Distributed Control of Microscopic Robots in Biomedical Applications

Current developments in molecular electronics, motors and chemical sensors could enable constructing large numbers of devices able to sense, compute and act in micron-scale environments. Such microscopic machines, of sizes comparable to bacteria, could simultaneously monitor entire populations of cells individually in vivo. This paper reviews plausible capabilities for microscopic robots and the physical constraints due to operation in fluids at low Reynolds number, diffusion-limited sensing and thermal noise from Brownian motion. Simple distributed controls are then presented in the context of prototypical biomedical tasks, which require control decisions on millisecond time scales. The resulting behaviors illustrate trade-offs among speed, accuracy and resource use. A specific example is monitoring for patterns of chemicals in a flowing fluid released at chemically distinctive sites. Information collected from a large number of such devices allows estimating properties of cell-sized chemical sources in a macroscopic volume. The microscopic devices moving with the fluid flow in small blood vessels can detect chemicals released by tissues in response to localized injury or infection. We find the devices can readily discriminate a single cell-sized chemical source from the background chemical concentration, providing high-resolution sensing in both time and space. By contrast, such a source would be difficult to distinguish from background when diluted throughout the blood volume as obtained with a blood sample

Actuation, Sensing And Control For Micro Bio Robots

The continuing trend in miniaturization of technology, advancements in micro and nanofabrication and improvements in high-resolution imaging has enabled micro- and meso-scale robots that have many applications. They can be used for micro-assembly, directed drug delivery, microsurgery and high-resolution measurement. In order to create microrobots, microscopic sensors, actuators and controllers are needed. Unique challenges arise when building microscale robots. For inspiration, we look toward highly capable biological organisms, which excel at these length scales. In this dissertation we develop technologies that combine biological components and synthetic components to create actuation, sensing and assembly onboard microrobots. For actuation, we study the dynamics of synthetic micro structures that have been integrated with single-cell biological organisms to provide un-tethered onboard propulsion to the microrobot. For sensing, we integrate synthetically engineered sensor cells to enable a system capable of detecting a change in the local environment, then storing and reporting the information. Furthermore, we develop a bottom-up fabrication method using a macroscopic magnetic robot to direct the assembly of inorganic engineered micro structures. We showcase the capability of this assembly method by demonstrating highly-specified, predictable assembly of microscale building blocks in a semi-autonomous experiment. These magnetic robots can be used to program the assembly of passive building blocks, with the building blocks themselves having the potential to be arbitrarily complex. We extend the magnetic robot actuation work to consider control algorithms for multiple robots by exploiting spatial gradients of magnetic fields. This thesis makes contributions toward actuation, sensing and control of autonomous micro systems and provides technologies that will lead to the development of swarms of microrobots with a suite of manipulation and sensing capabilities working together to sense and modify the environment

Bioinspired reorientation strategies for application in micro/nanorobotic control

Engineers have recently been inspired by swimming methodologies of microorganisms in creating micro-/nanorobots for biomedical applications. Future medicine may be revolutionized by the application of these small machines in diagnosing, monitoring, and treating diseases. Studies over the past decade have often concentrated on propulsion generation. However, there are many other challenges to address before the practical use of robots at the micro-/nanoscale. The control and reorientation ability of such robots remain as some of these challenges. This paper reviews the strategies of swimming microorganisms for reorientation, including tumbling, reverse and flick, direction control of helical-path swimmers, by speed modulation, using complex flagella, and the help ofmastigonemes. Then, inspired by direction change in microorganisms,methods for orientation control for microrobots and possible directions for future studies are discussed. Further, the effects of solid boundaries on the swimming trajectories of microorganisms and microrobots are examined. In addition to propulsion systems for artificial microswimmers, swimming microorganisms are promising sources of control methodologies at the micro-/nanoscale

