Design of experiment in drug development: optimal allocations in multi-arm clinical trials and design space for multi-step processes

In this thesis, we deal with the design of experiments in the drug development process, focusing on the design of clinical trials for treatment comparisons (Part I) and the design of preclinical laboratory experiments for proteins development and manufacturing (Part II). In Part I we propose a multi-purpose design methodology for sequential clinical trials. We derived optimal allocations of patients to treatments for testing the efficacy of several experimental groups by also taking into account ethical considerations. We first consider exponential responses for survival trials and we then present a unified framework for heteroscedastic experimental groups that encompasses the general ANOVA set-up. The very good performance of the suggested optimal allocations, in terms of both inferential and ethical characteristics, are illustrated analytically and through several numerical examples, also performing comparisons with other designs proposed in the literature. Part II concerns the planning of experiments for processes composed of multiple steps in the context of preclinical drug development and manufacturing. Following the Quality by Design paradigm, the objective of the multi-step design strategy is the definition of the manufacturing design space of the whole process and, as we consider the interactions among the subsequent steps, our proposal ensures the quality and the safety of the final product, by enabling more flexibility and process robustness in the manufacturing.

Distributed Large-scale Mixed-Integer Optimization with Application to Energy and Multi-robot Networks

Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.

Neural states in parietal areas during arm reaching

Since the first subdivisions of the brain into macro regions, it has always been thought a priori that, given the heterogeneity of neurons, different areas host specific functions and process unique information in order to generate a behaviour. Moreover, the various sensory inputs coming from different sources (eye, skin, proprioception) flow from one macro area to another, being constantly computed and updated. Therefore, especially for non-contiguous cortical areas, it is not expected to find the same information. From this point of view, it would be inconceivable that the motor and the parietal cortices, diversified by the information encoded and by the anatomical position in the brain, could show very similar neural dynamics. With the present thesis, by analyzing the population activity of parietal areas V6A and PEc with machine learning methods, we argue that a simplified view of the brain organization do not reflect the actual neural processes. We reliably detected a number of neural states that were tightly linked to distinct periods of the task sequence, i.e. the planning and execution of movement and the holding of target as already observed in motor cortices. The states before and after the movement could be further segmented into two states related to different stages of movement planning and arm posture processing. Rather unexpectedly, we found that activity during the movement could be parsed into two states of equal duration temporally linked to the acceleration and deceleration phases of the arm. Our findings suggest that, at least during arm reaching in 3D space, the posterior parietal cortex (PPC) shows low-level population neural dynamics remarkably similar to those found in the motor cortices. In addition, the present findings suggest that computational processes in PPC could be better understood if studied using a dynamical system approach rather than studying a mosaic of single units.

Safe and Collaborative Navigation & Interaction With Mobile Manipulators in Domestic Appliance Test Labs

Safe collaboration between a robot and human operator forms a critical requirement for deploying a robotic system into a manufacturing and testing environment. In this dissertation, the safety requirement for is developed and implemented for the navigation system of the mobile manipulators. A methodology for human-robot co-existence through a 3d scene analysis is also investigated. The proposed approach exploits the advance in computing capability by relying on graphic processing units (GPU’s) for volumetric predictive human-robot contact checking. Apart from guaranteeing safety of operators, human-robot collaboration is also fundamental when cooperative activities are required, as in appliance test automation floor. To achieve this, a generalized hierarchical task controller scheme for collision avoidance is developed. This allows the robotic arm to safely approach and inspect the interior of the appliance without collision during the testing procedure. The unpredictable presence of the operators also forms dynamic obstacle that changes very fast, thereby requiring a quick reaction from the robot side. In this aspect, a GPU-accelarated distance field is computed to speed up reaction time to avoid collision between human operator and the robot. An automated appliance testing also involves robotized laundry loading and unloading during life cycle testing. This task involves Laundry detection, grasp pose estimation and manipulation in a container, inside the drum and during recovery grasping. A wrinkle and blob detection algorithms for grasp pose estimation are developed and grasp poses are calculated along the wrinkle and blobs to efficiently perform grasping task. By ranking the estimated laundry grasp poses according to a predefined cost function, the robotic arm attempt to grasp poses that are more comfortable from the robot kinematic side as well as collision free on the appliance side. This is achieved through appliance detection and full-model registration and collision free trajectory execution using online collision avoidance.

