Emmanuel Orman

University of Health and Allied Sciences | UHAS · School of Pharmacy

I am conducting a study to assess the quality of selected parts of some herbal materials and also develop acceptance criteria for their quality attributes. I am supposed to sample these materials from across the length and breadth of the country and I am hoping to stratify the country into strata and further divide each stratum into clusters, and then randomly sample the materials from each of the clusters picked up through systematic sampling.

My challenge is with the calculation of a 'realistic' sample size that can then be used to determine the number of clusters and the number of samples from each cluster. Very often what I see in literature tends to be convenient sampling, which may not be representative of the population. The focus of my study however requires that my sampling is representative of the population in the country (and also realistic), especially because of the part that has to do with setting acceptance criteria.

I would be very grateful for your technical assistance. Thank you.

If i used different general purpose media, Tryptone Soy Agar, Nutrient Agar and Plate Count Agar to culture microbial contaminants in a product, how significant will the enumerations be from each other?

Having reviewed literature on the use of chemometric approaches in quality assessments of medicines (including herbal medicines), I realised that several approaches are adopted. For example, in preprocessing of the data for further analysis, literature reports of methods like normalisation, peak centering, warping, smoothing among others.

Having in mind that the way you preprocess the data may affect the final outcome of the multivariate analysis, I want to find out if there exist any protocol guiding the adoption of any of these tools. For instance, when analysing chromatographic data from HPLC, you may have to correct baseline, then warp and normalise or something. Also, when dealing with FTIR data, you may have to first correct baseline, normalise and smooth (how do you determine the smoothing points?) among others. Are there specific preprocessing tools for specific datasets (that is from different instruments like FTIR, HPLC, LC-MS, etc) and are there specific procedures for the use of such, so that irrespective of who is conducting such analysis, the outcome may always be reproducible?

Thank you.

Having reviewed literature on the use of chemometric approaches in quality assessments of medicines (including herbal medicines), I realised that several approaches are adopted. For example, in preprocessing of the data for further analysis, literature reports of methods like normalisation, peak centering, warping, smoothing among others.

Having in mind that the way you preprocess the data may affect the final outcome of the multivariate analysis, I want to find out if there exist any protocol guiding the adoption of any of these tools. For instance, when analysing chromatographic data from HPLC, you may have to correct baseline, then warp and normalise or something. Also, when dealing with FTIR data, you may have to first correct baseline, normalise and smooth (how do you determine the smoothing points?) among others. Are there specific preprocessing tools for specific datasets (that is from different instruments like FTIR, HPLC, LC-MS, etc) and are there specific procedures for the use of such, so that irrespective of who is conducting such analysis, the outcome may always be reproducible?

Thank you.