Last updated 11 July 2020
NextDose estimates pharmacokinetic (PK) and pharmacodynamic
(PD) parameters using a Bayesian method. These individual parameters are known
as empirical Bayes estimates (EBEs). The EBEs are used to individualize dose
predictions and to predict the time course of concentrations and biomarkers
such as INR.
The EBEs are determined in
part by population parameters and in part by any observations that are
available. The population parameters describe a standard individual based on
patient factors such as weight and renal function (e.g. weight=70 kg, renal function=1).
These patient factors are known as covariates. Covariates are used to predict a
group parameter value using covariate effects. For example, group clearance can be predicted from weight (WTKG) and renal
function (RF0 and population clearance by assuming clearance is linearly proportional
to RF and a theory based allometric function of WTKG (Equation 1):

Equation 1 
Individual estimates (EBEs)
of the parameter are then predicted from the group parameter value and an
individual specific random effect. This random effect is made up of a between
subject variability component (BSV) and a within subject variability component
(WSV). The within subject variability is usually estimated with reference to an
occasion and WSV is therefore commonly described as between occasion
variability (BOV). The definition of an occasion in NextDose
is a dosing interval which includes one or more observations.
Random effects are commonly
assumed to be lognormally distributed so that the individual clearance is
predicted using Equation 2:

Equation 2 
Figure 1 shows the
concentration predictions in a patient treated with vancomycin who had three
predose vancomycin concentration observations.
Figure 1
The
Bayesian dose predictions for these 3 observation occasions are shown in Figure 2
Figure 2
NextDose TCI vancomycin NNNN:20200617131151_conc_holfordGAV2020_AVG
Target: AUC 300 mg/L*h per 12 hours at steady state
Bayesian 
Route 
Predicted Dose 
Actual Dose 


