(1) Comprehensive training and knowledge transfer opportunities for ESRs have been successfully provided according to the project implementation plan and consist of the following (i) two training schools with a combination of courses, workshops, technical presentations, webinars and industrial site tours are offered by the network, and by (ii) secondments of ESRs. The training events implemented so far cover topics like multi-scale mathematical modelling, bioprocesses engineering, on-line measurements, data analysis, engineering thermodynamics, optimization, PhD project management, presentation skills, scientific writing or visit of the industrial biotech-production site. The secondments include both cross-sectorial (university-industry partnership) and inter-sectorial (secondment between two academic beneficiaries).
(2) Integration and exploitation of synergies among ModLife partners have been successfully established through intensive cooperation thanks to training and research collaboration through secondments of ESRs. This cooperation consist of the following research themes: (i) model-based optimisation of bioprocesses (IMPERIAL-RWTH), (ii) experimental characterization of pharmaceutical product formulations (UCBL-JANSSEN), (iii) model-based optimisation and design of oleo-chemical processes (ALAVAL-DTU), (iv) advanced optimization and monitoring of fermentation and pharmaceutical processes (USTRATH-DTU). Moreover, several joint scientific papers have been published, another publications are under preparation.
(3) Development of models and model-based optimization and control technologies and application for life sciences products and processes have been progressed excellently according to the project plan and that represent core activities of the ModLife network. In addition to the 3 model-based research themes mentioned in (2), further theoretical activities include for instance: modelling of creaming of emulsified products, thermodynamic modelling of active species partitioning in complex product formulations, development of methods for global Bayesian multi-objective optimisation and for dynamic optimisation with guaranteed satisfaction of path constraints, hybrid data-driven approach to prediction of environmental properties.
