National Science Foundation     |     Directorate for Engineering  (ENG)
Division of Chemical, Bioengineering, Environmental, & Transport Systems  (CBET)
 
CBET Research Highlights 
Notable Accomplishments from CBET Awards
 
 
1414 - Part A - Computational Design of Nanocarriers in Targeted Drug Delivery
 
Ravi Radhakrishnan  -  University of Pennsylvania

Outcome or Accomplishment:  Researchers in Engineering, Pharmacology, and Medicine at the University of Pennsylvania have partnered to discover new methods in nanobiotechnology for more easily designing tiny (nano) therapeutic particles that are of prime importance in increasing the efficacy while simultaneously reducing the side effects in disease treatment.  The researchers developed a molecular mathematical model and a computational program (software), which are able to accurately and quantitatively predict selective binding of therapeutic nano-drug carriers to the interfaces of distressed cells within specific organs in mice.

Ravi Radhakrishnan Image 1
    Figure 1.  Hybrid molecular-scale/ meso-scale model for nanocarrier interaction with cell surface mediated by the molecular specificity of multivalent antigen-antibody interactions.
 
Ravi Radhakrishnan, Associate Professor at the University of Pennsylvania, and his postdoc created this image, which appears on the cover of the 21 July 2011 issue of Biophysical Journal at: http://biophysicalsociety.wordpress.com/.  This image, however, does not show the yellow drug particles that are present in the nanocarrier as shown on the journal cover.
 
Ravi Radhakrishnan Image 2
    Figure 2.  Snapshot of mesoscale (100 nanometers-micron length scale) Monte Carlo model of cell membrane budding at finite temperature orchestrated by curvature inducing proteins in clathrin mediated endocytosis (CME).  Curvature inducing proteins (such as epsin) are represented by orange spheres.
 
Ravi Radhakrishnan Image Image 3
    Figure 3.  Coarse-grained model for epsin N-terminal homology domain (ENTH) interacting with a mixed DOPC/DOPS bilayer.  Coarse-grained molecular dynamics simulations using the MARTINI force field in the GROMACS simulation package are used to study the mechanism by which epsin induces curvature on charged lipid bilayers.  This figure depicts two epsin ENTH domains (orange) attached to a 7:3 mixed DOPC (blue) and DOPS (cyan) bilayer.  Calculation of the 3-dimensional stress tensor reveals the effect of epsin on membrane curvature.
 
Ravi Radhakrishnan Image Image 4
    Figure 4.  Snapshot of the microscale (micron length scale) Monte Carlo model of membrane budding from an organelle.  This system mimics budding and intracellular trafficking in endosomes within a cell.
 
Ravi Radhakrishnan Image Image 5
    Figure 5.  Multiscale modeling of vesicle budding from intracellular organelles orchestrated by protein assemblies.  Targeting drug delivery vehicles to intracellular organelles provides an additional layer of control to transform the efficacy of next generation therapeutic protocols using nanobiotechnology:
 
- 1 -  Snapshot from coarse-grained molecular dynamics simulations at the nm length scale (Top Row).  The MARTINI force field in the GROMACS simulation package are used to study the mechanism by which epsin induces curvature on charged lipid bilayers.  This figure depicts two epsin ENTH domains (orange) attached to a 7:3 mixed DOPC (blue) and DOPS (cyan) bilayer.  Calculation of the 3-dimensional stress tensor reveals the effect of epsin on membrane curvature.
 
- 2 -  Snapshot of mesoscale (100 nm length scale) Monte Carlo model of membrane budding at finite temperature orchestrated by curvature inducing proteins in clathrin mediated endocytosis (CME) (Middle Row).  Curvature inducing proteins such as epsin are represented by orange spheres.
 
- 3 -  Snapshot of the microscale (micron length scale) Monte Carlo model of membrane budding from an organelle (Bottom Row).  This system mimics budding and intracellular trafficking in endosomes within a cell.
 
Credit for All Images:  Ravi Radhakrishnan, University of Pennsylvania, Philadelphia, PA

Impact:  Even though many advances have been made in drug discovery since Edward Jenner's cowpox trial at the very end of the 18th century, for most therapeutic agents, only a small portion reaches the distressed cell or tissue within the disease carrying organ resulting in a huge loss of clinical efficiency while a large fraction ends up in unwanted areas, sometimes causing mild to serious side-effects.  This work on designing therapeutic nanocarriers for targeted drug delivery or transport seeks to fundamentally alter this approach by preferentially concentrating the drug in the cells or tissues affected while reducing their relative levels in the healthy tissues.  This customizable platform opens the door to personalized medicine by enabling precise control of side effects, regulation of dosage, and even the patient response.

Explanation/background:  Antibody coated nanocarriers facilitate the targeting to diseased tissue through the specific interaction of the antibodies with molecules known as receptors (biomarkers of a given disease).  The mathematical model and software developed under this research is predictive for binding of spherical nanocarriers to endothelial cells (a type of cell that lines blood vessels).  The software prescribes a critical design parameter, namely the number of antibody molecules to be coated on the nanocarrier of a given size so that the targeting (binding of the nanocarrier to the endothelial cell) is most efficient for the least amount of antibody per carrier.  This allows researchers to minimize the number of antibodies introduced in a given patient such that the levels are small enough that unnecessary immune response (a potentially allergic reaction or a serious side-effect) is prevented, but yet allows the nanocarrier to be lodged effectively at the site of the disease tissue.
 
