AIMC Topic: Drug Industry
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Text summarization for pharmaceutical sciences using hierarchical clustering with a weighted evaluation methodology.
Scientific reports
Aug 30, 2024
In the pharmaceutical industry, there is an abundance of regulatory documents used to understand the current regulatory landscape and proactively make project decisions. Due to the size of these documents, it is helpful for project teams to have info...
Explainable deep recurrent neural networks for the batch analysis of a pharmaceutical tableting process in the spirit of Pharma 4.0.
International journal of pharmaceutics
Jul 22, 2024
Due to the continuously increasing Cost of Goods Sold, the pharmaceutical industry has faced several challenges, and the Right First-Time principle with data-driven decision-making has become more pressing to sustain competitiveness. Thus, in this wo...
Leveraging AI and Machine Learning in Six-Sigma Documentation for Pharmaceutical Quality Assurance.
Zhongguo ying yong sheng li xue za zhi = Zhongguo yingyong shenglixue zazhi = Chinese journal of applied physiology
Jul 18, 2024
The pharmaceutical industry must maintain stringent quality assurance standards to ensure product safety and regulatory compliance. A key component of the well-known Six Sigma methodology for process improvement and quality control is precise and com...
Good machine learning practices: Learnings from the modern pharmaceutical discovery enterprise.
Computers in biology and medicine
May 21, 2024
Machine Learning (ML) and Artificial Intelligence (AI) have become an integral part of the drug discovery and development value chain. Many teams in the pharmaceutical industry nevertheless report the challenges associated with the timely, cost effec...
The IDMP Ontology - A Catalyst to Unleash the Potential of AI and Accelerate Data-Driven Decisions with Industry-Wide Standards.
Drug discovery today
May 7, 2024
How successful are AI-discovered drugs in clinical trials? A first analysis and emerging lessons.
Drug discovery today
Apr 30, 2024
AI techniques are making inroads into the field of drug discovery. As a result, a growing number of drugs and vaccines have been discovered using AI. However, questions remain about the success of these molecules in clinical trials. To address these ...
Machine vision-based non-destructive dissolution prediction of meloxicam-containing tablets.
International journal of pharmaceutics
Mar 17, 2024
Machine vision systems have emerged for quality assessment of solid dosage forms in the pharmaceutical industry. These can offer a versatile tool for continuous manufacturing while supporting the framework of process analytical technology, quality-by...
What they forgot to tell you about machine learning with an application to pharmaceutical manufacturing.
Pharmaceutical statistics
Feb 28, 2024
Predictive models (a.k.a. machine learning models) are ubiquitous in all stages of drug research, safety, development, manufacturing, and marketing. The results of these models are used inside and outside of pharmaceutical companies for the purpose o...
PatentNetML: A Novel Framework for Predicting Key Compounds in Patents Using Network Science and Machine Learning.
Journal of medicinal chemistry
Jan 5, 2024
Patents play a crucial role in drug research and development, providing early access to unpublished data and offering unique insights. Identifying key compounds in patents is essential to finding novel lead compounds. This study collected a comprehen...
ChatGPT or LLM in next-generation drug discovery and development: pharmaceutical and biotechnology companies can make use of the artificial intelligence-based device for a faster way of drug discovery and development.
International journal of surgery (London, England)
Dec 1, 2023
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