While the pharmaceutical industry evolves, the need for curriculum changes inherently follows suit. As healthcare systems have continuously improved through the use of big data and innovative care approaches, practicing pharmacists have also had to adjust and expand their roles. As such, it is imperative that the current and future pharmaceutical workforce is properly trained, taking into account new competencies that are needed to provide exceptional multidisciplinary patient healthcare. Pedagogies for Pharmacy Curricula presents emerging teaching practices and methods for pharmacy curricula and reviews pedagogic methodologies on the scope of pharmaceutical care in pharmacy curricula. The chapters present learning outcomes on general and specific topics, impact of undergraduate interventions on patient outcomes, and comparisons between different teaching pedagogies/models. While highlighting topic areas such as perspectives on learning and teaching, evidence-based practice education, and the relationships between academia and professionals, this book is ideal for health professionals, pharmacists, teachers, schools of pharmacy, medical school faculty, international organizations, clinicians, practitioners, researchers, academicians, and students who are interested in learning about the latest pedagogic methodologies in pharmacy curricula.

Transhumanism is widely misunderstood, in part because the media have exaggerated current technologies and branded the movement as dangerous, leading many to believe that hybrid humans may soon walk among us and that immortality, achieved by means of mind-uploading, is imminent. In this essential and clarifying volume, Stefan Lorenz Sorgner debunks widespread myths about transhumanism and tackles the most pressing ethical issues in the debate over technologically assisted human enhancement. On Transhumanism is a vital primer on the subject, written by a world-renowned expert. In this book, Sorgner presents an overview of the movement's history, capably summarizing the twelve pillars of transhumanist discourse and explaining the great diversity of transhumanist responses to each individual topic. He highlights the urgent ethical challenges related to the latest technological developments, inventions, and innovations and compares the unique cultural standing of transhumanism to other cultural movements, placing it within the broader context of the Enlightenment, modernity, postmodernity, and the philosophical writings of Nietzsche. Engagingly written and translated and featuring an introduction for North American readers, this comprehensive overview of the cultural and philosophical movement of transhumanism will be required reading for students of posthumanist philosophy and for general audiences interested in learning about the transhumanist movement.

Biomaterials for 3D Tumor Modeling reviews the fundamentals and most relevant areas of the latest advances of research of 3D cancer models, focusing on biomaterials science, tissue engineering, drug delivery and screening aspects. The book reviews advanced fundamental topics, including the causes of cancer, existing cancer models, angiogenesis and inflammation during cancer progression, and metastasis in 3D biomaterials. Then, the most relevant biomaterials are reviewed, including methods for engineering and fabrication of biomaterials. 3D models for key biological systems and types of cancer are also discussed, including lung, liver, oral, prostate, pancreatic, ovarian, bone and pediatric cancer. This book is suitable for those working in the disciplines of materials science, biochemistry, genetics, molecular biology, drug delivery and regenerative medicine.

Storing Digital Binary Data into Cellular DNA demonstrates how current digital information storage systems have short longevity and limited capacity, also pointing out that their production and consumption of data exceeds supply. Author Rocky Termanini explains the DNA system and how it encodes vast amounts of data, then presents information on the emergence of DNA as a storage technology for the ever-growing stream of data being produced and consumed. The book will be of interest to a range of readers looking to understand this game-changing technology, including researchers in computer science, biomedical engineers, geneticists, physicians, clinicians, law enforcement and cybersecurity experts.

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks.

Wearable Bioelectronics presents the latest on physical and (bio)chemical sensing for wearable electronics. It covers the miniaturization of bioelectrodes and high-throughput biosensing platforms while also presenting a systemic approach for the development of electrochemical biosensors and bioelectronics for biomedical applications. The book addresses the fundamentals, materials, processes and devices for wearable bioelectronics, showcasing key applications, including device fabrication, manufacturing, and healthcare applications. Topics covered include self-powering wearable bioelectronics, electrochemical transducers, textile-based biosensors, epidermal electronics and other exciting applications.

Biomedical Information Technology, Second Edition, contains practical, integrated clinical applications for disease detection, diagnosis, surgery, therapy and biomedical knowledge discovery, including the latest advances in the field, such as biomedical sensors, machine intelligence, artificial intelligence, deep learning in medical imaging, neural networks, natural language processing, large-scale histopathological image analysis, virtual, augmented and mixed reality, neural interfaces, and data analytics and behavioral informatics in modern medicine. The enormous growth in the field of biotechnology necessitates the utilization of information technology for the management, flow and organization of data. All biomedical professionals can benefit from a greater understanding of how data can be efficiently managed and utilized through data compression, modeling, processing, registration, visualization, communication and large-scale biological computing.