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Gunnar Cedersund

Project: Knowledge-driven drug development without animal experiments

In the last few years, mathematical modelling has displayed an unprecedented impact on drug development. For instance, recent specific approvals, and even more recent general guidelines, imply that computer simulations now can be used for regulatory approvals.

Since model simulations are cheaper and faster, such approvals often end the use of test animals for that application. We have modified such an approved type 1 diabetes model to also describe type 2 diabetes, a much more widespread and rapidly growing disease. Our award-winning model has been developed through numerous experimental/modelling iterations, and is already at use in several major pharmaceutical companies. However, this usage is still mostly done in traditional drug development pipelines, involving a series of cell and animal systems, which often display highly different outcomes.

To allow us to move to a radically new, knowledge-driven, more efficient, and increasingly human-centered pipeline, I will use uniquely informative data to do the four most important additions still needed in the model:

  1. storage and release of fatty acids

  2. specific drug-targets in heart and adipose tissue

  3. multi-level and long-term translations

  4. mapping from other animal-free systems

For these ground-breaking developments, the Swedish Fund for Research without Animal Experiments awarded me the first edition of their award – “Nytänkaren”. I am also a member of the steering group for the new government-initiated National Centre for 3R, and I am there active in more general promoting and structural changes on replacement, which goes beyond my own research, e.g. creating a national replacement network. With this grant, I could demonstrate in real ongoing drug development projects, done together with AstraZeneca, how our new knowledge-driven and increasingly animal-free drug development pipeline can work in a way that is economically beneficial for them, and which also helps to save both human and animal lives.

Elin Nyman

Project: Computer models within inflammation that reduce the need of animal experiments

The process of inflammation is important to understand since it is a key component in many common diseases: cancer, cardiovascular diseases, and infectious diseases such as covid-19 to mention a few. Even though substantial efforts have been made, there is a lack of a mechanistic understanding of both shared hallmarks of inflammatory processes, and mechanistic differences of importance for common diseases.

To study mechanisms, computer models has shown potential since they allow for quantitative hypothesis testing of proposed mechanisms. Developed models can be simulated to predict the outcome for new experiments and therefore used in knowledge-based experimental design. Such simulations can be extended to the scale of a whole population, where individual differences are included and therefore can be used to evaluate the effects of new drugs for different groups of individuals. Computer models can therefore bridge between detailed in vitro data and clinical observations – without the use of animal experiments.

In a collaboration between researchers at Örebro University, Linköping University, and AstraZeneca, the aim is to set up such a knowledge driven workflow to study the process of inflammation. We aim to extract and build functional general models of the process of inflammation, i.e. models that would be shared among both different organs and tissues and potentially also shared between different diseases. These general models can then be specialized in different ways to answer different clinically relevant questions about inflammation.

In summary, this project will use computer models together with human-derived in vitro and clinical data from the inflammatory process. The models will serve as a basis for a knowledge driven workflow, where mechanistic knowledge can be connected to clinical outcome, and where the use of animal experiments become superfluous.