On Jun 6, 2013, at 10:03 AM, Polwart Calum (COUNTY DURHAM AND DARLINGTON NHS FOUNDATION TRUST) <calum.polw...@nhs.net> wrote:
> Some colleagues nationally have developed a system which means they can pick > the optimal sets of doses for a drug. The system could apply to a number of > drugs. But the actual doses might vary. To try and explain this in terms > that the average Joe on the street might understand if you have some > amoxicillin antibiotic for a chest infection the normal dose for an adult is > 250 to 500mg increased to maybe 1000mg in severe cases. > > For a child it is dosed from a liquid and people usually go from 62.5mg, > 125mg to 250mg although you could measure any volume you wanted. > > What this new method has developed is a means to pick the "right" standard > doses so what above is 62.5, 125, 250, 500, 1000. However the method they've > used is really engineered about ensure the jump between doses is correct - > you'll notice that the list above is a doubling up method. > > But you can also have a doubling up method that went 50, 100, 200, 400, 800, > 1600 and pretty much as many as you can think of depending on your starting > point and there is no scientific means to pick that starting point. So > colleagues have developed their rather more complex equivalent of the > doubling method to determine the doses they need but they need to know if > they should start at 40, 50, 62.5 or some other number. > > Once they have the starting number they can calculate all the other doses. I > realise R can do that, and I realise using a loop of possible starting > numbers it can build all those options. > > Each patient then has a theoretical dose they should get lets say that's > 10mg/kg and you might treat patients from 5 to 120kg. They are then looking > to calculate the variance for each dose range so if we take the 50, 100, 200, > 400 model and said you'd give 50mg to anyone needing 0?? to 75mg 100mg to > anyone needing 76 - 150mg etc... from there they are taking that range and > saying that's a 31% overdose to a 33% underdose. Then they want to find if > there is a starting number which minimises the extent of under and > overdosing... > > Anyone know of an existing stats function in R that can easily do that and > almost then report from some inputs a single number that is the "best fit"? > > Calum The first place I would start is with the two relevant CRAN Task Views: http://cran.r-project.org/web/views/ClinicalTrials.html and http://cran.r-project.org/web/views/Pharmacokinetics.html There is also another package not listed above that might be relevant: http://cran.r-project.org/web/packages/scaRabee/ Regards, Marc Schwartz ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
