Cholecystokinin, Glucagon and Ghrelin ELISA
While insulin and many other hormones have been accurately measured routinely since decades, there are ongoing technical challenges with others. Cholecystokinin, glucagon
and ghrelin are among the most challenging to date. We have published experience in working with these hormones, including establishing our own assays and modifying
commercial kits and reagents. The path taken is determined by the needs of each study. How these hormones were measured 20 years ago may not even be publishable today.
As a result, these are typically custom assays, exploiting latest reagents and published knowledge.
Digestive Enzymes
There is an unmet need for assays of digestive enzyme activity for the next generation of pancreatic enzyme replacement therapy (PERT) drugs. We have a long history in enzymology, and it turned out that PERT investigations are a good match for our resources. Although new, enzyme assays of PERT drug activity are now up and running. This is rapidly evolving. New drugs are in the pipeline and new assays are being developed to study them. Modern PERT formulations have complex physical properties that must be accommodated.
Agriculture and Food
We have a long history of collaborations within agricultural and food industries. Aside from nutrition and obesity studies, we are equipped to measure plant hormones, such as gibberellin 3A (GA3), which must be tested for regulatory compliance during malt brewing and following treatment of seedless grapes. Amino acid production is increasing in EU and this too needs testing. High GA3 residue concentration is toxic and proinflammatory, whereas amino acid supplements are needed for hogs (lysine) and chickens (methionine).
Data Analysis and R Programming
Raw data typically needs to be processed before release. Examples of our work can be found across all our publications. In addition to most commercial statistics software, we can process data in FORTRAN, C and R programming language. We are pleased to have our first paper of 2026 published with an R code supplement to investigate p-value decline with increased sample size in survival data (Björner K et al, Upsala J Med Sci. 13250. 2026).