1 
IV 
1008 mg every 12 hours 
1250 mg 
10/06/2020 03:55 

2 
IV 
863 mg every 12 hours 
1250 mg 
12/06/2020 03:50 

3 
IV 
863 mg every 12 hours 
900 mg 
14/06/2020 04:05 

Proposed IV maintenance dose 911 mg every 12 hours (Bayesian Average)
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
3.36 
20 
24.9 
0.2 
1 
0 
38.9 
100 
2.87 
20.1 
24.9 
0.2 
1 
0 
38.9 
85.4 
2.88 
20 
24.9 
0.2 
1 
0 
38.9 
85.4 
Following the dose
predictions is a table of individual parameters (EBEs) and covariate effects. NextDose shows 8 values which are displayed for all
medicines.
The first 6 describe the
parameters clearance (CL), central volume of distribution (V) and
bioavailability (F). Following the EBE for each parameter is the fractional
change (f) from the group parameter value expressed as a percentage. When a
medicine is given parenterally then F is 1 and there is no random effect.
The EBE for
CL appears to decrease from 3.36 l/h to 2.87 L/h. This is explained by the
change in RF% from 100% to 85.4%. The first prediction of renal function was
made before a serum creatinine observation was provided so renal function is
assumed to be normal (100%). The second two occasion were associated with a serum
creatinine measurement and a 15% change in RF. The random effect difference for
this patient is 20% lower than the group prediction. For vancomycin this is
primarily due to between subject variability (BSV) because the between occasion
variability (BOV) in this model is small.
The last 2
standard values are the covariate effects, predicted fat free mass (FFM) and
renal function (RF). RF is expressed as a percentage where 100% means normal
renal function relative to predicted normal glomerular filtration rate.
FFM is used
to predict the effect of body size and composition on clearance, volume of
distribution and glomerular filtration rate. RF is used to predict a component
of clearance that is related to RF. The remaining component is not linked to RF
(nonrenal function clearance).
Medicine
specific values are shown with gentamicin, amikacin and vancomycin predictions.
This example is for vancomycin.
CLcr L/h 
Normal GFR L/h 
CPR uM/h 
RFss% 
CLcrss L/h 
CPRss uM/h 
. 
5.33 
. 
. 
. 
. 
4.55 
5.33 
150 
128 
6.55 
216 
4.55 
5.33 
150 
128 
6.55 
216 
The first (CLcr) is the predicted creatinine clearance which takes into account the time course of change in serum
creatinine (Scr) in order to predict the steady state
Scr. The next value is the predicted normal glomerular filtration rate (GFR).
GFR is predicted from size and maturation (Rhodin,
Anderson et al. 2009). Renal function is calculated from
the ratio of CLcr to normal GFR. CLcr
is calculated from the ratio of creatinine production rate (CPR) to Scr. The NextDose method for calculating CPR is based on a model
derived from combined GFR and SCr data (Rhodin,
Anderson et al. 2009)
The last 3 values are
predictions of RF, CLcr and CPR using methods for CLcr that assume the measured SCr
is at steady state (Schwartz 1992,
Matthews, Kirkpatrick et al. 2004)
There are
no medicine specific values shown for busulfan.
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
10.8 
36.7 
7.94 
8.7 
1 
0 
36.5 
. 
Methotrexate
has additional specific values for observed urine pH and predicted CLcr
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
Urine pH 
CLcr L/h 
7.77 
68.1 
41.2 
73.6 
1 
0 
55.9 
73.2 
7.00 
5.60 
9.25 
62.1 
48.4 
69 
1 
0 
55.9 
73.2 
7.00 
5.60 
There are 6
specific values for tacrolimus. Oral bioavailability is high during the first 2
days after transplant and fall to normal after day 2 (day of transplant is day
0). There is a BSV random effect on bioavailability upto
day 2 which is 63% lower than expected. The daily dose of prednisolone (Pred) affects oral bioavailability and in this case F is 75.6% of F without a steroid effect. The CYP3A5
genotype can affect both F and CL. In this case there is no genotype effect.
The haematocrit influences the measured whole blood
value of tacrolimus so its value (HCT) is shown here. Finally
the predicted plasma to blood fraction (fu) expressed
as a percentage 2.09% at a standardized blood concentration (HCT=45%) is shown.
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
9.09 
52.3 
43.3 
71.9 
0.720 
4.8 
70.4 
. 
9.09 
52.3 
43.3 
71.9 
0.841 
11.2 
70.4 
. 
Day Tx on F 
diffDTx F% 
Pred on F % 
GT CYP3A5 on F % 
GT CYP3A5 on CL % 
HCT % 
fu% at HCT 45% 
1 
62.687 
75.6 
100 
100 
29.0 
2.09 
1 
62.687 
75.6 
100 
100 
29.0 
2.09 
Linezolid
has 2 specific values. The first is the minimum inhibitory concentration (MIC,
2 mg/L). The second is the baseline platelet count (PLT0, cells/microL).
There is a
marked decrease in RF with a decrease in CL. Nephrotoxicity is a well known adverse effect of
linezolid.
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
MIC 
PLT0 
1.31 
47.6 
10.2 
45.4 
1 
0 
46.7 
23.4 
2.00 
212000 
1.31 
47.6 
10.2 
45.4 
1 
0 
46.7 
23.4 
2.00 
212000 
1.29 
47.6 
10.2 
45.4 
1 
0 
46.7 
20.7 
2.00 
212000 
1.29 
47.6 
10.2 
45.4 
1 
0 
46.7 
20.7 
2.00 
212000 
1.26 
47.6 
10.2 
45.4 
1 
0 
46.7 
15.3 
2.00 
212000 
1.25 
47.6 
10.2 
45.4 
1 
0 
46.7 
13.3 
2.00 
212000 
1.24 
47.6 
10.2 
45.4 
1 
0 
46.7 
13 
2.00 
212000 
1.24 
47.6 
10.2 
45.4 
1 
0 
46.7 
12.3 
2.00 
212000 
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
2.19 
33.3 
66.9 
5 
1 
0 
42.5 
. 
There are
