Laboratory Quality Management Systems and Automation for Analytical Sciences

课程简介

/ Indicative Syllabus Fundamental Principles of Laboratory Information Management Systems (LIMS) and Laboratory Automation • Overview of LIMS and automation • Historical development & components of LIMS • Benefits of implementing LIMS and automation Core components of LIMS and Laboratory Automation • Protocols for laboratory workflows • Sensors, actuators and controllers in laboratory automation • Basics of robotic systems • Common communication protocols Digital Transformation and Internet of Things (IoT) Fundamentals for LIMS and Laboratory Automation • IoT architecture: sensors, gateways, cloud platforms, etc • Cloud-based solutions on laboratories • Data security in IoT-enabled laboratories Quality Assurance and Compliance with International Standards • Quality Assurance and Control • ISO/IEC 17025 • ISO 15189 LIMS Integration and Data Management • Inventory Management • Personnel and Training • Equipment Management and Maintenance • Data Management, Analysis, Decision Making and Reporting Integrating Artificial Intelligence (AI) in solving real-world LIMS and Laboratory Automation • Introduction to AI/ Machine Learning • Automated data collection • Use of progamming language such as Python and GenAI in setting up laboratory automation • Integration with various instrumentation • Application of AI in data analysis and visualization for compliance in real-world cases

目标

This subject aims to equip students with a comprehensive understanding of laboratory automation within the framework of laboratory quality management systems. Students will gain proficiency in utilizing Laboratory Information Management Systems (LIMS) and related software to enhance laboratory operations, including sample tracking, data management, and quality control. The subject covers regulatory compliance, data integrity, and best practices for reporting, while emphasizing workflow optimization and resource utilization through LIMS integration. Learners will develop skills in troubleshooting, report and dashboard customization, and ensuring data security and confidentiality. Additionally, students will be prepared to train laboratory staff on LIMS functionalities and evaluate suitable LIMS solutions based on organizational needs, budget, and scalability, fostering efficient and effective laboratory management.

先修要求

/ Co-requisite/ Exclusion ABCT4708 Principle of Quality Assurances / ABCT4633 Quality Management and Laboratory Accreditation.

Teaching Pattern

Methodology The subject will be delivered mainly through lectures and tutorials. The lectures will be conducted to introduce the basic concepts of the topics in the syllabus which are then reinforced by learning activities involving demonstration and tutorial exercise. Students should complete exercises and hands-on activities using a range of AI, data analytics, and generative AI tools. The e-learning materials consisting of readings, exercises and