RE: [NMusers] Variability on infusion duration
Thanks to you all. I am trying several of these approaches and will report back! Paul Hutson, PharmD, BCOP Professor UWisc School of Pharmacy T: 608.263.2496 F: 608.265.5421 -Original Message- From: owner-nmus...@globomaxnm.com On Behalf Of Bill Denney Sent: Wednesday, August 05, 2020 12:38 PM To: Leonid Gibiansky ; Patricia Kleiner ; nmusers@globomaxnm.com Subject: RE: [NMusers] Variability on infusion duration Similar to Leonid's solution, you can try using an exponential distribution: D1 = DUR*(1-EXP(-EXP(ETA(1 The exponential within an exponential gives left skew and ensures that D1 ≤ DUR. For subjects who you know had an incomplete infusion duration, I would add an indicator variable (1 if incomplete, 0 if full duration) so that the subjects with complete duration have the known complete duration. D1 = DUR*(1 - Incomplete*EXP(-EXP(ETA(1 Thanks, Bill -Original Message- From: owner-nmus...@globomaxnm.com On Behalf Of Leonid Gibiansky Sent: Wednesday, August 5, 2020 12:51 PM To: Patricia Kleiner ; nmusers@globomaxnm.com Subject: Re: [NMusers] Variability on infusion duration may be D1=DUR*EXP(ETA(1)) IF(D1.GT.DocumentedInfusionDuration) D1=DocumentedInfusionDuration On 8/5/2020 12:18 PM, Patricia Kleiner wrote: > Dear all, > > I am developing a PK model for a drug administered as a long-term > infusion of 48 hours using an elastomeric pump. End of infusion was > documented, but sometimes the elastomeric pump was already empty at > this time. Therefore variability of the concentration measurements > observed at this time is quite high. > To address this issue, I try to include variability on infusion > duration assigning the RATE data item in my dataset to -2 and model > duration in the PK routine. Since the "true" infusion duration can > only be shorter than the documented one, implementing IIV with a > log-normal distribution > (D1=DUR*EXP(ETA(1)) cannot describe the situation. > > I tried the following expression, where DUR ist the documented > infusion > duration: > > D1=DUR-THETA(1)*EXP(ETA(1)) > > It works but does not really describe the situation either, since I > expect the deviations from my infusion duration to be left skewed. I > was wondering if there are any other possibilities to incorporate > variability in a more suitable way? All suggestions will be highly > appreciated! > > > Thank you very much in advance! > Patricia > > >
Re: [NMusers] Variability on infusion duration
to estimate duration and fix in population model. Regards, Ayyappa On Aug 5, 2020, at 1:04 PM, Bill Denney wrote: Similar to Leonid's solution, you can try using an exponential distribution: D1 = DUR*(1-EXP(-EXP(ETA(1 The exponential within an exponential gives left skew and ensures that D1 ≤ DUR. For subjects who you know had an incomplete infusion duration, I would add an indicator variable (1 if incomplete, 0 if full duration) so that the subjects with complete duration have the known complete duration. D1 = DUR*(1 - Incomplete*EXP(-EXP(ETA(1 Thanks, Bill -Original Message- From: owner-nmus...@globomaxnm.com On Behalf Of Leonid Gibiansky Sent: Wednesday, August 5, 2020 12:51 PM To: Patricia Kleiner ; nmusers@globomaxnm.com Subject: Re: [NMusers] Variability on infusion duration may be D1=DUR*EXP(ETA(1)) IF(D1.GT.DocumentedInfusionDuration) D1=DocumentedInfusionDuration On 8/5/2020 12:18 PM, Patricia Kleiner wrote: Dear all, I am developing a PK model for a drug administered as a long-term infusion of 48 hours using an elastomeric pump. End of infusion was documented, but sometimes the elastomeric pump was already empty at this time. Therefore variability of the concentration measurements observed at this time is quite high. To address this issue, I try to include variability on infusion duration assigning the RATE data item in my dataset to -2 and model duration in the PK routine. Since the "true" infusion duration can only be shorter than the documented one, implementing IIV with a log-normal distribution (D1=DUR*EXP(ETA(1)) cannot describe the situation. I tried the following expression, where DUR ist the documented infusion duration: D1=DUR-THETA(1)*EXP(ETA(1)) It works but does not really describe the situation either, since I expect the deviations from my infusion duration to be left skewed. I was wondering if there are any other possibilities to incorporate variability in a more suitable way? All suggestions will be highly appreciated! Thank you very much in advance! Patricia
