omation mbers - Society for Laboratory Automation and Screening
omation mbers - Society for Laboratory Automation and Screening
omation mbers - Society for Laboratory Automation and Screening
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8:30 am Thursday, February 5 High Throughput <strong>Screening</strong> – Automated Design Room A2<br />
Norm<strong>and</strong> Cloutier<br />
Bristol-Myers Squibb Co.<br />
5 Research Parkway<br />
Walling<strong>for</strong>d, Connecticut 06492<br />
norm<strong>and</strong>.cloutier@bms.com<br />
67<br />
Co-Author(s)<br />
James Gill<br />
Jonathan O’Connell<br />
David Stock<br />
The Implementation of Statistical Design of Experiments (DOE) in the Construction of Assays<br />
<strong>and</strong> High Throughput Screens<br />
Many of the problems confronting scientists in the high throughput screening laboratory require optimizing a single<br />
result which is dependent on many interacting factors. In many industries these multi-factorial problems have<br />
long been solved using Statistical Design of Experiments (DOE). However we find that existing statistical design<br />
software packages are not sufficient <strong>for</strong> assay design. We have found that the specific challenges in the HTS<br />
laboratory require additional tools <strong>and</strong> ef<strong>for</strong>ts to effectively implement DOE methodologies. The adoption of DOE<br />
requires somewhat of a paradigm shift <strong>for</strong> many scientists. The promise of underst<strong>and</strong>ing a whole system in a<br />
fraction of the usual number of experiments is often met with a great deal of skepticism. Mistakes in the execution<br />
of the work can lead to erroneous conclusions that DOE does not work. At Bristol-Myers Squibb, we have found<br />
that general DOE training of scientists along with the establishment of reliable automated DOE processes have<br />
been effective in creating a positive <strong>and</strong> production experience. We have developed an automated DOE system,<br />
based on the TECAN Genesis workstation. We use the SAS JMP statistics package to generate experimental<br />
designs <strong>and</strong> in-house software to drive the robotics. We have successfully applied DOE to a broad range of<br />
problems confronting high throughput screening as whole. This talk will cover the process of automated DOE <strong>for</strong><br />
assay design at Bristol-Myers Squibb. DOE successes, challenges in transferring this technology to experimenters,<br />
<strong>and</strong> lessons learned will also be presented<br />
9:00 am Thursday, February 5 High Throughput <strong>Screening</strong> – Automated Design Room A2<br />
W. Adam Hill<br />
Millennium Pharmaceuticals<br />
270 Albany Street<br />
Cambridge, Massachusetts 02139<br />
hill@mpi.com<br />
The Application of Design of Experiment in Developing Processes <strong>for</strong> Drug Discovery<br />
The statistical sampling which <strong>for</strong>ms the basis <strong>for</strong> Design of Experiment has been used <strong>for</strong> almost a century,<br />
exp<strong>and</strong>ing from its early implementation in agriculture to more modern uses including aircraft <strong>and</strong> automobile<br />
design. Design of Experiment is now becoming accepted as a tool in drug discovery. Using DOE <strong>for</strong> developing<br />
crystallization conditions <strong>for</strong> proteins, developing biochemical assays as well as cell-based assays has led<br />
to the determination of robust procedures in much reduced timeframes. This presentation will focus on the<br />
implementation of DOE software <strong>and</strong> hardware across Millennium <strong>and</strong> its impact on specific projects.<br />
PODIUM ABSTRACTS
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