msmnainar
★    

India,
2015-04-14 17:47
(3293 d 19:06 ago)

Posting: # 14685
Views: 6,435
 

 PK/PD modeling [Software]

Dear all

If I am correct different PK/PD model software packages adopted different programming for PK/PD model development purpose. However, in general which computer language programme(s) will be useful to learn/understand for the development of own PK/PD models.

Kindly provide your opinion.


Thanks


Edit: Category changed. [Helmut]

Sundar. M
Helmut
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Vienna, Austria,
2015-04-14 18:15
(3293 d 18:38 ago)

@ msmnainar
Posting: # 14686
Views: 5,403
 

 Coding from scratch

Hi Sundar,

re-inventing the wheel is burdensome and time-consuming. However, programming your own models is a great opportunity to understand the underlying concepts. I would suggest languages which have built-in methods for matrix-algebra, numeric integration, nonlinear optimization.

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msmnainar
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India,
2015-04-15 08:45
(3293 d 04:08 ago)

@ Helmut
Posting: # 14690
Views: 5,214
 

 Coding from scratch

Hi HS

Thanks for your information.

However, to write programming in R or Maxima particularly, would proficiency in C, C++ or Java computer languages help.

Thanks

Sundar. M
Helmut
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Vienna, Austria,
2015-04-15 16:23
(3292 d 20:30 ago)

@ msmnainar
Posting: # 14692
Views: 5,202
 

 Coding from scratch

Hi Sundar,

❝ […] to write programming in R or Maxima particularly, would proficiency in C, C++ or Java computer languages help.


Sure. Though some structures of R are derived from Lisp, the syntactical structure is very similar to the languages you mentioned. Furthermore, R allows linking to compiled subroutines in FOR­TRAN, C, C++ (see f.i. the RFortran project) if you want to speed things up.

The syntax of Maxima (core again derived from Lisp) is particular, but similar to other Computer Algebra Systems (Derive, Mathcad, …). Personally I use it sometimes when my algebra-skills are too limited – and implement the derived solution in R. One of the strengths of CASs is calculation with unlimited numeric precision – something you don’t really need in PK.

R will fail for any p >15 due to limited numeric precison (even in the 64bit version!):

p <- 15 # any >= 0
x <- rep(1*10^p, 3)+(-1:1)
# example: p = 1, x = (9, 10, 11)
# standard deviation should be /exactly/ 1
if(sd(x) == 1) {
  cat("pass:       SD(x) = 1\n")
  } else {
  cat("fail:       SD(x) != 1\ncalculated:", sd(x), "\n")
}
p <- 16
x <- rep(1*10^p, 3)+(-1:1)
if(sd(x) == 1) {
  cat("pass:       SD(x) = 1\n")
  } else {
  cat("fail:       SD(x) != 1\ncalculated:", sd(x), "\n")
}


Now in Maxima (p = 10,000‼):

load(descriptive)$
p: 10000;
x: ([1,1,1])*10^p+([-1,0,1]);
std1(x);

Which gives:
(%o2) 10000
(%o3) [899999999999999999999999999999[9941 digits]999999999999999999999999999999,
900000000000000000000000000000[9941 digits]000000000000000000000000000000,
900000000000000000000000000000[9941 digits]000000000000000000000000000001]
(%o4) 1

Amazing. I don’t know where Maxima’s limitations are, but 105,000,000 + {–1, 0, +1} gave still the correct standard deviation.

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