mittyri ★★ Russia, 20200927 16:25 (63 d 05:33 ago) Posting: # 21943 Views: 377 

Dear All, some time ago I discovered the difference between PHX and 'PK' package in R regarding lambda_z calculation for sparse dataset analysis. My question is which one looks more reasonable for you  PHX gets means of concs and then logtransforms it to prepare for regression analysis  PK gets logs and then calculates means for that logs to prepare for regression analysis what do you think? — Kind regards, Mittyri 
martin ★★ Austria, 20200928 06:40 (62 d 15:19 ago) (edited by martin on 20200928 06:50) @ mittyri Posting: # 21945 Views: 318 

Dear mittyri, The methods implemented in the R package PK are based on methods published in peer reviewed journals such as Noncompartmental estimation of pharmacokinetic parameters in serial sampling designs or here Noncompartmental estimation of pharmacokinetic parameters for flexible sampling designs based on logtransformation of individual values to estimate lambda_z. The rationale for logtransforming the indivdual values is that based on this approach the variancecovariance matrix can account for values both used for derving the AUC0t as well lambda_z used to estimate the AUC from t to infinity. I am not aware of a publication which justifies calculation of lambda_z in case of sparse sampling based on means only as implemented in PHX. In addition, attention should be paid to handling to values <LLOQ where you may find this paper of interest Methods for NonCompartmental Pharmacokinetic Analysis With Observations Below the Limit of Quantification. best regards & hope this helps martin PS.: I would like to use the opportunity to illustrate how important adequate handling of BLQ values are by using a theoretical example. Consider a serial sampling design (N=5 animals per time point) where all but one value is BLQ at the last time point and think about estimation of t1/2. Ignoring BLQ values at the last time point for 4 out of 5 animals will lead to a overestimated population t1/2 as the last time point is just driven by a single animal. The same is when you set BLQ values to zero as estimation of t1/2 requires some logtransformation and log of 0 is not defined and is therefore equivalent to omitting those BLQ values. 
mittyri ★★ Russia, 20201006 10:31 (54 d 11:28 ago) @ martin Posting: # 21972 Views: 206 

Dear Martin, I appreciate all the work was done for sparse analysis by you and your colleagues. I just have 2 suggestions regarding PK package:  is it possible to estimate lambda_z, not providing n.tail argument?  is it possible to specify for the group argument of 'eqv()' function what which one is the test and which one is the reference? — Kind regards, Mittyri 