Optimal pose selection for the calibration of an overconstrained Cable-Driven Parallel Robot

In this project an optimal pose selection method for the calibration of an overconstrained Cable-Driven Parallel robot is presented. This manipulator belongs to a subcategory of parallel robots, where the classic rigid "legs" are replaced by cables. Cables are flexible elements that bring advantages and disadvantages to the robot modeling. For this reason, there are many open research issues, and the calibration of geometric parameters is one of them. The identification of the geometry of a robot, in particular, is usually called Kinematic Calibration. Many methods have been proposed in the past years for the solution of the latter problem. Although these methods are based on calibration using different kinematic models, when the robot’s geometry becomes more complex, their robustness and reliability decrease. This fact makes the selection of the calibration poses more complicated. The position and the orientation of the endeffector in the workspace become important in terms of selection. Thus, in general, it is necessary to evaluate the robustness of the chosen calibration method, by means, for example, of a parameter such as the observability index. In fact, it is known from the theory, that the maximization of the above mentioned index identifies the best choice of calibration poses, and consequently, using this pose set may improve the calibration process. The objective of this thesis is to analyze optimization algorithms which aim to calculate an optimal choice of poses both in quantitative and qualitative terms. Quantitatively, because it is of fundamental importance to understand how many poses are needed. Not necessarily a greater number of poses leads to a better result. Qualitatively, because it is useful to understand if the selected combination of poses actually gives additional information in the process of the identification of the parameters.

Studio di fattibilità di un robot a cavi per la movimentazione in ambito navale

L’obbiettivo di questo elaborato di tesi è quello di eseguire uno studio di fattibilità per l’applicazione della tecnologia dei robot a cavi in ambito navale e della Difesa. Il lavoro è stato svolto presso l’azienda Calzoni di Calderara di Reno. In particolare, si è analizzata la possibilità di sostituire le tradizionali strutture rigide impiegate nella movimentazione di carichi con un sistema robotico azionato da cavi che fosse in grado di garantire caratteristiche quali modularità e una più facile riconfigurabilità. Sono state prese in considerazione diverse architetture di robot a cavi. Innanzitutto, si è verificato per ognuna il rispetto delle specifiche di progetto assegnate dall’azienda. Si è quindi condotta un’analisi cineto-statica sulle architetture potenzialmente idonee in modo tale da determinare quale fosse quella più prestazionale. Definita la migliore configurazione, se ne è sviluppato un primo concept preliminare.

Vision-Based Solutions for Human-Robot Collaboration in Industrial Workcells

Industrial robots are both versatile and high performant, enabling the flexible automation typical of the modern Smart Factories. For safety reasons, however, they must be relegated inside closed fences and/or virtual safety barriers, to keep them strictly separated from human operators. This can be a limitation in some scenarios in which it is useful to combine the human cognitive skill with the accuracy and repeatability of a robot, or simply to allow a safe coexistence in a shared workspace. Collaborative robots (cobots), on the other hand, are intrinsically limited in speed and power in order to share workspace and tasks with human operators, and feature the very intuitive hand guiding programming method. Cobots, however, cannot compete with industrial robots in terms of performance, and are thus useful only in a limited niche, where they can actually bring an improvement in productivity and/or in the quality of the work thanks to their synergy with human operators. The limitations of both the pure industrial and the collaborative paradigms can be overcome by combining industrial robots with artificial vision. In particular, vision can be exploited for a real-time adjustment of the pre-programmed task-based robot trajectory, by means of the visual tracking of dynamic obstacles (e.g. human operators). This strategy allows the robot to modify its motion only when necessary, thus maintain a high level of productivity but at the same time increasing its versatility. Other than that, vision offers the possibility of more intuitive programming paradigms for the industrial robots as well, such as the programming by demonstration paradigm. These possibilities offered by artificial vision enable, as a matter of fact, an efficacious and promising way of achieving human-robot collaboration, which has the advantage of overcoming the limitations of both the previous paradigms yet keeping their strengths.

