Standardization of Analytical Data: Best Practices
3 February 2025 | By ACD Labs
Learn about available formats for analytical data standardization, limitations, and how to ensure data is usable by lab scientists and AI/ML.
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3 February 2025 | By ACD Labs
Learn about available formats for analytical data standardization, limitations, and how to ensure data is usable by lab scientists and AI/ML.
Here, Shidong Shi, Head of Upstream Process Development, and Li Yang, Vice President of CMC Development at Altruist Biologics, discuss the key trends in upstream processing and highlight their approach for overcoming challenges in the field.
24 January 2025 | By LabVantage Solutions
In this webinar, find out how to take advantage of a connected digital ecosystem to enhance quality control, streamline manufacturing and, ensure regulatory compliance
Eleven drugs are poised to make waves in the pharmaceutical industry in 2025, according to the annual report.
The new US Food and Drug Administration (FDA) guidance will enhance credibility of AI models in drug and biological product regulatory submissions.
Dr Vladimir Makarov, AI Community lead, The Pistoia Alliance, explains that despite the willingness of the life sciences R&D industry to adopt artificial intelligence (AI), data integrity is a key area that must be addressed to ensure successful integration of this fast-evolving technology.
9 December 2024 | By European Pharmaceutical Review, sponsored by Charles River Laboratories
During this virtual panel, industry experts will explore the latest advances in environmental monitoring, discuss key challenges within the sector and approaches that can prevent and mitigate these issues.
Mike King, Senior Director, Product & Strategy (Quality, Regulatory, Safety & Detect), Digital Products & Solutions at IQVIA and Alex Denoon, Partner at Bristows Law Firm, explore the challenges of implementing the EU AI Act and the impact of GDPR requirements in life sciences.
Analysis cites personalised medicine, outsourcing and digitalisation as some of the key factors set to advance the pharmaceutical analytical testing market to 2032.
Increased adoption of artificial intelligence (AI) and machine learning (ML) in microbiology is set to be a key driver of the global automated microbiology market to 2033, research asserts.
The draft strategy, open for an eight-week public consultation, will help guide the direction of the network over the next few years.
The new appointee will create AI and machine learning solutions to support Eli Lilly’s medicines for patients globally.
The approach proposed in the paper suggests how artificial intelligence (AI) and machine learning (ML) could enhance process efficiency and product quality during complex manufacturing.
Data integrity is critical in Biopharma manufacturing yet is often difficult to achieve due to complex regulatory requirements and legacy data management systems, among the many factors. Furthermore, issues such as data accuracy, completeness and security impact product quality, regulatory compliance and ultimately patient safety. Addressing all these challenges demands…
22 July 2024 | By
These longer synthetic pathways present challenges for process chemists hoping to achieve an efficient API manufacturing process.