TY - JOUR
T1 - Multivariate evaluation of pharmacological responses in early clinical trials
T2 - a study of rIL-21 in the treatment of patients with metastatic melanoma
AU - Rasmussen, Morten Arendt
AU - Colding-Jørgensen, Morten
AU - Hansen, Lasse Tengbjerg
AU - Bro, Rasmus
PY - 2010/4
Y1 - 2010/4
N2 - WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Analysis of data from clinical trials is often performed using univariate statistics. • In early phases of clinical drug development, interpretation of rare clinical events can be difficult by univariate methods. • Principal component analysis has proven successful within related scientific areas such as, for example, genomics and metabonomics, where compression of data and extraction of maximum information are of utmost importance. WHAT THIS STUDY ADDS • This study reveals that multivariate chemometric methods coupled with visualization gives a comprehensive overview of early clinical trial data to guide dose and regimen selection and provides additional findings overlooked by traditional univariate methods. • This method revealed novel pharmacological patterns in the treatment of metastatic melanoma with recombinant interleukin-21. 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.
AB - WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Analysis of data from clinical trials is often performed using univariate statistics. • In early phases of clinical drug development, interpretation of rare clinical events can be difficult by univariate methods. • Principal component analysis has proven successful within related scientific areas such as, for example, genomics and metabonomics, where compression of data and extraction of maximum information are of utmost importance. WHAT THIS STUDY ADDS • This study reveals that multivariate chemometric methods coupled with visualization gives a comprehensive overview of early clinical trial data to guide dose and regimen selection and provides additional findings overlooked by traditional univariate methods. • This method revealed novel pharmacological patterns in the treatment of metastatic melanoma with recombinant interleukin-21. 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.
U2 - 10.1111/j.1365-2125.2009.03600.x
DO - 10.1111/j.1365-2125.2009.03600.x
M3 - Journal article
C2 - 20406222
SN - 0264-3774
VL - 69
SP - 379
EP - 390
JO - British Journal of Clinical Pharmacology, Supplement
JF - British Journal of Clinical Pharmacology, Supplement
IS - 4
ER -