Sviluppo di un sistema di Realta Aumentata applicato a un modello 3D della prostata, sviluppato a partire da immagini RM, al fine di facilitare la dissezione del tumore e la conservazione dei fasci neuro vascolari durante l'intervento chirurgico di prostatectomia radicale robot-assistita

La realtà aumentata (AR) è una nuova tecnologia adottata in chirurgia prostatica con l'obiettivo di migliorare la conservazione dei fasci neurovascolari (NVB) ed evitare i margini chirurgici positivi (PSM). Abbiamo arruolato prospetticamente pazienti con diagnosi di cancro alla prostata (PCa) sul base di biopsia di fusione mirata con mpMRI positiva. Prima dell'intervento, i pazienti arruolati sono stati indirizzati a sottoporsi a ricostruzione del modello virtuale 3D basato su mpMRI preoperatoria immagini. Infine, il chirurgo ha eseguito la RARP con l'ausilio del modello 3D proiettato in AR all'interno della console robotica (RARP guidata AR-3D). I pazienti sottoposti a AR RARP sono stati confrontati con quelli sottoposti a "RARP standard" nello stesso periodo. Nel complesso, i tassi di PSM erano comparabili tra i due gruppi; I PSM a livello della lesione indice erano significativamente più bassi nei pazienti riferiti al gruppo AR-3D (5%) rispetto a quelli nel gruppo di controllo (20%; p = 0,01). La nuova tecnica di guida AR-3D per l'analisi IFS può consentono di ridurre i PSM a livello della lesione dell'indice

A phase II, single arm study of CarbopLatin plus Etoposide with Bevacizumab and Atezolizumab in patients with exTEnded-disease small-cell lung cancer (SCLC) – CeLEBrATE trial

Small cell lung cancer (SCLC) is an aggressive neuroendocrine tumor diagnosed at extended disease SCLC (ES-SCLC) stage in about 70% of cases. The new standard of treatment for patients with ES-SCLC is a combination of platinum-etoposide chemotherapy and atezolizumab or durvalumab, two programmed cell death ligand 1 (PD-L1) inhibitory monoclonal antibodies (mAb). However, the benefit derived from the addition of PD-L1 inhibitors to chemotherapy in ES-SCLC was limited and restricted to a subset of patients. The vascular endothelial growth factor (VEGF) is the most important pro-angiogenic factor implicated in cancer angiogenesis, which is abundant in SCLC and associated with poor prognosis. Antiangiogenic agents, such as bevacizumab, a humanized mAb against VEGF, added to platinum-etoposide chemotherapy improved progression-free survival in SCLC in two trials, but it did not translate into a benefit in overall survival. Nevertheless, VEGF has also acts as a mediator of an immunosuppressive microenvironment and its inhibition can revert the immune-suppressive tumor microenvironment and potentially enhance the efficacy of immunotherapies. Based on available preclinical data, we hypothesized that VEGF inhibition by bevacizumab could improve atezolizumab efficacy in a synergistic way and designed a phase II single-arm trial of bevacizumab in combination with carboplatin, etoposide, and atezolizumab as first-line treatment in ES-SCLC. The trial, which is still ongoing, enrolled 53 patients, including those with treated or untreated asymptomatic brain metastases (provided criteria are met), who received atezolizumab, bevacizumab, carboplatin and etoposide for 4-6 cycles (induction phase), followed by maintenance with atezolizumab and bevacizumab for a maximum of 18 total cycles or until disease progression, patient refusal, unacceptable toxicity. The evaluation of efficacy of the experimental combination in terms of 1-year overall survival rate is not yet mature (primary objective of the trial). The combination was feasible and the toxicity profile manageable (secondary objective of the trial).

