The discouragingly high rates of attrition in drug development, and in particular in Phase 2, warrant a closer look at the decision criteria applied for investment in the next phase (Phase 3). We have in this article evaluated Stop/Go criteria after Phase 2, based on a model encompassing both Phase 2 and 3, as well as the eventual outcome on the market. The results indicate that the value of a drug project is often maximized if rather liberal decision criteria are applied. The routine adherence to standard criteria, e.g. requiring significance at 5% level, may lead to an unduly high rate of false negative decisions. This might ultimately hamper the productivity of drug development and leading to potentially useful drugs not being taken forward to benefit the intended patients.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/10543406.2021.1975129 | DOI Listing |
Brief Funct Genomics
December 2024
Department of Machine Learning, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa FL 33612, United States.
Objective: The primary objective of this study is to investigate various applications of artificial intelligence (AI) and statistical methodologies for analyzing and managing peritoneal metastases (PM) caused by gastrointestinal cancers.
Methods: Relevant keywords and search criteria were comprehensively researched on PubMed and Google Scholar to identify articles and reviews related to the topic. The AI approaches considered were conventional machine learning (ML) and deep learning (DL) models, and the relevant statistical approaches included biostatistics and logistic models.
Front Public Health
December 2024
Department of Basic Psychology II, Facultad de Psicología, Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain.
Introduction: Millions of people living in volcanic environments are at risk of experiencing volcanic eruptions, a natural disaster. This systematic review aimed to collect empirical evidence of the effects of volcanic eruptions on the mental health of the exposed populations.
Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted systematic searches on Scopus, PubMed, PsycINFO, Medline, and Web of Science (WoS) databases.
Front Immunol
December 2024
Department of Neurology, University of Virginia, Charlottesville, VA, United States.
Background: We evaluated comprehension and application of the 2015 neuromyelitis optica spectrum disorder (NMOSD) criteria core elements by neurologists in Latin America (LATAM) who routinely diagnose and care for NMOSD patients by (i) identifying typical/suggestive NMOSD syndromes, (ii) detecting typical MRI NMOSD lesions and meeting MRI dissemination in space (DIS) criteria, and (iii) evaluating historical symptoms suggestive of NMOSD.
Methods: We conducted an anonymous, voluntary, self-administered web- and case-based survey cross-sectional study from October 2023 to January 2024 of neurologists identified through the LACTRIMS database. Questions were presented first through iterative clinical cases or imaging, followed by questions directly evaluating comprehension of definitions.
Background: Frailty in older adults is linked to increased risks and lower quality of life. Pre-frailty, a condition preceding frailty, is intervenable, but its determinants and assessment are challenging. This study aims to develop and validate an explainable machine learning model for pre-frailty risk assessment among community-dwelling older adults.
View Article and Find Full Text PDFJ Mark Access Health Policy
December 2024
Department of Midwifery, School of Health Sciences, University of Western Macedonia, 50200 Ptolemaida, Greece;
This study evaluates the efficiency of public hospitals in Greece during the COVID-19 epidemic in 2020, using Data Envelopment Analysis (DEA) and the Analytical Hierarchy Process (AHP). Faced with unprecedented pressure from increased demand for medical services, these hospitals had to adapt quickly while playing a crucial role in supporting local economies, similar to the effect of tourism on rural economies. This study reveals that, despite average efficiency scores of 83% for result-oriented models (BCC) and 65% for constant return models (CCR), inefficiencies of scale emerged under the pressures of the pandemic.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!