Performance characteristics of the adjusted r 2 algorithm for determining the start of the terminal disposition phase and comparison with a simple r 2 algorithm and a visual inspection method

• Published in: Pharmaceutical statistics : the journal of the pharmaceutical industry Vol. 19; no. 2; pp. 88 - 100
• Main Author: Noe, Dennis A.
• Format: Journal Article
• Language: English
• Published: England 01.03.2020
• Subjects: Algorithms; Chemistry, Pharmaceutical - methods; Chemistry, Pharmaceutical - standards; Pharmacokinetics; Phase Transition; pharmacokinetics; noncompartmental data analysis (NCA); terminal disposition phase; adjusted r2 algorithm
• ISSN: 1539-1604; 1539-1612
• DOI: 10.1002/pst.1979

The adjusted r 2 algorithm is a popular automated method for selecting the start time of the terminal disposition phase ( t z ) when conducting a noncompartmental pharmacokinetic data analysis. Using simulated data, the performance of the algorithm was assessed in relation to the ratio of the slopes of the preterminal and terminal disposition phases, the point of intercept of the terminal disposition phase with the preterminal disposition phase, the length of the terminal disposition phase captured in the concentration‐time profile, the number of data points present in the terminal disposition phase, and the level of variability in concentration measurement. The adjusted r 2 algorithm was unable to identify t z accurately when there were more than three data points present in a profile's terminal disposition phase. The terminal disposition phase rate constant ( λ z ) calculated based on the value of t z selected by the algorithm had a positive bias in all simulation data conditions. Tolerable levels of bias (median bias less than 5%) were achieved under conditions of low measurement variability. When measurement variability was high, tolerable levels of bias were attained only when the terminal phase time span was 4 multiples of t 1/2 or longer. A comparison of the performance of the adjusted r 2 algorithm, a simple r 2 algorithm, and t z selection by visual inspection was conducted using a subset of the simulation data. In the comparison, the simple r 2 algorithm performed as well as the adjusted r 2 algorithm and the visual inspection method outperformed both algorithms. Recommendations concerning the use of the various t z selection methods are presented.