1. caNanoLab Overview January 2010 Use and Future Directions

2. Nanotechnology User Scenario (1 of 3) Excerpted from Samira Guccione (Stanford): Sorafenib is a Raf kinase inhibitor that disrupts the key Ras/Raf/MEK/ERK cellular pathway which is up-regulated in renal cell carcinoma, glioblastoma multiforme (GBM) and stomach cancer. The drug has significant side effects and a scientist hypothesizes nanoparticle-assisted targeted delivery of the drug will reduce dosing and side effects. A scientist interested in targeting this drug to GBM does research on possible nanoparticle- delivery systems that have the following properties: biocompatibility sufficiently long intravascular half-life to allow for repeated passage through and interactions with the activated endothelium the ability to have ligands and proteins conjugated on the surface in multivalent configuration to increase the affinity and avidity of interactions with endothelial receptors the ability to have functional groups for high-affinity surface metal chelation or radiolabeling for imaging the ability to encapsulate drugs the capability to have both imaging and therapeutic agents loaded on the same vehicle Furthermore, the scientist looks for information on nanoparticles that could potentially target the GBM. In Vivo Characterization Composition

3. Nanotechnology User Scenario (2 of 3) Integrin-targeted nanoparticles are identified. Synthesis involves UV cross linking an avb3-integrin-targeting ligand attached to a lipid, a diacetylene phospholipid and a cationic lipid. These are sonicated to form polymerized vesicles and the avb3- NP can serve as a scaffold for the attachment of therapeutic agents for imaging and therapy. The physical characteristics have been determined including size, zeta potential, IC50 in a cell adhesion assay, and the effect of multivalency IC50. Selectivity was also demonstrated in a receptor binding assay and it is not rapidly cleared from the target tissue. Previous studies have shown this particle to be highly stable, have no toxicity and to specifically target tumor associated vasculature in GBM when conjugated to GFP. Furthermore the particle has been used as an imaging agent when conjugated with Gd3+ or Indium11+. The avb3-NP-Sorafenib is synthesized. Sorafenib absorption characteristics are available and the concentration of the drug in the system is determined via spectroscopy methods. Other physical properties are characterized. Composition Physical Characterization In Vitro Characterization Composition

4. Nanotechnology User Scenario (3 of 3) The scientist investigates what data sets are available on in vivo use of the drug. A breast cancer xenograph subcutaneous model is found and cell lines from this system are also available. However toxicity data for the drug in animal models are not publicly available. The scientist contacts the drug manufacturer and begins in vitro testing. PK/PD in vitro tests, including drug uptake, toxicity and effectiveness, are performed in the model system cell lines, related and control cell lines by comparing the effects of drug alone, nanoparticle alone, and the combination. Next is in vivo testing with three established animal tumor models. The drug alone, nanoparticle alone, and the combination are administered and tumor size (and other parameters) is monitored. Finally efficacy, dosing, and side effects of the current dosing protocol are compared with targeted nanoparticle delivery of Sorafenib. In Vitro, In Vivo Characterization In Vivo Characterization

5. caNanoLab Overview caNanoLab is a portal designed to facilitate data sharing in the research community to expedite and validate the use of nanoparticles in biomedicine caNanoLab provides support for the annotation of nanoparticles with composition information, physical and in vitro characterizations (in vivo coming soon), protocols, and publications caNanoLab is based on the nanoparticle object model (nano-om), an initial representation of nanoparticles and their characterizations that leverages and extends concepts from the NCI’s Enterprise Vocabulary Services (EVS) and the Washington University Nanoparticle Ontology (NPO) caNanoLab is engineered to enable data sharing in a semantically interoperable fashion in the spirit of the NCI’s cancer Biomedical Informatics Grid (caBIG ® ) Current Version: caNanoLab 1.5 http://cananolab.abcc.ncifcrf.gov/caNanoLab/

