(Quantitative) Structure-Activity Relationships ((Q)SAR)
Our work
It is very common to find gaps in physico-chemical and (eco)toxicological data sets, which preclude confident hazard and risk assessment. Testing on vertebrate animals has ethical concerns across all sectors, and is banned for cosmetics marketed in Europe. Laboratory animal studies are in any case often undesirable for more mundane reasons such as time and costs. Where possible, we strive to help clients fill data gaps without a potentially costly and animal-intensive trip to the testing laboratory.
Computer models have been developed to predict the toxicological characteristics of an untested compound based on knowledge of the activity of others. (Q)SAR modelling is gaining regulatory acceptance. Indeed, in some sectors (Q)SAR analysis is a requirement. It can also be used as a screening exercise to inform a company on whether laboratory testing is scientifically justified.
Interpretation
Our vast experience in applying these toxicity models is matched by our expertise in interpreting the results. The limitations of (Q)SAR models must be understood and described, and the results should be applied appropriately. (Q)SAR results should always be interpreted in the context of any literature identified in searches of databases such as bibra’s own TRACE. Our toxicologists perform robust sanity checks on all of the outputs to ensure that predictions are sensible and consistent with our on-the-job knowledge and expectations.
Expertise/Leadscope
Bibra is an expert consulting partner of Leadscope, which we use frequently in-house, including for the evaluation of DNA-reactive compounds (particularly pharmaceutical impurities), in accordance with ICH guidance M7. Toxicology Director, Pete Watts and Senior Toxicologist, Chris Waine, are regular contributors to Leadscope’s continuing development through participation in working groups, and have been involved in several publications in the peer-reviewed literature.
Models
Our in-house team and expert partners can generate (Q)SAR predictions using a range of in silico models, including:
Helpful links
In silico toxicology protocols
Myatt et al. 2018: Regulatory Toxicology and Pharmacology (volume 96)
Genetic toxicology in silico protocol
Hasselgren et al. 2019: Regulatory Toxicology and Pharmacology (volume 107)
Some of our case studies in this area
Bisphenol A (BPA) Controversy
Blog articles
It is a truth not always recognised that toxicological hazard and risk assessment as currently practiced is a ball-park science, and a health criteria value – a Tolerable Daily Intake (TDI), a Permitted Daily Exposure (PDE) or similar – quoted to 2 significant figures is probably one significant figure more than the data really can confidently support. Occasionally practitioners will let the mask slip...
NAMs for NGRAs
Blog articles
Traditionally, toxicological risk assessment has involved identifying a point of departure (PoD) such as a NOAEL or LOAEL in a study of small creatures, adjusting it to be relevant to humans (to derive, for example, a TI or DNEL), and then calculating the margin of safety to a measured or estimated external exposure. As part of this process, toxicologists have to account for the uncertainties that arise in moving from the species, route and duration of the laboratory animal study to the real human world.
FDA memoranda: genotoxicity and carcinogenicity assessments of ENDS
Blog articles
As discussed in a previous blog post, the U.S. Food and Drug Administration (FDA) Center for Tobacco Products (CTP) has issued several “scientific policy memoranda” that provide some great insights into the Agency’s evaluation process. In June 2024, the FDA made two new memos available that relate to the genotoxicity and carcinogenicity assessment of chemical constituents of Electronic Nicotine Delivery Systems (ENDS).
