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Predicting Deviations

Bigfinite’s solution for Predictive Deviations uses artificial intelligence (AI) and machine learning to find patterns that may lead to a deviation and send an alert before deviations are recorded. Classical tools will raise alarms when each Critical Process Parameter (CPP) goes out of specification, but those same tools cannot send alerts for multivariate conditions. Using AI, Bigfinite can instrument analytics models on the combined set of parameters to see patterns that might yet lead to deviations, even when each parameter is within limits. Combined with Bigfinite’s Principal Component Analysis (PCA) to quantify the causal relationships, collective patterns can be identified and deviations predicted ensuring manufacturing processes will produce the best drug quality.

Flexible Contextual Models

As data is ingested, Bigfinite provides the ability to overlay flexible context on top of our serverless unstructured data lake in the cloud, adding horizontal context by grouping data on commonalities using custom tags. Then we create relationships between data sources with vertical context using associations.
Flexible Contextual Models
Process Definitions

Process Definitions and Instances

Run various process instances (data structures) that can be used and manipulated to learn more about your operations.

AI Pattern Recognition

Detect patterns and irregularities in data through our pattern recognition algorithm in real-time and different time ranges.
AI Pattern Recognition
AI Model Widgets

AI Model Widgets

A set of user-friendly, GMP-compliant AI solution widgets which can be used in conjunction with any data source.

Real-time Predictive Models

Real-time predictions and real-time feedback for running processes against optimal target models (e.g. golden batch) can help prevent future problems (preventive maintenance).
Real-time Predictive Models