Re: [NMusers] Variability on infusion duration
500 >> Ayyappa Chaturvedula wrote: >> Hi Patricia, >> What is the purpose of your modeling exercise? I am not sure your scenario >> could be assigned to any particular distribution. If you intend to simulate >> population from the model, then your assumptions would not be reasonable. If >> you have rich data, you may try individual modeling approach to estimate >> duration and fix in population model. Regards, >> Ayyappa >>>> On Aug 5, 2020, at 1:04 PM, Bill Denney >>>> wrote: >>> Similar to Leonid's solution, you can try using an exponential distribution: >>> D1 = DUR*(1-EXP(-EXP(ETA(1 >>> The exponential within an exponential gives left skew and ensures that D1 ≤ >>> DUR. >>> For subjects who you know had an incomplete infusion duration, I would add >>> an indicator variable (1 if incomplete, 0 if full duration) so that the >>> subjects with complete duration have the known complete duration. >>> D1 = DUR*(1 - Incomplete*EXP(-EXP(ETA(1 >>> Thanks, >>> Bill >>> -Original Message- >>> From: owner-nmus...@globomaxnm.com On Behalf >>> Of Leonid Gibiansky >>> Sent: Wednesday, August 5, 2020 12:51 PM >>> To: Patricia Kleiner ; nmusers@globomaxnm.com >>> Subject: Re: [NMusers] Variability on infusion duration >>> may be >>> D1=DUR*EXP(ETA(1)) >>> IF(D1.GT.DocumentedInfusionDuration) D1=DocumentedInfusionDuration >>>>> On 8/5/2020 12:18 PM, Patricia Kleiner wrote: >>>> Dear all, >>>> I am developing a PK model for a drug administered as a long-term >>>> infusion of 48 hours using an elastomeric pump. End of infusion was >>>> documented, but sometimes the elastomeric pump was already empty at >>>> this time. Therefore variability of the concentration measurements >>>> observed at this time is quite high. >>>> To address this issue, I try to include variability on infusion >>>> duration assigning the RATE data item in my dataset to -2 and model >>>> duration in the PK routine. Since the "true" infusion duration can >>>> only be shorter than the documented one, implementing IIV with a >>>> log-normal distribution >>>> (D1=DUR*EXP(ETA(1)) cannot describe the situation. >>>> I tried the following expression, where DUR ist the documented >>>> infusion >>>> duration: >>>> D1=DUR-THETA(1)*EXP(ETA(1)) >>>> It works but does not really describe the situation either, since I >>>> expect the deviations from my infusion duration to be left skewed. I >>>> was wondering if there are any other possibilities to incorporate >>>> variability in a more suitable way? All suggestions will be highly >>>> appreciated! >>>> Thank you very much in advance! >>>> Patricia > > > >
Re: [NMusers] Variability on infusion duration
Dear Patricia, Your infusion time will not be semantically distributed. I suppose maximum distribution toward planned DUR. But you may have left half of the distribution curve with maximum value of predetermined infusion time. So model is likely to be D1* (1-abs(THETA(1)*EPA(1))) On Wed, Aug 5, 2020, 12:50 PM Patricia Kleiner wrote: > Dear all, > > I am developing a PK model for a drug administered as a long-term infusion > of 48 hours using an elastomeric pump. End of infusion was documented, but > sometimes the elastomeric pump was already empty at this time. Therefore > variability of the concentration measurements observed at this time is > quite > high. > To address this issue, I try to include variability on infusion duration > assigning the RATE data item in my dataset to -2 and model duration in the > PK routine. Since the "true" infusion duration can only be shorter than > the > documented one, implementing IIV with a log-normal distribution > (D1=DUR*EXP(ETA(1)) cannot describe the situation. > > I tried the following expression, where DUR ist the documented infusion > duration: > > D1=DUR-THETA(1)*EXP(ETA(1)) > > It works but does not really describe the situation either, since I expect > the deviations from my infusion duration to be left skewed. I was > wondering > if there are any other possibilities to incorporate variability in a more > suitable way? All suggestions will be highly appreciated! > > > Thank you very much in advance! > Patricia > > > >
