IPQ Analytics' unique risk assessment platform involves advanced analytics, integrated technologies and statistical modeling to provide our clients with highly effective solutions for enhanced decision making, improved outcomes and higher return on investments. IPQ Analytics is particularly sensitive to the unique needs of its constituents who span life science organizations, investment funds, government institutions, payers and providers.
The foundation of our analytics platform (patent pending) is our ontology-based technology to extend knowledge dimensions spanning the clinical, molecular and commercial domains using natural language queries.
Our ontology interprets our client's specific problems by interpreting relevant concepts and relationships and mapping the extended knowledge dimensions against existing data in disparate content repositories.
The dimensionality of extended knowledge is then reduced to incorporate commercial priorities. Corresponding data is aggregated for further analysis based on a "pull" not "push" model. In a final step, the "pulled" data is analyzed using novel statistical models to compute the quantifiable risk for enhanced decision support.
- Customer Knowledgebase Retrieval
- Document Collection: Primary documents, provided by the client used in the decision making process, such as an investigator portfolio, feasibility study analysis, etc. considered critical by the client
- Digitization: All client documentation are digitized, if not already in digitized format
- Information Upload: The digitized documents are securely uploaded into the IPQ Document Library and uniquely cataloged by client and project to enable retrieval and referencing to specific documents during the analysis process. Confidential client information is protected in this secure system
- Evaluation of Customer Knowledgebase
- IPQ utilizes a team of expert editors (evaluators) with specific domain background, typically at the MD or PhD level, to oversee the document processing process within the IPQ Platform.
- Concept/Relationship Extraction: Document analysis and parsing is accomplished by thorough comparison of the concepts and relationships extracted from the Client Knowledgebase using the proprietary IPQ Ontology and IPQ Knowledgebase
- Ontology/Data Management – The IPQ Ontology serves as an analytics engine that represents the core of the IPQ analytics process. The IPQ Ontology is continually updated to include the latest concepts and relationships that could potentially affect the decision process.
- Source Data Association - The IPQ Ontology will be linked to data sources on the index/data field level and as such is able to identify and quantify the amount of data that directly corresponds to the relevant concepts and relationships.
- Gap Analysis - Identification of those concepts and relationships that are not present in the original client knowledgebase but are in the IPQ Knowledgebase will lead to evaluation as to their potential to be either risk factors or opportunities and presented to the client as natural language questions.
- Natural Language Questions Generation – Based on the gap analysis, context specific natural language questions are generated for use by the client to evaluate and prioritize (“P-Phase”) the most relevant issues for further evaluation.
- Client Report - At the completion of this analysis, the IPQ platform generates a comprehensive report containing a summary of the performed IPQ Gap Analysis, including processed client documentation, the list of generated Natural Language Questions, the type of data available to address each question, and an indication as to the potential relevance and importance of each question in the decision process.
The information is then used by the client to prioritize the potential risks/opportunities thereby allowing the quantification of risks/opportunities to be performed.
- Risk Quantification (Q-Phase) - allows quantification of aggregated data to evaluate quality, conflicts and completeness and estimate the degree of risk/opportunity. Thus information/knowledge, developed in the I-Phase becomes prioritized and actionable for commercial or strategic considerations. IPQ develops and implements quantitative assessment of risk using parametric and nonparametric statistical modeling and simulation methods as illustrated in the figure below.
Illustration of Q-Phase Process