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From: Jakob Ribbing <jakob.ribbing_at_pharmetheus.com>

Date: Thu, 2 Jun 2016 06:56:37 +0200

Sorry, an error in what I wrote below: It should be EXP(0)=1 =

concentration unit

Jakob Ribbing, Ph.D.

Senior Consultant, Pharmetheus AB

Cell/Mobile: +46 (0)70 514 33 77

Jakob.Ribbing_at_Pharmetheus.com

www.pharmetheus.com

Phone, Office: +46 (0)18 513 328

Uppsala Science Park, Dag Hammarskjölds väg 52B

SE-752 37 Uppsala, Sweden

This communication is confidential and is only intended for the use of =

the individual or entity to which it is directed. It may contain =

information that is privileged and exempt from disclosure under =

applicable law. If you are not the intended recipient please notify us =

immediately. Please do not copy it or disclose its contents to any other =

person.

On 02 Jun 2016, at 06:31, Jakob Ribbing <jakob.ribbing_at_pharmetheus.com> =

wrote:

*> Hi Ahmad,
*

*>
*

*> The two error models are equivalent (only that with Leonids suggested =
*

code, the additive-on-log-transformed error term (TH16) is estimated on =

variance scale, instead of standard deviation scale (approximate CV).

*> This inflated error rates for very low concentrations is what you get =
*

for additive+proportional on the log transformed scale, and I believe =

that has been discussed on nmusers previously as well, many years ago.

*> You could possibly use a cut-off for when lower IPRE should not lead =
*

to higher residual errors, but why not move to additive + proportional =

for the original concentration scale?

*>
*

*> Also, this implementation may be unfortunate:
*

*>> Y=(1-FLAG)*IPRE + W*EPS(1)
*

*> Effectively, when concentration predictions are zero (FLAG=1), e.g. =
*

for pre-dose samples or before commence of absorption, then you set the =

concentration prediction to EXP(1)=3.14 concentration units.

*>
*

*> Depending on what concentration scale you work on (i.e. if BLQ is much =
*

higher than this) it may be OK, but otherwise not.

*> Instead of applying a flag, just set IPRE to a negative value (low in =
*

relation to LOG(BLQ)), if you want to stay on the log-transformed scale.

*>
*

*> I hope this helps to solve your problem.
*

*>
*

*> Best regards
*

*>
*

*> Jakob
*

*>
*

*>
*

*>
*

*> Jakob Ribbing, Ph.D.
*

*>
*

*> Senior Consultant, Pharmetheus AB
*

*>
*

*>
*

*>
*

*> Cell/Mobile: +46 (0)70 514 33 77
*

*>
*

*> Jakob.Ribbing_at_Pharmetheus.com
*

*>
*

*> www.pharmetheus.com
*

*>
*

*>
*

*>
*

*> Phone, Office: +46 (0)18 513 328
*

*>
*

*> Uppsala Science Park, Dag Hammarskjölds väg 52B
*

*>
*

*> SE-752 37 Uppsala, Sweden
*

*>
*

*>
*

*>
*

*> This communication is confidential and is only intended for the use of =
*

the individual or entity to which it is directed. It may contain =

information that is privileged and exempt from disclosure under =

applicable law. If you are not the intended recipient please notify us =

immediately. Please do not copy it or disclose its contents to any other =

person.

*>
*

*>
*

*>
*

*>
*

*>
*

*> On 02 Jun 2016, at 04:27, Abu Helwa, Ahmad Yousef Mohammad - abuay010 =
*

<ahmad.abuhelwa_at_mymail.unisa.edu.au> wrote:

*>
*

*>> Dear NMusers,
*

*>>
*

*>> I am developing a PK model using log-transformed single-dose oral =
*

data. My question relates to using combined error model for =

log-transform data.

*>>
*

*>> I have read few previous discussions on NMusers regarding this, which =
*

were really helpful, and I came across two suggested formulas (below) =

that I tested in my PK models. Both formulas had similar model fits in =

terms of OFV (OFV using Formula 2 was one unit less than OFV using =

Formula1) with slightly changed PK parameter estimates. My issue with =

these formulas is that the model simulates very extreme concentrations =

(e.g. upon generating VPCs) at the early time points (when drug =

concentrations are low) and at later time points when the concentrations =

are troughs. These simulated extreme concentrations are not =

representative of the model but a result of the residual error model =

structure.