many covariates that affect voriconazole PK. Ritonavir (RTV), St John’s Wort
(SJW), prednisolone (or prednisone) (Pred), methyl
prednisolone (MePRed), dexamethasone (DEX). Phenytoin
(PHE) and rifampicin (RIF) are both inducing agents. The CYP2C19 genotype may
be associated with a reduced F (87.7% of normal) and CL (56.3% of normal). The
minimum inhibitory concentration (MIC, mg/L) is also shown.
RTV 
SJW 
Pred 
MePred 
DEX 
PHE or RIF 
GT CYP2C19 on F % 
GT CYP2C19 on CL % 
MIC mg/L 
0 
0 
0 
0 
0 
0 
87.8 
56.3 
1 
The
warfarin model estimates both PK and PD parameters.
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
0.141 
4.8 
29.8 
0.9 
1 
0 
66.0 
. 
The predicted baseline prothrombin complex
activity (PCA0) is shown here as 97.9% of normal. The PCA half
life (T2PCA) EBE is 11.5 h which is just under 0.5% higher than the
group value (fT2PC%). The potency of the Senantiomer of warfarin for
inhibition of PCA synthesis is 0.211 mg/L (C50 S) and is 6.39% of the group
value (fC50%). The exponent for the warfarin inhibition model is 2.75 (Hill)
and this is 1.52% higher than the group value. The potency of the Renantiomer
of warfarin as an inhibitor of Swarfarin is 2.4 mg/L. The VKORC1 genotype
affects the Swarfarin C50 so that it is 0.766 of normal. The CYP2C9 genotype
effect on Swarfarin clearance is negligible with a fractional increase of
0.01.
PCA0 % 
T2PCA h 
fT2PC% 
C50S mg/L 
fC50% 
Hill 
fHill% 
C50R mg/L 
FGT VKOR on C50 
FGT CYP2C9 on CLs 
97.9 
11.5 
0.469 
0.211 
6.393 
2.75 
1.52 
2.40 
0.766 
1.01 
Mycophenlate unbound clearance increases
substantially after a renal transplant (from 757 L/h to 1229 L/h over 1 month).
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
ALB g/L 
fu MPA % 
757 
27.4 
3263 
7.7 
0.950 
0 
66.1 
14.7 
32.0 
1.66 
750 
28.1 
3078 
1.6 
0.950 
0 
66.1 
14.7 
32.0 
1.66 
1449 
33.3 
3264 
7.8 
0.950 
0 
66.1 
14.7 
31.0 
1.71 
1576 
27.4 
3995 
31.9 
0.950 
0 
66.1 
14.7 
31.0 
1.76 
1229 
43.4 
2947 
2.7 
0.950 
0 
66.1 
14.7 
33.0 
1.38 
Both albumin and renal function influence
mycophenolate plasma protein binding. The serum albumin (ALB, g/L) is shown
along with RF. The unbound fraction of mycophenolate (unbound/total plasma)
decreased from 1.66% to 1.38% in the month after transplant.
Caffeine is
used in premature neonates to reduce the risk of apnea of prematurity
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
0.008 
0.9 
1.71 
19.7 
1 
0 
1.22 
. 
The number of days after birth (postnatal age,
PNA) for this neonate is 0. Height (HT) is 40 cm. The allometric fraction of
size affecting CL relative to a 70 kg adult is 0.05. The fractional maturation
of nonrenal function CL is 0.025 while the fractional maturation of renal
clearance is 0.171 (relative to adult). The birth method was vaginal (0) rather
than Caesarian (1).
PNA days 
HT cm 
FSIZCL 
FMAT CLnrf 
FMAT CLrf 
BIRTH V=0 C=1 
0 
40.0 
0.050 
0.025 
0.171 
0 
Hydroxychloroquine is used for the treatment of
lupus erythematosus and rheumatoid arthritis. Whole blood pharmacokinetics are
described based on a standard hematocrit (HCT) of 45%.
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
BMI kg/m^2 
ALB g/L 
HCT % 
VENT 
11.6 
25.2 
777 
5.7 
0.746 
0 
63.2 
52.7 
26.8 
35.0 
45.0 
1 
11.6 
25.2 
777 
5.7 
0.746 
0 
63.2 
52.7 
26.8 
35.0 
45.0 
1 
11.6 
25.2 
777 
5.7 
0.746 
0 
63.2 
52.7 
26.8 
35.0 
45.0 
1 
Body mass index (BMI), serum albumin (ALB), haematocrit (HCT) and use of artificial ventilation (0=no
ventilator, 1=ventilator) are the medicine specific factors.
The RELY
2011 PK model (Liesenfeld, T.
et al. 2011) has random effects on V and F but
not on CL so fCL % is always zero.
CL L/h 
fCL% 
V L 
fV% 
F 
fF% 
FFM kg 
RF% 
66.0 
0 
698 
0.8 
1.08 
8.1 
62.8 
43.8 
CLcr, Normal GFR, CPR, RFss%,
CLcrss, CPRss have the same
meaning as described for gentamicin, amikacin and vancomycin.
The RELY 2011 PK model predicts CL with a
sigmoid Emax model using CLcrss.
The fractional effect of CLcrss (F CLcrss CL) is relative to the size scaled asymptotic CL
(infinite CLcrss). The combined effects of three
concomitant medications (proton pump inhibitors, amiodarone, verapamil) on
bioavailability (F) is expressed as the % difference from no concomitant
medication effect.
CLcr L/h 
Normal GFR L/h 
CPR uM/h 
RFss% 
CLcrss L/h 
CPRss uM/h 
F CLcrss CL 
F ConMed F1 % 
3.32 
7.57 
308 
50.5 
3.56 
331 
0.514 
0 
Liesenfeld, K.H., L. T., C. Dansirikul, P. A. Reilly, S. J. Connolly, M. D. Ezekowitz, S. Yusuf, L. Wallentin, S. Haertter and A. Staab (2011). "Population pharmacokinetic analysis of the oral thrombin inhibitor dabigatran etexilate in patients with nonvalvular atrial fibrillation from the RELY trial." Journal of Thrombosis and Haemostasis 9(11): 21682175.
Matthews, I., C. Kirkpatrick and N. Holford (2004). "Quantitative justification for target concentration interventionparameter variability and predictive performance using population pharmacokinetic models for aminoglycosides." Br J Clin Pharmacol 58(1): 819.
Rhodin, M. M., B. J. Anderson, A. M. Peters, M. G. Coulthard, B. Wilkins, M. Cole, E. Chatelut, A. Grubb, G. J. Veal, M. J. Keir and N. H. Holford (2009). "Human renal function maturation: a quantitative description using weight and postmenstrual age." Pediatr Nephrol 24(1): 6776.
Schwartz, G. J. (1992). "Does kL/PCr estimate GFR, or does GFR determine k?" Pediatr Nephrol 6(6): 512515.
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