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Jean-Claude Bradley, profile picture
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NBCC Open Notebook Science Talk

The document discusses the importance of open notebook science (ONS) in accelerating drug discovery, emphasizing transparency, data provenance, and collaboration. It highlights various initiatives and tools that leverage educational systems and crowdsourcing to share scientific data and improve research efficiency. Key topics include methods for solubility prediction, the integration of web services, and the potential impact of ONS on intellectual property and scientific progress.

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Breast Cancer Insights•
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Accelerating Discovery by Sharing: a case for Open Notebook Science Jean-Claude Bradley May 1, 2011 National Breast Cancer Coalition Annual Advocacy Conference Associate Professor of Chemistry Drexel University
Outline Trends in sharing for drug discovery ONS for malaria research Crowdsourcing solubility with ONS Leveraging the educational system to contribute new science Open modeling and web services Discovering connections Moving forward: tools and practices
Industry is Sharing More
Opportunities for Competitive Collaboration
Some Initiatives Promoting More Openness in Drug Discovery
Motivation: Faster Science, Better Science
There are NO FACTS, only measurements embedded within assumptions Open Notebook Science maintains the integrity of data provenance by making assumptions explicit
TRUST PROOF
First record then abstract structure In order to be discoverable use Google friendly formats (simple HTML, no login) In order to be replicable use free hosted tools (Wikispaces, Google Spreadsheets) Strategy for an Open Notebook:
UsefulChem Project: Open Primary Research in Drug Design using Web2.0 tools Docking Synthesis Testing Rajarshi Guha Indiana U JC Bradley Drexel U Phil Rosenthal UCSF (malaria) Dan Zaharevitz NCI (tumors) Tsu-Soo Tan Nanyang Inst.
Malaria Target: falcipain-2 involved in hemoglobin metabolism Dana.org
The Ugi Reaction
Outcome of Guha-Bradley-Rosenthal collaboration
References to papers, blog posts, lab notebook pages, raw data
The Ugi reaction: can we predict precipitation? Can we predict solubility in organic solvents?
Crowdsourcing Solubility Data
ONS Challenge Judges
ONS Challenge Award Winners
Solubilities collected in a Google Spreadsheet
Rajarshi Guha’s Live Web Query using Google Viz API
Data provenance: From Wikipedia to…
… the lab notebook and raw data
Interactive NMR spectra using JSpecView and JCAMP-DX
(Andy Lang, Tony Williams) Open Data JCAMP spectra for education (Andy Lang, Tony Williams, Robert Lancashire)
Raw Data As Images Splatter? Some liquid
YouTube for demonstrating experimental set-up
The importance of raw data availability Missed in a prior publication on solubility for this compound
Case study: Chemical Information Retrieval course at Drexel (Fall 2009/2010) Leveraging the educational system to contribute new science
The Chemical Information Validation Sheet 567 curated and referenced measurements from Fall 2010 Chemical Information Retrieval course
The Chemical Information Validation Explorer (Andrew Lang)
Discovering outliers for melting points (stdev/average)
Investigating the m.p. inconsistencies of EGCG
Investigating the m.p. inconsistencies of cyclohexanone
Sigma-Aldrich, Acros and Wolfram Alpha apparently use the same sources for melting points
Sigma-Aldrich, Acros and Wolfram Alpha apparently use the same sources for boiling points
Sigma-Aldrich, Acros and Wolfram Alpha apparently DO NOT use the same sources for flash points
Most popular data sources
Alfa Aesar donates melting points to the public
Open Melting Point Explorer
Outliers MDPI dataset EPI (via ChemSpider)
Outliers Alfa Aesar
Inconsistencies and SMILES problems within MDPI dataset
MDPI Dataset labeled with High Trust Level
Open Melting Point Datasets
Open Random Forest modeling of Open Melting Point data using CDK descriptors (Andrew Lang) R2 = 0.78, TPSA and nHdon most important
Melting point prediction service
Other Web Services… (Andrew Lang) General Transparent Solubility Prediction
Convenient web services for solubility measurement and prediction (Andrew Lang)
Integration of Multiple Web Services to Recommend Solvents for Reactions (Andrew Lang)
Using melting point for temperature dependent solubility prediction
Semi-Automated Measurement of solubility via web service analysis of JCAMP-DX files (Andy Lang)
 
 
Solubility Prediction (Andy Lang uses Abraham Model)
Reaction Attempts Book
Reaction Attempts Book: Reactants listed Alphabetically
 
Dynamic links to private tagged Mendeley collections (Andrew Lang)
All ONS web services
For all Formats of ONS Projects
ONS Challenge Solubility Book cited for nanotechnology application
Visualizing molecule-researcher connection maps reveals link between 2 Open Notebooks (Todd and Bradley) (Don Pellegrino)
The Intersection of Open Notebooks (Bradley/Todd) and IP implications Open Notebook could have blocked patent if done earlier
Decanoic acid Water NaCl
Phrase searching for useful solubility applications
Search for applications of solubility for breast cancer research
Solubility prediction for Taxol using Abraham descriptors Pred Exp
Predicted temperature dependent solubility of Taxol in water (M)
Current research questions for Taxol solubility Does Taxol have a meaningful solubility in methanol or does it decompose too quickly? Why is methanol reported to decompose Taxol but not ethanol? Can the solubility of Taxol in solvent mixtures be predicted, especially for approved excipients? Can the solubility of Taxol analogs be used to create reliable models for the solubility of this class of compounds?
Moving Forward: Tools and Practices Use free hosted web tools and open data formats Google Spreadsheets (numerical data) Wikispaces (human readable format) YouTube, SlideShare, LuLu, Nature Precedings, etc. (multiple data formats) JCAMP-DX for spectral data Practices Report all findings immediately – even if tentative Participate in social media to share progress and find collaborators Abstract experiments and findings to machine readable formats and make these easily discoverable