Medicinal Plants
Traditional use, evaluated in modern terms
Medicinal plants come with a long record of use. That record can inform a judgement about safety, but it is not evidence of a particular function. Closing that gap is the work in this area.
Approach
The traditional literature is a source of hypotheses, not of conclusions. We translate those hypotheses into measurable variables and build a design capable of testing them.
Principal considerations
Define what is being tested, first
- Botanical name of the source plant, part used, origin and time of harvest
- How extraction solvent and conditions change the compositional profile
- Selection of marker compounds and their quantification, by HPLC or equivalent
- Batch uniformity — whether a single specification can be maintained for the whole study
A human trial on a material without a defined specification cannot attribute its result to that material, and is difficult to use as approval data.
Layers of safety evidence
- History of dietary use — record of use as a food and the range of intake
- Existing toxicity data — single and repeat dose, genotoxicity
- Interactions — reported interactions with drugs or materials likely to be taken concomitantly
- Special populations — exclusion criteria for pregnancy and lactation, children, chronic illness
Where safety data are sparse, inclusion criteria and the monitoring plan are designed more conservatively.
What to measure, and how much
- Translating the traditional purpose into a modern endpoint (for example 'restores energy' into a validated fatigue questionnaire plus biochemical markers)
- One clearly defined primary endpoint, with everything else as secondary
- Instruments with established validity — a questionnaire developed in-house is unlikely to be accepted as evidence
- For combination preparations, whether the design can separate the contribution of individual components
Working with combination preparations
Preparations combining several medicinal plants are common traditionally but awkward in study design, because the contribution of each component cannot be separated.
- Treat the combination itself as a single material with a fixed specification — the usual route for approval applications.
- Rely on prior data evaluating the principal components individually.
- Use a factorial design to separate the combination effects — which increases the sample size considerably.
Which route is appropriate depends on the intended deliverable (approval, publication or internal data). We settle it together at the consultation stage.
KGHCRI is not a medical institution and does not provide diagnosis, treatment or prescription. The content of this site is provided for research information purposes and does not claim that any product prevents or treats disease.