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By - Kossi Molley (he/il)

Rethinking Quality Processes in the AI Environment

Artificial intelligence (AI) rapidly transforms the biopharmaceutical industry, offering unprecedented opportunities to enhance efficiency, accuracy, and innovation. However, as AI becomes increasingly integrated into GMP-regulated processes, traditional quality management approaches must be rethought. This article delves into the critical aspects of GMP quality compliance in the AI era. It explores the top five reasons why

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By - Kossi Molley (he/il)

GMP Quality Compliance and the Role of AI in Biopharmaceuticals

Good Manufacturing Practice (GMP) quality compliance is a cornerstone of the biopharmaceutical industry, ensuring that products are consistently produced and controlled according to high standards. As artificial intelligence (AI) and machine learning (ML) find increasing applications across the sector, it’s essential to consider how quality management processes need to evolve. Incorporating AI into biopharmaceuticals can

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By - Kossi Molley (he/il)

Cross-Contamination in Biopharmaceutical : A Quality Perspective

In the biopharmaceutical industry, cross-contamination is a significant concern, with potential impacts on product safety, efficacy, and ultimately, patient health. Cross-contamination occurs when trace amounts of one product inadvertently mix with another product, equipment, or process stream. This can lead to compromised product integrity, regulatory non-compliance, and costly recalls. From a quality assurance (QA) perspective,

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By - Kossi Molley (he/il)

Applying Computerized System Assurance (CSA) to Legacy Systems

Computerized System Assurance (CSA) is a modern approach to validating automated systems, particularly in the life sciences industry. It emphasizes a risk-based methodology, focusing on product quality and patient safety, rather than the traditional, more burdensome Computer System Validation (CSV) approach [1], [2]. This article delves into the intricacies of CSA, highlighting the dos and

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By - Kossi Molley (he/il)

Addressing Drug Shortages with AI and ML

The use of artificial intelligence and machine learning in the pharmaceutical industry holds immense promise for overcoming drug shortages. By leveraging predictive analytics, real-time demand forecasting, quality control, regulatory compliance, inventory management, and early warning systems, AI and ML can help ensure that patients have reliable access to the medications they need.

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