Format

Send to

Choose Destination
J Pharmacokinet Pharmacodyn. 2016 Apr;43(2):123-35. doi: 10.1007/s10928-016-9464-2. Epub 2016 Feb 2.

Methods and strategies for assessing uncontrolled drug-drug interactions in population pharmacokinetic analyses: results from the International Society of Pharmacometrics (ISOP) Working Group.

Author information

1
Astellas, 1 Astellas Way, Northbrook, IL, 60062, USA. peter.bonate@astellas.com.
2
Merck and Co. Inc., 351 N Sumneytown Pike, North Wales, PA, 19454, USA.
3
Genentech Inc., 1 DNA Way, South San Francisco, CA, 94080, USA.
4
Eli Lilly and Company|Chorus, Lilly Corporate Center, Indianapolis, IN, 46285, USA.
5
U.S. Food and Drug Administration, 10903 New Hampshire Ave., Bldg 51, Room 3154, Silver Spring, MD, 20993, USA. justin.earp@fda.hhs.gov.
6
Novartis Pharmaceuticals Corporation, One Health Plaza, East Hanover, NJ, 07936, USA.
7
Uppsala University, Box 591, 75124, Uppsala, Sweden.
8
Boehringer Ingelheim Pharmaceutical Inc., 900 Ridgebury Road, Ridgefield, CT, 06877, USA.
9
Pfizer, 10646 Science Center Dr. CB10 Office 2448, San Diego, CA, 92121, USA.
10
Parexel International, Inc., 2520 Meridian Parkway, Durham, NC, 27713, USA.
11
Occams Coöperatie U.A., Malandolaan 10, 1187 HE, Amstelveen, The Netherlands.

Abstract

The purpose of this work was to present a consolidated set of guidelines for the analysis of uncontrolled concomitant medications (ConMed) as a covariate and potential perpetrator in population pharmacokinetic (PopPK) analyses. This white paper is the result of an industry-academia-regulatory collaboration. It is the recommendation of the working group that greater focus be given to the analysis of uncontrolled ConMeds as part of a PopPK analysis of Phase 2/3 data to ensure that the resulting outcome in the PopPK analysis can be viewed as reliable. Other recommendations include: (1) collection of start and stop date and clock time, as well as dose and frequency, in Case Report Forms regarding ConMed administration schedule; (2) prespecification of goals and the methods of analysis, (3) consideration of alternate models, other than the binary covariate model, that might more fully characterize the interaction between perpetrator and victim drug, (4) analysts should consider whether the sample size, not the percent of subjects taking a ConMed, is sufficient to detect a ConMed effect if one is present and to consider the correlation with other covariates when the analysis is conducted, (5) grouping of ConMeds should be based on mechanism (e.g., PGP-inhibitor) and not drug class (e.g., beta-blocker), and (6) when reporting the results in a publication, all details related to the ConMed analysis should be presented allowing the reader to understand the methods and be able to appropriately interpret the results.

KEYWORDS:

Concomitant; Covariate modeling; Drug interactions; Medications; Population pharmacokinetics

PMID:
26837775
DOI:
10.1007/s10928-016-9464-2
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center