Pharmaceutical Technology LABORATORY BEST PRACTICES 2018 27
traceability and security of data—integrity. Data integ-
rity is a fundamental traceability requirement in any
pharma/biotech. Companies must assess if the data are
trustworthy and if they can make business-critical de-
cisions based on it.
The gap with internal systems is that they are just
that: internal. Exposing them to CROs is possible, but
what happens when the CRO has their own systems,
which the CRO staff knows and readily uses? Essen-
tially, there is a problem of exchanging the audit log
for a piece of data between parties. New technologies
are being considered to solve this problem, such as
blockchain, which aim to provide a full history of
what has happened to something over time. Current
systems, however, do not use blockchain in this fash-
ion. While there are many blockchain companies and
platform providers, there currently are no real proven
providers of blockchain networks specifically for this
purpose.
Data quality
The final data-centric aspect that needs considering is
quality. This is also a barrier to sharing data, as quality
is subjective. To remove the subjective nature of what
the measure of quality is, the context for a piece of data
is needed. All things that could impact the data point
need to be known: what instrument it was run on,
what software was used to analyze it, what standards
were used to run the experiment, what conditions
were like in the lab (metrology); what other instru-
ments were used to prepare buffers and media and
were they calibrated properly, was the scientist trained,
did they make the buffer solution properly? The list
goes on. So, if this "context" is not present with the
data, then the quality of the data cannot be assessed,
and decisions made on it may be flawed. This is the
routine question every sponsor organization asks of
its CRO and proving it in a systematic, easy manner
is difficult, as much of the data exists in different soft-
ware systems. From an industry perspective, sponsors
would love a CRO to use their systems, but this is not
always possible or easy to set up due to enterprise sys-
tem security policies.
The utopian view would be a network of software
solutions—an ecosystem—that all work seamlessly
together to deliver the data collaboration services re-
quired. The reality is that the industry is not there yet,
but there are emerging endeavours to help address this,
such as the Allotrope Foundation, who are looking to
"revolutionize the way [they] acquire, share, and gain
insights from scientific data, through a community
and the framework for standardization and linked
data" (2) and the Pistoia Alliance, which supports
and funds projects that transform R&D innovation
through pre-competitive collaboration (3). Each effort
is focused on breaking down the barriers to data and
process sharing in pharma and biotech.
CROs are a necessary part of the small-molecule and
biologics drug development lifecycle, but increasingly,
customer expectations go beyond a simple PDF report
as a deliverable. Getting the right data solution in place
that allows safe, secure, and direct collaboration should
be a critical objective with the data from the entire life-
cycle of a drug being available at the sponsor scientist's
fingertips. The industry is some way from the utopian
state at the moment, and the business model aspects
of this requirement need to be worked out and not just
the core software and technical data sharing aspects.
References
1. FDA, NDA and BLA Applications, FDA.gov, www.fda.gov/drugs/de-
velopmentapprovalprocess/howdrugsaredevelopedandapproved/
drugandbiologicapprovalreports/ndaandblaapprovalreports/default.
htm, accessed Aug. 10, 2018.
2. Data Standard, Allotrope Foundation, (2018), online, www.allo-
trope.org, accessed Oct. 3, 2018.
3. N. Lynch and D. Proudlock, Home–Pistoia Alliance, online, Pis-
toiaalliance.org, (2018), accessed Oct., 3 2018.
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