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Re: SEED status with SAEM method

From: hai le ba <lebahai01>
Date: Thu, 5 Nov 2020 14:24:50 +0100

Yes, I totally agree with you. I have tested on the other kind of dataset
(more than 1 point per ID). All of the parameters are perfectly estimated.
Now, I'm trying to find an answer for the case of 1 PK point per each ID.
And, I have this problem with the number of seed options in the SAEM method=
.
Many thanks for your suggestion.

Hai, LE Ba
Ph.D Student
La faculté de Pharmacie - Aix Marseille université
Hanoi university of Pharmacy
Email: lebahai01
           hailb
bahai.le


On Thu, Nov 5, 2020 at 1:05 PM Jakob Ribbing <jakob.ribbing
>
wrote:

> I see.
>
> In that case this becomes kind of a theoretical exercise that can not be
> applied on a real dataset.
> Estimation of both IIV and sigma may be “feasible" based on distr=
ibutional
> assumptions.
> But in reality, the random part of the parameter variability (IIV) does
> not perfectly follow a log-normal distribution.
> And the residual error will not be perfectly normal (additive).
> From that perspective I think it is healthy that FOCE/FOCEI does not
> converge, and it is not surprising that other estimation methods are ill
> behaved.
>
> Maybe you should consider at least a percentage of subjects with multiple
> observations?
>
> Best regards
>
> Jakob
>
>
>
> Jakob Ribbing, Ph.D.
>
> Senior Consultant, Pharmetheus AB
>
>
> Cell/Mobile: +46 (0)70 514 33 77
>
> Jakob.Ribbing
>
> www.pharmetheus.com
>
> Phone, Office: +46 (0)18 513 328
>
> Uppsala Science Park, Dag Hammarskjölds väg 36B
> SE-752 37 Uppsala, Sweden
>
>
>
> This communication is confidential and is only intended for the use of th=
e
> individual or entity to which it is directed. It may contain
> information that is privileged and exempt from disclosure under applicabl=
e
> 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 5 Nov 2020, at 11:58, hai le ba <lebahai01
>
> Sorry, I've copied a wrong code of model.
> The right is:
> "$PK
>
> MU_1= LOG(THETA(1))
>
> KA=EXP(MU_1+ETA(1))
>
> MU_2=LOG(THETA(2))+ THETA(4)*LOG(AGE/60.13)
> CL= EXP(MU_2+ETA(2))
>
> MU_3=LOG(THETA(3))+THETA(5)*LOG(WEI/66.49)
> V=EXP(MU_3+ETA(3))
>
> S2=V
> IF (TIME.LT.12) TAD=TIME
> IF (TIME.GE.12.AND.TIME.LT.24) TAD=TIME-12
> IF (TIME.GE.12.AND.TIME.LT.36) TAD=TIME-24
> IF (TIME.GE.36.AND.TIME.LT.48) TAD=TIME-36
>
> $ERROR
> EP1=EPS(1)
> IPRED=F
> IRES=DV-IPRED
> W=F
> IWRES=IRES/W
> Y=IPRED+EPS(1)*W
>
> Many thanks for your support!
> Best regards,
>
> Le jeu. 5 nov. 2020 à 11:15, hai le ba <lebahai01
crit :
>
>> Dear Sir Jakob and Jeroen,
>> Thanks for your reply.
>> In fact, i've a one compartment model, with two levels of random effect
>> (IIV, EPS) and covariate effect on CL, V.
>> $PK
>>
>> MU_1= LOG(THETA(1))
>>
>> KA=EXP(MU_1+ETA(1))
>>
>> MU_2=LOG(THETA(2)+ THETA(4)*LOG(AGE/60.13))
>> CL= EXP(MU_2+ETA(2))
>>
>> MU_3=LOG(THETA(3)+THETA(5)*LOG(WEI/66.49))
>> V=EXP(MU_3+ETA(3))
>>
>> S2=V
>> IF (TIME.LT.12) TAD=TIME
>> IF (TIME.GE.12.AND.TIME.LT.24) TAD=TIME-12
>> IF (TIME.GE.12.AND.TIME.LT.36) TAD=TIME-24
>> IF (TIME.GE.36.AND.TIME.LT.48) TAD=TIME-36
>>
>> $ERROR
>> EP1=EPS(1)
>> IPRED=F
>> IRES=DV-IPRED
>> W=F
>> IWRES=IRES/W