Engineering microrobots for targeted cancer therapies from a medical perspective

Systemic chemotherapy remains the backbone of many cancer treatments. Due to its untargeted nature and the severe side effects it can cause, numerous nanomedicine approaches have been developed to overcome these issues. However, targeted delivery of therapeutics remains challenging. Engineering microrobots is increasingly receiving attention in this regard. Their functionalities, particularly their motility, allow microrobots to penetrate tissues and reach cancers more efficiently. Here, we highlight how different microrobots, ranging from tailor-made motile bacteria and tiny bubble-propelled microengines to hybrid spermbots, can be engineered to integrate sophisticated features optimised for precision-targeting of a wide range of cancers. Towards this, we highlight the importance of integrating clinicians, the public and cancer patients early on in the development of these novel technologies

Enzyme Powered Nanomotors Towards Biomedical Applications

[eng] The advancements in nanotechnology enabled the development of new diagnostic tools and drug delivery systems based on nanosystems, which offer unique features such as large surface area to volume ratio, cargo loading capabilities, increased circulation times, as well as versatility and multifunctionality. Despite this, the majority of nanomedicines do not translate into clinics, in part due to the biological barriers present in the body. Synthetic nano- and micromotors could be an alternative tool in nanomedicine, as the continuous propulsion force and potential to modulate the medium may aid tissue penetration and drug diffusion across biological barriers. Enzyme-powered motors are especially interesting for biomedical applications, owing to their biocompatibility and use of bioavailable substrates as fuel for propulsion. This thesis aims at exploring the potential applications of urease-powered nanomotors in nanomedicine. In the first work, we evaluated these motors as drug delivery systems. We found that active urease- powered nanomotors showed active motion in phosphate buffer solutions, and enhanced in vitro drug release profiles in comparison to passive nanoparticles. In addition, we observed that the motors were more efficient in delivering drug to cancer cells and caused higher toxicity levels, due to the combination of boosted drug release and local increase of pH produced by urea breakdown into ammonia and carbon dioxide. One of the major goals in nanomedicine is to achieve localized drug action, thus reducing side-effects. A commonly strategy to attain this is the use moieties to target specific diseases. In our second work, we assessed the ability of urease-powered nanomotors to improve the targeting and penetration of spheroids, using an antibody with therapeutic potential. We showed that the combination of active propulsion with targeting led to a significant increase in spheroid penetration, and that this effect caused a decrease in cell proliferation due to the antibody’s therapeutic action. Considering that high concentrations of nanomedicines are required to achieve therapeutic efficiency; in the third work we investigated the collective behavior of urease-powered nanomotors. Apart from optical microscopy, we evaluated the tracked the swarming behavior of the nanomotors using positron emission tomography, which is a technique widely used in clinics, due to its noninvasiveness and ability to provide quantitative information. We showed that the nanomotors were able to overcome hurdles while swimming in confined geometries. We observed that the nanomotors swarming behavior led to enhanced fluid convection and mixing both in vitro, and in vivo within mice’s bladders. Aiming at conferring protecting abilities to the enzyme-powered nanomotors, in the fourth work, we investigated the use of liposomes as chassis for nanomotors, encapsulating urease within their inner compartment. We demonstrated that the lipidic bilayer provides the enzymatic engines with protection from harsh acidic environments, and that the motility of liposome-based motors can be activated with bile salts. Altogether, these results demonstrate the potential of enzyme-powered nanomotors as nanomedicine tools, with versatile chassis, as well as capability to enhance drug delivery and tumor penetration. Moreover, their collective dynamics in vivo, tracked using medical imaging techniques, represent a step-forward in the journey towards clinical translation.[spa] Recientes avances en nanotecnología han permitido el desarrollo de nuevas herramientas para el diagnóstico de enfermedades y el transporte dirigido de fármacos, ofreciendo propiedades únicas como encapsulación de fármacos, el control sobre la biodistribución de estos, versatilidad y multifuncionalidad. A pesar de estos avances, la mayoría de nanomedicinas no consiguen llegar a aplicaciones médicas reales, lo cual es en parte debido a la presencia de barreras biológicas en el organismo que limitan su transporte hacia los tejidos de interés. En este sentido, el desarrollo de nuevos micro- y nanomotores sintéticos, capaces de autopropulsarse y causar cambios locales en el ambiente, podrían ofrecer una alternativa para la nanomedicina, promoviendo una mayor penetración en tejidos de interés y un mejor transporte de fármacos a través de las barreras biológicas. En concreto, los nanomotores enzimáticos poseen un alto potencial para aplicaciones biomédicas gracias a su biocompatibilidad y a la posibilidad de usar sustancias presentes en el organismo como combustible. Los trabajos presentados en esta tesis exploran el potenical de nanomotores, autopropulsados mediante la enzima ureasa, para aplicaciones biomédicas, y investigan su uso como vehículos para transporte de fármacos, su capacidad para mejorar penetración de tejidos diana, su versatilidad y movimiento colectivo. En conjunto, los resultados presentados en esta tesis doctoral demuestran el potencial del uso de nanomotores autopropulsados mediante enzimas como herramientas biomédicas, ofreciendo versatilidad en su diseño y una alta capacidad para promover el transporte de fármacos y la penetración en tumores. Por último, su movimiento colectivo observado in vivo mediante técnicas de imagen médicas representan un significativo avance en el viaje hacia su aplicación en medicina

