Objectives: O1.1: Identify the technical, physiological, and clinical requirements for the production of micro-particles/needles suitable for integration into ingestible devices. O1.2: Explore various formulations and excipients to achieve instant, enteric, and sustained release of the active pharmaceutical ingredient (API). O1.3: Develop production methods for micro-particles/needles using appropriate API-containing formulations. O1.4: Manufacture micro-particles/needles suitable for potential integration into ingestible devices. O1.5: Assess the release profiles of the produced micro-particles/needles in relevant in-vitro systems. O1.6: Investigate convenient methods for incorporating micro-particles/needles into ingestible devices. O1.7: Evaluate the performance and efficiency of these microparticles/ needles in drug delivery using relevant ex-vivo systems.
Individual Doctoral project
Expected Results: R1.1: Enhanced comprehension of critical design and physiological considerations for micro-particles/needles utilised in oral drug delivery. R1.2: Determined the ideal materials and production processes for micro-particles/needles. R1.3: Generating microparticles/needles with diverse release profiles suitable for various conditions. R1.4: Defined practical techniques for integrating solid microparticles/needles or liquid formulations into ingestible devices. R1.5: Established ex-vivo systems to explore the potential of an oral drug delivery platform.
Objectives: O2.1: Identify the technical, physiological, and clinical prerequisites for retentive patches capable of residing within the intestine without disrupting its function. O2.2: Investigate various mucoadhesive materials suitable for patch fabrication. O2.3 Developpractical and scalable methods for the production of mucoadhesive patches. O2.4: Examine the interaction between pharmaceutical formulations and mucoadhesive patches, including their carrying capacity for the highest dose. O2.5: Assess the release profile of the active pharmaceutical ingredient (API) from mucoadhesive patches through in-vitro studies. O2.6: Evaluate the applicability of these patches in relevant ex-vivo studies.
Expected Results: R2.1: Enhanced comprehension of the physiological, technical, and clinical constraints associated with retentive mucoadhesive patches. R2.2: Identification of bio-inspired mucoadhesive materials suitable for patch fabrication. R2.3: Validation of production methods for mucoadhesive patches. R2.4: Assessment of the mucoadhesive properties of patches composed of diverse materials. R2.5: Improved insight into methods for incorporating APIs into mucoadhesive patches. R2.6: Establishment of ex-vivo systems to investigate the adhesive capabilities of the patches.
Objectives: O3.1: Identify the technical, physiological, and clinical prerequisites for hydrogel based kirigami/origami for oral drug delivery. O3.2: Develop a comprehensive understanding of hydrogel properties, including swelling behaviour, biocompatibility, and responsiveness to physiological conditions. O3.3: Design and optimise kirigami/origami patterns for hydrogel structures to achieve favourable drug release profile. O3.4: Fabricate hydrogel-based kirigami/origami devices using advanced manufacturing techniques, ensuring scalability and reproducibility. O3.5: Characterise the mechanical, swelling, and drug release properties of the developed hydrogel-based devices in simulated gastrointestinal environments. O3.6: Evaluate the in-vitro and ex vivo performance of the kirigami/origami devices for drug release, including their ability to target specific gastrointestinal regions.
Expected Results: R3.1: Enhanced comprehension of the physiological, technical, and clinical constraints associated with hydrogel based kirigami/origami. R3.2: Identification and synthesis of hydrogel materials with right properties such as desire swelling behaviour. R3.3: Identification of kirigami/origami designs and patterns that can be used in oral drug delivery. R3.4: Validation of advanced production methods for designed hydrogels. R3.5: Improved insight into hydrogel potential to target specific regions of the gastrointestinal tract. R3.6: Establishment of in-vitro and ex-vivo systems to investigate the behaviour of hydrogel based kirigami/origami designs.
Objectives: O4.1: To determine quantitative data about human and endoscopic tract anatomy to set operative requirements and distance specifications for design purposes of the localisation system and strategy. O4.2: To investigate sensing principles and technologies for designing the external localisation platform. O4.3: To develop an assessment testbench and mock-up systems to evaluate the macroscopic functions and performances. O4.4: To develop the external localisation system (hardware) for ingestible devices. O4.5: To implement the external localisation strategy (algorithms and software) for pose estimation and tracking. O4.6: To assess the performances of the localisation system in laboratory and in-vitro conditions for pose estimation and tracking (i.e., distance travelled within the gastrointestinal tract).
