"The UN was not created to take mankind to heaven, but to save humanity from hell." --Dag Hammarskjöld, United Nations Secretary-General 1953-1961 The turn of the 21st century was an objective low point in the history of human health: AIDS was scourging Africa, millions of women died each year in child birth, and billions suffered under malnourishment and poverty. In response, the United Nations launched its Millennium Development Goals (MDGs), an ambitious charter that since 2000 has measurably reduced the worldwide burdens of poverty, hunger, and disease. With the MDGs set to expire in 2015, continued progress on these fronts is anything but certain. In addition to the persisting threats of the 20th century, globalization has sped the development of new threats--pandemics, climate change, chronic disease--that now threaten rich and poor countries equally. "To Save Humanity" is a collection of short, honest essays on what single issue matters most for the future of global health. Authored by the world's leading voices from science, politics, and social advocacy, this collection is both a primer on the major issues of our time and a potential blueprint for post-2015 health and development. This unparalleled collection will provide illuminating and thought-provoking reading for anyone invested in our collective future and well-being.

Pharmaceutical companies, academic researchers, and government agencies such as the Food and Drug Administration and the National Institutes of Health all possess large quantities of clinical research data. If these data were shared more widely within and across sectors, the resulting research advances derived from data pooling and analysis could improve public health, enhance patient safety, and spur drug development. Data sharing can also increase public trust in clinical trials and conclusions derived from them by lending transparency to the clinical research process. Much of this information, however, is never shared. Retention of clinical research data by investigators and within organizations may represent lost opportunities in biomedical research. Despite the potential benefits that could be accrued from pooling and analysis of shared data, barriers to data sharing faced by researchers in industry include concerns about data mining, erroneous secondary analyses of data, and unwarranted litigation, as well as a desire to protect confidential commercial information. Academic partners face significant cultural barriers to sharing data and participating in longer term collaborative efforts that stem from a desire to protect intellectual autonomy and a career advancement system built on priority of publication and citation requirements. Some barriers, like the need to protect patient privacy, pre- sent challenges for both sectors. Looking ahead, there are also a number of technical challenges to be faced in analyzing potentially large and heterogeneous datasets. This public workshop focused on strategies to facilitate sharing of clinical research data in order to advance scientific knowledge and public health. While the workshop focused on sharing of data from preplanned interventional studies of human subjects, models and projects involving sharing of other clinical data types were considered to the extent that they provided lessons learned and best practices. The workshop objectives were to examine the benefits of sharing of clinical research data from all sectors and among these sectors, including, for example: benefits to the research and development enterprise and benefits to the analysis of safety and efficacy. Sharing Clinical Research Data: Workshop Summary identifies barriers and challenges to sharing clinical research data, explores strategies to address these barriers and challenges, including identifying priority actions and "low-hanging fruit" opportunities, and discusses strategies for using these potentially large datasets to facilitate scientific and public health advances.

Despite the extensive body of evidence that informs regulatory decisions on pharmaceutical products, significant uncertainties persist, including the underlying variability in human biology, factors associated with the chemistry of a drug, and limitations in the research and clinical trial process itself that might limit the generalizability of results. As a result, regulatory reviewers are consistently required to draw conclusions about a drug's safety and efficacy from imperfect data. Efforts are underway within the drug development community to enhance the evaluation and communication of the benefits and risks associated with pharmaceutical products, aimed at increasing the predictability, transparency, and efficiency of pharmaceutical regulatory decision making. Effectively communicating regulatory decisions necessarily includes explanation of the impact of uncertainty on decision making. On February 12 and May 12, 2014, the Institute of Medicine's Forum on Drug Discovery, Development, and Translation held public workshops to advance the development of more systematic and structured approaches to characterize and communicate the sources of uncertainty in the assessment of benefits and risks, and to consider their implications for pharmaceutical regulatory decisions. Workshop presentations and discussions on February 12 were convened to explore the science of identifying and characterizing uncertainty in scientific evidence and approaches to translate uncertainties into decisions that reflect the values of stakeholders. The May 12 workshop presentations and discussions explored tools and approaches to communicating about scientific uncertainties to a range of stakeholders in the drug development process. Characterizing and Communicating Uncertainty in the Assessment of Benefits and Risks of Pharmaceutical Products summarizes the presentation and discussion of both events. This report explores potential analytical and communication approaches and identifies key considerations on their development, evaluation, and incorporation into pharmaceutical benefit- risk assessment throughout the entire drug development lifecycle.

With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the dif

Vol. 34 includes "Special tariff conference issue" Nov. 6, 1925.