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Using the work-flow management functionality in the PharmaHUB ( www.pharmahub.org ). L. Mockus , G. Joglekar , J.M. Laínez , G.V. Reklaitis. Outline . The PharmaHUB Pegasus – automated workflow Illustrative example of automated workflow Experimental data management – manual workflow
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Using the work-flow management functionality in the PharmaHUB(www.pharmahub.org) L. Mockus, G. Joglekar, J.M. Laínez, G.V. Reklaitis
Outline • The PharmaHUB • Pegasus – automated workflow • Illustrative example of automated workflow • Experimental data management – manual workflow • Final remarks
PharmaHUB mission • Resource for collaboration and sharing: • Science and engineering research on innovations in pharmaceutical manufacturing • Information, knowledge, modeling & decision support tools for drug product & process design • Educational materials & experiences for education and training of pharmaceutical engineers & scientists
The PharmaHUB (www.pharmahub.org) Online simulation… …and more! Cyber-infrastructure for scientific research, education, and collaboration • Web-based • Community of • contributors • users • Support for • uploading resources • tags • reviews/ratings • asking questions • forming groups • Collection of • resources • tools
What does the HUB offer? • Mechanism for Uploading New Resources • Online presentations • Series • Downloads • Tools • Interactive simulation tools • Tool development area • Subversion repository for source code control • A ticketing system for bug tracking • Wiki area for project documentation • Ratings and citations • Wikis and blogs • User groups for private collaboration • User support area
Bayesian framework for dosage individualization Individualized dose? Inter-patient variability
Workflow Initial guess for PK parameters Confidence level Interval of admin. Time-concentration data TOOL I Parameter estimation for Gabapentin (oral administration) PK parameter samples TOOL II Dosage regimen individualization Means Covariance matrix Marginal distributions Confidence region for concentration (Midpoint) Number of samples Feasible dose range Tuning parameter
Simulation Results Sampling from posterior distributions Marginal distributions Optimal dose Concentration confidence region
Goal: PowderProperties Data • Develop a data model for managing experimental powderproperties data • Data traceable to raw materials: API + excipients • Develop templates for systematic and consistent procedure for populating data repositories • Add all properties measured within ERC to pharmaHUB • Develop the following functionalities • Query/look up data • Present data • Demonstrate with data from two groups • Dry granulation group - Drucker-Prager Cap model parameters – for die compaction simulation • Rutgers blending experiments
Concluding remarks • Integration of tools for providing a manner of creating workflows within the PharmaHUB • Rappture & Pegasus • Material data management