Author(s): Rasmussen MA, ColdingJrgensen M, Hansen LT, Bro R
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Abstract AIMS: Evaluation of the utility of multivariate data analysis in early clinical drug development. METHODS: A multivariate chemometric approach was developed and applied for evaluating clinical laboratory parameters and biomarkers obtained from two clinical trials investigating recombinant human interleukin-21 (rIL-21) in the treatment of patients with malignant melanoma. The Phase I trial was an open-label, first-human dose escalation safety and tolerability trial with two separate dosing regimens; six cycles of thrice weekly (3/w) vs. three cycles of daily dosing for 5 days followed by 9 days of rest (5+9) in a total of 29 patients. The Phase II trial investigated efficacy and safety of the '5+9' regimen in 24 patients. RESULTS: From the Phase I trial, separate pharmacological patterns were observed for each regimen, clearly reflecting distinct properties of the two regimens. Relations between individual laboratory parameters were visualized and shown to be responsive to rIL-21 dosing. In particular, novel systematic pharmacological effects on liver function parameters as well as a bell-shaped dose-response relationship of the overall pharmacological effects were depicted. In validation of the method, multivariate pharmacological patterns discovered in the Phase I trial could be reproduced by the dataset from the Phase II trial, but not from univariate exploration of the Phase I trial. CONCLUSIONS: The new data analytical approach visualized novel correlations between laboratory parameters that points to specific pharmacological properties. This multivariate chemometric data analysis offers a novel robust, comprehensive and intuitive tool to reveal early pharmacological responses and guide selection of dose regimens.
This article was published in Br J Clin Pharmacol
and referenced in Journal of Clinical & Cellular Immunology