# PharmPK Discussion - Weighted curve fitting with Berkeley Madonna

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• On 19 Jul 2010 at 16:02:16, David Bourne (david.at.boomer.org) sent the message
`The following message was posted to: PharmPKIs it possible to perform a weighted curve fit with Berkeley Madonna?  That is, can the data be weighted by some function representing  reciprocal variance. I note the method for weighting difference data  sets when performing curve fitting but this does not seem to allow  weighting individual data points. Log transforming the data appears to  allow weighting by 1/val^2. Am I missing something?Thank you, David Bourne`
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• On 20 Jul 2010 at 14:59:37, "Solapure, Suresh" (suresh.solapure.at.ASTRAZENECA.com) sent the message
`In the Berkeley Madonna version 8.3.11 that I frequently use for PKPD  modelling, there is no provision for weighted Least Square analysis. In  PK data analysis, it is recommended that we use Ordinary Least Square  (OLS method) analysis without applying weights only if the concentration  data is used after log transformation. Usual practise for PK model  fitting is ILS or Iterated Least Square analysis where 1/(predicted Y  square) is used as weight in successive iterations. Cheers. Suresh M.Solapure`
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• On 20 Jul 2010 at 14:38:09, "Roger W. Jelliffe" (jelliffe.at.usc.edu) sent the message
`The following message was posted to: PharmPKDear Suresh and all,  I would suggest that the best thing to do with weights is not tomess with Mother Nature. First, determine the assay SD (not CV%!) at about 5sample points covering the range of the assay. Divide these samples into atleast 5 (more is better) aliquots. Measure each aliquot and determine theassay mean and SD at each point. Next, fit the relationship between assayconc and its SD with a polynomial of up to 3rd order. Now you have a goodestimate of the SD for any sample that goes through your assay system.  Now, use a population modeling software package such as the NPAGsoftware in the MM-USCPACK collection, and estimate the remainingenvironmental noise in the system either  by estimating Gamma, amultiplicative factor, of Lambda, an additive factor. In this way you nowknow how much of the noise in the system is due to the assay and how much tothe environment. Useful info. And again, you are not INVENTING weights. Youare not messing with Mother Nature, which is a big no-no.  You might look at:Jelliffe RW, Schumitzky A, Van Guilder M, Liu M, Hu L, Maire P, Gomis P,Barbaut X, and Tahani B: Individualizing Drug Dosage Regimens: Roles ofPopulation Pharmacokinetic and Dynamic Models, Bayesian Fitting, andAdaptive Control. Therapeutic Drug Monitoring, 15: 380-393, 1993.Bustad A, Terziivanov D, Leary R, Port R, Schumitzky A, and Jelliffe R:Parametric and Nonparametric Population Methods: Their ComparativePerformance in Analysing a Clinical Data Set and Two Monte Carlo SimulationStudies. Clin. Pharmacokinet., 45: 365-383, 2006.All the best,Roger Jelliffe`
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