>> Y=IPRED+EPS(1)*W
>>
>> I've used this model to simulate the complete database (10 000 IDs). Fro=
m
>> this database, the smaller dataset was randomly generated with respect t=
o
>> the rule of one PK sample per each ID. After that, I want to check how
>> many IDs are necessary to get a good estimation for each method ( FOCEI,
>> SAEM, BAYES, composite (ITS/SAEM/IMP/BAYES))?
>>
>> For FOCEI, I can't get convergence.
>>
>> For SAEM, I've got some troubles with the stability for EPS when I tried
>> to change the SEED status?
>> Otherwise, the good estimations were obtained with RSE (10-20%) for the
>> other parameters.
>>
>>
>> convergence for this setting of NBURN.
>> "
>> Convergence achieved
>>
>> STOCHASTIC PORTION WAS COMPLETED
>> REDUCED STOCHASTIC PORTION WAS COMPLETED"
>>
>> Could you give me some instructions?
>>
>> Many thanks in advance for your responses.
>> Best regards,
>> Hai, LE Ba
>> Ph.D Student
>> La faculté de Pharmacie - Aix Marseille université
>> Hanoi university of Pharmacy
>> Email: lebahai01
>> hailb
>> bahai.le
>>
>>
>> On Thu, Nov 5, 2020 at 10:43 AM Jakob Ribbing <
>> jakob.ribbing
>>
>>> Dear LE Ba,
>>>
>>> You did not share much information on your model, except that you have
>>> one observations per subject and that EPS (or rather sigma) is estimate=
d (I
>>> assume then a continuous endpoint).
>>> Is thisyour only level of random effect, so that you have no omega/eta
>>> for IOV or IIV? With one observations per subject it will be difficult =
to
>>> find support for more than one level.
>>> And for a model with only residual error (no IIV), would not the FO
>>> Estimation method be sufficient, so why would you need to use SAEM for =
this
>>> data/model?
>>>
>>> Best regards
>>>
>>> Jakob
>>>
>>>
>>>
>>> Jakob Ribbing, Ph.D.
>>>
>>> Senior Consultant, Pharmetheus AB
>>>
>>>
>>> Cell/Mobile: +46 (0)70 514 33 77
>>>
>>> Jakob.Ribbing
>>>
>>> www.pharmetheus.com
>>>
>>> Phone, Office: +46 (0)18 513 328
>>>
>>> Uppsala Science Park, Dag Hammarskjölds väg 36B
>>> 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 applica=
ble
>>> 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 5 Nov 2020, at 09:41, hai le ba <lebahai01
>>>
>>> Hello nmusers,
>>> I've tried to test the SAEM method on my dataset (1 sample for each ID)
>>> with different SEED status. Sometimes, I've got good results (with RSE
>>> <50%), but sometimes I can't get it.
>>>
>>> Example:
>>> $EST METHOD=SAEM INTERACTION NBURN=3000 NITER=500 AUTO=1 PRINT=
=100
>>> SEED=123456789
>>> $EST METHOD=IMP EONLY=1 PRINT=1 NITER=5 ISAMPLE=1000 MAPITER=
=0
>>> I've got EPS : 0.00064 (RSE=63%)
>>>
>>> but
>>> $EST METHOD=SAEM INTERACTION NBURN=3000 NITER=500 AUTO=1 PRINT=
=100
>>> SEED=123235489
>>> $EST METHOD=IMP EONLY=1 PRINT=1 NITER=5 ISAMPLE=1000 MAPITER=
=0
>>> I've got EPS : 0.0223 (RSE=18%)
>>>
>>> Could i trust on the good results (EPS=0.0223)? How can we control th=
is
>>> problem?
>>>
>>> Thank you very much,
>>> Hai, LE Ba
>>> Ph.D Student
>>> La faculté de Pharmacie - Aix Marseille université
>>> Hanoi university of Pharmacy
>>> Email: lebahai01
>>> hailb
>>> bahai.le
>>>
>>>
>>>
>

Received on Thu Nov 05 2020 - 08:24:50 EST

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