bfPREP

bfPREP™ is an AI-driven data cleaning and harmonization platform from Bullfrog AI, purpose-built for biopharma companies, CROs, translational researchers, and health IT teams. It automates the most time-consuming and error-prone stages of data preparation — cleaning, standardizing, and integrating clinical, omics, imaging, and real-world datasets — so teams can move from raw data to analysis-ready outputs faster and with greater confidence.

In life sciences environments, manual data curation, inconsistent formats, and missing values routinely delay time-to-decision and introduce risk into AI/ML workflows. bfPREP™ addresses this by applying AI that is trained on biomedical data, enabling it to distinguish genuine clinical outliers from data errors and to apply controlled vocabularies and normalization rules that reflect biological and clinical reality.

Core Capabilities

• AI-Driven Data Cleaning: Smart detection of anomalies, duplicates, outliers, and missing values, with automated fixes and human-in-the-loop controls to maintain oversight.
• Multi-Modal Data Harmonization: Prepares and integrates omics, clinical, imaging, and real-world datasets with cross-platform compatibility across diverse data sources.
• Scalable, Cloud-Native Architecture: Operates across AWS, Azure, GCP, or on-premises environments, scaling effortlessly to meet enterprise data demands.

Why Raw or 'Clean' Data Still Fails Without bfPREP™

• Free-text categories fragment the same concept into multiple representations (e.g., RUL vs. right upper lobe vs. lung apex).
• Units drift across records (lb vs. kg, cm vs. inches) with ambiguous bare numbers that lack context.
• Drug regimen strings explode into inconsistent variants (dose-reduced, +RT) instead of canonical concepts.
• False heterogeneity dilutes statistical signal and breaks subgrouping in downstream analyses.
• Models learn unit artifacts rather than underlying biology, undermining predictive validity.

What bfPREP™ Delivers on Every Dataset

• Standardization: Lesion locations and other categorical fields are mapped to controlled organ and subsite categories.
• Normalization: Drug regimens are normalized into primary regimen plus modifier components.
• Supplementation: Derived columns such as BMI, categorical groupings, and time-to-event variables (e.g., PFS) are added using explicit, documented rules.
• Quality Control: Censoring flags and validity indicators are included to support modeling reliability and flag records requiring review.
• Auditability: Every derived column is accompanied by a manifest recording inputs, method, version, and coverage — ensuring full traceability.

Data Prep Audit Report

• Data Complexity and Readiness Assessment: A difficulty rating for your dataset showing how complex, incomplete, or unstructured it is, along with a sample extraction demo illustrating how bfPREP™ handles challenging data.
• Feature Enrichment Blueprint: A derived-feature dataset demonstrating how bfPREP™ can expand existing data, plus recommendations for high-value features that could be added to unlock deeper insights and predictive power.
• Outlier and Artifact Intelligence: Identification of data outliers, artifacts, and inconsistencies that could skew models or analyses, enabling proactive correction before investing further in AI/ML workflows.

Who bfPREP™ Is Built For

• Clinical Operations Teams: Accelerate database lock and regulatory submission timelines.
• Health IT Managers: Standardize EHR, trial, and lab data securely and efficiently.
• Bioinformatics and Translational Science Teams: Harmonize and quality-control omics and multi-source datasets.
• Real-World Data Analysts: Standardize messy healthcare data for value-based analyses.
• CROs: Deliver clean, validated datasets to sponsors with confidence.

Integration with bfLEAP™

• bfPREP™ is designed to feed directly into Bullfrog AI's bfLEAP™ causal analytics engine.
• Once data is cleaned and harmonized, teams can immediately run patient stratification models, trial optimization simulations, target discovery analytics, and predictive biomarker assessments.
• The combined workflow compresses time-to-insight, with bfPREP™ reported to reduce data preparation time by up to 80%.

bfPREP™ supports end-to-end interoperability from data ingestion through to export, making datasets analysis-ready, submission-ready, and shareable. The platform operates across cloud and on-premises environments and is designed to integrate seamlessly into existing life sciences data infrastructure.