CASE INTRODUCTION
In the pharmaceutical manufacturing sector, batch failures and deviations in Critical Quality Attributes (CQAs) pose substantial risks, leading to significant financial, operational, and reputational damages. These disruptions can affect drug supply, elevate drug costs, and, most critically, endanger human lives. Hence, both pharmaceutical companies and regulatory agencies such as the FDA and EMA are dedicated to eradicating production failures to ensure public health and uphold the industry's integrity.
Root cause analysis for batch deviations typically spans 2 to 6 months, scrutinizing 1,000 to 10,000 parameters per batch. This extensive analysis involves Critical Process Parameters (CPP) and Critical Material Attributes (CMA) across numerous batches, relying on a non-predictive, manual, and partially electronic data extraction process. This method often fails to leverage past knowledge and depends heavily on individual expertise, leading to low confidence and inefficacy in preventing failures.
Nuron offers a transformative solution that automates deviation and root cause analysis, reducing the timeframe from months to mere hours or days. By employing an AI-driven, step-by-step, and data-centric approach, Nuron swiftly identifies the root causes of deviations and failures, moving away from intuition-based methods. Moreover, Nuron's machine learning capabilities provide real-time predictions of CQAs, failures, and deviations. This is achieved by integrating live production batch data with historical data from numerous previous batches. The automation of the ETSAD (Extraction, Transformation, Search, Analysis, and Decision-Making) workflow significantly enhances efficiency and accuracy, paving the path towards zero failures in pharmaceutical manufacturing.
PROBLEM
Batch failures and deviations in critical quality attributes (CQAs) cause significant financial, operational, and reputational losses for pharma companies.
These issues result in significant disruptions to drug supply, increased drug prices, and, most importantly, potential threats to human lives. Consequently, pharmaceutical companies and regulatory agencies, such as the FDA and EMA, are deeply committed to eliminating production failures to safeguard public health and maintain the integrity of the pharmaceutical industry
5-10% batches have quality issues
62% Drug shortage caused by quality failures
CAUSE
Root cause analysis for batch deviations and failures takes 2 to 6 months, involving 1000-10,000 parameters per batch.
Critical process parameters (CPP) and material attributes (CMA) impacting quality attributes require analysis of data from 10s to 100s of batches.
The current manual and partially electronic data extraction process is non-predictive, post-partum, does not use past knowledge, and relies on individual experience, resulting in low confidence and an inability to prevent failures promptly.
Current Manual Process for CSR
NURON DATA-TO-DECISION MAKING SOLUTION
Nuron automates the deviation and root cause analysis, completing the process in a matter of hours to days, a significant improvement over the traditional timeframe of months
Nuron's solution utilizes an Al-driven, step-by-step, and data-driven approach rather than relying in individuals' intuition, to swiftly identify the root causes of deviations and failures
Additionally, our machine learning capabilities enable real-time predictions of Critical Quality Attributes (CQAs), failures, and deviations
This is achieved by seamlessly integrating live production batches' data and documents with information extracted from tens to hundreds of previous batches
Automation of ETSAD Workflow
(Extraction, Transformation, Search, Analysis, and Decision-Making)
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Multi-Batch Analysis
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Step-by step Data to Decision Workflow |
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Gen AI
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Critical Factors
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GENAI POWERED REPORT ANALYSIS & WRITING
Nuron harnesses the power of GenAl to efficiently search and extract insights from various sources, including previous investigation reports, CAPA reports, equipment reports, and other relevant documents. Additionally, we deploy custom GenAl solutions to automate the process of report writing.
Paper Docs PDF, Word etc. Structured Data Images
Custom GenAl
Full Text Search Q/A Search Similarity Search Data Analysis
Full Text Search Q/A Search Similarity Search Data Analysis
VIDEO
Achieving Zero Failures in Pharma Manufacturing with AI: A Deep Dive into Nuron's Data-to-Decision Solution
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Learn more about how Nuron's AI-driven solutions can transform pharmaceutical manufacturing and ensure zero failures. Get the full case study by clicking the link below to delve into the detailed insights and methodologies.
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CONTACT FOR A DEMO
Contact us to better understand your business needs
Nitin Kumar - Ph.D. - CEO and Founder
nitin@nuron.io • 1 627 820 4631
Dr. Himanshu Sharma - Head, Business Development
himanshu.sharma@nuron.io • +91 8451941616
Or
To know more about Nuron's expertise in pharma, click below
https://www.nuron.io/pharmaceuticals.html