Background: The development of new antidepressant drugs has reached a plateau. There is an unmet need for faster, better, and safer medications, but as placebo-response rates rise, effect sizes shrink, and more studies fail or are negative, pharmaceutical companies are increasingly reluctant to invest in new drug development because of the risk of failure. In the absence of an identifiable human pathophysiology that can be modeled in preclinical studies, the principal point of leverage to move beyond the present dilemma may be improving the information gleaned from well-designed proof-of-concept (POC) studies of new antidepressant drugs with novel central nervous system effects. With this in mind, a group of experts was convened under the auspices of the University of Arizona Department of Psychiatry and Best Practice Project Management, Inc.
Participants: Forty-five experts in the study of antidepressant drugs from academia, government (U.S. Food and Drug Administration and National Institute of Mental Health), and industry participated. EVIDENCE/CONSENSUS PROCESS: In order to define the state of clinical trials methodology in the antidepressant area, and to chart a way forward, a 2-day consensus conference was held June 21-22, 2007, in Bethesda, Md., at which careful reviews of the literature were presented for discussion. Following the presentations, participants were divided into 3 workgroups and asked to address a series of separate questions related to methodology in POC studies. The goals were to review the history of antidepressant drug trials, discuss ways to improve study design and data analysis, and plan more informative POC studies.
Conclusions: The participants concluded that the federal government, academic centers, and the pharmaceutical industry need to collaborate on establishing a network of sites at which small, POC studies can be conducted and resulting data can be shared. New technologies to analyze and measure the major affective, cognitive, and behavioral components of depression in relationship to potential biomarkers of response should be incorporated. Standard assessment instruments should be employed across studies to allow for future meta-analyses, but new instruments should be developed to differentiate subtypes and symptom clusters within the disorder that might respond differently to treatment. Better early-stage POC studies are needed and should be able to amplify the signal strength of drug efficacy and enhance the quality of information in clinical trials of new medications with novel pharmacologic profiles.
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http://dx.doi.org/10.4088/jcp.v69n1001 | DOI Listing |
3D Print Med
December 2024
Diagnostic Imaging Department, Hospital de la Santa Creu i Sant Pau, Sant Antoni Maria Claret 167, 08025, Barcelona, Spain.
Background: 3D technologies [Virtual and Augmented 3D planning, 3D printing (3DP), Additive Manufacturing (AM)] are rapidly being adopted in the healthcare sector, demonstrating their relevance in personalized medicine and the rapid development of medical devices. The study's purpose was to understand the state and evolution of 3DP/AM technologies at the Point-of-Care (PoC), its adoption, organization and process in Spanish hospitals and to understand and compare the evolution of the models, clinical applications, and challenges in utilizing the technology during the COVID-19 pandemic and beyond.
Methods: This was a questionnaire-based qualitative and longitudinal study.
Neurol Int
December 2024
Department of Immunology, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iași, Romania.
: Several significant associations between certain Human Leukocyte Antigen (HLA) alleles and myasthenia gravis (MG) subtypes were established in populations from Western Europe and North America and, to a lesser extent, from China and Japan. However, such data are scarcely available for Eastern Europe. This study aimed to analyze the associations of HLA Class I and II alleles with MG and its serological subtypes (with anti-acetylcholine receptor autoantibodies, RAch+MG, and double-seronegative, dSNMG) in myasthenic patients of Romanian descent.
View Article and Find Full Text PDFBiosensors (Basel)
December 2024
School of Engineering, Ulster University, Belfast BT15 1ED, UK.
Lateral flow assays are widely used in point-of-care diagnostics but face challenges in sensitivity and accuracy when detecting low analyte concentrations, such as thyroid-stimulating hormone biomarkers. This study aims to enhance assay performance by leveraging textural features and hybrid artificial intelligence models. A modified Gray-Level Co-occurrence Matrix, termed the Averaged Horizontal Multiple Offsets Gray-Level Co-occurrence Matrix, was utilised to compute the textural features of the biosensor assay images.
View Article and Find Full Text PDFAnal Chem
December 2024
NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening & Guangdong-Hongkong-Macao Joint Laboratory for New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China.
A simple, rapid, and visual approach is developed to perform diagnosis of urinary tract infection (UTI) and antimicrobial susceptibility testing (AST) by employing smart bifunctional DNA (bfDNA) sensors, exonuclease III, concatermers of CuO nanoparticles (CuONPs), and gold NPs (AuNPs) aggregation [AuNPs agglutination (AA)], namely, the bfDEC-AA method. The bfDNA sensors serve as probes for identifying 16S rRNA genes of bacterium or 18S rRNA of fungus and as mediators connecting the concatermers of CuONPs. The AA as a signal source is triggered by Cu(I)-catalyzed azide-alkyne cycloaddition click chemistry.
View Article and Find Full Text PDFHuan Jing Ke Xue
January 2025
College of Resources, Sichuan Agricultural University, Chengdu 611130, China.
Exploring the composition of regional soil organic carbon (SOC) components and identifying their influencing factors are of utmost importance to deeply understand the potential mechanisms of SOC change in cropland soil. Based on data from 871 soil sampling points, this study explored the characteristics of soil particulate and mineral-associated organic carbon (POC and MAOC) in the surface soil of cropland and the relationships with climate, terrain, soil texture, agricultural land-use type, and fertilization across the Sichuan basin using analysis of variance, correlation analysis, and a random forest model. The results showed that the average content of POC and MAOC in the surface soil of cropland was 5.
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