6. CDE and Terminology Development Efforts Washington University Nanoparticle Ontology (NPO) NCI BiomedGT Nanotechnology Terminology caNanoLab Users Group, Community Discussion Groups, and the caBIG® Nano WG In Vivo Characterizations Instruments/Techniques Characterization/Conditions Minimal Information

7. caNanoLab Primary User Base: NCL Nanotechnology Characterization Laboratory (NCL) – Fort Detrick, MD Serves as a national resource and knowledge base for cancer researchers to facilitate the regulatory review of nanotechnologies intended for cancer therapies and diagnostics Provides the critical infrastructure and characterization services to nanomaterial providers to accelerate the transition of basic nanoscale particles and devices into clinical applications Characterizes nanoparticles' physical attributes, their in vitro biological properties, and their in vivo compatibility using animal models Physico-chemical: Size Shape Composition Molecular weight Surface chemistry Identity Purity Stability Solubility In Vitro: Pharmacology Blood contact properties Immune cell function Cytotoxicity Mechanistic toxicology Sterility In Vivo: ADME Safety Efficacy http://ncl.cancer.gov/assay_cascade.asp

8. caNanoLab Primary User Base: CCNEs The NCI Alliance for Nanotechnology in Cancer is a comprehensive initiative involving public and private sectors, designed to accelerate the application of the best capabilities of nanotechnology to cancer Centers of Cancer Nanotechnology Excellence (CCNEs) are members of the NCI Alliance for Nanotechnology in Cancer aimed at the development and application of nanotechnology and nanoscience solutions in support of the diagnosis and treatment of cancer CCNEs are composed of a investigators from a variety of organizations (public and private) http://nano.cancer.gov/about_all iance/mission.asp CCNE LeadGOALS Washington University *caNanoLab User Explore nanotechnologies applied to cancer, and their translation, commercialization, and application in the clinical environment Stanford *caNanoLab User Utilize nanotechnology for the benefit of cancer patient management. Evaluate whether the use of ex vivo diagnostics with in vivo diagnostics can impact future cancer patient management. University of California, San Diego Perfect a practical nanotechnology base to diagnose, treat, and monitor cancers Emory University and Georgia Institute *caNanoLab User Integrate nanotechnology with cancer biomolecular signatures (biomarkers) for personalized and predictive oncology Accelerate the development of bioconjugated nanoparticles for cancer molecular imaging, molecular profiling, and personalized therapy MIT and Harvard (Mass Gen Hospital) Develop and translate nanotechnologies to diagnose and treat cancer Support applications of nanotechnology including targeted therapies, diagnostics, noninvasive imaging, and molecular sensing Northwestern University Design and test nanomaterials and nanodevices for their translational application into the clinic. Develop novel and innovative nanoscale technologies for cancer detection, diagnosis, and treatment California Institute of Technology Develop and validate tools for the early detection and stratification of cancer through measurements of serum and tissue-based biomarkers Evaluate molecular therapeutics for cancer based upon the evaluation of small tissue and serum samples, for protein- and gene-based biomarkers Evaluate the immunotherapy of cancer by the detection and proteomic/genomic analysis of rare circulating cells Preparation of cancer molecular imaging probes through chemical technology and chip-based technology-labeled chemical reaction circuits Carolina Center Design and fabricate novel and innovative nanodevices with subsequent evaluation using informative biological models (mouse models)

9. NCI CCNEs (1 of 2)

10. NCI CCNEs (2 of 2)

11. cananoLab Collaborative Environment Future Biomedical Research Community CCNE Investigator Alliance Investigator nano-om caBIG™ caGrid (Advertise, Discover, Query, Security - Data and Analytical Grid Services) Animal Models Clinical, Genomics, Proteomics, Tissue/Pathology, Imaging, caBIG™ Services Future caNanoLab Portal Nanoparticle Characterizations and Protocols nano-om Nanotechnology Techniques, Assays, Protocols Regulatory Agencies caNanoLab Portal NCL caB2B Nanoparticle Characterizations and Protocols Nanoparticle Characterizations and Protocols Nanoparticle Characterizations and Protocols

