How to navigate the challenges of ML and AI in pharmaceutical R&D
Navigating the integration of machine learning (ML) and artificial intelligence (AI) in pharmaceutical R&D involves overcoming data management, quality, and expertise challenges to unlock their full potential in drug discovery, reveals Richard Lee, Director, Core Technology and Capabilities, ACD/Labs Published by Scientific Computing World Pharmaceutical companies are under constant pressure to innovate and bring new...
Benchtop NMR Spectroscopy for Quick and Easy Identification of Illicit Street Drugs with Database Software
Coupling benchtop NMR spectroscopy with the databasing capabilities of NMR Workbook Suite to boost illicit drug detection. This app note explores how this accessible, affordable, and automatable workflow enables seamless identification of highly cut street drug mixtures and can even detect derivatives or similar components—a valuable capability for New Psychoactive Substances (NPS) detection in forensic analysis....
How To Be a Spectral Superstar—Structure Verification Made Easy
If your primary goal in analyzing NMR, LC/MS, or other types of analytical data is to answer questions such as “Did I make what I think I made?” or “How clean is my product?” then this webinar is for you! You might often find yourself using various analytical techniques to confirm, identify, and characterize chemical...
The Importance of Digitalization in Pharmaceutical R&D
In this episode, ACD/Labs Vice President of Innovation and Informatics Strategy, Andrew Anderson, and Strategic Partnerships Director, Graham McGibbon continue their discussion on digitalization and digital transformation in the context of pharmaceutical R&D. They assess how well the industry is adapting to the current digital landscape, and what can be done to contribute to the...
Software-assisted Process for Efficient and Expedited Development of Chromatographic Methods (SPEED-CHROM)
Jens Richards from Corteva Agriscience shares how the company’s SPEED-CHROM initiative aided in increasing the confidence and productivity of a young team with minimal industry experience. Find out how leveraging predictive modelling, using optimized instrumentation, and ensuring efficient communication can result in significantly faster and more accurate method development.
Retention Modelling: Principles, advantages and potential pitfalls to avoid
Technical Laboratory Supervisor from Shimadzu, Jen Field, discusses the principles, benefits, and challenges of retention modelling in chromatography, highlighting its advantages in streamlining method development by optimizing separations, reducing experimental workload, and saving resources. In the presentations, Jen shares practical tips to improve model accuracy with the aid of software tools such as ACD/Labs Method...
Using ACD/Labs’ ASV: Comparing compounds and using additional information and data
Identifying the correct structural isomer resulting from a reaction can be a challenge for automated structure verification (ASV) systems and chemists alike. Learn how AstraZeneca is optimizing their ASV workflow and incorporating reaction prediction tools and IR data to efficiently and accurately identify their reaction products.