The BioSim Network contributes towards the objectives of the Life Sciences and Health Priority of the 6th European Framework Programme through the development of a dynamic, systems-oriented and more quantitative understanding of a variety of biomedical and pathological processes of relevance to the treatment of chronic progressive diseases such as diabetes, hypertension, cancer, mental disorders, and different forms of tremor.
A main objective for the BioSim Network is to provide the tools for a more rational information handling in the drug development process in order to stimulate industrial activity and ensure the availability of a broad range of safe and effective drugs.
With this objective we shall:
- develop close collaborations in the area of biosimulation between large pharmaceutical industries, small and medium-sized enterprises, regulatory agencies, and academic research groups across existing national and institutional borders.
- integrate biomedical research activities from bioinformatics and functional genomics over cellular metabolic and electrophysiological processes, neurology and endocrinology to immunology and pharmacology.
- combine the classical pharmacokinetic and pharmacodynamic methods with mechanism-based modelling, biosimulation, complex systems theory and other approaches from systems biology and modern information technology.
- establish well-structured training and education programmes in biosimulation and create a European forum for research in systems biology and mechanism-based modelling.
- maintain an open communication with the public in order to clarify both the potential and the difficulties associated with the use of biological simulation models.
The BioSim Network involves 26 academic research groups from 11 different European countries, 9 small and medium sized enterprises, Novo Nordisk A/S, and the regulatory agencies in Denmark, Holland, Spain and Sweden.
An effective use of simulation models in the pharmaceutical industry is obviously conditioned by the acceptance of this approach by the regulatory authorities. The BioSim Network aims at serving as a catalyst for this process. The participating agencies will define research areas and drug development processes where the use of simulation models can provide important answers, take part in the assessment of the obtained results, and contribute through the formulation of guidelines for the industry with respect to the use of simulation models. We'll try to extend the collaboration to other European agencies and to establish a closer contact to the US Food and Drug Administration on these problems.
The small and medium-sized enterprises represent a broad spectrum of different interests and expertises ranging from the discovery of drug candidates over clinical and pre-clinical trials of new drugs to the development of statistical and mechanism-based simulation models and of new simulation software.
Our objectives in relation to these enterprises are to stimulate their growth and help them improve their techniques and products by providing closer collaborations with academic research groups and by testing, using and disseminating information about these techniques and products. We are obviously interested in extending the collaboration to other small and medium-sized enterprises with interests in biosimulation, but the Network cannot provide financial contributions to such collaboration.
Novo Nordisk A/S is the only large industrial partner in the BioSim Network. Several other large pharmaceutical industries have decided to avoid the legal and managerial complexities associated with being a participant in a Network of Excellence, but to collaborate directly with individual BioSim partners, either academic research groups or small and medium-sized enterprises. Main objectives of these collaborations are to strengthen industry-university relations, to contribute towards the solution of concrete problems of significance for the industry, and to train a sufficient number of highly qualified PhD's and post docs. The BioSim Network is strongly interested in an extension of this type of collaboration.
The Network will also collaborate with stakeholders such as hospitals and patient organisations. This type of collaboration may, for instance, lead to models of treatment procedures and to life-cycle models that can illustrate the effects of various long term medication schedules.
The underlying rationale for the above efforts is the need for improvements in the medical treatment of a large number of different diseases. Patients may rightfully expect new and effective drugs to become available as a result of the significant breakthroughs that have occurred in genomics and other areas of biomedical science. However, in spite of steadily increasing R&D expenditures in the pharmaceutical industry the number of new important drugs seems to decrease, and rising drug prices is becoming a matter of concern in many countries.
The high development costs and long lead times of new drugs are associated with the large number of clinical and other trials that a drug must undergo to document its function and show that adverse side effects do not occur. The use of professional simulation models can simplify the drug development process enormously by exploiting the information available in each individual trial much more effectively. This approach is used in many other industries where computer simulation allows new concepts and designs to be tested and optimised long before the first example of the product is manufactured. The simulation approach is strongly recommended by the US Food and Drug Administration, both because of its potential for reducing the development costs, and because of the associated reduction in the use of laboratory animals and test persons. Through the establishment of "Virtual Populations" variations in the efficacy and possible side effects of a new drug can be predicted on a gender and age specific basis and /or for patients with specific gene modifications.
The development of a more quantitative description of biomedical systems as the fundament for a disease-driven drug development process requires an unusually broad range of insights and skills in the biological as well as in the technical and mathematical realms. As described elsewhere, the BioSim Network commands outstanding expertises in bioinformatics, biochemistry, cellular biology and electrophysiology, intercellular communication, physiology, endocrinology, neurology, nephrology, pharmacology, pharmacokinetics, systems biology, complex systems theory, and in silico modelling and simulation techniques.
Formulation of biological simulation models also requires close collaboration between experimental and theoretical partners. Modelling is the translation of scientific hypotheses into a formal mathematical framework. In order to improve, the models must continuously be confronted with new experimental data, and precisely this process of generating new hypotheses and formulating critical experiments represents the most effective way of expanding our knowledge about drug function. A large number of experiments are performed in connection with the testing of drugs. However, these experiments will typically be focused rather narrowly on the action of a particular drug. There is a need to validate and consolidate the models through a broader range of experiments. Hence, the BioSim Network involves a number of experimental groups, all of broad international recognition.
Contrary to the conventional assumption of homeostasis, many biological systems have unstable equilibrium points and operate in a pulsatile or oscillatory mode. This is the case, for instance, for the release of pituitary hormones that typically occurs in more or less regular two-hour intervals. In several cases it has been reported that the cellular response to an oscillatory signal is stronger than the response to a constant signal of the same average magnitude, suggesting that the oscillatory dynamics plays a role in the regulatory effect of the hormone. Rhythmic and pulsatile signals are also encountered in intracellular processes as well as in the communication between cells. Many nerve cells are excitable and respond in an unusual fashion to small external stimuli. Other cells display complicated patterns of spikes and bursts.
Phenomena of this type are presently at the centre of interest for much research in the field of "Complex Systems". The phenomena are characterised by abrupt changes in behaviour as a parameter is changed, by the co-existence of several possible behaviours for the same set of parameters, by unusual reaction patterns in the presence of noise, and by the production of randomly locking time series even in the absence of noise. The appearance of complex systems theory for the first time seems to provide us with the mathematical tools and concepts required for a more detailed description of the behaviour of many biological control systems. Several partners in the BioSim Network have played a leading role in the formulation of complex systems theory and, in particular, in its application to biological and biomedical systems.
With its competence in genomics and bioinformatics, the BioSim Network can also contribute to the development of a methodology for the prediction of druglikelihood. Neural networks can be used to pre-screen drug candidates and to predict absorption rates, binding affinities, metabolic rate constants, etc., from knowledge about previously examined compounds. This allows the subsequent biochemical screening to be performed on a reduced set of candidates that have a higher likelihood of possessing the desired functionality. |