AIConflux: Blending Diverse Data for AI Transformation - 4 to 6 Wk Proof of Concept

Background: The BioPharma industry heavily relies on data to drive innovation, ensure regulatory compliance, enhance patient safety, inform business decisions, and improve healthcare outcomes. Utilizing data effectively has become a strategic imperative to optimize the results and efficiency of the Biopharma processes. However, a significant hindrance to this goal is the inadequacy of current data management systems in handling the complexity, diversity, and interconnectedness of data streams. Data is often siloed within convoluted datasets, placing the burden on average citizen data users to extract results and derive meaningful analyses. This places an unreasonable expectation on them to write complex queries reflecting an understanding of enterprise-wide data. Consequently, this strains their valuable time and hampers their ability to execute other meaningful tasks relevant to their roles successfully. Furthermore, existing systems fall short in assisting users with this problem, resulting in poor data utilization, lower-than-expected returns on data investments, and citizen data users spending an excessive amount of time on data administrative and processing tasks.

Semantic Querying: The AIConflux solution utilizes GPT-based models for accurate interpretation of the semantic meaning of natural language queries. The semantic meaning is then enriched with a contextual awareness that this is a product meant to handle the nuances of specialized medical terminology and complex pharma queries.

Query Optimization: The query is iteratively improved upon in consultation with the user. For the same, algorithms have been implemented for optimizing and refining queries, allowing users to receive precise and meaningful results efficiently. AIConflux provides recommendations for query improvement based on user interactions and historical queries.

Data Integration: AIConflux provides the capability to seamlessly integrate diverse data types, including genomic data, clinical records, and literature. AIConflux accomplishes this by: • Breaking down the query into data elements that would be required and making an informed estimate about the dataset where those elements would reside. • These data elements reside in disparate data structures. AIConflux supports multiple data structures commonly found in life sciences databases. • These data elements differ in data types that would be returned from the datasets as well, some of them being images, texts, graphs, among others. AIConflux has the ability to synthesize these data elements into composite insights.

Adaptive Learning: AIConflux is by nature a learning and AI driven solution. Being a GPT model, it improves to adapt to evolving language use and user preferences over time. The learning is not limited to semantics but is incorporated in every layer of the solution, from query generation to data synthesis to better serve and adapt to the needs of the end user. To summarize, AIConflux provides an intuitive interface for interacting efficiently with complex datasets using natural language & extract actionable insights. The solution employs the following Microsoft services- Open AI, Azure AD, Azure Cosmos DB, Azure API Manager, Azure CDN, Azure Traffic Manager, Azure Functions, Azure Blob Storage, Microsoft Cognitive Services, Microsoft RDS.

Highlights: H1: A single-point GPT solution that enables accurate semantic understanding, seamless data integration across sources and an adaptive interface for users to interact intuitively all at the same time. H2: Allows for the discovery of hidden relationships and patterns within pharmaceutical data, leading to more informed decision-making in areas like drug discovery, clinical trials, and patient outcomes. H3: With continuous learning and customization capabilities, information retrieval and decision-assistance keep getting better with every iteration.

This solution is ideal for Lifesciences’ customers looking to search and analyze complex data sets from multiple data sources. Contact Us to get started!