Biomedical Engineering Reference
In-Depth Information
23]. On the other side, open, public chemistry and biology data repositories
(PubChem, ZINC, eMolecules, ChemSpider, etc. [24, 25]) focus on publicly
available data and are not designed for comprehensive data archiving. For
example, recent articles have assessed the expanding public and commercial
databases containing bioactive compounds [8, 9, 18, 19, 23, 27]. Such open
repositories clearly lack the ability to specify private data or limit sharing to
selected groups so users have been forced to make a choice between sharing
all or none of their data. What is perhaps needed is a selective, secure, col-
laborative software. For community-based drug discovery to work within the
larger biopharmaceutical industry, a platform must have:
1.
Strong privacy, security, and collaborative software features
2.
Ability to handle both free text and complex, heterogeneous drug dis-
covery data and molecular structures, capturing not just small molecules
but larger products seen in the biotechnology industry
3.
Data presentation and organization that allow both humans and comput-
ers to easily draw conclusions and prioritize experiments, leading to new
insights
In general, tools that enable the
selective
sharing of diverse data would be
a valuable asset, especially within the area of neglected disease drug develop-
ment for which the need for collaborative efforts has been well documented
[26, 27]. Due to relaxed commercial considerations, neglected disease research-
ers are certainly more open to selective, appropriate sharing and they are
therefore an ideal, forward-thinking community to evaluate innovative data-
sharing concepts, with potentially transformational implications for all drug
discovery efforts [28].
Exploiting more than six years of experience of using cloud computing and
Web 2.0 [24], Collaborative Drug Discovery (CDD) has developed a unique
Web-based software currently helping scientists optimally identify and advance
novel drug candidates. The software allows scientists to not only manage and
analyze their data more effectively but also optionally share their data effort-
lessly and securely to the degree they want, with whomever they wish, at the
time of their choosing [19]. It allows them to easily toggle between and simul-
taneously mine across private, shared, and public data sets. The CDD software
and existing user network are uniquely positioned to improve collaborations
in the neglected disease space, thereby increasing the effi ciency of drug dis-
covery and development [4].
As a test case for collaborative drug discovery, we will describe our plans to
further develop CDD using intelligent informatics. This will facilitate collabo-
ration among researchers that are working on similar projects or diseases and
bridge across private data networks to retrieve more meaningful pubic data.
Because of the secure and confi gurable sharing capabilities, researchers from
pharma, academia, government, and foundations are open to sharing selected
data and algorithms via CDD. We will also describe how this database:
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