Presentation of DDMoRe
Lutz Harnisch and Mats Karlsson
Model based-drug development (MBDD) is accepted as a vital approach in understanding patient risk/benefit and attrition. At the core of MBDD lies Modelling and Simulation (M&S), a technology providing the basis for informed, quantitative decision-making.
M&S facilitates the continuous integration of available information related to a drug or disease into constantly-evolving mathematical models capable of describing and predicting the behaviour of studied systems to address the questions researchers, regulators and public health care bodies face when bringing drugs to patients. The full adoption of MBDD is perturbed by a lack of common tools, languages and ontologies for M&S, which often leads to inefficient reuse of data and duplication of effort by academic, industrial and regulatory stakeholders.
The Drug Disease Model Resources (DDMoRe) consortium’s strategy will have standards as its core: a newly developed common definition language for data, models and workflows, along with an ontology-based standard for storage and transfer of models and associated metadata. A drug and disease model library will be developed as a public resource. Its flexibility and power will be showcased by the addition of “proof of concept” drug and disease models from key therapeutic areas such as diabetes and oncology.
An open-source interoperability framework will be the backbone for the integration of M&S applications into seamless standardized but flexible workflows. Initially, currently-used tools (e.g. NONMEM, WinBUGS, Matlab, R) will be integrated into the framework.
From the outset resources will also be dedicated to new application development which will be steered by identified gaps in the M&S software ecosystem. The DDMoRe project’s standards and tools – intended as the gold standard for future collaborative drug and disease M&S - will be supported by comprehensive training and will be made publicly accessible.
The DDMoRe consortium draws together its expert partners from across Europe including 5 SMEs and 9 academic partners who will be working together to accomplish the aims of the project with 10 EFPIA companies.