RLS: In addition to the predictive capability, what will the lab of the future be like?


GT: Wi-Fi has reduced communication con- straints, but this is only partly played out. Each instrument or workstation


will self-


identify and report status to the analyst and other stakeholders. This will be integrated with LIMS systems [sic] and the BIOVIA Unified Lab to keep track of samples, reagents, staff and deadlines. I anticipate that self-checking will become more sophisticated, including cross-checking that the proposed sample and method are consistent.


Out-of-specification results and quality audits will be anticipated and supported over the prod- uct lifetime, which may span several operating systems from the instrument to enterprise level.


RLS: How will laboratory staff be affected?


GT: Electronic notebooks will become more useful in the lab, [and] not just used in stationary situations; mobility will enable the elimination of paper finally. But local NFC, which stands for near field communications, will provide detailed logs of people and events. Today this is partially implemented with RFID [radio- frequency identification] chips and fingerprint readers. Future developments will include biometric information, such as an iris scan, or a personal ID bracelet that logs in the analyst from information on the bracelet.


Further out, heads-up displays will read the method and guide the lab tech to the next step and illustrate the desired process. This is already being implemented with personal eyeware such as Google Glass. This may lead to live video exchanges with colleagues, which might be very useful in method transfers and maintaining proficiency across many sites.


RLS: What about sustainability? I understand that in 2013, the electrical power consumed by data farms was about 2% of the global energy diet. Plus, the doubling time is less than two years. A genome consumes about 7 kilowatt hours of storage. Is this sustainable?


GT: Moore’s law is working on energy efficiency also. We will need new, more energy-efficient storage devices, and these are in development. Spinning discs will be replaced, hopefully soon, with solid-state memory. This should offer greatly improved speed, reliability and energy efficiency.


RLS: How do you see the evolution of future technology? I see a contrast in the way that sound recording, primarily music, jumps from one format to the next about every 10 years.


GT: I anticipate that laboratory communica- tion will be slower to develop than consumer electronics. The market is smaller, and instru- ments have longer useful lives. I expect that


adoption will be more a continuum than disruptive breakthrough.


For example, wearable displays and heads- up safety glasses will probably evolve over decades. After all, despite all the advantages, adoption of electronic laboratory notebooks has been slower than many predicted. But the biometric bracelet or necklace may be a simple extension of the company ID card.


RLS: Social media use in the lab has lagged behind its adoption by consumers. What do you see?


GT: Social media could play a role in helping networking among users of particular instru- ments. Points of technique could be especially useful. Video communication could help in method transfer. This is done some inside an enterprise, but I could see how this could be extended to consultants.


In the area of forensic science, I can see that continuous recording via body cams could help restore credibility to forensics. This is similar to the current use of cell phones and body cam- eras by police. In the lab, the cameras could be tied to ELNs [electronic laboratory notebooks] so that visual evidence would corroborate the analytics, particularly in sample manipulation and preparation. The recent publicized prob- lems with crime labs must be addressed.


RLS: What should we lab rats be implementing now?


GT: Lab staff should be concerned about “truth and trust.” As laboratory work advances using ever more sophisticated technology, it is essential that we validate our results to support valid decision-making. Metrology without integrity is an oxymoron. Look for ways that computers can help systematize our work and results. Humans too often fail doing routine tasks, but computers are not good at recognizing the unexpected. Clearly, good science needs both. So automate where you can, but do not lose sight of the process. Continue to look for opportunities for improve- ment. I think that in-process optimization routines are an excellent current opportunity.


Robert L. Stevenson, Ph.D., is Editor Emeritus, American Laboratory/Labcompare; e-mail: rlsteven@yahoo.com.


AMERICAN LABORATORY • 41 • AUGUST 2015


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