12. caNanoLab Operational Environment caBIG™ caGrid (Advertise, Discover, Query, Security - Data and Analytical Grid Services) NCLWash U Stanford Georgia Tech NCI CBIIT 21 Protocols, 18 Nanoparticles, 20 Physico-Chemical and 54 In Vitro Characterizations, 7 Publications from NCL Public Experiments 608 Publications from NCI CCNE (I/F to PubMed) 530+ Particles Curated from Literature and CCNEs, 75 Publications 25 Particles from Stanford Experiments 3 Nanoparticles from Georgia Tech Experiments

13. caNanoLab High-Level Concepts Nanoparticle Sample Composition Characterization In Vitro Characterization In Vivo Characterization (Under Development) Therapeutic Targeting Diagnostic Imaging Molecular Weight Purity Physical State Relaxivity Shape Size Solubility Surface Physico-Chemical Characterization Carbon Nanotube Complex Particle Dendrimer Emulsion Fullerene Liposome Metal Particle Polymer Quantum Dot Cytotoxicity Immunotoxicity Toxicity Animal Models Treatment Imaging Pharmacokinetics Toxicology Publication Nanomaterial Entity Functionalizing Entity Chemical Associations Attachment Encapsulation Entrapment Protocol

14. Composition A Nanomaterial Entity describes the base particle and any Composing Elements (core, coat, shell) associated with the particle Specific nanoparticle types (dendrimer) have different composition properties (branch, generation) Nanoparticles share common types of composing elements Functionalizing Entities support the addition of components that give the particle a function such as diagnostic imaging, targeting, and/or therapeutic Chemical Associations allow for the association of components of the nanoparticle entity with other nanoparticle or functionalizing entities Nanoparticle Entities can be associated to support the formulation of complex particles (liposome embedded in a quantum dot) Composition Nanomaterial Entities Functionalizing Entities Chemical Associations Biopolymer (Name, Sequence) Carbon Nanotube (Wal l Type, Avg. Length, Diameter, Chirality) Dendrimer (Branch, Generation) Emulsion (Polymer Name) Fullerene (# of Carbons) Liposome (Polymer Name) Metal Particle Polymer (Initiator) Quantum Dot Attachment Encapsulation Entrapment Antibody (Type, Species) Biopolymer (Type) Small Molecule (Alt Name) Coat Core Shell Lipid Composing Elements Modifier Monomer Repeat Unit Terminal Group

15. Physico-Chemical Characterizations Physico-Chemical Characterizations determine the material and structural properties of a nanoparticle Nanoparticles are polydisperse and exhibit diverse physico-chemical properties based on the experimental conditions (ph, temperature, solvent) or applied instruments/techniques Physico-Chemical Characterizations (size, shape) have a direct impact on biological interaction Molecular Weight Size Molecular Weight Physical State Purity Type (fluid-gas, solid crystal, …) Shape Solubility Surface PDI Size Type (2D-Circle..) Aspect Ratio Min Dimension Max Dimension Solvent (saline, …) isSoluble Critical Concentration Charge Surface Area Zeta Potential isHydrophobic Relaxivity % Purity R1 R2 T1 T2 Physico-Chemical Characterizations