L\'evy walks

Random walk is a fundamental concept with applications ranging from quantum physics to econometrics. Remarkably, one specific model of random walks appears to be ubiquitous across many fields as a tool to analyze transport phenomena in which the dispersal process is faster than dictated by Brownian diffusion. The L\'{e}vy walk model combines two key features, the ability to generate anomalously fast diffusion and a finite velocity of a random walker. Recent results in optics, Hamiltonian chaos, cold atom dynamics, bio-physics, and behavioral science demonstrate that this particular type of random walks provides significant insight into complex transport phenomena. This review provides a self-consistent introduction to L\'{e}vy walks, surveys their existing applications, including latest advances, and outlines further perspectives.Comment: 50 page

Development, evolution and genetic analysis of C. elegans-inspired foraging algorithms under different environmental conditions

In this work 3 minimalist bio-inspired foraging algorithms based on C. elegans’ chemotaxis and foraging behaviour were developed and investigated. The main goal of the work is to apply the algorithms to robots with limited sensing capabilities. The refined versions of these algorithms were developed and optimised in 22 different environments. The results were processed using a novel set of techniques presented here, named Genotype Clustering. The results lead to two distinct conclusions, one practical and one more academic. From a practical perspective, the results suggest that, when suitably tuned, minimalist C. elegans-inspired foraging algorithms can lead to effective navigation to unknown targets even in the presence of repellents and under the influence of a significant sensor noise. From an academic perspective, the work demonstrates that even simple models can serve as an interesting and informative testbed for exploring fundamental evolutionary principles. The simulated robots were grounded in real hardware parameters, aiming at future application of the foraging algorithms in real robots. Another achievement of the project was the development of the simulation framework that provides a simple yet flexible program for the development and optimisation of behavioural algorithms

Optimal active particle navigation meets machine learning

The question of how "smart" active agents, like insects, microorganisms, or future colloidal robots need to steer to optimally reach or discover a target, such as an odor source, food, or a cancer cell in a complex environment has recently attracted great interest. Here, we provide an overview of recent developments, regarding such optimal navigation problems, from the micro- to the macroscale, and give a perspective by discussing some of the challenges which are ahead of us. Besides exemplifying an elementary approach to optimal navigation problems, the article focuses on works utilizing machine learning-based methods. Such learning-based approaches can uncover highly efficient navigation strategies even for problems that involve e.g. chaotic, high-dimensional, or unknown environments and are hardly solvable based on conventional analytical or simulation methods.Comment: 7 pages, 3 figure