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<TITLE>Re: [RASMB] Precision of c(s) method</TITLE>
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<BLOCKQUOTE>Hi Matt<BR>
<BR>
I think that Tom has put things very nicely, but here are just one or two extra points.<BR>
<BR>
We do an awful lot of analyses for a range of bio/pharma products, and whilst mostly this is done 'in confidence' I have no problems about drawing and stating a few general conclusions based upon our experience. Needless to say, antibodies of one sort or another are not unknown as samples provided to us for analysis, the issue of 'what sort of aggregates if any are present' forms a good 50% of our commercial work,, and as you say there is a growing interest in the regulatory bodies in having formulations controlled and validated in these terms. <BR>
<BR>
The issue of aggregation is complex. I agree with Tom that you can, on a good day work to around 1%. By which I mean that you can under favourable circumstances say that a preparation is 99% monomeric, rather than 100%. Antibodies are actually quite good to work with, their s value is higher than that of smaller proteins, and their shape does to some extent limit diffusion and hence improve resolution. BUT - resolution with respect to what? If we are talking dimer, then that 1% limit is believable. If what is present at the 1% level - other than monomer - is a broad range of higher oligomers, then you will have an uphill task in saying whether such material is there or not. You really cannot distinguish a range of species each present in miniscule amount from baseline in a c(s) plot. I personally do like to compute a ls-g(s) profile when looking for small amounts of perhaps poorly defined dimer (not so much with Ab's) - but this offers no improvement at all for broad spectrum oligomers. The best you can do is to state that "this was a SEC-purified prep - it <I>must</I> have been stripped of these things"! But that assumes that no changes occur between column and AUC.<BR>
<BR>
It may be that high precision sedimentation equilibrium can help here - that technique can 'see' a bit of higher M stuff in a way that SV does not. We have some new approaches going in this area, which I will be talking about at the London Meeting in 2 weeks time. <BR>
<BR>
The lack of any real theoretical (or even solidly empirical) knowledge base concerning aggregation is appalling. 'Experts' tend to be people who stroke their beards and murmur things like 'adding a bit of trehalose/whatever often works . . . . ' Big bits of ill-defined material are a major pain in bio/pharma formulations, yet how do they form? Is the presence of small amounts of higher oligomers a sign of their incipient formation? And 100 other question. But no funding body will touch such questions ('too applied'). <BR>
<BR>
Actually, I will stop here before I <I>really</I> get onto one of my soap-boxes.<BR>
<BR>
Arthur<BR>
<BR>
<BR>
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Arthur J Rowe<BR>
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University of Nottingham<BR>
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<BLOCKQUOTE><TT>Hi Matt-<BR>
This is an excellent, but difficult, question. I expect there will be a <BR>
good discussion. Here's my two cents:<BR>
Sedimentation velocity is a technique of *accuracy* and not merely <BR>
precision. The x-axis of a c(s) plot has real physical meaning, and the <BR>
data from an experiment stand on their own (no standards are needed). <BR>
Size exclusion is a technique of precision- reproducibility is all that <BR>
is required, and the reproducibility is relative to a set of standards. <BR>
Hence, SV and SEC are truly orthogonal methods.<BR>
Since SV is a technique of accuracy, reproducibility depends on <BR>
everything being the same. While much of an experiment is under your <BR>
control, and thus can be made reproducible, some aspects are hard for <BR>
you to control. For example, small differences in centerpieces and how <BR>
they are assemble can make a difference. Certainly the reproducible <BR>
alignment of the centerpieces is important. Most importantly, c(s) is <BR>
curve fitting and can ONLY tell you about precision and not accuracy. <BR>
Changes to the fitting parameters will affect the result returned by the <BR>
analysis.<BR>
That said, careful work typically can get you to the 1% range.<BR>
If you want to be sure that you have 1% of an aggregate (an accuracy <BR>
question), however, you must do repeated experiments- you will never be <BR>
able to be certain by reanalyzing the same set of data (which can only <BR>
tell you about precision).<BR>
Best wishes,<BR>
Tom<BR>
<BR>
<BR>
Parker, Matthew wrote:<BR>
<BR>
> Hi folks.<BR>
><BR>
> I was wondering if people could give their views on the degree of <BR>
> precision that can be expected from the c(s) method, or other methods <BR>
> for fitting SV data, for assessing the degree of aggregate formation <BR>
> in a protein sample. (Monoclonal antibodies, in particular.) The FDA <BR>
> is starting to ask for ³orthogonal methods² to back up SEC data on <BR>
> aggregate formation. Is it reasonable to expect that SV can give the <BR>
> same degree of reproducibility when dealing with, say, 1 to 5% <BR>
> aggregated species? Has anybody done any systematic determinations of <BR>
> the precision of the method? (Subjective impressions are also welcome!)<BR>
><BR>
> Thanks,<BR>
><BR>
> Matt<BR>
><BR>
> Matthew Parker, Ph.D.<BR>
><BR>
> Analytical and Pharmaceutical Sciences<BR>
><BR>
> Immunogen, Inc.<BR>
><BR>
> 128 Sydney St.<BR>
><BR>
> Cambridge, MA 02139<BR>
><BR>
> (617) 444-2028<BR>
><BR>
> (617) 995-2544 fax<BR>
><BR>
> matthew.parker@immunogen.com <mailto:matthew.parker@immunogen.com><BR>
><BR>
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<BR>
-- <BR>
Department of Biochemistry and Molecular Biology<BR>
University of New Hampshire<BR>
Durham, NH 03824-3544<BR>
Phone: 603-862-2459<BR>
FAX: 603-862-0031<BR>
E-mail: Tom.Laue@unh.edu<BR>
www.bitc.unh.edu<BR>
www.camis.unh.edu<BR>
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