Relative influence of gaze and static arm position in the Superior Parietal Lobule of the macaque monkey during reaching

The superior parietal lobule (SPL) of macaques is classically described as an associative cortex implicated in visuospatial perception, planning and control of reaching and grasping movements (De Vitis et al., 2019; Galletti et al., 2003, 2018, 2022; Fattori et al., 2017; Hadjidimitrakis et al., 2015). These processes are the result of the integration of signals related to different sensory modalities. During a goal-directed action, eye and limb information are combined to ensure that the hand is transported at the gazed target location and the arm is maintained steady in the final position. The SPL areas V6A, PEc and PE contain cells sensitive to the direction of gaze and limb position but less is known about the degree of independent encoding of these signals. In this thesis, we evaluated the influence of eye and arm position information upon single neuron activity of areas V6A, PEc and PE during the holding period after the execution of arm reaching movement, when the gaze and hand are both still at the reach target. Two male macaques (Macaca fascicularis) performed a reaching task while single unit activity was recorded from areas V6A, PEc and PE. We found that neurons in all these areas were modulated by eye and static arm positions with a joint encoding of gaze and somatosensory signals in V6A and PEc and a mostly separate processing of the two signals in PE. The elaboration of this information reflects the functional gradient found in the SPL with the caudal sector characterized by visuo-somatic properties in comparison to the rostral sector dominated by somatosensory signals. This evidence well agree also with the recent reallocation of areas V6A and PEc in Brodmann’s area 7 depending on their similar structural and functional features with respect to PE belonging to Brodmann’s area 5 (Gamberini et al., 2020).

Preventing worker’s musculoskeletal disorders with wearable inertial sensors: ergonomics and modelling of physical human-robot interactions

The most widespread work-related diseases are musculoskeletal disorders (MSD) caused by awkward postures and excessive effort to upper limb muscles during work operations. The use of wearable IMU sensors could monitor the workers constantly to prevent hazardous actions, thus diminishing work injuries. In this thesis, procedures are developed and tested for ergonomic analyses in a working environment, based on a commercial motion capture system (MoCap) made of 17 Inertial Measurement Units (IMUs). An IMU is usually made of a tri-axial gyroscope, a tri-axial accelerometer, and a tri-axial magnetometer that, through sensor fusion algorithms, estimates its attitude. Effective strategies for preventing MSD rely on various aspects: firstly, the accuracy of the IMU, depending on the chosen sensor and its calibration; secondly, the correct identification of the pose of each sensor on the worker’s body; thirdly, the chosen multibody model, which must consider both the accuracy and the computational burden, to provide results in real-time; finally, the model scaling law, which defines the possibility of a fast and accurate personalization of the multibody model geometry. Moreover, the MSD can be diminished using collaborative robots (cobots) as assisted devices for complex or heavy operations to relieve the worker's effort during repetitive tasks. All these aspects are considered to test and show the efficiency and usability of inertial MoCap systems for assessing ergonomics evaluation in real-time and implementing safety control strategies in collaborative robotics. Validation is performed with several experimental tests, both to test the proposed procedures and to compare the results of real-time multibody models developed in this thesis with the results from commercial software. As an additional result, the positive effects of using cobots as assisted devices for reducing human effort in repetitive industrial tasks are also shown, to demonstrate the potential of wearable electronics in on-field ergonomics analyses for industrial applications.

A ROS-based software architecture for a versatile collaborative dual-armed autonomous mobile robot for the manufacturing industry

