Risk and benefit asssessment

 

Vanilla pods and orchid flower isolated on white backgroundIndustry, regulators and other stakeholders are often challenged to analyse the risks as well as benefits of botanicals used in plant food supplements.

PlantLIBRA developed a methodology for risk assessment that integrates compound-based information with composition data, preparation-level evidence, and history-of-use to provide an informative evidence-based assessment, which is compatible with the methodologies proposed by authorities worldwide.

Grading of evidence allows effective decision-making, and helps direct further research. Different risk assessment approaches – from the margin of exposure to the threshold of toxicological concern – are combined to maximise the information derived from datasets. Adverse events are  retrieved systematically, using grey literature (when applicable) and thoroughly analysed for causality.

PlantLIBRA risk assessments of botanicals have been developed using an interactive Wiki-based platform, allowing multidisciplinary work by a broad set of experts.

Using ePlantLIBRA, assessments for botanicals can be rapid or in-depth. PlantLIBRA botanicals benefit assessments are based on the totality of evidence; simultaneously and rigorously addressing different regulatory thresholds from those based on human randomised clinical trials (RCT) to those used more traditionally. They also help identify and quantify data gaps.

QuinoaSystematic review of the literature about botanicals underpins risk and benefit assessments. PlantLIBRA’s methodology means comprehensive reviews can be performed or updated quickly as well as providing a stand-alone service.

Case study 

Problem: there was wide concern that some botanical preparations contain genotoxic compounds, and should be banned from the market.

ePlantLIBRA: we conducted an in-depth analysis of published composition data, simulated various potential compositional combinations, and concluded the compounds of concern can be kept at very low or non-detectable levels. It is, however, an issue that needs to be managed carefully but, in most cases, a ban was not necessary.