Lab Product (Base Package and Deep Cleaning Package)

Cornerstone AI's Lab Product is a laboratory data standardization platform designed for pharmaceutical researchers, real-world evidence teams, and life sciences data providers. It transforms raw, inconsistent laboratory data into clean, analysis-ready datasets by leveraging AI-powered Natural Language Processing (NLP) to automate the time-consuming manual work that typically delays research timelines. The platform is offered in two tiers — the Base Package and the Deep Cleaning Package — each targeting different levels of data preparation need.

By addressing the widespread problem of missing or inconsistent LOINC codes, non-standardized units, and anomalous results, Cornerstone AI enables analysts to identify more patients, run more reliable cohort studies, and improve the overall commercializability of laboratory data assets.

Base Package: Core Capabilities

• Automatically assigns LOINC codes to lab records using Cornerstone AI's NLP-based prediction engine, dramatically increasing LOINC code assignment rates where 60–80% of raw lab records are typically missing them.
• Standardizes test names across datasets, improving consistency and reliability of test identification.
• Improves patient matching and accurate test counts across disparate laboratory sources.
• Preserves raw data granularity while layering on CAI-based LOINC codes, ensuring analysts retain full access to original records.
• Reduces the manual effort required to query and analyze lab data, accelerating research workflows.
• Improves the commercial value of laboratory data assets for data owners and vendors.

Deep Cleaning Package: Advanced Capabilities

• Includes all features of the Base Package, plus a comprehensive suite of additional data quality enhancements.
• Standardizes measurement units across lab results, resolving inconsistencies that make cross-dataset comparisons difficult and error-prone.
• Automatically converts raw result values into standardized formats, eliminating the need for manual unit conversion and reducing the risk of misinterpretation.
• Performs result imputation to address gaps in lab data records.
• Applies anomaly detection algorithms to identify and flag abnormal or erroneous data points, enhancing overall data accuracy.
• Delivers clean, ready-to-use laboratory data instantly, automating work that would otherwise take weeks of manual effort.
• Further refines datasets for downstream analysis, making lab data immediately actionable for research and analytics teams.

Key Benefits and Measurable Impact

• Accelerates the process of standardizing lab data for pharmaceutical and real-world evidence research.
• Improves both the coverage and accuracy of LOINC code assignments by more than 50%.
• Enables identification of more patient records that meet lab criteria for a given analysis, which is especially critical for small or rare-disease cohorts.
• Trims up to 8 weeks off research timelines through standardized test efficiency.
• Reduces study timelines by an additional 2 weeks through simplified unit and reference range handling.
• Boosts data value by approximately 20% through smarter and more complete test identification.

Workflow: Before and After

1. Raw laboratory data arrives with missing LOINC codes, inconsistent test names, varied measurement units, and potential anomalies that make analysis unreliable and labor-intensive.
2. Cornerstone AI ingests the raw data and applies NLP-driven LOINC code assignment, test name standardization, unit conversion, anomaly detection, and imputation automatically.
3. Cleaned and standardized lab data is returned, ready for immediate use in cohort identification, comparative analysis, and research reporting — without weeks of manual preparation.

Cornerstone AI's Lab Product has been validated in partnership with leading life sciences data organizations including Komodo Health, Diaceutics, and Loopback Analytics, and has demonstrated measurable improvements in patient cohort identification, test coverage, and data quality for pharmaceutical research workflows.