 | Nick, I would, of course, have to disagree that regulatory and marketing are minor shadows in the big picture - that is how new medicine come to improve health. I would suggest that better use of existing medicine is not much more than a minor shadow, and while I think you're almost certainly right (as usual), I can think of only a couple of examples where this has been empirically shown that pk/pd informed dosing insight GENERATED AFTER APPROVAL is better. Clearly the pk/pd work done for regulatory and marketing (yes, I said pk/pd work done for marketing) is a central part of any drug development proces!
s. Regulatory and marketing are necessary evils to getting new medicines to patients and play a central role in motivating pk/pd work. WRT the role of the academic: First, I'd point out that industry is very, very interested in seeing their drugs used optimally. There is no better marketing that having colleagues say that Drug X seems to consistently work better than Drug Y. Not that the pharma industry is altruistic (the companies aren't, although many of the employees are), this is just good business. At the same time, it is clear that a drug with a very complex dosing scheme will not be used (unless there are not other options, as in anti seizure drugs and chemotherapy). A drug that isn't used really doesn't help patients very much. Drug companies would (in my experience) love to see their drugs used optimally. Providers should be willing to put in the effort to do so. Providers also should eat less red meat, l!
ose weight, exercise more and use condoms (am I allowed to say that on
this forum?). They aren't willing to do those things either. I have seen disappointingly little progress in all of the above issues (except one) in the last 20 years. Please let me know when the academics have solved any of these problems. Mark Mark Sale MD
Next Level Solutions, LLC
www.NextLevelSolns.com
919-846-9185
-------- Original Message --------
Subject: Re: [NMusers] Reporting Modeling Results
From: Nick Holford <n.holford@auckland.ac.nz>
Date: Thu, October 25, 2007 2:40 pm
To: nmusers <nmusers@globomaxnm.com>
Mark,
We have a different view of the big picture. Regulatory and marketing are minor shadows in the big picture of using medicines to improve health.
My job as a university based researcher is not to fill forms for companies to send to regulatory agencies to tick boxes and write regulatory labels.
I work with clinicians to develop practical insights into treating children. Brian Anderson is a paediatric specialist who applies and teaches the concepts of rational dosing to clinicians. We work together to help understand PKPD in children and find ways to bring it to clinical use.
The idea is to define the science first and then to apply it eg. with tables of doses at different ages and weights. These tables are simple to generate and distribute for clinicians to use. We certainly dont expect people to apply the complex models that have been used to describe and understand the biology at the bedside.
I would hope that John Mondick can be supported by contemporary scientific literature to educate his colleague about science. After that they can find a way to apply the science in a suitable format for busy clinicians.
Nick
>
>
>
> Nick,
> I think, in the big picture, it is important to remember why we do all this. It isn't for our own
> entertainment, or to congratulate each other on how insightful we are. It is to provide useful
> information to providers. We are not (we hope) the real audience for our work. It probably isn't
> realistic to expect non-oncologist pediatricians to scale doses allometrically. It seems to be
> unrealistic for other physicians (except neurologists) to scale doses at all. Dose/kg may be the best
> we can hope for. I'm quite sure it is unrealistic to expect drug companies to request labels for non!
> -chemotherapy drugs based on allometric scaling (really bad marketing move) Doing so - although
> perhaps scientifically correct, would likely lead to even more dosing errors that we currently see,
> with undemonstrated clinical benefit.
> So, how to report depends on who your audience is. If it is a bunch of nerds who know what
> eignevalues are, allometric scaling is great, if it is people who have 12 minutes to examine,
> diagnose and treat a patients, maybe we can keep it simple. Doing otherwise puts use are risk for
> irrelevance.
>
>
>
> Mark Sale MD
> Next Level Solutions, LLC
> www.NextLevelSolns.com
> 919-846-9185
>
> -------- Original Message --------
> Subject: Re: [NMusers] Reporting Modeling Results
> From: Nick Holford <n.holford@auckland.ac.nz>
> Date: Thu, October 25, 2007 12:20 am
> To: nmusers <nmusers@globomaxnm.com>
> Cc: Brian Anderson <briana@adhb.govt.nz>
>
> John,
>
> Leonid correctly points out that it makes no difference in terms of parameter
> estimation what weight is used for parameter 'normalization' because this is just a
> linear scaling factor.
>
> My colleague, Brian Anderson, and I have preferred to consider this 'normalising'
> weight as a standard weight. We do not try to make anything 'normal' but simply
> choose a scale that will provide us with a parameter that represents a standard
> human. We use a weight of 70 kg as the standard (Holford 1996). This makes it
> easier to compare parameters estimated in different populations, e.g. adults and
> children, because the parameters are scaled to the same standard size. Recently
> we have pointed out that use of a size standard with a suitable model for
> maturation allows the simple prediction of adult clearances from data collected in
> children (Anderson et al 2007b). We note that this cannot be done in the reverse
> direction i.e. adult data cannot be used to predict the maturational changes in
> clearance which occur in very young humans.
>
> Leonid mentions that results are "routinely reported as V/kg or CL/m^2, etc" but
> this is simply tradition without any discernible scientific rationale - especially the
> use of the square metre as the standardising factor. Drugs are not eliminated to any
> important extent via the skin so there is no mechanistic reason for this. The surface
> area method is a hangover of discredited theories of allometric scaling. The per kg
> method of scaling clearance is also a problem because it leads to the misguided
> viewpoint that clearance is larger in children in adults (Anderson & Holford 1997).
>
> Perhaps you can help your investigator colleague to read some of the published
> literature in this area so that he/she can get a clearer understanding of the size
> scaling issue.
