Applying AI Across All Stages of Drug Development
To learn more about the application of AI across all stages of development, from drug design to clinical trials, Technology Networks spoke with Dr. Yuan Wang, head of research analytics at UCB.
How To Guide
How To Reduce Data Integrity Risk
The aim of this guide is to provide practical advice on how to reduce data integrity risk and ensure GxP compliance. Learn from those in the industry who have failed to comply with data integrity regulations and who have been on the receiving end of an FDA inspection.
Wearable Parkinson’s Monitor Uses AI To Detect Symptoms
Study shows wearable Parkinson’s monitor, which uses machine learning to detect and assess motor symptoms, is more than 95% accurate when compared to expert evaluation.
Microbes Are Essential for Determining How Much Carbon Is Stored in the Soil
Microbes are by far the most important factor in determining how much carbon is stored in the soil, which has implications for mitigating climate change and improving soil health for food production.
Deep Learning Aids Development of Super-Resolution Ultrasound
Researchers at the Beckman Institute for Advanced Science and Technology used deep learning to develop a new framework for super-resolution ultrasound.
Multidimensional Mass Spectrometry and Machine Learning: A Recipe for Richer Metabolomics
A new metabolomics workflow has been developed that combines state-of-the-art analytical instrumentation, which generates information-rich data, with a novel machine learning-based algorithm tailored to process it.
Improving Time-to-Value for GxP Computer Systems
Jim Brooks shares top tips to overcome the biggest validation challenges and best practices for building and implementing a digital process data strategy to lead to smarter and faster validation.
The Role of Smart Technology in Mitigating the Risk of Human Error and Improving Productivity in Pharmaceutical Quality Control
In this article, discover the role HPLC plays in ensuring regulatory compliance and reliability of throughput, and how labs can automate to eliminate errors and build reliability into their processes.
How To Guide
Revolutionary Binding Kinetics Analysis
Conventional bioassays often require labeled detection reagents to provide a measurable readout. However, modifications to molecular structure and/or function can skew results, and non-specific binding of the labels themselves can lead to an unwanted background signal.
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Exploring Bioinformatics for Genomic and Transcriptomic Sequencing Data
Download this guide to discover what you need for whole genome sequencing analysis, what you need for RNA sequencing analysis and how to analyze each type of data.
Ten Guidelines for Adopting Ontologies To Create FAIRer Scientific Data
Deciding to implement ontologies into your data management practices can be daunting and a difficult sell to business stakeholders. This article outlines the challenges and offers 10 guidelines for kickstarting your ontologies journey.
Standardizing Analytical Data With AnIML
This listicle presents AnIML — an open XML-based, vendor-neutral and human-readable file format that can be used to store data from different analytical instruments. This facilitates the achievement of FAIR (i.e., findable, accessible, interoperable and reusable) data which is a prerequisite for proper data management, data stewardship and a successful digital transformation strategy.