Expected Results: R4.1: Understanding the typical physical measurements and anatomical features of the endoluminal tract and close/connected anatomy (e.g., abdomen) for design purposes of the localisation system and strategy. R4.2: Defining the most promising sensing principle for designing a localisation strategy for ingestible devices. R4.3: Reliable methodologies and testing test bench for assessing localisation (pose estimation and distance travelled) performance in a controlled multi-dimensional environment. R4.4: Integrated physical platform (hardware) for ingestible devices localisation. R4.5: Optimized algorithms and strategy (software) for estimating the ingestible device position, orientation and distance travelled; Demonstration of the external localisation performance in terms of accuracy, repeatability, dependability and robustness.
Objectives: O5.1: To determine medical requirements and technical specification for the design of sampling and delivery mechanisms applied to the gastrointestinal tract (e.g., reservoir volumes, brushing mechanisms, interaction conditions). O5.2: To define performance indicators, testbenches and experimental protocols to assess novel sampling and delivery mechanisms. O5.3: To implement magnetomechanical models to design the intelligent mechanisms. O5.4: To develop single components and integrated prototypes and preliminary tests. O5.5: To integrate single components in monolithic ingestible capsules for sampling and delivery. O5.6: To validate the developed mechanisms and integrated systems in laboratory and in-vitro conditions for assessing sampling and delivery performance (e.g., volume and type of sampled contents, device-tissue interaction forces).
Expected Results: R5.1: Understanding tribological and tissue interactions properties, as well as clinical aspects to be translated in technical specifications, to design sampling and delivery ingestible devices. R5.2: Reliable methodologies and validation testbenches for assessing sampling and delivery capability of ingestible devices. R5.3: Optimized algorithms for the model-based design of magneto-mechanical intelligent devices. R5.4: Stand-alone components as basic modules of the sampling and delivery mechanisms and devices. R5.5: Integrated ingestible devices validated in laboratory. R5.6: Demonstration of the functionalities of the sampling and delivery mechanisms integrated in the intelligent robots, using the developed physical simulator
Objectives: O6.1: To determine quantitative data about human and endoscopic tract anatomy to set operative requirements and technical specifications for design purposes of the physical simulator. O6.2 To design and implement a CAD-to-CAM software to interpret human anatomies, together with imposed constraints (e.g., complexity indexes, scale factors), for the definition of components and modules to realize the gastrointestinal physical simulator. O6.3: To define and realize a sensing framework for the evaluation of user-specific training status, together with training protocols for tailored education. O6.4 To develop flexible 3D printed moulds for creating the gastrointestinal tract segments, ancillary components (e.g., polyps, peristaltic adjunct module and sensors), and connectors. O6.5: To assemble segments, together with ancillary modules, to create e complete realistic physical gastrointestinal tract simulator. O6.6: To validate the physical simulator in laboratory and in-vitro conditions for assessing functionalities and personalized training and education programmes.
Expected Results: R6.1: Understanding the typical physical measurements and anatomical features of the endoluminal tract and close/connected anatomy (e.g., abdomen) for design purposes of the physical simulator. R6.2: CAD-to-CAM software for the gastrointestinal tract and ancillary modules design and development. R6.3: Development of a sensing framework for user-specific training status assessment and definition of connected protocols for tailored education. R6.4: Realization of gastrointestinal segments and ancillary modules (e.g., peristaltic elements, simulated polyps) for the development of the complete physical simulation platform. R6.5: Development of a complete gastrointestinal physical simulation platform for tailored education and training. R6.6: Demonstration of the functionalities of the physical simulation platform, together with the comprehensive training framework, through user-specific studies and comparative analysis.
Objectives: O7.1: Identify the clinical, social, and technical requirements for developing robust artificial intelligence (AI)-based image/video analysis methods. O7.2: Investigate state-of-the-art transparent, interpretable, and ultimately explainable AI methods. O7.3: Investigate approaches enhancing the robustness of the AI methods for analysis of endoscopic image sequences under real conditions, including tolerance to uncertainty, content diversity, transformations and deformations, and devices for coherence and consistency of inferences. O7.4: Investigate machine learning (ML) methods and algorithms capable of effectively learning to characterize a realistically diverse endoscopic image content belonging to multiple different semantic categories from as few as possible but representative training samples, with as few as possible annotation requirements, while preserving privacy and offering a sufficient image characterization performance, efficiently. O7.5: Investigate video captioning approaches and methods rendering them interpretable/explainable. O7.6: Evaluate the performance of the respective AI methods and algorithms on multi-patient datasets that include publicly available datasets enabling comparisons and reproducibility of research. O7.7: Engage clinicians for the evaluation of the trustworthiness of the AI methods and their applicability in real clinical setups.
