Biomedical Engineering Reference
In-Depth Information
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Where do you obtain that data and information?
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Where, if any place, do you store annotations or comments about the
work you have performed on targets?
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Approximately how many targets per year does your Research Unit
(RU) have in active research? How many are new?
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What are your pain points around target selection and validation?
Based on these discussions, we developed a solid understanding of what
the user community required from the new system and the benefi ts that
these could bring. Highlights included:
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Use of internet tools: most colleagues described regular use of the
internet as a primary mechanism to gain information on a potential
target. Google and Wikipedia searches were most common, their speed
and simplicity fi tting well with a scientist's busy schedule. The users
knew there were other resources out there, but were unclear as to
which were the best for a particular type of data, or how to stay on top
of the ever-increasing number of relevant web sites.
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Data diversity: many interviewees could describe the types of data that
they would like to see in the system. Although there were some
differences between scientists from different research areas (discussed
later), many common areas emerged. Human genetics and genomic
variation, disease association, model organism biology, expression
patterns, availability of small molecules and the competitor landscape
were all high on the list. Given that we identifi ed an excess of 40
priority internal and external systems in these areas, there was clearly
a need to help organise these data for Pfi zer scientists.
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Accessing the internal target portfolio: many in the survey admitted
frustration in accessing information on targets the company had
previously studied. Such queries were possible, particularly via the
corporate portfolio management platforms. However, these were
originally designed for project management and other business concerns,
and could not support more 'molecular' questions such as 'Show me all
the company targets in pathway X or gene family Y'. As expected, this
issue was particularly acute for new colleagues who had not yet
developed 'work arounds' to try to compile this type of information.
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Capturing proteins 'of interest': one of the most interesting fi ndings
was the desire to track proteins of interest to Pfi zer scientists but that
were not (yet) part of the offi cial research portfolio. This included
emerging targets that project teams were monitoring closely as well as
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