*>>
*

*>> My questions:
*

*>> 1. Is there a way to solve this problem for the indicated =
*

formulas?

*>> 2. Are the two formulas below equally valid?
*

*>> 3. Is there an alternative formula that I can use which does =
*

not have this numerical problem?

*>> 4. Any reference paper that discusses this subject?
*

*>>
*

*>> Here are the two formulas:
*

*>> 1. Formula 1: suggested by Mats Karlsson with fixing SIGMA to =
*

1:

*>> W=SQRT(THETA(16)**2+THETA(17)**2/EXP(IPRE)**2)
*

*>>
*

*>> 2. Formula 2: suggested by Leonid Gibiansky with fixing SIGMA =
*

to 1:

*>> W = SQRT(THETA(16)+ (THETA(17)/EXP(IPRE))**2 )
*

*>>
*

*>> The way I apply it in my model is this:
*

*>>
*

*>> FLAG=0 ;TO AVOID ANY CALCULATIONS OF =
*

LOG (0)

*>> IF (F.EQ.0) FLAG=1
*

*>> IPRE=LOG(F+FLAG)
*

*>>
*

*>> W=SQRT(THETA(16)**2+THETA(17)**2/EXP(IPRE)**2) ;FORMULA 1
*

*>>
*

*>> IRES=DV-IPRE
*

*>> IWRES=IRES/W
*

*>> Y=(1-FLAG)*IPRE + W*EPS(1)
*

*>>
*

*>> $SIGMA
*

*>> 1. FIX
*

*>>
*

*>> Best regards,
*

*>>
*

*>> Ahmad Abuhelwa
*

*>> School of Pharmacy and Medical Sciences
*

*>> University of South Australia- City East Campus
*

*>> Adelaide, South Australia
*

*>> Australia
*

*>
*

Received on Thu Jun 02 2016 - 00:56:37 EDT

Date: Thu, 2 Jun 2016 06:56:37 +0200

Sorry, an error in what I wrote below: It should be EXP(0)=1 =

concentration unit

Jakob Ribbing, Ph.D.

Senior Consultant, Pharmetheus AB

Cell/Mobile: +46 (0)70 514 33 77

Jakob.Ribbing_at_Pharmetheus.com

www.pharmetheus.com

Phone, Office: +46 (0)18 513 328

Uppsala Science Park, Dag Hammarskjölds väg 52B

SE-752 37 Uppsala, Sweden

This communication is confidential and is only intended for the use of =

the individual or entity to which it is directed. It may contain =

information that is privileged and exempt from disclosure under =

applicable law. If you are not the intended recipient please notify us =

immediately. Please do not copy it or disclose its contents to any other =

person.

On 02 Jun 2016, at 06:31, Jakob Ribbing <jakob.ribbing_at_pharmetheus.com> =

wrote:

code, the additive-on-log-transformed error term (TH16) is estimated on =

variance scale, instead of standard deviation scale (approximate CV).

for additive+proportional on the log transformed scale, and I believe =

that has been discussed on nmusers previously as well, many years ago.

to higher residual errors, but why not move to additive + proportional =

for the original concentration scale?

for pre-dose samples or before commence of absorption, then you set the =

concentration prediction to EXP(1)=3.14 concentration units.

higher than this) it may be OK, but otherwise not.

relation to LOG(BLQ)), if you want to stay on the log-transformed scale.

the individual or entity to which it is directed. It may contain =

information that is privileged and exempt from disclosure under =

applicable law. If you are not the intended recipient please notify us =

immediately. Please do not copy it or disclose its contents to any other =

person.

<ahmad.abuhelwa_at_mymail.unisa.edu.au> wrote:

data. My question relates to using combined error model for =

log-transform data.

were really helpful, and I came across two suggested formulas (below) =

that I tested in my PK models. Both formulas had similar model fits in =

terms of OFV (OFV using Formula 2 was one unit less than OFV using =

Formula1) with slightly changed PK parameter estimates. My issue with =

these formulas is that the model simulates very extreme concentrations =

(e.g. upon generating VPCs) at the early time points (when drug =

concentrations are low) and at later time points when the concentrations =

are troughs. These simulated extreme concentrations are not =

representative of the model but a result of the residual error model =

structure.

formulas?

not have this numerical problem?

1:

to 1:

LOG (0)

Received on Thu Jun 02 2016 - 00:56:37 EDT