Expected Results: R.7.1: In-depth understanding of the imaging features, the diverse content of the GI tract images, the key design principles for trustworthy AI and its application requirements in the context of medical image characterization. R7.2: Interpretable/explainable AI methods that offer meaningful insights, essential for clinicians to incorporate them into everyday clinical practice, and respective evidence from user evaluation studies. R7.3: Robust, reliable and privacy-preserving AI methods for semantic image/video characterization and video captioning, with fewer training requirements. R7.4: Results from the evaluation of the efficiency and effectiveness of the developed AI methods in reproducible experimental setups. R7.5: Results from clinical user evaluation studies evaluating the trustworthiness in real setups.
Objectives: O8.1: Determine the technical, clinical and physiological requirements for accurate in-vivo measurements using energyefficient camera sensors in ingestible devices. O8.2: Investigate AI-based trustworthy depth estimation methods and ML strategies optimizing the accuracy for contactless distance measurement between tissue structures or other findings, and the camera of ingestible devices in-vivo. O8.3: Investigate computer vision methods for robust, contactless, without physical reference, measurement of the size of tissue structures and other findings in-vivo with an uncertainty estimation. O8.4: Investigate travel-distance measurement methods exploiting the depth estimation methods in conjunction with other visual cues, for localization of ingestible devices from a reference location in-vivo with an uncertainty estimation. O8.5: Develop different datasets for training, validation and testing of the afore mentioned AI-based visual measurement methods based on realistic simulated environments and phantom models, such as phantoms created by additive manufacturing, lifelike materials, or animal tissues. O8.6: Evaluate the investigated measurement methods on the developed datasets.
Expected Results: R8.1: In-depth understanding of the challenges related to performing measurements in a real in-vivo environment, the available visual cues and the technical aspects of the ingestible devices. R8.2: Methods developed for in-vivo visual measurements. R8.3: Proof-of-concept computer simulations. R8.4: Datasets for training, validation and testing of visual measurement methods. R8.5: Results from evaluation of the effectiveness of the developed visual measurement methods on the developed datasets, including evaluations by clinicians.
Objectives: O9.1: Determine the technical, clinical and physiological requirements for the geometric, multiphysics and appearance modelling and simulation of the gastrointestinal (GI) tract and ingestible devices, for applications of clinical interest. O9.2: Investigate image analysis methods for the development of high-fidelity 3D geometric models of the GI tract. O9.3: Investigate generative AI (GAI) methods for endoscopic image-driven modelling and rendering of the natural appearance of the GI tract and its content, including uncertainty-aware interpretable GAI methods. O9.4: Development of at least one near-physiological multiphysics model of a GI tract segment, and simulation of its interaction with ingestible devices. O9.5: Combine the developed models (multi-model), verify and validate them in vitro via phantom models. O9.6: Develop demonstration software for evaluation by clinicians, including a virtual environment for testing an indicative camera-enabled ingestible device, and training clinicians in detecting/recognizing abnormalities.
Expected Results: R9.1: In-depth understanding of the imaging features, the diverse image content of the GI tract, the technical characteristics of ingestible devices, and the application requirements in the context of 2D/3D medical image synthesis, realistic tissue modelling, reconstruction and simulation. R9.2: A parametric, personalizable geometric model of the GI tract. R9.3: Generative AI methods for 2D/3D image synthesis. R9.4: A parametric, personalizable multi-model of the GI tract featuring realistic appearance and physical characteristics. R9.5: Results from the verification and validation of the multi model. R9.6: Demonstration software of clinical interestintegrating the developed methods, evaluated by clinicians.
Objectives: O10.1: To develop closed-form models based on fundamental studies of near-field shaping using superposition of spherical harmonics. O10.2: Based on the developed models, to analyse near-field sensitivity to variations of physiological parameters of GI tract and develop design rules for the radio-frequency (RF) structures. O10.3: Based on the obtained rules, develop reconfigurable RF structures and circuits that enable multiplexed bio-sensing, connectivity, and localization modalities. O10.4: Realize, characterize, and integrate RF structures on a flexible PCBs to conform to the ingestible device’s encapsulation.
