ヒト in vivo の予測
ファーマコキネティクス―演習による理解> data$time
[1] 1 2 3 5 7 8 10 20 30 60 90 120
> library(PK)
> data <- read.csv("/Users/kzfm/PK/pk53.csv")
> auc.complete(conc=data$conc, time=data$time)
Estimation for a complete data design
AUC AUMC
observed 172.9950 7183.805
interpolated NA NA
infinity 220.5125 16772.150
血漿中濃度だから血液中濃度に変換
> RB = 1.2
> AUCb = 220.5125 * 1.2
> AUCb
[1] 264.615
0.265 umol*min/mL
肝での全代謝物をAUCbで除すればよいので
> CLh = (0.921+0.671)/0.265
> CLh
[1] 6.007547
> fp =0.78
> Rb = 1.20
> Fh = 1-CLh/Qh
> Fh
[1] 0.8998742
> F <- function(a){4*a/((1+a)^2*exp((a-1)/2/0.17)-(1-a)^2*exp(-(a+1)/2/0.17))-0.900}
> uniroot(f,c(0.1,10))
$root
[1] 1.035727
$f.root
[1] -2.312838e-05
$iter
[1] 11
$estim.prec
[1] 6.103516e-05
> res <- uniroot(f,c(0.1,10))
> RN <- (res$root^2 - 1)/(4*DN)
> CLh_uint = RN*Qh/fb
> CLh_uint
[1] 9.872855
> data = read.csv("/Users/kzfm/PK/pk53_2.csv")
> data
time qrat qhuman
a 5 6.5 7.9
b 10 13.8 16.1
c 15 19.9 24.7
d 20 26.6 32.0
e 30 39.3 46.2
f 60 60.8 72.9
g 90 73.2 82.0
> rat_res <- lm(data$qrat[1:5]/0.1 ~ data$time[1:5])
> rat_res
Call:
lm(formula = data$qrat[1:5]/0.1 ~ data$time[1:5])
Coefficients:
(Intercept) data$time[1:5]
3.595 13.038
> human_res <- lm(data$qhuman[1:5]/0.1 ~ data$time[1:5])
> human_res
Call:
lm(formula = data$qhuman[1:5]/0.1 ~ data$time[1:5])
Coefficients:
(Intercept) data$time[1:5]
8.784 15.314
> CLh_uint_rat = 13.038/0.4*51.2/1000*44
> CLh_uint_human = 15.314/0.5*52.5/1000*24.3
> CLh_uint_rat
[1] 73.43002
> CLh_uint_human
[1] 39.07367
ラットのin vivoのデータとin vitroのデータの比からヒトのin vitroのデータを用いヒトin vivoを予測。本の計算はミクロソーム蛋白の量を間違ってる(問題文は0.1なのに0.5で計算してる)けど、最終的に比になっているので結果に影響はないようだ。
> CLh_uint_human * (9.872855/CLh_uint_rat)
[1] 5.253556