China
Africa
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Statistical Approaches in the Development of Digital Therapeutics
Published in Oleksandr Sverdlov, Joris van Dam, Digital Therapeutics, 2023
Oleksandr Sverdlov, Yevgen Ryeznik, Sergei Leonov, Valerii Fedorov
Finally, quantum computing is an area of innovation that can potentially lead to large scientific benefits in drug discovery and development, including DTx, long term. Quantum computing, a nascent technology that works inherently differently from traditional computing, promises solutions to specific problems in which classical computers are limited. Examples include molecular simulation and complex optimization problems, e.g., settings which can be reduced to quadratic unconstrained binary optimization problems (QUBO); see Fedorov and Leonov (2018). Industry analysts forecast pharmaceutical organizations to be a significant beneficiary once the technology is deployable (Zinner et al., 2022).
Big Data Analytics in Healthcare Data Processing
Published in Punit Gupta, Dinesh Kumar Saini, Rohit Verma, Healthcare Solutions Using Machine Learning and Informatics, 2023
Tanveer Ahmed, Rishav Singh, Ritika Singh
The technological research perspective is very important for improving future research in the field of healthcare. BDA’s healthcare insights may benefit from new peripheral technologies. Future researchers should look at the potential benefits of cutting-edge technology in healthcare, such as augmented reality, quantum computing, and machine learning. Another interesting research topic is how upcoming technologies such as digital twins, 5G connectivity, and the physical internet can be leveraged to improve healthcare delivery.
COVID-19 and Global Public Goods
Published in Rui Nunes, Healthcare as a Universal Human Right, 2022
This implies the adoption of a different ethics on behalf of people, and therefore, the use of medicine, health technologies, and modern information and communication technologies (including artificial intelligence (AI), quantum computing, and the treatment of big data) according to principles of justice and equity, of centralization in the sick person and in their quality of life, and in the protection of essential civilizational values, such as respect for individual privacy (European Union 2016). However, imperative reasons for global public health may, transiently and justifiably, in a proportional manner and with a concrete purpose originate a different course of action. For example, AI has been used with enormous success in China and Canada for contact tracing, that is, to identify all people (contacts) who have been exposed to respiratory droplets or secretions from a COVID-19 case. Undoubtedly, contact tracing using AI is more effective than manual tracking, thus allowing the stratification of the risk of exposure and implementing measures such as prophylactic isolation or surveillance. Thus, AI can help prevent the spread of this infectious disease (Shachar et al. 2020).
Emerging technologies and their potential for generating new assistive technologies
Published in Assistive Technology, 2021
Sarah Abdi, Irene Kitsara, Mark S. Hawley, L. P. de Witte
Advances in connectivity and computing can have a huge potential to improve the connectivity of AT devices as well as the digital experiences of end-users. For example, 5 G, the new generation of mobile networks, allows data transfer over high speed and lower latency networks (Deloitte, 2019). Similarly, edge computing – an emerging computing paradigm – can improve real-time responses through allowing the processing to occur closer to the source of the data (Deloitte, 2019). These advances can help data processing within IoT systems and improve the connectivity of AT devices (MIT, 2016b; WEF, 2015a). Improvements in network connectivity can also improve the users’ experiences of virtual and augmented reality, where delays in data processing may have a negative impact on their interactions with this technology (Deloitte, 2018, 2019). Quantum computing is another emerging computing paradigm that could potentially enable computers to perform calculations in a manner that are faster and more efficient than that of conventional computers (MIT, 2018; WEF, 2018). Quantum computing is expected to have significant disruptive potential and help advance various technological fields including AI (WEF, 2017). However, this technology is still in early stages of development and there is some ambiguity regarding its AT application areas (MIT, 2018; WEF, 2017, 2018).
Is high performance computing a requirement for novel drug discovery and how will this impact academic efforts?
Published in Expert Opinion on Drug Discovery, 2020
Savíns Puertas-Martín, Antonio J. Banegas-Luna, María Paredes-Ramos, Juana L. Redondo, Pilar M. Ortigosa, Ol’ha O. Brovarets', Horacio Pérez-Sánchez
A completely different emerging technology is quantum computing. Quantum computers take advantage of quantum mechanics to obtain features like parallel superposition, which allows them to efficiently compute parallel and distributed programs [27]. Thanks to the nature of these quantum processes, solving fundamental problems for drug discovery related to modeling, simulation and molecular properties can be made possible. With the superposition of n qubits, the quantum version of a bit, 2 n possibilities can be represented and computed at the same time. That means many solutions can be explored at once, which makes it a strong candidate for solving optimization problems, such as finding the maximum similarity or the best docking. Currently D-Wave [28] systems are already starting to use quantum annealing processes to find solutions to optimization problems. Companies such as IBM, ATOS, and GOOGLE are making concerted efforts to develop these new technologies and to provide access to prototypes or simulators of quantum computers to promote the development of quantum computing software, which provides an insight into future trends.
Targeting thermoTRP ion channels: in silico preclinical approaches and opportunities
Published in Expert Opinion on Therapeutic Targets, 2020
Gregorio Fernández-Ballester, Asia Fernández-Carvajal, Antonio Ferrer-Montiel
We can expect more sophistication in docking for better predicting interactions and evaluating drug binding sites, and MD methods to refine, optimize, and explore the kinetic and thermodynamic properties of ligand binding and unbinding from the target channel [77]. MD methods will also evaluate these parameters considering the protein environment, i.e. the lipid bilayer, water, ions and the interaction with other proteins. Currently, the complexity of these systems is limiting the MD simulation and has fostered the development of alternative, computing time saving strategies that yielded good results. Clearly, MD methods will maximally benefit from the development of quantum computing that will represent the next revolution in drug design, systems pharmacology and systems biology.