Expected Results: R10.1: Derivation of theoretical models that allow to simultaneously predict and control both the sensitivity and radiation efficiencies based on the source’s near-field. R10.2: Implementation of the developed models (e.g., in Python). R10.3: Engineered design (in numerical solvers) resizing the sensing/connectivity/localization functionality according to established specifications. R10.4: A wireless prototype that successfully demonstrates the multiplexed functionality.
Objectives: O11.1: Estimate the environmental impact of commercially available CE using Eco-Audit or similar tools with DC13. O11.2: Evaluate the sustainability and performance of an optimised inkjet printing process needed to produce simple sensors, printed electronic circuits and other functional elements using nanoparticle and organic semiconductor inks. O11.3: Using multiphysics simulation tools such as COMSOL and CAD software determine the optimal geometry and layout of the functional layers. O11.4: Print and characterise the performance of a single printed sensor layer consisting of strain, temperature, and pH interdigitated electrode sensors. O11.5: Print and characterise a single printed signal processing layer consisting of a simple organic transistor circuit using electrical characterisation equipment. O11.6: Print and characterise a single magnetic nanoparticle composite layer, align nanoparticles and demonstrate response to an applied magnetic force. O11.7: Integrate layers onto a wired capsule and test under simulated GI conditions at SSSA.
Expected Results: R11.1: Defined optimal process parameters for printed sensors and circuits. R11.2: Benchtop demonstrator of individual layers operating under simulated intestinal conditions. R11.3: Benchtop demonstrator of integrated layers wrapped around a wired capsule operating under simulated intestinal conditions. R11.4: Demonstrator of integrated layers wrapped around a wired capsule operating in an intestinal phantom. R11.5: Analysis of sustainability of this approach versus commercially available CE.
Objectives: O12.1: To determine the technical and physiological requirements for an impedance sensing and optical imaging capsule. O12.2: To quantify the change in impedance with pathology on excised human tissue from the Biobank using benchtop measurement systems. Measurements to be supplemented by clinical diagnosis. O12.3: To ascertain the optimal design, pitch and number of electrodes embedded with capsule shell through COMSOL simulations, experimental validation and technical constraints. O12.4: Test benchtop electronics for capsule. O12.5: Integrate electronics into capsule and test in simple benchtop system. O12.6: Investigate computer vision methods for specific and sensitive detection of inflammatory bowel disease with existing datasets. O12.7: Experimental validation in ex-vivo tissue.
Expected Results: R12.1: A greater understanding of the physiological and technical design constraints for multimodal ingestible devices. R12.2: An analysis of the difference in electrical impedance between healthy human tissue and human tissue with varying degrees of severity of inflammatory bowel disease. R12.3: Benchtop demonstrations of multi-modal capsule. R12.4: Ex-vivo validation of capsule. R12.5: Quantification of the benefits of multimodality for inflammation detection versus a mono modality approach
Objectives: O13.1: To determine the optimal design for a flexible triboelectric nanogenerator (TENG) powered by intestinal peristalsis, which is informed by technical and physiological constraints (intestinal contact forces) using a mathematical model based on contact mechanics. O13.2: Fabricate optimised TENG design using UoB cleanroom. O13:3: Test TENG on a benchtop system and compare to model. O13:4: Demonstrate TENG integrated with energy storage and low power electronic systems and sensor. O13.5: Package system in capsule of varying diameters. O13.6: Test packaged systems of varying diameters in a suitable intestinal phantom model (ex-vivo porcine tissue and emulator at SSSA) and compare to a mathematical model to determine the effect of changing contact forces and performance.
Expected Results: R13.1: Understanding the correlation between design parameters, technical constraints, gastrointestinal physiology and TENG performance for use in ingestible devices. R13.2: A reliable methodology for manufacturing flexible TENGs. R13.3: A mathematical model describing relationship between surface area, intestinal forces and device performance. R13.4: Benchtop demonstrator of TENG and associated electronic systems. R13.5: Packaged device with TENG capable of powering electronics in an intestinal phantom. R13.6: An analysis of the sustainability implications of using energy harvesting over silver oxide coin batteries.
Funding scheme: This research has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Actions Doctoral Network INTELLI-INGEST Grant Agreement N° 101169012 and the UKRI Horizon Europe Guarantee under Grant Agreement EP/U536726/1