@BOOK{NAP author = "National Academies of Sciences, Engineering, and Medicine", title = "Innovations in Pharmaceutical Manufacturing on the Horizon: Technical Challenges, Regulatory Issues, and Recommendations", isbn = "978-0-309-08867-1", abstract = "In 2002, the U.S. Food and Drug Administration (FDA) launched the Pharmaceutical Quality for the 21st Century Initiative to encourage adoption of innovative technologies that would lead to an agile, flexible pharmaceutical manufacturing sector. The goal was to encourage a transition to manufacturing processes and approaches that could produce high-quality drugs reliably without extensive regulatory oversight. Much progress has been made toward that goal as the industry has developed and advanced new technologies, but more progress is required as recent natural disasters and the coronavirus pandemic have revealed vulnerabilities in supply chains and highlighted the need to modernize pharmaceutical manufacturing further.\nAt the request of the FDA Center for Drug Evaluation and Research (CDER), Innovations in Pharmaceutical Manufacturing on the Horizon identifies emerging technologies - such as product technologies, manufacturing processes, control and testing strategies, and platform technologies - that have the potential to advance pharmaceutical quality and modernize pharmaceutical manufacturing for products regulated by CDER. This report describes many innovations to modernize the manufacture of drug substances and drug products, to advance new control approaches, and to develop integrated, flexible, and distributed manufacturing networks within 5-10 years. ", url = "https://nap.nationalacademies.org/catalog/26009/innovations-in-pharmaceutical-manufacturing-on-the-horizon-technical-challenges-regulatory", year = 2021, publisher = "The National Academies Press", address = "Washington, DC" } @BOOK{NAP author = "National Academies of Sciences, Engineering, and Medicine", editor = "Joe Alper", title = "Big Data and Analytics for Infectious Disease Research, Operations, and Policy: Proceedings of a Workshop", isbn = "978-0-309-45011-9", abstract = "With the amount of data in the world exploding, big data could generate significant value in the field of infectious disease. The increased use of social media provides an opportunity to improve public health surveillance systems and to develop predictive models. Advances in machine learning and crowdsourcing may also offer the possibility to gather information about disease dynamics, such as contact patterns and the impact of the social environment. New, rapid, point-of-care diagnostics may make it possible to capture not only diagnostic information but also other potentially epidemiologically relevant information in real time. With a wide range of data available for analysis, decision-making and policy-making processes could be improved. \n\nWhile there are many opportunities for big data to be used for infectious disease research, operations, and policy, many challenges remain before it is possible to capture the full potential of big data. In order to explore some of the opportunities and issues associated with the scientific, policy, and operational aspects of big data in relation to microbial threats and public health, the National Academies of Sciences, Engineering, and Medicine convened a workshop in May 2016. Participants discussed a range of topics including preventing, detecting, and responding to infectious disease threats using big data and related analytics; varieties of data (including demographic, geospatial, behavioral, syndromic, and laboratory) and their broader applications; means to improve their collection, processing, utility, and validation; and approaches that can be learned from other sectors to inform big data strategies for infectious disease research, operations, and policy. This publication summarizes the presentations and discussions from the workshop.", url = "https://nap.nationalacademies.org/catalog/23654/big-data-and-analytics-for-infectious-disease-research-operations-and-policy", year = 2016, publisher = "The National Academies Press", address = "Washington, DC" }