A perspective on paperless operations in a modern bioanalytical laboratory

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Transcription:

7th Open Meeting Beyond the Horizon - Painting a new landscape A perspective on paperless operations in a modern bioanalytical laboratory Spotlight on e-data Workshop Jim Brennan Wednesday 19 November 2014

Abstract The goal of eliminating paper in the bioanalytical laboratory has existed for decades. Many approaches have been employed to achieve this. Laboratory information management systems (LIMS) have been used successfully to maintain bioanalytical data, assuring their accuracy and consistency over the life cycle from the sample tracking, instrument results processing and final result reporting steps. As regulatory requirements increased, ligand binding assays became more prevalent and additional bioanalytical data needed to be captured electronically LIMS evolved and electronic laboratory notebooks (ELN) came into the mix. Now we see the achievement of a paperless bioanalytical laboratory is possible. Added benefits of these efforts is a reduction in the data management burden on bioanalytical scientists, improved data quality review, more efficient reporting and cost savings for pharmaceutical companies and contract research organizations. This presentation will focus on the types of data managed by bioanalytical laboratories, common bioanalytical data management approaches, the supporting infrastructure and what is on the horizon for a paperless bioanalytical data environment. LabWare [2]

Outline n Going paperless in a bioanalytical laboratory n Relevant e-data n Commonly utilized software n Approaches to eliminating paper n Challenges with current approaches n What s on the horizon and beyond LabWare [3]

The Paperless Bioanalytical Laboratory n It has been achieved! n Scientists are managing data more efficiently. n Data access has improved. n Quality review is easier. n Reporting is better. Are these paperless systems fast, easy-to-use, interoperable, compliant and truly paperless? LabWare [4]

e-data in Bioanalytical Processes Protocol Report Draft QA Review Sample Receipt Data Review Archive Sample Storage Analysis SOPs, Training Adapted from Patel, S., Huang, Q., Jian, W., Edom, R., and Weng, N., Overview: Fundamentals of a Bioanalytical Laboratory, 2013, in Li, W., Zhang, J., and Tse, F.L.S., Handbook of LC-MS Bioanalysis: Best Practices, Experimental Protocols, and Regulations, Wiley, Hoboken, p. 15. LabWare [5]

Some Common Bioanalytical Software lims eln Laboratory Information Management System Track samples Manage laboratory work Capture results Produce laboratory reports Electronic Laboratory Notebook Replace paper notebooks Document research Experiments & Procedures sdms Scientific Data Management System LabWare [6] das Data Acquisition System dms Document Management System

LIMS and ELN LIMS: Log Samples ELN: Procedures & Methods Lab Workflow Management Review and Report Results LabWare [7]

LIMS and ELN But we have many coins in our pocket! LabWare [8]

Bringing the pieces together n Efficient interoperability n Tools to extract data from one system and export to others Files Database to database API Web Services n Which data? n Some examples LabWare [9]

Bioanalytical Software Tools LIMS Centric ext das sdms pk lims dms eln LabWare [10]

Bioanalytical Software Tools Report Centric eln lims pk Report erp lims crm LabWare [11]

Bioanalytical Data Management Systems Study Centric report TABLES GRAPHS TEMPLATES lims SAMPLES TESTS RESULTS eln EXPERIMENTS PROCEDURES LOGBOOKS REVIEW APPROVAL STORE REPORT dms LabWare [12]

Bioanalytical Data Management Systems Study Centric report lims STUDY eln dms LabWare [13]

Bioanalytical Data Management Systems n Diverse combinations n Developed gradually n Custom applications n Unique LabWare [14]

Challenges n Maintaining multiple systems n Interfaces n User acceptance and training n Validation n Flexibility LabWare [15]

Bioanalytical Data Management Horizon Rethinking Bioanalytical Data Management n Open-source software n Common data standards n Convergence of informatics systems LabWare [16]

Open-source software n Economical n Built collaboratively n We already see it in bioanalysis: LabWare [17]

Common Data Standards n More than just savings in time and money n More than just interoperability n Data accuracy n Scientists can do the science n Easier transfer of data between partners n Decision making is simplified LabWare [18]

Convergence of informatics systems n Complimentary functionality n Evolving towards a common technology n Less interfacing n Still need interoperability PLATFORM LabWare [19]

Final thoughts on going paperless n Many options for data management n Watch for functionality overlap n Plan well n Ongoing support and maintenance n Adaptability and flexibility lims eln sdms dms LabWare [20]