Re: [NMusers] Variability on infusion duration
Hi Patricia, What is the purpose of your modeling exercise? I am not sure your scenario could be assigned to any particular distribution. If you intend to simulate population from the model, then your assumptions would not be reasonable. If you have rich data, you may try individual modeling approach to estimate duration and fix in population model. Regards, Ayyappa > On Aug 5, 2020, at 1:04 PM, Bill Denney wrote: > > Similar to Leonid's solution, you can try using an exponential distribution: > > D1 = DUR*(1-EXP(-EXP(ETA(1 > > The exponential within an exponential gives left skew and ensures that D1 ≤ > DUR. > > For subjects who you know had an incomplete infusion duration, I would add > an indicator variable (1 if incomplete, 0 if full duration) so that the > subjects with complete duration have the known complete duration. > > D1 = DUR*(1 - Incomplete*EXP(-EXP(ETA(1 > > Thanks, > > Bill > > -Original Message- > From: owner-nmus...@globomaxnm.com On Behalf > Of Leonid Gibiansky > Sent: Wednesday, August 5, 2020 12:51 PM > To: Patricia Kleiner ; nmusers@globomaxnm.com > Subject: Re: [NMusers] Variability on infusion duration > > may be > D1=DUR*EXP(ETA(1)) > IF(D1.GT.DocumentedInfusionDuration) D1=DocumentedInfusionDuration > >>>> On 8/5/2020 12:18 PM, Patricia Kleiner wrote: >> Dear all, >> I am developing a PK model for a drug administered as a long-term >> infusion of 48 hours using an elastomeric pump. End of infusion was >> documented, but sometimes the elastomeric pump was already empty at >> this time. Therefore variability of the concentration measurements >> observed at this time is quite high. >> To address this issue, I try to include variability on infusion >> duration assigning the RATE data item in my dataset to -2 and model >> duration in the PK routine. Since the "true" infusion duration can >> only be shorter than the documented one, implementing IIV with a >> log-normal distribution >> (D1=DUR*EXP(ETA(1)) cannot describe the situation. >> I tried the following expression, where DUR ist the documented >> infusion >> duration: >> D1=DUR-THETA(1)*EXP(ETA(1)) >> It works but does not really describe the situation either, since I >> expect the deviations from my infusion duration to be left skewed. I >> was wondering if there are any other possibilities to incorporate >> variability in a more suitable way? All suggestions will be highly >> appreciated! >> Thank you very much in advance! >> Patricia
Re: [NMusers] Variability on infusion duration
Hi Patricia, What is the purpose of your modeling exercise? I am not sure your scenario could be assigned to any particular distribution. If you intend to simulate population from the model, then your assumptions would not be reasonable. If you have rich data, you may try individual modeling approach to estimate duration and fix in population model. Regards, Ayyappa > On Aug 5, 2020, at 1:04 PM, Bill Denney wrote: > > Similar to Leonid's solution, you can try using an exponential distribution: > > D1 = DUR*(1-EXP(-EXP(ETA(1 > > The exponential within an exponential gives left skew and ensures that D1 ≤ > DUR. > > For subjects who you know had an incomplete infusion duration, I would add > an indicator variable (1 if incomplete, 0 if full duration) so that the > subjects with complete duration have the known complete duration. > > D1 = DUR*(1 - Incomplete*EXP(-EXP(ETA(1 > > Thanks, > > Bill > > -Original Message- > From: owner-nmus...@globomaxnm.com On Behalf > Of Leonid Gibiansky > Sent: Wednesday, August 5, 2020 12:51 PM > To: Patricia Kleiner ; nmusers@globomaxnm.com > Subject: Re: [NMusers] Variability on infusion duration > > may be > D1=DUR*EXP(ETA(1)) > IF(D1.GT.DocumentedInfusionDuration) D1=DocumentedInfusionDuration > >>> On 8/5/2020 12:18 PM, Patricia Kleiner wrote: >> Dear all, >> I am developing a PK model for a drug administered as a long-term >> infusion of 48 hours using an elastomeric pump. End of infusion was >> documented, but sometimes the elastomeric pump was already empty at >> this time. Therefore variability of the concentration measurements >> observed at this time is quite high. >> To