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How to fund your research into alternatives for animal models in research and drug development

February 23 2016

The drug development process is widely recognised to be cumbersome and costly. From all compounds found in the discovery phase only 1% will eventually enter the market. Moreover, the whole process (from discovery to market introduction) takes on average 12 years and requires an average investment of around €2,3M. The low success rates have - amongst others - been correlated to the use of animal models in the pre-clinical phase. Because these models are insufficiently predictive for the human situation, promising pre-clinical candidates tend to fail in the clinical phase. Here we present the top 3 opportunities to fund your research into developing alternatives for animal models in research and drug development.

To date, several alternatives to animal models exist, we will briefly discuss three of them here. Clearly, each of these approaches have their own drawbacks and limitations. However, these will not be discussed here.

  1. Human induced pluripotent stem cell (hiPSC) technology. hiPSC-derived cells are highly suitable for drug efficacy testing as they are patient-derived and can thus be used to create "disease-in-a-dish" systems. Examples are using co-cultures or “organ-on-a-chip” models containing various cell types from a patient, in order to investigate more complex physiological processes and predict drug effects for specific patients or patient groups.
  2. Organoids. These three-dimensional organ-buds grown in vitro recapitulate not only the shape/build but also the rudiments of function of their in vivo counterparts. Organoids have the potential to move from laboratory proof-of-concepts to relevant tools in the drug discovery pipeline. Indeed, organoids could finally provide a key missing link between compound screening and clinical trials, and could serve as models for testing drug efficacy in target organs, for toxicity in liver models or for bioavailability through intestinal system models.
  3. Big data based in sillico testing. Predictive modelling of biological processes and drugs becomes significantly more sophisticated and widespread. By leveraging the diversity of available molecular and clinical data, predictive modelling could help to identify new potential-candidate molecules with a high probability of being successfully developed into drugs that act on biological targets safely and effectively.

We have identified the following funding opportunities for research into these three directions. Please follow the link to our funding database for more details.

  1. SMEInst-05-2016-2017. Supporting innovative SMEs in the healthcare biotechnology sector. Project budget; 0.5-2.5M. Duration: max 24 months. Consortium size: no partners required. Next deadline: 14-04-2016.
  2. Eurostars. Project budget: dependents on the type of organisation and country (in NL max €500k). Duration: max 36 months. Consortium size: one or more partners required. Next deadline: 15-09-2016.
  3. h2020-SC1-PM-18-2017. Big Data supporting Public Health policies. Project budget: €6M. Duration: no maximum. Consortium size: one or more partners required. Next deadline:16-02-2016.
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Contact

Andree Schram, PhD
+31 (0)30 7370779