FEB 27, 2019 6:00 AM PST

The Missing Link to Improving Efficiency and Productivity in the Digital Lab

Presented at: Drug Discovery 2019
C.E. Credits: P.A.C.E. CE Florida CE
Speaker
  • Chief Commercial Officer, Somark Innovations
    Biography
      Jay has spent the past 30 years as a commercial lead in marketing and sales for several of the top leading life science providers including Corning Life Sciences and Charles River Laboratories. He recently joined Somark Innovations as Chief Commercial Officer where he is responsible for the global sales and marketing organization as well as supporting all new technology launches. He is an advocate for better science and science processes as he ultimately believes these will bring about cures faster.

    Abstract

    The Chain of Custody in our labs is the unbroken link between the objects used in your research: your people, the animal models, the cell lines, reagents, compounds; the lab instruments and devices; the data records your store your data in; the link between the analytics and the data collected. In the Smart Lab – there is no place for uncertainty. SMART requires your research and data to be Specific, measurable, auditable, repeatable BUT, preclinical research is a long way from being SMART.

    Learning Objectives: 

    1. Manual recording of experimental data, manual input of results data – they leave the process open to human error, transcription issues and  do not provide audit trails and lack transparency. In the late 80,  early 90s there was an often quoted saying in the early days of data science: Garbage in; Garbage out. 
    2. There is significant excitement, rightfully so, about Machine Learning and AI. But if you are training your algorithms on poor quality data – really how good are your algorithms? The key strategic advantage of a SmartLab based on digital ID and automated data collection is the data authenticity, accuracy and reliability.  And what you will see is the higher quality of data will drive insights faster. You can even start to move toward near real time discovery of  exceptions, of errors, of trends.


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