uu.seUppsala University Publications
Change search
Link to record
Permanent link

Direct link
BETA
Lacroix, B. D.
Alternative names
Publications (3 of 3) Show all publications
Lacroix, B., Karlsson, M. & Friberg, L. (2014). Simultaneous Exposure-Response Modeling of ACR20, ACR50, and ACR70 Improvement Scores in Rheumatoid Arthritis Patients With Certolizumab Pegol. CPT Pharmacometrics and Systems Pharmacology, 3(10), 1-11
Open this publication in new window or tab >>Simultaneous Exposure-Response Modeling of ACR20, ACR50, and ACR70 Improvement Scores in Rheumatoid Arthritis Patients With Certolizumab Pegol
2014 (English)In: CPT Pharmacometrics and Systems Pharmacology, ISSN 2163-8306, Vol. 3, no 10, p. 1-11Article in journal (Refereed) Published
Abstract [en]

The Markovian approach has been proposed to model ACR response (ACR20, ACR50 or ACR70) reported in rheumatoid arthritis clinical trials to account for the dependency of the scores over time. However, dichotomizing the composite ACR assessment discards much information. Here we propose a new approach for modeling together the 3 thresholds: a continuous-time Markov exposure-response model was developed, based on data from 5 placebo-controlled certolizumab pegol clinical trials. This approach allows adequate prediction of individual ACR20/50/70 time-response, even for non-periodic observations. An exposure-response was established over a large range of licensed and unlicensed doses including phase II dose-ranging data. Simulations from the model (50 to 400 mg every other week) illustrated the range and sustainability of response (ACR20: 56 to 68%, ACR50: 27 to 42%, ACR70: 11 to 22% at week 24) with maximum clinical effect achieved at the recommended maintenance dose of 200 mg every other week.

Place, publisher, year, edition, pages
Nature Publishing Group: , 2014
Keywords
Rheumatoid arthritis, ACR, ACR20, ACR50, ACR70, exposure-response modeling, Markov, certolizumab pegol
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy; Pharmaceutical Science; Pharmacology
Identifiers
urn:nbn:se:uu:diva-247891 (URN)10.1038/psp.2014.41 (DOI)
Available from: 2015-03-25 Created: 2015-03-25 Last updated: 2018-01-11Bibliographically approved
Lacroix, B. D., Friberg, L. E. & Karlsson, M. O. (2012). Evaluation of IPPSE, an alternative method for sequential population PKPD analysis. Journal of Pharmacokinetics and Pharmacodynamics, 39(2), 177-193
Open this publication in new window or tab >>Evaluation of IPPSE, an alternative method for sequential population PKPD analysis
2012 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 39, no 2, p. 177-193Article in journal (Refereed) Published
Abstract [en]

The aim of this study is to present and evaluate an alternative sequential method to perform population pharmacokinetic-pharmacodynamic (PKPD) analysis. Simultaneous PKPD analysis (SIM) is generally considered the reference method but may be computationally burdensome and time consuming. Evaluation of alternative approaches aims at speeding up the computation time and stabilizing the estimation of the models, while estimating the model parameters with good enough precision. The IPPSE method presented here uses the individual PK parameter estimates and their uncertainty (SE) to propagate the PK information to the PD estimation step, while the IPP method uses the individual PK parameters only and the PPP&D method utilizes the PK data. Data sets (n = 200) with various study designs were simulated according to a one-compartment PK model and a direct Emax PD model. The study design of each dataset was randomly selected. The same PK and PD models were fitted to the simulated observations using the SIM, IPP, PPP&D and IPPSE methods. The performances of the methods were compared with respect to estimation precision and bias, and computation time. Estimated precision and bias for the IPPSE method were similar to that of SIM and PPP&D, while IPP had higher bias and imprecision. Compared with the SIM method, IPPSE saved more computation time (61%) than PPP&D (39%), while IPP remained the fastest method (86% run time saved). The IPPSE method is a promising alternative for PKPD analysis, combining the advantages of the SIM (higher precision and lower bias of parameter estimates) and the IPP (shorter run time) methods.

Keywords
PKPD analysis, NONMEM 7, IPPSE, PPP&D, IPP
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-173323 (URN)10.1007/s10928-012-9240-x (DOI)000301865700005 ()
Available from: 2012-04-24 Created: 2012-04-23 Last updated: 2018-01-12Bibliographically approved
Lacroix, B. D., Lovern, M. R., Stockis, A., Sargentini-Maier, M. L., Karlsson, M. .. .. & Friberg, L. E. (2009). A pharmacodynamic Markov mixed-effects model for determining the effect of exposure to certolizumab pegol on the ACR20 score in patients with rheumatoid arthritis. Clinical Pharmacology and Therapeutics, 86(4), 387-395
Open this publication in new window or tab >>A pharmacodynamic Markov mixed-effects model for determining the effect of exposure to certolizumab pegol on the ACR20 score in patients with rheumatoid arthritis
Show others...
2009 (English)In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 86, no 4, p. 387-395Article in journal (Refereed) Published
Abstract [en]

The American College of Rheumatology (ACR) 20% preliminary definition of improvement in rheumatoid arthritis (RA) (ACR20) is widely used in clinical trials to assess response to treatment. The objectives of this analysis were to develop an exposure-response model of ACR20 in subjects receiving treatment with certolizumab pegol and to predict clinical outcomes following various treatment schedules. At each visit, subjects were classified as being ACR20 responders or ACR20 nonresponders or as having dropped out. A Markov mixed-effects model was developed to investigate the effects of the drug on the transitions between the three defined states. Increasing certolizumab pegol exposure predicted an increasing probability of becoming a responder and remaining a responder, as well as a reduced probability of dropping out of treatment. Data from simulations of the ACR20 response rate support the use of dosing regimens of 400 mg at weeks 0, 2, and 4 followed by 200 mg every 2 weeks, or an alternative maintenance regimen of 400 mg every 4 weeks.

National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-120653 (URN)10.1038/clpt.2009.136 (DOI)000270303500016 ()19626001 (PubMedID)
Available from: 2010-03-15 Created: 2010-03-15 Last updated: 2018-01-12
Organisations

Search in DiVA

Show all publications