Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins*

Sinisi, Stefano; Alimguzhin, Vadim; Mancini, Toni; Tronci, Enrico; Mari, Federico; Leeners, Brigitte

doi:10.3233/fi-2020-1943

Cited by 15 publications

(8 citation statements)

References 70 publications

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“…Also, in order to further increase the size of the areas we can manage, we plan to hybridise our approach with iterative improvement techniques like local-search and meta-heuristic methods (see, e.g., [58,59,60]) specially suited for large instances (e.g., those in [61]), of course sacrificing optimality guarantees. Finally, we aim at reducing the need of linear constraint over-approximations by exploiting simulation-based approaches (e.g., [62,63,64,65]) driven by intelligent search (e.g., [66,67]).…”

Section: Discussionmentioning

confidence: 99%

MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks*

Chen

Finzi

Mancini

et al. 2020

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In critical infrastructures like airports, much care has to be devoted in protecting radio communication networks from external electromagnetic interference. Protection of such mission-critical radio communication networks is usually tackled by exploiting radiogoniometers: at least three suitably deployed radiogoniometers, and a gateway gathering information from them, permit to monitor and localise sources of electromagnetic emissions that are not supposed to be present in the monitored area. Typically, radiogoniometers are connected to the gateway through relay nodes. As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper, we address the problem of computing a deployment for relay nodes that minimises the overall cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance). We show that, by means of a computation-intensive pre-processing on a HPC infrastructure, the above optimisation problem can be encoded as a 0/1 Linear Program, becoming suitable to be approached with standard Artificial Intelligence reasoners like MILP, PB-SAT, and SMT/OMT solvers. Our problem formulation enables us to present experimental results comparing the performance of these three solving technologies on a real case study of a relay node network deployment in areas of the Leonardo da Vinci Airport in Rome, Italy.

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Section: Discussionmentioning

confidence: 99%

MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks*

Chen

Finzi

Mancini

et al. 2020

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“…As the digital twin works in an autonomous virtual world, it can be studied without impacting the physical structure and biological system. DT, keep the promise to minimize time and cost for the safety and efficacy evaluation of pharmacological drugs, reduce the need for humans and other animals testing, and allow precision medicine (Sinisi et al, 2020). The concept of digital twin (DT) is to create stochastic simulations to produce future "what if" scenarios (Fuller et al, 2020) to improve performance and prevent design flaws.…”

Section: Fig 1: Mechanism Of Actionmentioning

confidence: 99%

To explore the pharmacological mechanism of action using digital twin

al.¹

2022

Int. j. adv. appl. sci.

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With the advent of medical technology and science, the number of animals used in research has increased. For decades, the use of animals in research and product testing has been a point of conflict. Experts and pharmaceutical manufacturers are harming animals worldwide during laboratory research. Animals have also played a significant role in the advancement of science; animal testing has enabled the discovery of various novel drugs. The misery, suffering, and deaths of animals are not worth the potential human benefits. As a result, animals must not be exploited in research to assess the drug mechanism of action (MOA). Apart from the ethical concern, animal testing has a few more downsides, including the requirement for skilled labor, lengthy processes, and cost. Because it is critical to investigate adverse effects and toxicities in the development of potentially viable drugs. Assessment of each target will consume the range of resources as well as disturb living nature. As the digital twin works in an autonomous virtual world without influencing the physical structure and biological system. Our proposed framework suggests that the digital twin is a great reliable model of the physical system that will be beneficial in assessing the possible MOA prior to time without harming animals. The study describes the creation of a digital twin to combine the information and knowledge obtained by studying the different drug targets and diseases. Mechanism of Action using Digital twin (MOA-DT) will enable the experts to use an innovative approach without physical testing to save animals, time, and resources. DT reflects and simulates the actual drug and its relationships with its target, however presenting a more accurate depiction of the drug, which leads to maximize efficacy and decrease the toxicity of a drug. In conclusion, it has been shown that drug discovery and development can be safe, effective, and economical in no time through the combination of the digital and physical models of a pharmaceutical as compared to experimental animals.

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“…Together with the model by (37) a previous version of the model by (38) formed the basis for the development of computational tools to enable in silico clinical trials in reproductive endocrinology (39,40). In particular, by introducing variability into model parameters (41)(42)(43), the authors could analyze inter-individual variability in the cycle and automatically synthesize, by means of artificial intelligence guided by patient digital twins, optimal personalized treatments for the patients at hand (44). However, the tools could only be applied to the downregulation phase before follicular stimulation, because the feedback mechanisms from the ovaries to the pituitary were not implemented in the modified model.…”

Section: Mathematical Modeling Of the Female Menstrual Cyclementioning

confidence: 99%

Mathematical Modeling and Simulation Provides Evidence for New Strategies of Ovarian Stimulation

et al. 2021

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New approaches to ovarian stimulation protocols, such as luteal start, random start or double stimulation, allow for flexibility in ovarian stimulation at different phases of the menstrual cycle. It has been proposed that the success of these methods is based on the continuous growth of multiple cohorts (“waves”) of follicles throughout the menstrual cycle which leads to the availability of ovarian follicles for ovarian controlled stimulation at several time points. Though several preliminary studies have been published, their scientific evidence has not been considered as being strong enough to integrate these results into routine clinical practice. This work aims at adding further scientific evidence about the efficiency of variable-start protocols and underpinning the theory of follicular waves by using mathematical modeling and numerical simulations. For this purpose, we have modified and coupled two previously published models, one describing the time course of hormones and one describing competitive follicular growth in a normal menstrual cycle. The coupled model is used to test ovarian stimulation protocols in silico. Simulation results show the occurrence of follicles in a wave-like manner during a normal menstrual cycle and qualitatively predict the outcome of ovarian stimulation initiated at different time points of the menstrual cycle.

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Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins*

Cited by 15 publications

References 70 publications

MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks*

MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks*

To explore the pharmacological mechanism of action using digital twin

Mathematical Modeling and Simulation Provides Evidence for New Strategies of Ovarian Stimulation

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