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Subject:
From:
Jerry Bromenshenk <[log in to unmask]>
Reply To:
Informed Discussion of Beekeeping Issues and Bee Biology <[log in to unmask]>
Date:
Sat, 4 May 2013 11:55:13 -0400
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Pete says: <You are not really addressing the issue, which is: Why Maryann  
Frazier felt compelled to address the EPA and the USDA in a national press  
conference over their alleged non-recognition of academic research due to 
lack  of compliance to Lab Procedures. 

Does anyone think that the Fraziers are  not performing their studies 
according to sufficient rigor? To me this seems to  be the tip of the iceberg of 
a much bigger question: If the Fraziers are on to  something, and it is 
being ignored for any reason>
 
Actually, I'm saying that her statement runs contrary to what  EPA is 
legally mandated to do.  EPA clearly outlines their approach to  data resultant 
from 'research lacking compliance' - and please, let's drop  the adjective 
ACADEMIC.  It is not an ACADEMIC matter - its a matter of  data accuracy 
irrespective of who or what type of institution  conducted the study.
 
Contrary  to the assertions of the Fraziers, EPA  does not necessary reject 
data just because it was exploratory and/or not  performed under GLP.
 
In the agency’s  own words:  "Ideally, tests to gather such information 
have been conducted  under optimum conditions and follow good laboratory 
practice (GLP). However, for  the purpose of satisfying a specific .. data 
element2, it is  important to consider existing information that might not have 
been generated  under ideal conditions."
 
Even other  published scientists have acknowledged that: :If the  study is 
well conducted and reproducible and the interpretation is clear, it can  be 
used by EPA to support risk  assessment. 

The Fraziers often cite European studies.  In Europe, there is always a 
push to standardize or  harmonize everything, regardless of whether their 
standard approach works in  other countries – I’ve been involved in those types 
of discussions since the  late 1970s – and its always the same.  I remember 
a series of workshops aimed at long-term monitoring and the  selection of 
sentinel/indicator animals and plants.  Only problem, many of the proposed  
species were unique to Europe and did not occur in North  America. 
Thus, one  will see reference in European studies to the Klimisch  score.   
EPA has been accused of blindly following this  approach and in doing so 
rejecting useful data.  
EPA has addressed this  accusation, saying:  The  Klimisch method “ is 
similar in principle to EPA’s tiered approach in that both  methods present 
specific criteria for evaluating existing data. In fact, the  data reliability 
criteria presented by Klimisch and by EPA (in Tier I) are  remarkably 
similar. The difference between the two approaches is in how the  criteria are 
used. 
Klimisch et al.  use their criteria in the following scoring system for 
evaluating data reliability3: 1 = reliable  without restrictions; 2 = reliable 
with restrictions; 3 = not reliable; and 4  =not assignable. The Klimisch 
ranking system does not conflict with the EPA  approach.  
Klimisch et al.  define adequacy as “the usefulness of data for risk 
assessment purposes”,  whereas EPA uses the "term to mean usefulness for hazard 
identification  purposes." 
EPA goes on  to state: Assigning a  numerical value to each study is both 
useful and comprehensive; however, EPA  believes using the same criteria as a 
screen (Tier I as described below) results  in the appropriate “weeding out”
of data/studies not useful in describing an  endpoint. For example, studies 
assigned Klimisch reliability codes “3" or “4"  would not advance to Tier 
II in the EPA approach, except for those cases in  which a 
weight-of-the-evidence analysis might be used (see  below). 
NOTE the  weight-of-the-evidence criteria is important and applies to the  
type of studies in question.  When weight-of-the-evidence  comes into play, 
and EPA applies their Tiered Approach:  
"Tier I assesses  “experimental fitness”; thus, existing data rejected in 
Tier I for a particular  endpoint may
be identified as a data gap that needs to be filled by  testing." 
Jerry 


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