taken into account because it’s very difficult to do that.
The second reason is because many of the diseases are what we call multifactorial: they have many different underlying mechanisms and if you try to use a drug which has only a single mechanism, it will not succeed and will not be effective enough to treat patients.
This complex and multi-factorial nature of the diseases means another approach is needed: one that is conceptual and technical. The conceptual approach is the so-called Systems Biology approach; the corollary is the associated technology involving modelling and simulation and is what we call biosimulation.
However, I feel I must make a distinction here because people often confuse the modelling I am talking about with the modelling of chemical structures, which is known of as computer-assisted molecular modelling. This is not what Rhenovia is doing.
What we are modelling are the biological mechanisms which contribute to the signal conduction and dialogue between nerves cells in the brain, with a view to reproducing the pathological situation in patients.
The technique reproduces on the computer experiments which are done on the bench or using animals, to provide a model that simulates reality. It simulates the nerve transmission which may be interrupted or over excited in pathological conditions.
How can biosimulation be used to discover new medications?
This is a very interesting point because the basic way to search for a new medication is using what is known of as the ‘target approach’. This refers to when there is a hypothesis that a compound acts on a specific target, for example, which could be, say, a receptor, a transporter or an enzyme in the brain cells.
However, the issue with the complexity I mentioned is that you never know if the compound has hit a single target or several, and increasing in the levels of complexity, from the cellular level to networks and brain circuits, you are not sure anymore whether the effect is definitely there or whether the effect is amplified.
Where biosimulation helps in drug discovery is in the fact that you can really see when you act on a specific target what the consequence of an action is. You can see what the impact is at the cellular and higher levels. So, you can identify new targets, you can eventually gain a better understanding of the mechanism of older targets, and even identify possible new mechanisms of older targets.
Also, in terms of the multifactorial aspect, we believe the multifactorial nature of diseases means you have to act at several places at the same time. In other words, new medications will be associations or combinations of different types of drugs or agents which are acting at several places at once.
So, there are quite a number of really new, potential applications for drug discovery that will hopefully increase their success rate.
Rhenovia have recently developed a computer simulator for the biological mechanisms of epilepsy. Please can you explain how the simulator was developed and what challenges had to be overcome?
Yes, the point here, in the context of epileptic seizures, is that you have hyper-excitability. So, the nerve cells in the brain are over excited, they are firing at a very high frequency which causes the symptoms of epilepsy such as convulsions.
What we did in this study was to generate hyper-excitability by increasing the activity of the neurons so that we could research the pathological conditions of epileptic seizures and identify biological mechanisms at the cellular level which contribute to this hyper-excitability. Of course, the computer has a number of applications that can be used once you have achieved this over excitability.
We faced quite a number of challenges when developing such a simulator because you have to integrate so many biological mechanisms to be sure what is really contributing to the hyper excitability.
So, to answer your question, the challenge was generating a realistic reproduction of the pathological situation in patients.
We started by using recordings that had been made while patients were undergoing biopsies, where you can make electrical recordings and see the hyper-excitability.
We were able to reproduce it in the same direction. There are brain preparations that can be used and ways to generate the electrical pattern formations seen in epilepsy.
For example, by lowering the concentration of magnesium or administering different types of drugs, you can generate this hyper-excitability. Really the challenge was to be able to do this… taking what is normally done during experiments on patients and doing the same thing using a computer…. and, yes, we succeeded.
Has the simulator been validated by laboratory experiments?
For this program, the so called RHENEPI program, we brought together a certain number of experts, both clinicians as well as experimentalists. They carried out in vitro experiments using the brain preparations I mentioned before to simulate and record the hyper-excitability and also generated epileptic-type seizures in mice (in vivo) and recorded the appearance of hyper-excitability in mice brains. For this program, there was a constant interaction between the experimentalists, the clinicians, and Rhenovia as the modeller.
The validation came from the fact that we were able to reproduce the experimental situation, generate a certain number of hypotheses, make a certain number of predictions based on the computer model and then have the experimentalists confirm in their experiments what had occurred in the simulation.
What are the key applications of the simulator?
Rhenovia has many different simulators, but this particular simulator deals with epileptic seizures, hyper-excitability, and the different types of effect. The main application is in dealing with anti-epileptic drugs, with the first focus being on the possibility of identifying new generation anti-epileptic drugs by seeing what mechanisms are involved in removing this form of epileptic pattern.
Hopefully it will lead to more anti-epileptic drugs, a better understanding of the existing anti-epileptic drugs, and improvement of these older anti-epileptic drugs.
Another aspect of this program was that if you can generate convulsions on the computer, you can also assess the generation of this hyper-excitability across any type of drugs.
