Safety assessment of protein A and derivation of a parenteral health-based exposure limit.

Protein A (PA) is a bacterial cell wall component of Staphylococcus aureus whose function is to bind to Immunoglobulin G (IgG). Given its ability to bind IgG as well as its stability and resistance to harsh acidic and basic cleaning conditions, it is commonly used in the affinity chromotography purification of biotherapeutics. This use can result in levels of PA being present in a drug product and subsequent patient exposure.

Quantum-Mechanics Calculations Elucidate Skin-Sensitizing Pharmaceutical Compounds.

Skin sensitization is a critical end point in occupational toxicology that necessitates the use of fast, accurate, and affordable models to aid in establishing handling guidance for worker protection. While many in silico models have been developed, the scarcity of reliable data for active pharmaceutical ingredients (APIs) and their intermediates (together regarded as pharmaceutical compounds) brings into question the reliability of these tools, which are largely constructed using publicly available nonspecialty chemicals. Here, we present the quantum-mechanical (QM) Computer-Aided Discovery and REdesign (CADRE) model, which was developed with the bioactive and structurally complex chemical space in mind by relying on the fundamentals of chemical interactions in key events (versus structural attributes of training-set data).

Harmonisation of read-across methodology for drug substance extractables and leachables (E&Ls).

Health-based exposure limits (HBELs) are derived for leachables from polymeric components that interact with the drug substance which exceed a safety concern threshold (SCT). However, given the nature of leachables, there is not always chemical-specific toxicology data. Read-across methodology specific to extractables and leachables (E&Ls) was developed based on survey data collected from 11 pharmaceutical companies and methodology used in other industries.

Improvements to in silico skin sensitisation predictions through privacy-preserving data sharing.

In silico models are often built solely on publicly available data which may mean that they are less predictive for proprietary chemical space. Data sharing initiatives can improve the performance of such models, but organisations are often unable to share their data due to the need to protect their business interests and maintain the confidentiality of the chemicals in their research and development programmes. In silico models like Derek Nexus, which use expert knowledge to develop structural alerts based on chemical toxicity, can use proprietary data to identify new areas of chemical space and/or refine existing alerts whilst still preserving the privacy of the confidential data.

An Evaluation of the Occupational Health Hazards of Peptide Couplers.

Peptide couplers (also known as amide bond-forming reagents or coupling reagents) are broadly used in organic chemical syntheses, especially in the pharmaceutical industry. Yet, occupational health hazards associated with this chemical class are largely unexplored, which is disconcerting given the intrinsic reactivity of these compounds. Several case studies involving occupational exposures reported adverse respiratory and dermal health effects, providing initial evidence of chemical sensitization.