RIIPT - Technology Platforms

Decision Support System(DSS) / Biomarker Discovery Validation in Lung Carcinoma

Decision Support System (DSS)
The current decision making processes are normally ad hoc, trial-and-error and human-dependent, which often lead to inefficient, non cost-effective or wrong decisions due to the lack of systemic approach and sufficient information. Our decision support system (DSS) provides a platform for customers to systematically, strategically and consistently design and deploy their decision making process at right place, right time and for right person, so as to improve the accuracy, efficiency and cost-effectiveness of decision making. DSS is a web-based knowledge-driven system, it provides convenient manners and tools for knowledge composing, management and execution.
Major Components of DSS:
Graphical knowledge composer Web-based inference engine (performer) Tester of validating business logics Knowledge base Adaptor (web-client and web-service)

Applications:
Healthcare, including clinical decision support, and personal health management Knowledge management in organizations Logistics flow management and optimization Financial workflow and decision making Insurance policy check and fraud prevention Construction workflow management Design workflow Quality assurance process (ISO certification) Other processes requiring protocol
Customers:
Internal faculties in PolyU External organizations of business or industry that need systematically deploy optimal decision making procedures
Benefits:
Facilitate less experienced workers to follow consistent and complex processes Provide thorough consistent process to structure a decision making process Protocols can be developed with minimal training individuals Protocols can be easily edited and used by all sharing the system
Working interface: DSS interfaces with existing computer system of an organization:
User do not need shift normal working process Fetch data and create a knowledge bank And in the mean time can maintain high security
Graphical knowledge composer (GKC)
GKC is a software platform to help users to design and deploy their field knowledge and workflow. GKC makes this process easy-and-quick similar to drawing a flowchart.

Key Features of GKC:
User friendly: Graphical user interface Web-based: support remote editing through web Standalone: easily embedded into other software Virtual knowledge: knowledge and data is decoupled in the knowledge expression Reliable: 3-level knowledge saving (local computer, server computer, and knowledge base); restoring unsaved knowledge due to abrupt events Flexible: Different types of knowledge, etc.
Key Features of WIE:
Standalone: can be easily plugged into different software environment Web-based: communicating with business system through web for getting data and sending feedback. Multi-user support Parallel computing: scalable to large application Example on clinical decision making: Knowledge of diabetes diagnosis Diabetes diagnosis is expressed to be a series of clinical rules.
Example on clinical decision making:
Knowledge of diabetes diagnosis Diabetes diagnosis is expressed to be a series of clinical rules.	The flow of diabetes diagnosis can be easily implemented by the GKC
Type-2 DM-Clinical Practice Guideline (CPG): The workflow of type-2 DM treatment	Workflow output with decision making
Contact: Dr. Zhu Hai-long, rihlzhu@polyu.edu.hk
Collaborators:

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Biomarker Discovery and Validation in Lung Carcinomaomamamaa
Lung carcinoma is the leading cause of cancer-related deaths worldwide. Better prognosis is inevitably linked to early detection and intervention of the disease. Therefore, there is a great need to discover and validate sensitive and specific biomarkers for its routine diagnosis and prognosis. In collaboration with The Department of Applied Biology and Chemical Technology from The PolyU, local hospitals and hospitals from Mainland, RIIPT is engaged in the discovery of new effective biomarkers on lung carcinoma.

Flow Chart of Biomarker Discovery	Proteomic Techniques

In this research, state-of-the-art technologies in genomics and proteomics such as DNA microarray, quantitative-real-time-PCR, DNA sequencing technology, gel-based proteomics electrophoresis, MALDI-TOF/TOF mass spectrometry and liquid chromatography-linked tandem mass spectrometry are used. Up to now, nearly 20 candidate genetic biomarkers and 18 candidate protein biomarkers have been identified from a bulk of patients’ samples. The validation process in candidate protein biomarkers is now being in progress.
Ultimately, it is intended that a panel of sensitive and specific biomarkers as a potential diagnostic tool for lung cancer screening can be developed.
Contact: Dr. Yoki Butt, riyoki@polyu.edu.hk
Collaborators:
Harvard University Zhong Shan Hospital
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The current decision making processes are normally ad hoc, trial-and-error and human-dependent, which often lead to inefficient, non cost-effective or wrong decisions due to the lack of systemic approach and sufficient information.