Analytical Technique Comparisons using LINKlumetics.com/wp-content/uploads/2020/01/Lumetics... ·...
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www.postersession.com Characterization and control of protein aggregation requires the use of a wide range of analysis techniques. Transcribing, aggregating and comparing data from multiple measurements with different size ranges, resolutions, and output formats is very labor intensive. Recent advancements in data management and visualization technologies now allow for automated data extraction directly from analytical equipment measurement files, and automated processing of this data for detailed orthogonal and complimentary technique comparisons. Analytical Technique Comparisons using LINK C. Merchant, Ph.D., D. Thomas LINK was used to automatically transcribe measurement data directly from equipment measurement files into a centralized database. Sample information exemplifying a typical stability study, such as storage time point and storage temperature, were parsed from each data file. LINK Analysis templates for the purpose of technology comparisons were constructed, and updated in real-time with each data import. Sample datasets were made available from Flow Microscopy (MFI), Light Obscuration (HIAC), RMM (Archimedes), NTA (NanoSight), DLS (DynaPro, Zetasizer), and SEC/cIEF (Empower). Analysis templates were developed for the purpose of comparing: a) Particle Counting Techniques b) DLS Techniques b) MFI and HIAC – Stability Study c) MFI and FlowCAM Sub-Populations d) Archimedes Sub-Populations e) Particle Counting and DLS f) Particle Mass g) Disparate Techniques h) High-Throughput EPD Summaries Introduction Methods It was found that the LINK data management and analysis tool provided direct comparison of orthogonal and complimentary analytical techniques in a fully automated fashion, dramatically improving the speed of analysis and eliminating the possibility of transcription errors. Future work will involve exploring how multi-variate data visualization tools and statistical analysis within the LINK tool might further contribute to the characterization and control of protein formulations. Conclusions Dashboard 1 shows particle counting techniques for user- specified size ranges. Particle images are included, where applicable. Dashboard 2 compares DLS techniques and provides summary statistics of any parameters measured by equipment software. Dashboard 3 illustrates particle counting technique comparisons for USP 788/787 size ranges, as a function of stability study parameters (e.g. time, temp), highlighting trends in concentration between different techniques. Dashboards 4 and 5 permit comparison of multiple user- defined subpopulations (e.g. silicone oil or protein populations) based on particle morphology or particle density/buoyancy assumptions. Dashboard 6 compares particle counting techniques and DLS using particle volume distributions as a function of size. Particle shape and density assumptions are required to convert count to volume %. Dashboard 7 highlights the mass of the particle/aggregate population, vs. particle count. Dashboard 8 compares entirely disparate techniques, such as particle formation detected by counters vs. changes in SEC chromatograms. Dashboard 9 permits summarization of high-throughput well plate experiments, or specific EPD studies. Discussion Dashboard 1: Particle Counting Techniques Dashboard 2: DLS Techniques Dashboard 3: MFI and HIAC – Stability Study Dashboard 5: Archimedes Sub-Populations Dashboard 6: Particle Counting and DLS Dashboard 4: MFI and FlowCAM Sub-Populations Dashboard 7: Particle/Aggregate Mass Dashboard 8: Disparate Techniques Dashboard 9: High-Throughput EPD Summaries
Transcript of Analytical Technique Comparisons using LINKlumetics.com/wp-content/uploads/2020/01/Lumetics... ·...
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Characterization and control of protein aggregationrequires the use of a wide range of analysis techniques.Transcribing, aggregating and comparing data frommultiple measurements with different size ranges,resolutions, and output formats is very labor intensive.Recent advancements in data management andvisualization technologies now allow for automated dataextraction directly from analytical equipment measurementfiles, and automated processing of this data for detailedorthogonal and complimentary technique comparisons.
Analytical Technique Comparisons using LINKC. Merchant, Ph.D., D. Thomas
LINK was used to automatically transcribe measurementdata directly from equipment measurement files into acentralized database. Sample information exemplifying atypical stability study, such as storage time point andstorage temperature, were parsed from each data file.LINK Analysis templates for the purpose of technologycomparisons were constructed, and updated in real-timewith each data import.
Sample datasets were made available from FlowMicroscopy (MFI), Light Obscuration (HIAC), RMM(Archimedes), NTA (NanoSight), DLS (DynaPro,Zetasizer), and SEC/cIEF (Empower). Analysis templateswere developed for the purpose of comparing:
a) Particle Counting Techniquesb) DLS Techniquesb) MFI and HIAC – Stability Studyc) MFI and FlowCAM Sub-Populationsd) Archimedes Sub-Populationse) Particle Counting and DLSf) Particle Mass g) Disparate Techniquesh) High-Throughput EPD Summaries
Introduction
Methods
It was found that the LINK data management and analysistool provided direct comparison of orthogonal andcomplimentary analytical techniques in a fully automatedfashion, dramatically improving the speed of analysis andeliminating the possibility of transcription errors. Futurework will involve exploring how multi-variate datavisualization tools and statistical analysis within the LINKtool might further contribute to the characterization andcontrol of protein formulations.
Conclusions
Dashboard 1 shows particle counting techniques for user-specified size ranges. Particle images are included, whereapplicable.
Dashboard 2 compares DLS techniques and providessummary statistics of any parameters measured byequipment software.
Dashboard 3 illustrates particle counting techniquecomparisons for USP 788/787 size ranges, as a function ofstability study parameters (e.g. time, temp), highlightingtrends in concentration between different techniques.
Dashboards 4 and 5 permit comparison of multiple user-defined subpopulations (e.g. silicone oil or proteinpopulations) based on particle morphology or particledensity/buoyancy assumptions.
Dashboard 6 compares particle counting techniques andDLS using particle volume distributions as a function ofsize. Particle shape and density assumptions are required toconvert count to volume %.
Dashboard 7 highlights the mass of the particle/aggregatepopulation, vs. particle count.
Dashboard 8 compares entirely disparate techniques, such asparticle formation detected by counters vs. changes in SECchromatograms.
Dashboard 9 permits summarization of high-throughput wellplate experiments, or specific EPD studies.
Discussion
Dashboard 1: Particle Counting Techniques Dashboard 2: DLS Techniques Dashboard 3: MFI and HIAC – Stability Study
Dashboard 5: Archimedes Sub-Populations Dashboard 6: Particle Counting and DLSDashboard 4: MFI and FlowCAM Sub-Populations
Dashboard 7: Particle/Aggregate Mass Dashboard 8: Disparate Techniques Dashboard 9: High-Throughput EPD Summaries