The industrial context is changing rapidly due to advancements in technology fueled by the Internet and Information Technology. The fourth industrial revolution counts integration, flexibility, and optimization as its fundamental pillars, and, in this context, Human-Robot Collaboration has become a crucial factor for manufacturing sustainability in Europe. Collaborative robots are appealing to many companies due to their low installation and running costs and high degree of flexibility, making them ideal for reshoring production facilities with a short return on investment. The ROSSINI European project aims to implement a true Human-Robot Collaboration by designing, developing, and demonstrating a modular and scalable platform for integrating human-centred robotic technologies in industrial production environments. The project focuses on safety concerns related to introducing a cobot in a shared working area and aims to lay the groundwork for a new working paradigm at the industrial level. The need for a software architecture suitable to the robotic platform employed in one of three use cases selected to deploy and test the new technology was the main trigger of this Thesis. The chosen application consists of the automatic loading and unloading of raw-material reels to an automatic packaging machine through an Autonomous Mobile Robot composed of an Autonomous Guided Vehicle, two collaborative manipulators, and an eye-on-hand vision system for performing tasks in a partially unstructured environment. The results obtained during the ROSSINI use case development were later used in the SENECA project, which addresses the need for robot-driven automatic cleaning of pharmaceutical bins in a very specific industrial context. The inherent versatility of mobile collaborative robots is evident from their deployment in the two projects with few hardware and software adjustments. The positive impact of Human-Robot Collaboration on diverse production lines is a motivation for future investments in research on this increasingly popular field by the industry.

Integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment

The computer controlled screwdriver is a modern technique to perform automatic screwing/unscrewing operations.The main focus is to study the integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment.This thesis describes a concept of automatic screwing mechanism composed by universal robots, in which one arm of the robot is for inserting cables and the other is for screwing the cables on the control panel switch gear box. So far this mechanism is carried out by human operators and is a fairly complex one to perform, due to the multiple cables and connections involved. It's for this reason that an automatic cabling and screwing process would be highly preferred within automotive/automation industries. A study is carried out to analyze the difficulties currently faced and a controller based algorithm is developed to replace the manual human efforts using universal robots, thereby allowing robot arms to insert the cables and screw them onto the control panel switch gear box. Experiments were conducted to evaluate the insertion and screwing strategy, which shows the result of inserting and screwing cables on the control panel switch gearbox precisely.

Strategie produttive e di marketing nell'industria cinematografica e televisiva: i casi di Mr. Robot e No Time to Die

La tesi si occupa di delineare una panoramica sul sistema dell'industria dei media e in particolare delle tendenze contemporanee produttive e di marketing volte ad attirare il maggior numero di consumatori. Si prende in esame il prodotto cinematografico dal punto di vista economico e di marketing delineandone i diversi processi: dal marketing mix alle tecniche di segmentazione, targeting e posizionamento fino alle diverse componenti del prodotto stesso che influenzano le scelte dei fruitori. Quest'ultimi esprimono esigenze diverse ed è per questo che è importante che si conosca la domanda a cui rivolgersi e saper comunicare nel modo più adeguato possibile. Nella contemporaneità lo spettatore è sempre più attivo e coinvolto poiché con la sovrabbondanza di offerta si cerca di produrre contenuti più complessi, serializzati e high concept proprio con l'obiettivo di attrarre. Nell'era della convergenza, come definita da Henry Jenkins, si parla di prosumer, ovvero di soggetti che partecipano attivamente al consumo dei prodotti producendo a loro volta contenuti. A queste dinamiche, il marketing contemporaneo risponde a sua volta con forme esperienziali e a forme virali che possano attirare l'attenzione. Analizzo a tal proposito la campagna marketing della serie tv Mr. Robot in quanto si inserisce all'interno della complessità produttiva e della transmedialità e il caso cinematografico della campagna di No Time to Die, l'ultimo film del franchise di 007, in era pandemica.

Dynamic Human Robot Interaction Framework Using Deep Learning and Robot Operating System (ROS): a practical approach

Trying to explain to a robot what to do is a difficult undertaking, and only specific types of people have been able to do so far, such as programmers or operators who have learned how to use controllers to communicate with a robot. My internship's goal was to create and develop a framework that would make that easier. The system uses deep learning techniques to recognize a set of hand gestures, both static and dynamic. Then, based on the gesture, it sends a command to a robot. To be as generic as feasible, the communication is implemented using Robot Operating System (ROS). Furthermore, users can add new recognizable gestures and link them to new robot actions; a finite state automaton enforces the users' input verification and correct action sequence. Finally, the users can create and utilize a macro to describe a sequence of actions performable by a robot.