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Genomic Biomarkers for Pharmaceutical Development
Genomic Biomarkers for Pharmaceutical Development: Advancing Personalized Health Care provides an in-depth review of the state of translational science across all stages of pharmaceutical development with a special focus on personalized health care. This book provides a complete picture of biomarker development and validation in a pharmaceutical setting while addressing the inherent challenges of targeting the appropriate indications, biomarker robustness, regulatory hurdles, commercialization and much more. It features case studies devoted to the applications of pharmacogenomics, toxicogenomics, and other genetic technologies as they support drug discovery and development. With chapters wri...
Waste to Profit
Waste to Profit: Environmental Concerns and Sustainable Development gives information about selecting the most suitable technology for waste treatment and energy recovery under different conditions. It contains techno-economic analysis, life cycle assessment, optimization of tools and technologies, including overview of various technologies involved in the treatment of wastes and factors influencing the involved processes. Finally, it explores the environmental, socioeconomic, and sustainability impact of different waste-to-energy systems. Features: Reviews energy sources and technologies from waste, their environmental interactions, and the relevant global energy policies Provides overview ...
Genomic Biomarkers for Pharmaceutical Development
The goal of personalized healthcare in the treatment of cancer is to reduce the attrition of novel oncology drugs and improve patient outcomes. The discovery and application of novel biomarkers is essential for the successful implementation of personalized healthcare for cancer patients. This chapter focuses on the types of biomarkers that can be utilized clinically to guide treatment decisions in multiple cancer indications, including pharmacodynamic, predictive, prognostic, resistance, and surrogate biomarkers. Furthermore, multiple distinct examples highlight how the successful implementation of these biomarkers into clinical practice has benefited particular subsets of patients. Although these successful examples represent important first steps in using simple biomarkers to predict patient response, significant challenges still exist in prospectively identifying or co-developing biomarkers as companion diagnostics. The roles next generation sequencing and innovative biomarker-driven clinical trial design may play in overcoming these challenges are discussed.
Genomic Biomarkers for Pharmaceutical Development
Asthma is a heterogeneous disorder on molecular, cellular, physiological, and clinical levels, but there is a lack of consensus on how discrete subtypes of asthma should be defined. Gene expression profiling of bronchial samples from asthma patients and healthy controls has enabled the definition of molecular subtypes of asthma which correspond to distinct pathophysiological features. Genomic data from bronchial samples has been used to identify non-invasive biomarkers such as serum periostin, fractional exhaled nitric oxide (FeNO), and blood eosinophil counts which correspond to these molecular subtypes. These biomarkers have been used in recent proof-of-concept clinical trials of investigational biologic therapies directed at the type 2 cytokines interleukin (IL) 5 and 13 to stratify patients according to the activity of the targeted pathways, enabling the enrichment of subsets of patients most likely to show clinical benefit from those interventions. However, translating these biomarkers into companion diagnostic tests subject to regulatory approval will be a complex process, and intriguing initial findings must be verified prospectively in pivotal clinical trials.
Genomic Biomarkers for Pharmaceutical Development
The focus of this chapter is on the development of miRNA diagnostics and the process for miRNA biomarker development. We discuss pancreatic cancer as a model for the application of miRNA-based tests in different clinical biopsy specimen types. Asuragen’s miRInform® Pancreas test illustrates the development of a laboratory developed test (LDT) that was validated in compliance with Clinical Laboratory Improvement Amendments (CLIA) and College of American Pathologists (CAP) regulations. We provide an overview of work on miRNA-based signatures which is focused on resolving clinical dilemmas in solid and cystic pancreatic lesions. We also review some of the promising miRNA candidates identified in biofluids from other cancer types. These studies highlight the emergence of miRNA-based diagnostic tools which have the potential to impact the clinical management of cancer by guiding early diagnosis, aiding in the assessment of patients’ prognosis, and enabling the identification of novel, more effective therapeutic targets.
Genomic Biomarkers for Pharmaceutical Development
Although we have seen increased spending on drug research and development, the submission of new drug applications to the US Food and Drug Administration (FDA) has steadily decreased over the past 15 years. Meanwhile, toxicology is celebrating the ten-year anniversary of the introduction of toxicogenomics, a field that was anticipated to change our way of conducting toxicology with enhanced safety assessment. Despite the excitement, and a decade of further technical advancement, the anticipated benefits have been slow to reach the clinical bedside. The failure to translate toxicogenomics to drug development faster, illustrates the need for further innovations in its methodology as well as in its technology. This review introduces the concept of toxicogenomics, summarizes the prominent applications of this relatively young discipline in drug development, and provides a future perspective of advancement in this field.
The Elegant Gathering
An exploration of the act of collecting and the cultural implications of a family collection in the Chinese context
JJAP Letters
None
Machine Learning for Cyber Security
The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China. The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.