address this issue, I try to include variability on infusion >> duration assigning the RATE data item in my dataset to -2 and model >> duration in the PK routine. Since the "true" infusion duration can >> only be shorter than the documented one, implementing IIV with a >> log-normal distribution >> (D1=DUR*EXP(ETA(1)) cannot describe the situation. >> I tried the following expression, where DUR ist the documented >> infusion >> duration: >> D1=DUR-THETA(1)*EXP(ETA(1)) >> It works but does not really describe the situation either, since I >> expect the deviations from my infusion duration to be left skewed. I >> was wondering if there are any other possibilities to incorporate >> variability in a more suitable way? All suggestions will be highly >> appreciated! >> Thank you very much in advance! >> Patricia
RE: [NMusers] Variability on infusion duration
Similar to Leonid's solution, you can try using an exponential distribution: D1 = DUR*(1-EXP(-EXP(ETA(1 The exponential within an exponential gives left skew and ensures that D1 ≤ DUR. For subjects who you know had an incomplete infusion duration, I would add an indicator variable (1 if incomplete, 0 if full duration) so that the subjects with complete duration have the known complete duration. D1 = DUR*(1 - Incomplete*EXP(-EXP(ETA(1 Thanks, Bill -Original Message- From: owner-nmus...@globomaxnm.com On Behalf Of Leonid Gibiansky Sent: Wednesday, August 5, 2020 12:51 PM To: Patricia Kleiner ; nmusers@globomaxnm.com Subject: Re: [NMusers] Variability on infusion duration may be D1=DUR*EXP(ETA(1)) IF(D1.GT.DocumentedInfusionDuration) D1=DocumentedInfusionDuration On 8/5/2020 12:18 PM, Patricia Kleiner wrote: > Dear all, > > I am developing a PK model for a drug administered as a long-term > infusion of 48 hours using an elastomeric pump. End of infusion was > documented, but sometimes the elastomeric pump was already empty at > this time. Therefore variability of the concentration measurements > observed at this time is quite high. > To address this issue, I try to include variability on infusion > duration assigning the RATE data item in my dataset to -2 and model > duration in the PK routine. Since the "true" infusion duration can > only be shorter than the documented one, implementing IIV with a > log-normal distribution > (D1=DUR*EXP(ETA(1)) cannot describe the situation. > > I tried the following expression, where DUR ist the documented > infusion > duration: > > D1=DUR-THETA(1)*EXP(ETA(1)) > > It works but does not really describe the situation either, since I > expect the deviations from my infusion duration to be left skewed. I > was wondering if there are any other possibilities to incorporate > variability in a more suitable way? All suggestions will be highly > appreciated! > > > Thank you very much in advance! > Patricia > > >
Re: [NMusers] Variability on infusion duration
Just realized the typical value of this estimate cannot be 1.0. You may need other transformation. Sam > On August 5, 2020 9:59 AM Sam Liao wrote: > > > Dear Patricia, > This distribution might to analogous to relative bioavailability estimate, > which is bounded between 0 to 1. Typically, we use the logit-transformation > in F1 estimate. > For example: > m1 = log(θ1/(1- θ1)) > EE1 = m1 + η1 > F1 = exp(EE1)/[1 +exp(EE1)] > > Best regards, > Sam Liao, > Pharmax Research > > > On August 5, 2020 9:18 AM Patricia Kleiner wrote: > > > > > > Dear all, > > > > I am developing a PK model for a drug administered as a long-term infusion > > of 48 hours using an elastomeric pump. End of infusion was documented, but > > sometimes the elastomeric pump was already empty at this time. Therefore > > variability of the concentration measurements observed at this time is > > quite > > high. > > To address this issue, I try to include variability on infusion duration > > assigning the RATE data item in my dataset to -2 and model duration in the > > PK routine. Since the "true" infusion duration can only be shorter than the > > documented one, implementing IIV with a log-normal distribution > > (D1=DUR*EXP(ETA(1)) cannot describe the situation. > > > > I tried the following expression, where DUR ist the documented infusion > > duration: > > > > D1=DUR-THETA(1)*EXP(ETA(1)) > > > > It works but does not really describe the situation either, since I expect > > the deviations from my infusion duration to be left skewed. I was wondering > > if there are any other possibilities to incorporate variability in a more > > suitable way? All suggestions will be highly appreciated! > > > > > > Thank you very much in advance! > > Patricia
