BSC Webinar: An In-Silico Method To Predict Cardiotoxicity In Botanical Substances

The HESI Botanical Safety Consortium will host a webinar on Tuesday November 29 at 11 am ET from Dr. Jeremy Billson (InoCardia) entitled “An In-Silico Method To Predict Cardiotoxicity In Botanical Substances”. This work is a pilot project, using a predictive model for cardiovascular liabilities with botanical constituents. On the webinar Jeremy will walk through the model, our preliminary results, and will have time for questions and discussion of next steps.

Abstract:
Many botanicals are biologically active and are used to derive pharmaceuticals. Early-stage and easily accessible methods of identifying unwanted bioactivity/side-effects/toxicities in botanical constituents are required to induce better safety pharmacology practices. InoCardia’s in silico assay predicts CV-toxicity by identifying the similarity between the characterised constituent contained within its database and a test constituent. Given the database contains many pharmaceuticals derived from nature, we wondered if this could form the basis of a simple, reliable and accessible tool to identify CV-toxicity in botanicals.

Experts identified a set of known botanical constituents documented to elicit a cardiovascular response in humans. An additional set containing constituents considered to be CV-effect free was also identified. Samples from each set were assessed in InoCardia’s in silico assay and hits flagged according to their risk of CV-effects & potential toxicity.17 botanical constituents known to elicit a cardiovascular response in humans were assessed. Within the set, (i) 12 were flagged as ‘Positive’ – meaningfully likely to elicit a CV response in man, (ii) 0 were flagged as ‘Negative’ - meaningfully unlikely to elicit a CV response (0 false negatives) and (iii) 5 were flagged as ‘No Significant Result’ – these botanicals had no meaningfully similar partner in the structure database and so no prediction could be made.

The increasing power of in silico and AI methods is driving change and disrupting established work-patterns. Here we demonstrate the use of an in silico method to quickly identify botanicals with potential CV liabilities. Such assays are faster, more accessible, lower-cost and animal use sparing compared to conventional in vitro and in vivo methods.

The meeting will be recorded and is open to all. Link to join is below.

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