Innovation idea of the proposal is to create a standalone personalized-medicine computational platform that use patient-specific tumour parameters to recommend nanomedicine-based drug delivery systems which would be the most optimal to treat specific patient. It will be done by using a computational platform that is under development in the ongoing FET Open project EVO-NANO. The core of PACE will be to develop IP in EVO-NANO in accordance to market and regulatory demands thus increasing both the technology readiness level (TRL) as well as the investment readiness level (IRL). The ultimate objective will be to position IP from EVO-NANO for market uptake through the completion of exhaustive commercial due diligence which will create the market strategy from gathered market research. The project will consist of several stages that are organized so that each step further funnels the research down to ever greater levels of focus. Stages are: 1- Ideation, IP / Business Model Preliminary Research and Positioning; 2 -Market Research, which is divided into two sub-stages: 2A – Macro Market Research and Analysis, and 2B – Application Research and Analysis; 3- Market Strategy; and 4- Exploitation. The impact of this proposal will be the creation of monetarily valuable IP and/or the foundation for the creation of a business that can create monetary value. Although the ongoing FET Open project EVO-NANO will have social impact toward treating cancer, PACE is aimed at gathering the necessary market information to position EVO-NANO for market uptake. In other words, these projects will increase the competiveness of European SMEs while contributing/supporting European industrial leadership in nano-personalized medicine technologies. The dissemination of PACE will go beyond simply broadcasting the IP and will be specifically aimed at targeting the audience decided upon in the market research stage.

The overall aim of the project is the upgrade of knowledge, skills and social capacity of UNSFA in the field of environmental sciences, with special focus on agrometeorology and related ecosystem sciences (such as plant physiology, crop management). The main tool for reaching that aim will be establishment of the AgMnet+ research network at UNSFA in collaboration with leading international research institutions BOKU and UNIFI. As a strategy to improve S&T capacities of UNSFA, AgMnet+ will introduce the concepts of small study groups (SSGs) of UNSFA, BOKU and UNIFI students and develop joint study teaching material in English and native languages. BOKU and UNIFI partners will implement goal-driven measurement and modelling training in the selected research fields for AgMnet+ members. Additionally, EU partners will organise expert training related to preparation of research project proposals for AgMnet+ researchers. Intensive exchange of short term scientific visits, guest lectures and students visits among partner institutions will contribute to improved eligibility of AgMnet+ members for participation on EU projects, increased number of papers in peer-review journals and increased citation. Finally, AgMnet+ will serve as a robust basis for the further sustainable development of the selected research fields at UNSFA, in Serbia and wider region of Western Balkan Countries. Strategic partnership with BOKU and UNIFI, initiated by this project will significantly enhance the research and innovations capacities of UNSFA and help to upgrade the knowledge and skills of both of its students and researchers. Additionally, it will reduce potential "crowding out" effect at BOKU and UNIFI and increase research and social capacity of all project participants.

Bio-hybrid machines (BHMs) combine living cell actuators with artificial materials in order to achieve greater autonomy, flexibility, and energy efficiency compared to standard robots. However, BHMs are developed in silos of individual research groups, making their development more of an art relying on individual knowledge, intuition, and skills than on standardized decision-making processes. To push the manufacturing of BHMs towards bio-intelligent paradigm and model-based engineering, we propose to develop a self-monitoring and self-controlling manufacturing pipeline of BHMs. To realize such a pipeline, we would need to (i) Develop a modeling and simulation framework that will streamline the processes of design, quoting, manufacturing, verification, and reporting, thus significantly reducing error-prone manual steps. Also, given that actuators in BHMs are living cells, which greatly expands the parameter space, we believe that the development of BHMs would greatly benefit from AI-guided modeling process to optimize search for the most efficient design; (ii) To experimentally test, optimize, and verify the platform by developing a proof-of-principle reconfigurable modular catheter BHM; (iii) To group all necessary manufacturing equipment into an integrated bio-intelligent manufacturing cell (BIMC) and demonstrate its adaptable operation. As a proof-of-principle, we will use BHM catheter as it is an innovative medical device that would be able to arrive into hard-to-reach regions of the human body and release drugs there.

EVO-NANO aims to create an integrated cross-disciplinary platform for the artificial evolution and assessment of nanoparticle-based drug delivery systems. Nanoparticles (NP) are increasingly being studied in cancer research for their ability to improve diagnosis accuracy and/or deliver tailored treatments directly to tumours. However, their effective biodistribution is still a major limitation. The challenge is to discover how to program collective behaviour of the trillions of NP interacting in a complex tumour environment. Finding effective NP designs that give rise to desired outcome will require a new class of evolutionary algorithms that can simultaneously 1) generate novel NP-based anti-cancer strategies, 2) search over a large space of solutions, and 3) adapt to a wide variety of scenarios. Our novel evolutionary approach will be integrated with molecular dynamics simulations, PhysiCell (http://physicell.mathcancer.org) and STEPS simulators that reproduces realistic NP motion and interactions within the tumour environment and with other NP. The most promising NP designs will then be synthesized and tested in vivo and in vitro on breast and colon cancer stem cells using mouse cancer xenografts and microfluidic testbeds featuring cancer microenvironments. To promote translation of the platform from early stage research into a commercialized product for patients, we will work with industrial partner ProChimia Surfaces, organize ‘Industry Open Days’ for potential investors and develop a translation strategy. EVO-NANO is a multidisciplinary project that will create an entirely novel NP design platform for new cancer treatments, capable of autonomously evolving both innovative and adaptive solutions. The proposed platform has the potential to be at the forefront of cancer nanomedicine by enabling much faster development and assessment of new cancer treatments, than is done today. The project will generate concrete tools for the predictive design of nanomedicines that could be applied in other clinical fields.