Re: [NMusers] Variability on infusion duration
Dear Patricia, This distribution might to analogous to relative bioavailability estimate, which is bounded between 0 to 1. Typically, we use the logit-transformation in F1 estimate. For example: m1 = log(θ1/(1- θ1)) EE1 = m1 + η1 F1 = exp(EE1)/[1 +exp(EE1)] Best regards, Sam Liao, Pharmax Research > On August 5, 2020 9:18 AM Patricia Kleiner wrote: > > > Dear all, > > I am developing a PK model for a drug administered as a long-term infusion > of 48 hours using an elastomeric pump. End of infusion was documented, but > sometimes the elastomeric pump was already empty at this time. Therefore > variability of the concentration measurements observed at this time is quite > high. > To address this issue, I try to include variability on infusion duration > assigning the RATE data item in my dataset to -2 and model duration in the > PK routine. Since the "true" infusion duration can only be shorter than the > documented one, implementing IIV with a log-normal distribution > (D1=DUR*EXP(ETA(1)) cannot describe the situation. > > I tried the following expression, where DUR ist the documented infusion > duration: > > D1=DUR-THETA(1)*EXP(ETA(1)) > > It works but does not really describe the situation either, since I expect > the deviations from my infusion duration to be left skewed. I was wondering > if there are any other possibilities to incorporate variability in a more > suitable way? All suggestions will be highly appreciated! > > > Thank you very much in advance! > Patricia
Re: [NMusers] Variability on infusion duration
may be D1=DUR*EXP(ETA(1)) IF(D1.GT.DocumentedInfusionDuration) D1=DocumentedInfusionDuration On 8/5/2020 12:18 PM, Patricia Kleiner wrote: Dear all, I am developing a PK model for a drug administered as a long-term infusion of 48 hours using an elastomeric pump. End of infusion was documented, but sometimes the elastomeric pump was already empty at this time. Therefore variability of the concentration measurements observed at this time is quite high. To address this issue, I try to include variability on infusion duration assigning the RATE data item in my dataset to -2 and model duration in the PK routine. Since the "true" infusion duration can only be shorter than the documented one, implementing IIV with a log-normal distribution (D1=DUR*EXP(ETA(1)) cannot describe the situation. I tried the following expression, where DUR ist the documented infusion duration: D1=DUR-THETA(1)*EXP(ETA(1)) It works but does not really describe the situation either, since I expect the deviations from my infusion duration to be left skewed. I was wondering if there are any other possibilities to incorporate variability in a more suitable way? All suggestions will be highly appreciated! Thank you very much in advance! Patricia
[NMusers] Variability on infusion duration
Dear all, I am developing a PK model for a drug administered as a long-term infusion of 48 hours using an elastomeric pump. End of infusion was documented, but sometimes the elastomeric pump was already empty at this time. Therefore variability of the concentration measurements observed at this time is quite high. To address this issue, I try to include variability on infusion duration assigning the RATE data item in my dataset to -2 and model duration in the PK routine. Since the "true" infusion duration can only be shorter than the documented one, implementing IIV with a log-normal distribution (D1=DUR*EXP(ETA(1)) cannot describe the situation. I tried the following expression, where DUR ist the documented infusion duration: D1=DUR-THETA(1)*EXP(ETA(1)) It works but does not really describe the situation either, since I expect the deviations from my infusion duration to be left skewed. I was wondering if there are any other possibilities to incorporate variability in a more suitable way? All suggestions will be highly appreciated! Thank you very much in advance! Patricia