16. In Vitro Characterizations In Vitro Characterizations determine the effect of nanoparticles on living cells in an artificial laboratory environment outside of the living organism In Vitro Characterizations test a nanoparticles’ binding, pharmacology, and update properties monitored by cell and molecular biology methods In Vitro Characterizations also determine a nanomaterial’s blood contact properties, the particle’s interaction with cellular-level components, and an examination of the particle’s therapeutic and/or diagnostic functionality In Vitro Characterizations Cytoxicity Targeting Oxidative Stress Cell Death Method (Apoptosis, Necrosis) Cell Line Cell Viability (LC50, % cell viability ) Caspase Apoptosis (% of control) Coagulation (APTT, …) Hemolysis (isHemolytic) Plasma Protein Binding (% Bound) Platelet Aggregation (% aggregation vs. control ) Immune Cell Function Blood Contact CFU GM (# of Colonies) Chemotaxis Complement Activation Cytokine Induction (IL8, …) Leukocyte Proliferation NK Cell Cytotoxic Activity Oxidative Burst Phagocytosis Metabolic Stability Transfec- tion

17. In Vivo Characterizations (Coming Soon) In Vivo Characterizations determine the effect of nanoparticles on living organisms In Vivo Characterizations include animal information, treatment information, pharmacokinetics, and toxicology and are not specific to nanoparticles In Vivo Characterization concepts are derived from the CDISC SEND (v2.3) and SDTM (v3.2.1) standards for animal tox studies and human clinical trials pharmacokinetics, respectively Support for In Vivo Characterizations will include interfaces to NBIA (Images), caMOD (Animal Model), and caELMIR (Animal Information) In Vivo Characterizations Animal Information ToxicologyTreatment Information Pharmaco- kinetics Animal Model ID (caMOD ID) Species Strain Diet (Feed, Water) Animal ID (caElmir ID) Age Gender Behavior Disposition Administrative Route Regimen Surgery Type Dosing Group # of Animals Dose Dose Volume Behavioral Toxicology Clinical Chemistry Clinical Observation Developmental Tox Hematology Histopathology Gross Pathology Organ/Body Weight Survival AUC Bioavailability Clearance Clearance Route Half Life TMax CMax Volume of Distribution

18. Publications and Protocols caNanoLab allows users to submit Protocols for characterization, safety, radiolabeling, sample preparation, and other types of protocols Protocols can be associated with Characterizations Protocols can be submitted without Characterizations Multiple versions of Protocols can be submitted caNanoLab allows users to search and submit Publications and other types of Reports Samples can be associated with multiple Publications Publications can be submitted without Samples Auto-completion has been implemented for PubMed publications leveraging PubMed’s HTTP API for retrieving XML Publications Protocols

19. caNanoLab Search Facilities caNanoLab provides a basic search that allows researchers to perform local searches or search across caNanoLab grid nodes for publically available Protocols, Samples, Characterizations, and Publications caNanoLab 1.5 includes an advanced search feature that allows users to perform range queries APIs (grid and convenience functions) are provided to facilitate more advanced search capabilities caOBR will leverage caNanoLab grid services to retrieve caNanoLab data from the Nanoparticle Ontology (NPO) caNanoLab can leverage caOBR for ontological queries across multiple data sources Results are displayed based on a user’s authorization Remote Search/Browse Advanced Search caOBR Search

20. Client Presentation Tier Business Tier Persistence Tier EIS Tier caNanoLab Database File System HTML Browser caNanoLab Architecture Customized Application Service Object Business Service Objects Domain Objects DTOsUtility ObjectsCSM APIs Hibernate API Hibernate O/R Mapping Customized DAO JSP Servlet Struts Taglib JSTL Display Taglib Struts Validator DWR Ajax HTML Images JavaScript CSS

21. caNanoLab Key Future Vision Support for Study information and Study Outcome Implementation of In Vivo Characterizations Support for Animal Information and Treatment Interface with caMOD for animal models Provide cross reference to caELMIR for animal information Support for Pharmacokinetics and Toxicology data Interface to NBIA in support of imaging Interface to caBIO for Drug Annotations Support for Structure-Activity-Relationships Interface with Modeling and Simulation Tools Advanced Search, Visualization, and Analysis Allow user to select visualization and analysis tools (e.g. heat map, spreadsheet, distribution graph, GenePattern, and other analysis tools) in support of cross particle comparison Add Google-like search on home page (Integrate with caOBR) with auto-complete based on NPO terms Add links to caB2B in support of advanced grid searches across caGrid data services Support for Minimal Information Standards Import/export minimal information from caBIG Nano WG standards Interface with the NPO (Data submission and retrieval) Implementation of Grid Level Security Continued inter-agency collaborations to working towards regulatory approval on the use of nanotechnology in biomedicine Continue to promote data sharing in the nanotechnology community, increase current data sets, and provide access to comprehensive data sets 3D Dendrimer Model

