Massive experimental, computational, and clinical studies have been performed worldwide, and are still ongoing, to understand and characterize Covid-19 molecular basis and transmission mechanisms, to develop diagnostics and vaccines, and to search for small chemical drug candidates and therapeutic proteins and peptides. Impressive results have been obtained for transmission control and vaccines so far, but what is the status of the other therapeutic options? The crisis has exposed different types of weaknesses in biomedical research in many countries. What can we learn from this crisis in the field of drug discovery and development so as to emerge stronger? The Covid-19 crisis has revealed the strengths of modern drug discovery and vaccine development but also exposed different types of weaknesses that would need to be addressed to be better prepared for a possible next global health crisis. These challenges/weaknesses/obstacles are of very different nature and as such hard to tackle. For instance, in addition to the inherent challenging nature of the scientific discovery, some scientists have mentioned insufficient local/national coordination and observed a fragmented drug discovery research, others have underlined a lack of coordination between the academic system and the private sector, an inadequate international global coordination and cooperation, others highlighted insufficient infrastructures, inappropriate financial supports, limited discussions between the scientific community performing the research and the public health authorities, decision makers and the society, while some remarked insufficient education/training about drug discovery and development leading to confusion… The crisis also raised important scientific questions about the technologies that would need to be used during an emergency situation, combined, integrated, or developed so as to accelerate the identification of small molecule drug candidates and of therapeutic peptides/proteins.

The novel coronavirus disease 2019 (COVID-19) pandemic has posed a major threat to human life and health. This book is beneficial for interdisciplinary students, researchers, and professionals to understand COVID-19 and how computational intelligence can be used for the purpose of surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease. The book contains different aspects of COVID-19 that includes fundamental knowledge, epidemic forecast models, surveillance and tracking systems, IoT- and IoMT-based integrated systems for COVID-19, social network analysis systems for COVID-19, radiological images (CT, X-ray) based diagnosis system, and computational intelligence and in silico drug design and drug repurposing methods against COVID-19 patients. The contributing authors of this volume are experts in their fields and they are from various reputed universities and institutions across the world. This volume is a valuable and comprehensive resource for computer and data scientists, epidemiologists, radiologists, doctors, clinicians, pharmaceutical professionals, along with graduate and research students of interdisciplinary and multidisciplinary sciences.

This report synthesises the lessons emerging from an OECD Development Assistance Committee peer learning exercise on how innovation efforts can be strengthened, individually and collectively, to achieve the 2030 Agenda.

There have been tremendous advancements in the Pharmacology of Infectious Diseases in recent years. These recent advancements underline the importance of a multidisciplinary approach in the study of infectious diseases. In order to explore this fast-growing area, Frontiers is launching a new series of Research Topics focusing on the evolution of methods, processes, scientific breakthroughs and technology advances in the field of Pharmacology of Infectious Diseases. In this article collection, we seek contributions exploring the changing context, the recent advances, the challenges, and the emerging new perspectives within the field.

The devastating impacts of coronavirus (COVID-19) on developing countries have tested the limits, ingenuity and flexibility of development co-operation while also uncovering best practices. This 58th edition of the Development Co-operation Report draws out early insights from leaders, OECD members, experts and civil society on the implications of coronavirus (COVID-19) for global solidarity and international co-operation for development in 2021 and beyond.

This book summarizes state-of-the-art antiviral drug design and discovery approaches starting from natural products to de novo design, and provides a timely update on recently approved antiviral drugs and compounds in advanced clinical development. Special attention is paid to viral infections with a high impact on the world population or highly relevant from the public health perspective (HIV, hepatitis C, influenza virus, etc.). In these chapters, limitations associated with adverse effects and emergence of drug resistance are discussed in detail. In addition to classical antiviral strategies, chapters will be dedicated to discuss the non-classical drug development strategies to block viral infection, for instance, allosteric inhibitors, covalent antiviral agents, or antiviral compounds targeting protein–protein interactions. Finally, current prospects for producing broad-spectrum antiviral inhibitors will be also addressed. The book is distinctive in providing the most recent update in the rapidly evolving field of antiviral therapeutics. Authoritative reviews are written by international scientists well known for their contributions in their topics of research, which makes this book suitable for researchers not only within the antiviral research community but also attractive to a broad audience in the drug discovery field. This book covers molecular structures and biochemical mechanisms mediating the antiviral effects, while discussing various ligand design strategies, which include traditional medicinal chemistry, computational chemistry, and chemical biology approaches. The book provides a comprehensive review of antiviral drug discovery and development approaches, particularly focusing on current innovations and future trends.

Nanoparticle therapeutics: Production Technologies, Types of Nanoparticles, and Regulatory Aspects employs unique principles for applications in cell-based therapeutics, diagnostics and mechanistics for the study of organ physiology, disease etiology and drug screening of advanced nanoparticles and nanomaterials. The book focuses on the extrapolation of bioengineering tools in the domain of nanotechnology and nanoparticles therapeutics, fabrication, characterization and drug delivery aspects. It acquaints scientists and researchers on the experiential and experimental aspects of nanoparticles and nanotechnology to equip their rational application in various fields, especially in differential diagnoses and in the treatment of diverse diseased states. This complete resource provides a holistic understanding of the principle behind formation, characterization, applications, regulations and toxicity of nanoparticles employing myriad principles of nanotechnology. Investigators, pharmaceutical researchers, and advanced students working on technology advancement in the areas of designing targeted therapies, nanoscale imaging systems and diagnostic modalities in human diseases where nanoparticles can be used as a critical tool for technology advancement in drug delivery systems will find this book useful. Brings together the novel applications of nanotechnology in biological fields Explores perspectives on technologies through highly organized tables, illustrative figures and flow charts Addresses key multidisciplinary challenges faced by nanotechnologists to foster collaboration among biologists, chemists, physicists, engineers and clinicians

Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are executed on diverse architectures to save resources. It provides a comprehensive overview of the novel approaches to machine learning research that consider resource constraints, as well as the application of the described methods in various domains of science and engineering. Volume 3 describes how the resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples. In the areas of health and medicine, it is demonstrated how machine learning can improve risk modelling, diagnosis, and treatment selection for diseases. Machine learning supported quality control during the manufacturing process in a factory allows to reduce material and energy cost and save testing times is shown by the diverse real-time applications in electronics and steel production as well as milling. Additional application examples show, how machine-learning can make traffic, logistics and smart cities more effi cient and sustainable. Finally, mobile communications can benefi t substantially from machine learning, for example by uncovering hidden characteristics of the wireless channel.