Periodic Reporting for period 1 - CoDe4Bio (COmputational DEsign for 4D BIOfabrication: harnessing programmable materials for dynamic pre-clinical cancer models)
Periodo di rendicontazione: 2023-01-01 al 2025-06-30
Cancer represents a serious global problem, responsible for 9.6 million deaths in 2018, with this number expected to increase to 19.2 million by 2040. Particularly, blood cancer cases account for approximately 6% of all cancer cases. Although important clinical progress has been made, it is reported that up to 60% of new anti-cancer drugs fail in phase III randomized controlled human trials, due to unacceptable toxicity or inefficacy, and this number is much higher than for other diseases. Accordingly, the prediction of the effectiveness of anti-cancer drugs is considered the “holy grail” of clinical oncology.
3D in vitro pre-clinical models play a key role in fighting this burden by encompassing all the activities prior to clinical trials, from tumor microenvironment reconstruction to drug candidate selection. However, the frequent failure of promising pre-clinical drug candidates highlights two major drawbacks of these models: (i) the difficult reproduction of the highly dynamic tumor microenvironment, subjected to numerous physical cues (e.g. stiffness variations, mechanical loads), that is typical not only of solid cancers, but also of haematological malignancies; (ii) their experimental nature that suffers from high costs, long times, and limited understanding.
CoDe4Bio plans to make these 3D models dynamic by adding a 4th dimension, that is time. Accordingly, our core goal is to develop predictive affordable dynamic in vitro cancer models for drug screening through a synergistic in silico/in vitro approach exploiting 4D biofabrication.
Consequently, activities are conducted in order to: (i) propose customized base materials for dynamic 4D in vitro models capable of shape and property changes upon the application of an external stimulus, mimicking the dynamic physical cues within the tumor microenvironment; (ii) develop predictive tools for 4D biofabrication; (iii) integrate a clinical perspective, with application to chronic lymphocytic leukemia.
The fulfillment of this goal will enable a deep understanding on how cancer cells respond to drugs under dynamic physical stimulation, that is crucial to develop more effective treatments.
3D in vitro pre-clinical models play a key role in fighting this burden by encompassing all the activities prior to clinical trials, from tumor microenvironment reconstruction to drug candidate selection. However, the frequent failure of promising pre-clinical drug candidates highlights two major drawbacks of these models: (i) the difficult reproduction of the highly dynamic tumor microenvironment, subjected to numerous physical cues (e.g. stiffness variations, mechanical loads), that is typical not only of solid cancers, but also of haematological malignancies; (ii) their experimental nature that suffers from high costs, long times, and limited understanding.
CoDe4Bio plans to make these 3D models dynamic by adding a 4th dimension, that is time. Accordingly, our core goal is to develop predictive affordable dynamic in vitro cancer models for drug screening through a synergistic in silico/in vitro approach exploiting 4D biofabrication.
Consequently, activities are conducted in order to: (i) propose customized base materials for dynamic 4D in vitro models capable of shape and property changes upon the application of an external stimulus, mimicking the dynamic physical cues within the tumor microenvironment; (ii) develop predictive tools for 4D biofabrication; (iii) integrate a clinical perspective, with application to chronic lymphocytic leukemia.
The fulfillment of this goal will enable a deep understanding on how cancer cells respond to drugs under dynamic physical stimulation, that is crucial to develop more effective treatments.
After two years of activities, the team has successfully accomplished several intermediate achievements, in line with the core goal and with what proposed in the Description of the Action. These achievements stem from novel methodologies as well as interdisciplinary developments that span from material synthesis, processing, and characterization to biofabrication and biological testing, via multiphysics modelling and computational mechanics. In particular:
(i) Achievements related to activities proposing customized base materials:
- Innovative 4D printing approach using extrusion technology to fabricate structures with reversible shape changes made from semi-crystalline polymer networks (publication n. 2), combining expertise from chemistry to materials science and technology.
- Original approach to fabricate gradient-based polymeric structures capable to bend upon immersion in a solvent (publication n. 7). This approach combines expertise from materials science and technology and mathematical modeling.
- New synergistic approach to optimize simultaneously material composition, properties, and thermal activation of shape changes in semi-crystalline polymer networks, combining expertise from chemistry to materials science.
(ii) Achievements related to activities developing predictive tools for 4D biofabrication:
- New theoretical formulation (publication n. 4) to model all crosslinked semi-crystalline polymer networks with two, or more, crystalline domains, demonstrating high accuracy when compared with our data on PCL-MA (publication n. 5) and literature data on copolymer networks.
- Development and comparison of analytical, semi-empirical, neural network, and finite element models to predict mechanical properties vs. void fraction in 3D printed lattice structures (publication n. 3), providing key guidelines for selecting the best design method based on needs and available data.
(iii) Achievements related to activities integrating a clinical perspective, with application to chronic lymphocytic leukemia:
- We provided insights into shape memory polymers for 4D biofabrication with a literature overview (publication n. 1). Moreover, the first comprehensive review on programmable materials has been published, providing useful insights and new ideas on how to approach their development and implementation (publication n. 6).
(i) Achievements related to activities proposing customized base materials:
- Innovative 4D printing approach using extrusion technology to fabricate structures with reversible shape changes made from semi-crystalline polymer networks (publication n. 2), combining expertise from chemistry to materials science and technology.
- Original approach to fabricate gradient-based polymeric structures capable to bend upon immersion in a solvent (publication n. 7). This approach combines expertise from materials science and technology and mathematical modeling.