>
> The bottom line:
>
> 'We conclude with the proposal that, at least in terms of pharmacokinetics, the
> widely quoted aphorism “Children are not small adults” should be changed to
> “Children are small adults — babies are young children.” ' Anderson & Holford
> 2007a
>
> Nick
>
> 1. Holford NHG. A size standard for pharmacokinetics. Clinical Pharmacokinetics
> 1996;30:329-332
> 2. Anderson BJ, McKee AD and Holford NHG. Size, myths and the clinical
> pharmacokinetics of analgesia in paediatric patients. Clin Pharmacokinet
> 1997;33:313-27
> 3. Anderson BJ, Holford NH. Mechanism-Based Concepts of Size and Maturity
> in Pharmacokinetics. Annu Rev Pharmacol Toxicol 2007a Oct 3; [Epub ahead of
> print]
> 4. Anderson BJ, Allegaert K, Van den Anker JN, Cossey V and Holford NH.
> Vancomycin pharmacokinetics in preterm neonates and the prediction of adult
> clearance. Br J Clin Pharmacol 2007b;63:75-84
>
>
> Leonid Gibiansky wrote:
> >
> > Hi John,
> > I think you can safely separate statistics/mathematics and clinical use.
> > I would fit the model in the shape and form suitable to get the best
> > results (normalized to a typical patient in your case) and then report
> > the results in the form most convenient for the clinical use. If this is
> > per-kg values, then report it as they request. If you look in the
> > literature, results are routinely reported as V/kg or CL/m^2, etc.
> >
> > On a side not, I am actually surprised that you got different results
> > with different scaling. For the allometric scaling with fixed power, two
> > parameterizations:
> >
> > CL=TCL*WT^0.75 and CL=TCL*(WT/10)^0.75
> >
> > differ by the fixed factor
> > (1/10)^0.75 = 0.18
> >
> > I am not sure how this can influence your model CI so strongly. I would
> > check how you stratify the bootstrap data sets. Could it be that
> > stratification on something else depend on parameterization?
> >
> > If you would estimate the power:
> >
> > CL=TCL*(WT/10)^THETA()
> >
> > then parametrization would be more likely to affect CI, but for the
> > fixed power I would look for other explanations of the differences. It
> > would be easier to discuss the model if you would attach the PK block of
> > the nonmem code.
> >
> > Leonid
> >
> > --------------------------------------
> > Leonid Gibiansky, Ph.D.
> > President, QuantPharm LLC
> > web: www.quantpharm.com
> > e-mail: LGibiansky at quantpharm.com
> > tel: (301) 767 5566
> >
> > John Mondick wrote:
> > > I would like to get some feedback from the group concerning the reporting of
> modeling results. I have a Pop PK model developed from data arising from 124
> pediatric patients, age 1 to 48 months. All of the structural parameters have been
> scaled allometrically, with the median body weight used as the reference value.
> After accounting for body size, a covariate model was incorporated to describe
> maturational changes in CL for young children. The maturation of clearance was
> modeled using an exponential model proposed in:
> > >
> > > Andersen et al. Population clinical pharmacology of children: modelling
> covariate effects. Eur J Pediatr. 2006
> > >
> > > Two parameters are estimated as part of this model * the fractional change in
> CL for a typical one month old patient (beta - estimated to be 0.76 (0.589, 0.96)
> for this analysis) and a maturational half-life (TCL - 3.82 (1.57, 6.95) months).
> CI’s are from the bootstrap.
> > >
> > > The problem that I am running into is how to report the modeling results. It
> seems very natural to me to report the model results normalized to median body
> weight (L/h/10.4 kg^0.75). One of the study investigators disagrees with me and
> would like to report the results on a per kg basis (L/h/kg^0.75). This seems to be
> counterintuitive to me, as I tend to think about what represents the “typical
> patient.” It also makes no sense to me to represent the CL in a one kg child. The
> argument is that reporting in this manner makes more sense to clinicians and that
> there is no such thing as a typical child.
> > >
> > > So in an attempt to appease the investigator, I fit the same model with no
> weight normalization. The estimated parameters are equivalent to what would be
> scaled from the weight-normalized model, but there is no covariance matrix (not
> surprising). It becomes problematic when the bootstrap results are considered *
> beta = 0.78 (0.005, 0.995), TCL = 3.90 (0.001, 6.018). Again, this is not
> surprising given that the covariate model is not centered.
> > >
> > > I have attempted to make several compromises, including reporting the
> parameter estimates in both median weight-normalized terms and normalized per
> kg. I have also included scaled CL estimates for typical patients at several ages
> and body weights. This hasn’t met the approval of the investigator, who is now
> insisting that I report the model building procedure from the median weight model,
> but report scaled parameters only on a per kg basis. This is wrong in my opinion
> and is actually more confusing to someone who is trying to understand the model.
> > >
> > > Can I get the group’s opinion on this? Am I being stubborn looking at the
> world through a modeler’s point of view?
> > >
> > > Thanks,
> > >
> > >
> > >
> > >
> > > John Mondick PhD
> > > Research Assistant Professor
> > > Division of Clinical Pharmacology and Therapeutics
> > > The Children's Hospital of Philadelphia
> > > Tel (267) 426-2292
> > > FAX (215) 590-7544
> > > Email: mondick@email.chop.edu
> > >
> > >
>
> --
> Nick Holford, Dept Pharmacology & Clinical Pharmacology
> University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
> n.holford@auckland.ac.nz tel:+64(9)373-7599x86730 fax:+64(9)373-7090
> www.health.auckland.ac.nz/pharmacology/staff/nholford
>
>
>
>
--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
n.holford@auckland.ac.nz tel:+64(9)373-7599x86730 fax:+64(9)373-7090
www.health.auckland.ac.nz/pharmacology/staff/nholford
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