After 3 and a half years the Evo Nano project is drawing to a close, so we would like to reflect on the goals of the project and achievements of our researchers.
We are a consortium of seven partners (six research and one industry) with the shared goal of creating an entirely new nanoparticle design platform capable of autonomously evolving solutions for cancer treatment. Evo Nano brings together expertise in computer science, artificial evolution, modelling, microfluidics, and medicine.
The aim of the Evo Nano project was to create an integrated platform for the artificial evolution and validation of novel drug delivery systems for cancer treatment using nanoparticles (NP). The project had four main objectives:
- Developing open-ended evolutionary algorithms to explore a wide range of nanoparticle designs, considering the effect of different shapes, sizes, coatings and charges on their ability to reach and penetrate tumours.
- Implementing a computational platform for the autonomous generation of new nanoparticle-based strategies that specifically target cancer stem cells (CSC) of breast and colon origin.
- Streamlining synthesis of functionalised NPs suggested by our computational platform.
- Developing an integrated platform for the validation of the efficacy of artificially evolved NP designs, composed of in vitro micro-fluidics that mimic major physiological barriers for NP tumour delivery and in vivo pre-clinical tests.
Tumours are characterised by phenotypically and functionally different cancer cell populations. Intra-tumoural different cancer cell populations can confer resistance to therapy and promote metastatic spread. CSCs are scarce within a tumour (0.1-10%). CSCs have the ability to self-renewal/differentiate, initiate tumours, migrate and metastasize. Evo Nano researchers have been testing and validating new therapeutic strategies based on nanotechnology. Nanomedicine is the medical application of nanotechnology. Nanomedicines for cancer treatment can be used for targeted drug delivery to tumour cells, however, clinical translation of cancer nanomedicines remains low. The Evo Nano team have been tackling this by developing an artificial intelligence based platform for creating novel drug delivery systems. The human body is immensely complex, and testing all design parameters and strategies for different tumour scenarios would be at best extremely costly, if not outright impossible. Therefore, the goal was to harness the power of biological creative evolvability, apply it to nanomedicine and create lasting benefits for patients.
Tumour-on-a-chip system consists of a microfluidic device that simulates tumour cell tissue structure and functional units in-vitro. An important unresolved issue in nanomedicine research is to optimize nanoparticle pharmacokinetics with the aim of increasing their bio-availability inside the tumour to therapeutic levels. Evo Nano exclusively worked with gold NPs stabilized with thiolated ligands that enables: stability and solubility in water, controlled multi-functionalization, precise size control and monodispercity, multivalent targeting potential, non-toxicity and manufacture ability proven under GMP conditions. Our research partners at ProChimia provided mixed-charged NPs covered with certain ratios of positively and negatively charged ligands that can selectively target lysosomes in cancerous cells while exhibiting only marginal cytotoxicity towards normal cells i.e. NPs have selectively killed cancer cells in vitro without using any toxic anti-cancer agents. The team at ProChimia can provide services to any other researchers interested in nanoparticle functionalization.
Evo Nano researchers have been developing tumour-on-a-chip devices to replace the conventional cell culture models for ex-vivo models that are closer to reality, and help to reduce the need for animal studies during the development of cancer nanomedicines. Evo Nano researchers have been recreating the different tumour physiological micro-environments involved during the transport and distribution of nanoparticles into tumours which could lead to faster clinical translation of nanomedicines.
The interdisciplinary nature of the Evo Nano team allowed researchers to design and validate tumour-on-a-chip models together with in silico models to ensure that we have the appropriate parameters and contrasted relevant data. Our computational groups worked on developing systems able to innovatively generate and test novel nanoparticle-based strategies in silico. Our chemical synthesis group dealt with translating those in silico outputs to actual chemical procedures so they can synthesize the corresponding functionalized nanoparticles. Our microfluidics group designed a set of next generation tumour-on-a-chip devices that integrates tissue culture, flow control, nutrient supply and waste removal functions. Finally, our clinical group worked on designing appropriate targeting strategies for tracking circulating tumour cells (CSC) in vivo. The challenge was for the Evo Nano team to integrate all these elements into a unified pipeline which goes from AI-powered artificial evolution of novel NP-based drug delivery systems, to their synthesis, rapid in vitro testing and finally in vivo validation.
We are pleased to announce the Evo Nano platform is coming soon.
We hope this will create new foundations for rapid development and assessment of new anti-cancer treatments as well as help pharmaceutical companies to tailor novel treatments to patients rapidly and with lower costs.
Evolvable platform for programmable nanoparticle based cancer therapies future perspectives include:
- To develop a data pipeline for secure retrieval and sharing of patient-derived information and simulation results.
- To reconstruct patient-specific digital twin tumours based on retrieved patient-derived data.
- To validate the virtual tumour using high-quality longitudinal clinical trial data.
- To modularize the platform and enable the seamless incorporation of new simulation tools.
Thank you all so much for joining us on this journey!
The Evo Nano team
This project has received funding from the European Union’s Horizon 2020 FET Open programme under grant agreement. No. 800983.