- New synergistic approach to optimize simultaneously material composition, properties, and thermal activation of shape changes in semi-crystalline polymer networks, combining expertise from chemistry to materials science.
(ii) Achievements related to activities developing predictive tools for 4D biofabrication:
- New theoretical formulation (publication n. 4) to model all crosslinked semi-crystalline polymer networks with two, or more, crystalline domains, demonstrating high accuracy when compared with our data on PCL-MA (publication n. 5) and literature data on copolymer networks.
- Development and comparison of analytical, semi-empirical, neural network, and finite element models to predict mechanical properties vs. void fraction in 3D printed lattice structures (publication n. 3), providing key guidelines for selecting the best design method based on needs and available data.
(iii) Achievements related to activities integrating a clinical perspective, with application to chronic lymphocytic leukemia:
- We provided insights into shape memory polymers for 4D biofabrication with a literature overview (publication n. 1). Moreover, the first comprehensive review on programmable materials has been published, providing useful insights and new ideas on how to approach their development and implementation (publication n. 6).
The progress significantly beyond the state-of-the-art concerns:
- 4D printed chemically crosslinked semicrystalline networks (publication n. 2). Several additive manufacturing techniques have been used for shape memory polymers. However, most 4D printing studies focus solely on irreversible shape memory effects (SME), limiting applications requiring reversible behavior. Notably, no research has explored the challenges of 4D fabrication via extrusion technology for structures with reversible two-way SME. Because of its cost-effectiveness, user-friendly nature, and wide availability of thermoplastic polymers, material extrusion can offer noteworthy advantages. We thus developed a novel 4D printing approach using extrusion technology (and in line UV crosslinking) to fabricate structures made of semi-crystalline polymer networks featuring the reversible two-way SME. These polymers are highly attractive, given their easy tailorability, excellent shape-memory performances, and fast responses to stimuli. Moreover, our systems are highly biocompatible and thus suitable for the biomedical field and, importantly, for the biological purposes of CoDe4Bio. Our achievement opens the floodgates to implement 4D printing via a cost-effective and user-friendly extrusion technology for developing dynamic structures to be used in a wide variety of applications also beyond the focus of CoDe4Bio.
- Design and manufacturing of self-folding gradient-based soft actuators (publication n. 7, awarded with an inside front cover). Using the same technology, we developed a novel approach to fabricate soft actuators based on semi-crystalline polymer networks, also proposing a theoretical model to predict bending. The proposed approach overcomes current approaches that generally rely on smart hydrogels, multiple materials, or pre-stretched systems to fabricate self-folding actuators. In fact, this approach simplifies the design and fabrication steps by achieving bending using a single material whose properties vary along the thickness of the structure. Moreover, it avoids the need for multi-material printers, adhesion issues typical of multi-material designs, limited mechanical properties of hydrogels, and additional setups for pre-stretch application.
- Development of a new approach for property tuning in semi-crystalline networks. This approach will offer a new way to optimize properties in semi-crystalline networks while avoiding relying on chemical modifications alone. We expect these experiments to provide the most comprehensive characterization of these materials.
- Flexible theoretical formulation for multi-phase semi-crystalline networks (publication n. 4). The model depicts an important contribution as the proposed formulation represents the first model with the capability to address the characterization of all crosslinked semi-crystalline polymer networks with two, or more, crystalline domains.
- 4D printed chemically crosslinked semicrystalline networks (publication n. 2). Several additive manufacturing techniques have been used for shape memory polymers. However, most 4D printing studies focus solely on irreversible shape memory effects (SME), limiting applications requiring reversible behavior. Notably, no research has explored the challenges of 4D fabrication via extrusion technology for structures with reversible two-way SME. Because of its cost-effectiveness, user-friendly nature, and wide availability of thermoplastic polymers, material extrusion can offer noteworthy advantages. We thus developed a novel 4D printing approach using extrusion technology (and in line UV crosslinking) to fabricate structures made of semi-crystalline polymer networks featuring the reversible two-way SME. These polymers are highly attractive, given their easy tailorability, excellent shape-memory performances, and fast responses to stimuli. Moreover, our systems are highly biocompatible and thus suitable for the biomedical field and, importantly, for the biological purposes of CoDe4Bio. Our achievement opens the floodgates to implement 4D printing via a cost-effective and user-friendly extrusion technology for developing dynamic structures to be used in a wide variety of applications also beyond the focus of CoDe4Bio.
- Design and manufacturing of self-folding gradient-based soft actuators (publication n. 7, awarded with an inside front cover). Using the same technology, we developed a novel approach to fabricate soft actuators based on semi-crystalline polymer networks, also proposing a theoretical model to predict bending. The proposed approach overcomes current approaches that generally rely on smart hydrogels, multiple materials, or pre-stretched systems to fabricate self-folding actuators. In fact, this approach simplifies the design and fabrication steps by achieving bending using a single material whose properties vary along the thickness of the structure. Moreover, it avoids the need for multi-material printers, adhesion issues typical of multi-material designs, limited mechanical properties of hydrogels, and additional setups for pre-stretch application.
- Development of a new approach for property tuning in semi-crystalline networks. This approach will offer a new way to optimize properties in semi-crystalline networks while avoiding relying on chemical modifications alone. We expect these experiments to provide the most comprehensive characterization of these materials.
- Flexible theoretical formulation for multi-phase semi-crystalline networks (publication n. 4). The model depicts an important contribution as the proposed formulation represents the first model with the capability to address the characterization of all crosslinked semi-crystalline polymer networks with two, or more, crystalline domains.