Welcome to the CBS 130 – Use of machine learning to predict the RF values
In this latest issue of the CAMAG Bibliography Service, we present an innovative concept combining the lately introduced complementary development solvents concept (CDS) with machine learning which effectively allows the prediction of the RF values and might have the potential to become the future of HPTLC data analysis.
Presented applications from customers worldwide comprise:
- Extractable and leachable studies of pharmaceutical products packed in plastics
- Detection and quantification of 5-hydroxymethylfurfural in honey
- Stability testing of dihydroartemisinin
- HPTLC-based fingerprinting of fructooligosaccharides
Enjoy reading!