22. Study Hierarchy Study Sample (s) Characterization (s) Protocol Finding (s) Composition Publication (s) Technique (s)/ Instrument (s) Outcome(s)

23. Example Study Outcomes Study AimMeasurements/Calculations Anti-Tumor Activity Measure of cytotoxicity specificity; Killing of targeted cells (e.g. receptor-positive) cells Median Survival time vs. predicted survival time Response as defined by RECIST (e.g. change in tumor size, change in tumor growth rate) Decrease in cancer specific antigen Lack of systemic toxicity- blood cell counts; changes in body weight Tumor Targeting In vivo biodistribution measurements Enhanced potency Tumor localization Change in tumor luciferase activity Cellular uptake Therapeutic Time release of the drug Reduced toxicity Angiogenic Inhibition (of nanoparticle as therapeutic agent and ability to nanoparticle image contrast agent to detect) Change in mean blood vessel density Change in tumor volume Protein expression (e.g. VEGF, Nestin, other protein expression in nascent blood vessels and growing tumor) Antimicrobial Photodynamic Activity Gram-type-specific photoxicity Transfection DNA release in cytoplasm and nucleoplasm Change in Fusibility Extent of DNA binding

24. Collaborations caNanoLab Users Group Composed of members of the Cancer Centers of Nanotechnology Excellence (CCNEs) – Wash U, Stanford, Georgia Tech, MIT, NCL, and others Assists in feature review and prioritization NCI Nanotechnology In Vivo Characterization Discussion Group Composed of members of the NCI, FDA, EPA, NIOSH, NNCO, and others Assists in the identification of in vivo concepts including pharmacokinetics, toxicology, animal information, treatment information, and imaging caBIG ICR Nanotechnology Work Group Provides recommendations on nanoinformatics and aims in the development of data sharing standards and ontology governance caBIG Projects caMOD, NBIA/AIM, caBIO, caB2B, and caOBR National Nanotechnology Coordination Office (NNCO) Brings together organizations from diverse disciplines (material science, biomedicine) in support of nanoparticle information exchange Oregon State Nanomaterial Biological Interactions (NBI) Knowledgebase NIOSH Nanoparticle Information Library (NIL) in support of nanotechnology health and safety

25. Acknowledgements and References NCI Piotr Grodzinski, PhD, NCI OTIR Director of Nanotechnology for Cancer Programs Anand Basu, NCI CBIIT Director of Applications Juli Klemm, NCI CBIIT ICR Director; Nano WG Sponsor Frank Hartel, PhD NCI CBIIT Director NCI Enterprise Vocabulary Services (EVS) Ptak Krzysztof, PhD, NCI Alliance Coordinator Jill Hadfield, NCI Tech Writing Lead caNanoLab Team (NCI CBIIT) SAIC - Sharon Gaheen, Sue Pan, Henry Hou Lockheed – Elizabeth Hahn-Dantona NCL Scott McNeil, PhD, Marty Fritts, PhD, Anil Patri, PhD, Jennifer Hall, PhD, Stephen Stern, PhD CCNEs Washington University - Nathan Baker, PhD, Dennis Thomas, PhD, Michal Lijowski, PhD, Rojit Pappu, PhD, Peter Jones Stanford - David Paik, PhD Georgia Tech - May Wang, PhD MIT, Frank Gu, PhD