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European Pharmaceutical Review Issue 3 2024
European Pharmaceutical Review Issue 3 includes articles on microbiology, downstream bioprocessing and drug development. Register your details now to download this exclusive content.
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Artificial Intelligence
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Regulation and legislation in the era of automation and digitalisation
Experts at IP firm Finnegan discuss if the pharmaceutical industry is ready for the innovation and technologies that digitalisation and automation will bring, and whether these advances are a threat or ally to intellectual property rights in the sector.
news
The IMA Group at ACHEMA 2024 : All-In-One solutions for the pharmaceutical sector
At ACHEMA 2024, IMA Pharma will showcase its latest innovations, offering a range of advanced pharmaceutical product packaging and processing technology solutions.
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Technology innovation aiding process spectroscopy market growth
Research suggests that the process spectroscopy market will gain a compound annual growth rate (CAGR) of 5.33 percent by 2033.
podcasts
EPR Podcast 25 – FAIR Data in Pharma – Giovanni Nisato, Pistoia Alliance
In this podcast, Giovanni Nisato, Project Manager at the Pistoia Alliance discusses data integrity and the progress towards implementation of FAIR data principles in the pharmaceutical industry.
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GSK pledges £45m to support global AMR prevention
The CEO of GSK shared that the company is “proud to be a founding partner, and hope others will join us to support this urgent priority” in tackling AMR.
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MHRA publishes strategy on AI regulation
Incorporating artificial intelligence (AI) into the MHRA’s regulatory processes could help the agency focus on key priorities such as innovation.
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From viral vectors to nucleic acids: biopharma’s evolving manufacturing landscape
In this interview, Vikas Gupta, President of CDMO ReciBioPharm, outlines several key trends shaping the biopharma manufacturing landscape, including the rise of nucleic acid-based therapeutics, and the quest for continuous manufacturing.
whitepaper
Whitepaper: Redefining Clinical Trial Decision-Making: Leveraging NLP for extracting insights from unstructured data
Leveraging next-gen technologies such as NLP in data ingestion and extraction, can enable systems to seamlessly extract and analyse such free texts.
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Analytica 2024 in overview
Between 9 - 12 April 2024, the world’s leading trade fair analytica will once again open its doors in Munich to the international laboratory industry. At analytica, industry experts, exhibitors and visitors gather to explore the latest developments in laboratory technology, analysis and biotechnology. The fair, covering the entire spectrum…
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Delivery systems for biologics
Designing systems for delivery of biologics is often a significant challenge during clinical development. Here, Dave Li, Edyta Działo and Anna Baran of KCR Consulting highlight the need for balancing safety, effectiveness, cost and reducing patient discomfort.
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2024 Pharmaceutical industry trends – discover the latest pharma quality and manufacturing trends
Some of the most sought-after human experiences are health and happiness. Although pharmaceutical companies cannot determine personal happiness, they are working to improve personal health outcomes that can tip the scale. The demand for personalised medicines, cell and gene therapies, hyperresponsive and patient-centric healthcare, real-world data fuelled by artificial intelligence…
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Implications of AI regulation for data integrity
According to research, organisations should invest in training for those working with artificial intelligence (AI) to support data integrity assurance in AI applications.
webinar
Process analytical technology: applications and opportunities for pharma
15 February 2024 | By European Pharmaceutical Review, sponsored by Mettler Toledo, Bruker and 908Devices
During this virtual panel, industry experts will discuss the latest advances and applications of process analytical technology in the pharmaceutical sector.
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Pharma Horizons: Artificial Intelligence
EPR's inaugural Pharma Horizons report explores the latest advances in artificial intelligence (AI) and machine learning (ML) for drug development, pharmaceutical manufacturing and quality control.