One of the biggest challenges in the pharma industry is that many of the compounds which are tested in the discovery stage, carry a risk of producing convulsant effects. We wonder if our technology can allow us to anticipate this risk - that’s exactly what we want to do with the simulator.
For example, it is known that penicillin was certainly the first antibiotic discovered, but it was also the first antibiotic to show proconvulsant effects.
If you can anticipate this right at the beginning or very early on in the drug discovery process, you can save a lot of time and a lot of money because you can guide the developers and say to them, “wait a minute, be careful, here you have risks.”
This applies to any kind of drug: those for the cardiovascular system, those used in oncology, for example. It also has interesting implications for other compounds such as pollutants, chemicals and environmental substances which may carry risks.
You could help the regulatory authorities, for example, when the chemical industry or agrochemical industry are making pesticides that carry a risk of proconvulsant effects… you can warn them, and say, “be careful, here you’re doing something which might be dangerous.”
What impact do you think the simulator will have on the future of epilepsy treatments?
We are entering a completely new world, so to speak, and definitely the most important objective of this program is to be able to generate new anti-epileptic drugs with better efficacy and fewer side effects.
There’s one thing which is extremely important to mention and that is the large proportion of epileptic patients who are resistant to treatment and, certainly for the time being, have no existing treatment. Also, there is quite a large proportion undergoing treatment now, who, after a while will become resistant to treatment.
So, there’s a real need to come up with better treatments and this is definitely, in my opinion, one of the most important applications.
Also, because the simulator will be able to measure or generate hyper-excitability or hypo-excitability, it will be very helpful in many different therapeutic indications in the central nervous system because I would say these two things are the underlying basis of almost all brain diseases.
Being able to use this tool to tweak the different biological mechanisms to correct the hyper- or the hypo- activity, will be very helpful for many, many different types of disease.
In addition, about the point I mentioned regarding treatment resistance, what doctors are doing is starting with one drug and then switching to another one or they add a second one or eventually they add a third one to improve the efficacy. This is very empirical and done on a trial and error rather than a rational basis.
First of all, you cannot generalize this approach and secondly it is associated with potential risks. Hopefully, our technology will be able to guide the clinicians to rationalize this kind of combination therapy approach and ensure that even if efficacy is not improved, it is at least not inducing side effects.
What are Rhenovia’s plans for the future?
The core business of Rhenovia is to provide studies for a certain number of stakeholders using these kinds of simulators. We have several different simulators which can be used for different diseases and applications and our plan now is to really diversify our markets in order to expand our service and partnership activities to the pharma companies.
Of course, we would aim our technology at pharma and biotech companies but also to other fields of interest. For example, one domain that we are active in is that of defence.
Coming back to the subject of epileptic seizures and hyper excitability, this is one aspect of what is called neurotoxicity and we know, for example, that one of the neurotoxic effects of the chemical weapons used recently in Syria is convulsions. So, the platform will enable us to identify more efficacious antidotes against these kinds of toxic agents.
Another area of interest is the agrochemical sector. We know that pesticides are inducing seizures, amongst other things, in people exposed to them such as the farmers working with them.
The plan in terms of developing simulators is to have as many of them as possible. We can use the same basic structure of our simulator across many different applications as it can be adjusted for each specific purpose and be customized for the specific needs of the clients.
How do you plan to fund this development?
I feel we’ve been lucky that within the framework of the French calls for projects, we have been able to make this simulator for epilepsy. Now, we have to expand all this, we have to consolidate the finances in order to spread our service and to execute contracts with all different types of clients. Therefore, we are in our second phase of fundraising.
We are looking for investors who are following Rhenovia, in order to make our financial structure much safer. The economic situation is difficult and of course we have to consolidate this to make sure that we can really expand and bring these new technologies to the market. The fund raising we’ve initiated in March 2013 aims to achieve 2.5 million Euros.
Where can readers find more information?
At our website: http://www.rhenovia.com
About Dr. Serge Bischoff
Serge Bischoff, PhD, President and CEO, co-founded in 2007 Rhenovia Pharma, a word leading biotech company in biosimulation providing services to optimize the drug discovery process of pharma and biotech companies.
After having spent 5 years at INSERM in Paris, where he completed his PhD thesis in neurobiology, Serge Bischoff moved to the big pharmaceutical industry.
He was a research scientist at Synthelabo-Sanofi in Bagneux for 5 years before spending 24 years at Ciba and Novartis in Basel, Switzerland, where he occupied managerial functions as Head of Drug Discovery Programs in psychiatric and neurodegenerative diseases.
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