Search

Type here to search the website for related content

Search

Show results for
  • Pages ()
  • Blog ()
  • In the News ()
  • Press Releases ()
  • Events ()
  • Webinars ()
  • Resources ()
  • Success Stories ()

IDBS Blog

Back to IDBS Blog

lightbulb

Pharma and biotech companies have invested heavily in externalized research, development, and manufacturing in recent years – but their methods of sharing critical data are still rarely fit for purpose.

Typically, collaborator data is simply packaged up in a PDF format and sent via email. Job well done, right? Not quite…

96% of pharma executives say their companies have plans to collaborate with strategic partners.[i]  And, according to Deloitte, externally developed assets account for over half of their survey respondents’ late stage pipeline; of that co-developed assets account for 30%.[ii]

Publicly traded companies that depend on collaboration often emphasize the risk that should “any failure on the part of our collaborator to comply with applicable laws and regulatory requirements… could have an adverse effect on our revenues as well as involve us in possible legal proceedings.”[iii]

The current methods of collaboration present the following issues:

Collaborating through PDF reports is inefficient

When experimental reports are received they are usually in a PDF format, making the extraction of data (against which to perform advanced analysis) difficult and time consuming. Because data is manually transcribed from the PDF to an analysis template, transcription errors are common. Studies measuring the error when transcribing paper-based data sets into an electronic system found:

  • For every 100 characters transcribed, more than two of those characters are transcribed incorrectly
  • The studies showed a 2.6% average transcription error rate.[iv],[v],[vi]

And, because the reports only summarize the end result, the collaboration sponsor may not know the context of the experiment, including failures of experimental design or execution, or be certain that the correct scientific analysis and business rules were followed. To make matters worse, endpoint data is devoid of sample or instrument metadata, such as calibration status, that can be used to prove compliance with a SOP. Endpoint data, unlike the raw data that generates it, cannot be re-analyzed or compared to raw data sets generated by the collaboration sponsor’s in-house team[vii].

Collaborating through email is not secure

When reports are shared, they are usually sent through email. An industry survey showed that 84% of respondents admitted to sending classified or confidential information via email.[viii]  Sharing data through email presents several risks including the lack of traceability (attachments and email are uncontrolled with no audit trail), the poor security of email systems, and circumventing compliance with federal regulations (by forwarding or storing restricted information outside of the corporate firewall).

The lack of security is a problem. In one US State of Cybercrime Survey, 79% of respondents said they detected a security incident in the past 12 months.

Complicated collaboration tools have poor user adoption

Users demand simple and intuitive interfaces to perform daily tasks. Complicated, “feature-rich” tools with poor user interfaces encourage users to go around the system, and inconsistent usage causes the tool to be out of sync with actual work being done. Because usage is not consistent, more users go around it, cascading the inaccuracies, and resulting in a complete distrust of the records.

Innovation requires informal networks

To support the random occurrences that fuel innovation, organizations benefit from a collaboration tool that facilitates sharing ideas beyond the traditional project team. Studies from Stanford University and the University of Chicago illustrate the benefit of informal, cross departmental networking[ix]. A collaboration tool that enables users to view popular content, follow thought leaders, and engage them and their peers in conversation helps to create and maintain the types of networks needed to drive innovation. So, how can IDBS help?

The E-WorkBook Cloud creates a single environment for R&D collaboration that combines work planning, data capture and review features in one place. E-WorkBook eliminates the risks associated with sharing valuable IP through email or uncontrolled file transfer sites. To find out more, contact us here.

 

References

[i] “Managing Innovation in Pharma – Pharmaceutical industry perspectives on the Global Innovation Survey 2013”, PwC, 2013

[ii] “Measuring the return from pharmaceutical innovation 2014”, Deloitte LLP, 2014

[iii] Biogen 2015 Annual Report

[iv] Smyth ET, McIlvenny G, Barr JG, Dickson LM, Thompson IM. Automated entry of hospital infection surveillance data Infect Control Hosp Epidemiol 1997;18:486-491

[v] Jorgensen CK, Karlsmose B. Validation of automated forms processing. A comparison of Teleform with manual data entry. Comput Biol Med 1998;28:659-667

[vi] Weber BA, Yarandi H, Rowe MA, Weber JP. A comparison study: paper-based versus web-based data collection and management Appl Nurs Res 2005;18:182-185

[vii] “The Business Challenges of Externalizing R&D”, http://www.scientificcomputing.com/article/2015/12/business-challenges-externalizing-rd

[viii] “Are Employees Putting Your Company’s Data at Risk?, Survey Results Exposing Risky Person-to-Person File Sharing Practices”, Ipswitch File Transfer, 2012

[ix] In the Stanford study, participants that maintained diverse networks that expanded beyond their area of focus were three times more innovative as theirs peers (as measured by the number of trademarks registered, patents filed, or new products released, among other factors).  The University of Chicago study evaluated innovation at Raytheon Corporation and found that innovative thinking was more common among employees with active networks outside of their division as compared to peers who shared information only among their own group – “Where Good Ideas Come From”, Steven Johnson, 2010, p166.