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Impurity Identification, Management, and Control

Develop quality pharmaceuticals and chemicals with ACD/Labs’ chemical prediction and impurity control software

“What’s that peak?”

A substance that you do not recognize is present in your product above the threshold of concern. Chemists of all types encounter this problem. What is this contaminant? What is its toxicity profile? How can I purify my final product?

What control strategy can I use to avoid this impurity?
ACD/Labs offers a catalog of software tools to assist with every step of your impurity management workflow. Our programs help you to characterize chemical structures, predict toxicity profiles, develop chromatography methods, manage process control data, and more.

Characterizing unknown compounds is challenging work. Our software allows you to use analytical data to quickly dereplicate and verify chemical structures. For novel compounds, use our applications to quantitatively evaluate the fit between a proposed structure and experimental spectra.

ACD/Labs is a world leader in structure elucidation and dereplication software, so you can identify your impurities with confidence.

  • Determine impurity identity from mass spectroscopy and NMR data
  • Perform de novo elucidation for complex unknown structures
  • Automatically sort and filter the best structure candidates based on structure/spectrum fit

It is not enough to identify an impurity’s structure; the next challenge is determining its safety profile. Even when a substance is below the threshold of concern you must demonstrate that it is safe.

Avoid weeks of work in the laboratory or expensive off-site testing. Use predictive software to determine the toxicological properties of novel compounds in a fraction of the time. ACD/Labs offers a state-of-the-art prediction platform to investigate your pharmaceutical and chemical impurities at the click of a button.

  • Predict mutagenicity, clastogenicity, carcinogenicity, endocrine disruption, and more
  • Save hundreds of hours of unnecessary biological assays
  • Use the predicted data as part of your ICH M7 submissions to regulators

Chromatography is essential for the proper quantification and separation of impurities. Unfortunately, chromatographic method development is often time-consuming and unsystematic, leaving your team with a method that is unreliable.

Take the guesswork out of method development. Streamline chromatographic methods by combining physicochemical property predictions with method optimization tools to efficiently generate robust separations.

  • Calculate logP, logD, and pKa to assist with chromatographic method development
  • Predict retention times for target compounds using groups of structurally similar molecules
  • Use simulations and resolution maps to identify the most robust conditions

Combining reaction engineering, synthetic chemistry, and chemical analytics to control impurities means using a variety of systems and then collating the data. Spreadsheets and PDFs are not designed to handle the analytical and process data your team needs.

With a chemistry manufacturing and controls (CMC) decision support tool, you can bring together data from across an organization into one piece of software, so your team can make decisions faster and focus on the science.

  • Simplify fate and purge experimental data management
  • Develop impurity control strategies using Quality by Design (QbD) principles
  • Improve product quality by connecting supply chain information with analytical data
Customer Reviews
“[The] Software provides a platform for the paperless flow of information from raw data files that has reduced data analysis cycle time from more than a week to less than a day.”

John Stafford
Eli Lilly

“We are generating knowledge too fast to stay in people’s heads. ACD/Labs has helped us create a repository of knowledge that doesn’t forget, doesn’t go senile, doesn’t retire, and doesn’t leave the company for a competitor.”

Steve Thomas
Scientific Leader, GSK

“An automated intelligence workflow was implemented that has led to enhanced integrity and quality of compounds submitted for biological testing.”

Philip Keyes
Lexicon Pharmaceuticals

“Clearly the industry-standard PhysChem prediction models and deserve the position. They are the most consistent predictions that are applicable and usable in more complex models of drug-likeness.”

Computational Chemist