Currently submitted to: JMIR Formative Research
Date Submitted: Jun 20, 2019
Open Peer Review Period: Jun 24, 2019 - Aug 19, 2019
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note “no longer under consideration” will appear above).
Peer-review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a “Peer-Review Me” button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed “version of record” (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
From random Brownian motion of particles to high automation laboratory: a brief history of correlation time
Laboratory automation is the actual frontier for the increase of productivity and reduction of samples turnaround time (TAT), in turn used as a key indicator of laboratory performance. However, due to the statistical distribution of TAT values, classical parameters (mean, standard deviation, percentiles) fail to describe each single sample processing “story”. The driving idea of the present work is to assimilate the samples flow in an automation laboratory to the movement of molecules in solution by means of Dynamic Light Scattering Correlation Function analysis expansion.
The aim of the approach is the increase of productivity and the reduction of laboratory process cycle times thus improving data quality level. The most widely known application of laboratory automation technology is robotics, based on many different automated laboratory instruments, devices (the most common being autosamplers), software algorithms and methodologies assembled together to form an unique production chain starting from the arrival of the biological sample in the lab to the output of clinical useful final results.
TAT values from 10000 samples were used to build a correlation function. Through a time course, each sample perfectly correlates with its initial status (no results available) until its specific TAT value is reached and assumes a value of 1; after the TAT is reached (produced results) it no more correlates and its status value becomes 0. The generated correlation function is simply the normalized progressive timing sum of all analyzed samples status conditions at each specific time.
By correlation function analysis, several parameters to describe the general performance of the system as well as each individual sample status are derived and applied to monitor the efficiency of the automation chain in real time mode.
Our original approach to laboratory automation leads to the possibility of determining measurable criteria able to describe the entire system capacity to buffer and reduce problems both on the full performance or on spot samples, consequently developing a new tool to evaluate different or improved performing systems Clinical Trial: none
Request queued. Please wait while the file is being generated. It may take some time.
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.