Buch, Englisch, 245 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 440 g
ISBN: 978-981-16-3073-6
Verlag: Springer Nature Singapore
From the foreword by Ratan Tata, India
“This book will be a guide for students and professionals alike in quality assurance practices related to clinical research labs. The historical research and fundamental principles make it a good tool in clinical research environments. The country has a great need for such a compilation in order to increase the application of domestic capabilities and technology”Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Pharmazie
- Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Neurowissenschaften, Kognitionswissenschaft
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Public Health, Gesundheitsmanagement, Gesundheitsökonomie, Gesundheitspolitik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Neurologie, Klinische Neurowissenschaft
Weitere Infos & Material
1 Historical Overview of Quality Assurance in Biological Research.- 2 Conceptual framework of research data auditability.- 3 Management of skilled human resources by Youth Oriented Good Laboratory Practices (YOG).- 4 Operationalization of research SOPs for PhD scholars.- 5 Creating Data Recording Sheets (DRS) in quality management system.- 6 The value of Master Schedules in benchmarking research productivity.- 7 Logsheets and the Academic Progress of PhD Students.- 8 Instigation and adherence to the quality assurance program to avoid academic conflicts.- 9 Data fraud and essence of data verifiability.- 10 The role of document control and archiving records in laboratory management.- 11 Academic Social Responsibility and Quality Assurance in the developing world – a framework for implementation.- 12 Good Laboratory Practices: Lab orientations, meetings and value of communication.- 13 Role of data digitization on data integrity.