This book provides deep insight into key technologies that will modernize pharmaceutical manufacturing and facilitate digital transformation. Throughout the book we discuss technologies, application and challenges for applying digital technology in pharmaceutical industry, including Focus on an overview of Industry 4.0 and its application in the pharmaceutical field The most recent advances in the pharmaceutical industry Understanding the concepts of emerging technology trends for drug discovery. The pharmaceutical industry is on the cusp of a new age, with the need for personalized therapy, more complex production processes, smaller batch sizes and rising manufacturing costs. It is necessary to continuously adapt to the rapidly changing environment using novel technology and improved operational efficiency and flexibility. To achieve this, intelligent manufacturing seems to be a definite answer. Pharma 4.0 is a framework for adapting digital strategies to the unique contexts of pharmaceutical manufacturing.

This book brings together insights for cancer management from emerging sophisticated information and communication technologies such as artificial intelligence, data science, and big data analytics. It focuses on targeted disease treatment using big data analytics, providing information about targeted treatment in oncology, challenges and application of big data in cancer therapy. Featured topics include: Recent developments in the fields of artificial intelligence, machine learning, medical imaging, personalized medicine, computing and data analytics for improved patient care. Description of the application of big data with AI to discover new targeting points for cancer treatment. Summary of several risk assessments in the field of oncology using big data. Focus on prediction of doses in oncology using big data We are in the era of large-scale science. In oncology there is a huge number of data sets grouping information on cancer genomes, transcriptomes, clinical data, and more. The challenge of big data in cancer is to integrate all this diversity of data collected into a unique platform that can be analyzed, leading to the generation of readable files. The possibility of harnessing information from all the accumulated data leads to an improvement in cancer patient treatment and outcome. Solving the big data problem in oncology has multiple facets. Big data in Oncology: Impact, Challenges, and Risk Assessment brings together insights from emerging sophisticated information and communication technologies such as artificial intelligence, data science, and big data analytics for cancer management. The book is written for academics, research scholars, health care professionals, hospital management, pharmaceutical chemist, biomedical industry, software engineers and IT professionals.

Nowadays, raw biological data can be easily stored as databases in computers but extracting the required information is the real challenge for researchers. For this reason, bioinformatics tools perform a vital role in extracting and analyzing information from databases. Bioinformatics Tools and Big Data Analytics for Patient describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery for patient care. The book gives details about the recent developments in the fields of artificial intelligence, cloud computing, and data analytics. It highlights the advances in computational techniques used to perform intelligent medical tasks. Features: Presents recent developments in the fields of artificial intelligence, cloud computing, and data analytics for improved patient care. Describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery. Summarizes several strategies, analyses, and optimization methods for patient healthcare. Focuses on drug discovery and development by cloud computing and data-driven research The targeted audience comprises academics, research scholars, healthcare professionals, hospital managers, pharmaceutical chemists, the biomedical industry, software engineers, and IT professionals.

This book highlights the role of Biomedical Engineering (BME) used in diagnosis (e.g., body scanners) and treatment (radiation therapy and minimal access surgery in order to prevent various diseases). In recent years, an important progress has been made in the expansion of biomedical microdevices which has a major role in diagnosis and therapy of cancer. When fighting cancer, efficacy and speed are of the utmost importance. A recently developed microfluidic chip has enabled a breakthrough in testing the efficacy of specialized cancer drugs. Effective cancer-targeting therapies will require both passive and active targeting strategies and a thorough understanding of physiologic barriers to targeted drug delivery. Targeted cancer treatments in development and the new combinatorial approaches show promise for improving targeted anticancer drug delivery and improving treatment outcomes. This book discusses the advancements and innovations in the field of BME that improve the diagnosis and treatment of cancer. This book is focused on bioengineering approaches to improve targeted delivery for cancer therapeutics, which include particles, targeting moieties, and stimuli-responsive drug release mechanisms. This book is a useful resource for students, researchers, and professionals in BME and medicine.

This book provides a multidisciplinary overview of the design and implementation of systems for remote patient monitoring and healthcare. Readers are guided through the components of such a system and shown how they could be integrated into a coherent framework for deployment in practice. The book ends with a discussion of case studies to provide practical examples and design methods for remote healthcare systems with different needs. This book contains information that will be helpful to undergraduate and postgraduate students, academic and professional researchers, and individuals who employ computational intelligence. By presenting new models of care and support, AI in medicine is having an impact on the entire value chain of clinical practice and the patient care delivery system. This is especially evident in telemedicine breakthroughs, where applications of AI are utilized to assist, complement, or create new forms of remote healthcare. Through the use of communications technology, telemedicine enables medical professionals to examine, diagnose, and treat patients remotely. Now, the technology might also integrate online diagnostics, etc., to increase the effectiveness of the healthcare system and enhance patient outcomes. By enabling elderly people to live independently, technological advancements in fields like remote patient monitoring (RPM) systems can revolutionize senior care. Medical diagnosis will improve, and remote patient monitoring will become simpler thanks to artificial intelligence. The resistance of many patients and doctors to using the telemedicine idea for medical visits will probably be overcome by AI automation.