By coating the nanocarrier with antibodies specific to clinical biomarkers of cardiovascular disease and cancer, this new approach can be implemented in a translational setting for optimizing treatment protocol in such lethal diseases.  The computational model and software developed in this research accurately and quantitatively predicts the ratio of nanocarriers bound to the endothelial cells to those that remain unbound, for a given size of the nanocarrier, number of antibody molecules per nanocarrier, and level of biomarker molecules per endothelial cell, thereby facilitating an unprecedented level of customization in the design of smart therapeutic vehicles for targeted drug delivery.  The findings were first published in the journal: Proceedings of the National Academy of Sciences USA.  Citation: 2010, 107(38), 16530-16535.  A follow-up study extending the power of the model appeared as a cover article (see Figure 1) in the Biophysical Journal, July 2011 (101/2) issue.



CBET Research Highlight - Part B - Engineering Technical Information

1414 - Computational Design of Nanocarriers in Targeted Drug Delivery

Ravi Radhakrishnan  -  University of Pennsylvania

Background:  Targeted delivery of functionalized nanocarriers coated with specific targeting antibodies to endothelium (or cells coating the blood vessels) remains an important design challenge in pharmacological and biomedical sciences.  The use of antibody coated (or functionalized) nanocarriers offers a wide range of targeting options through tunable design parameters (size, shape, type, method of functionalization, etc.).  This necessitates a multiparameter optimization for achieving efficacious targeting in drug delivery applications including delivery of cancer therapeutics.  Rational design of functionalized nanocarriers faces many challenges owing to the complexities of molecular and geometric parameters surrounding cell surface receptor-antibody interactions, nanocarriers size, shape, lack of accurate characterization of hydrodynamic, physico-chemical barriers for nanocarrier uptake/arrest, and uncertainty in the targeting environment in vivo.  The use of mathematical models can significantly enhance the rational engineering and design of functionalized nanocarriers in targeted drug delivery applications.

Results:  A computational methodology based on Metropolis Monte Carlo has been developed to calculate the absolute binding free energy between functionalized nanocarriers and endothelial cell surfaces.  The calculated nanocarrier binding free energy landscapes yield binding affinities that agree quantitatively when directly compared against analogous measurements of specific antibody-coated nanocarriers (100 nm in diameter) to intracellular adhesion molecule-1 expressing cell surface in in vitro cell-culture experiments.  Computational determination of the binding affinities is a significant challenge because it involves the calculation of absolute binding free energies.  This requires extensive sampling over conformational space and determination of various (translational and rotational) entropy changes upon binding.  The researchers under this NSF funded project have developed a model to calculate the binding affinity of spherical nanocarrier functionalized with anti-ICAM-1 antibody to ICAM-1 expressing endothelial cell surface.  Using a Monte Carlo approach, they have computed binding free energy landscapes, which have allowed them to systematically investigate the effects of a wide range of experimentally tunable parameters, including the receptor surface density, antibody coverage on nanocarriers, flexural rigidity of the receptors, presence of glycocalyx, and effect of shear flow.  The researchers have shown that their model predictions can quantitatively describe the results of three broad classes of experiments, namely: (i) binding measurements of nanocarriers in cell culture, (ii) in vivo targeting of nanocarriers to pulmonary (lung) endothelium in mice, and (iii) biophysical characterization of nanocarrier-cell interaction using atomic force microscopy.
 
The researchers have developed a general protocol to calculate the absolute binding affinity for specific binding of nanocarriers to functionalized surfaces mediated through receptor-antibody interactions.  Their results for the binding affinities of 100 nm antibody-coated nanocarriers at large surface coverage to ICAM-1 expressing endothelial cells shows several hundred-fold enhancements in binding compared with that of isolated antibody to ICAM-1.  This prediction agrees remarkably well with experimental measurements of the carrier affinity to cells in cell culture.  The results on the computed effect of surface coverage of antibodies on nanocarrier binding suggest a linear effect of surface coverage interluded by exponential changes.  In the linear regimes, the average multivalency (or the number of receptor-antibody bonds per nanocarrier) is not altered, and the linear effect arises from contributions of translational and rotational entropy losses upon nanocarrier binding.  At the interludes, denoted by threshold of antibody coverages, the authors predict an exponential effect of coverage on carrier binding affinity due to a step change in multivalency.  The authors have also investigated the effect of shear and the presence of glycocalyx on their results in order to mimic conditions in vivo in mice.  The model results imply a negligible effect of shear (for shear rate S less than or equal to 6000 s-1).  Moreover, the glycocalyx while reducing the fractional binding at a given coverage, does not alter the dependence of coverage on binding affinity.  Most significantly, the model predictions of surface coverage of antibody on the nanocarrier versus nanocarrier binding affinity agrees remarkably well with in vivo results, while simultaneously providing consistent agreement force-rupture experiments performed using atomic force microscopy.
 
The effect of antibody surface coverage of nanocarrier on binding simulations revealed a threshold value below which the carrier binding affinities reduced drastically and drop lower than that of single anti-ICAM-1 molecule to ICAM-1.  The model suggested that the dominant effect of changing the surface coverage around the threshold was through a change in multivalent interactions; that is more than one antibody on the carrier engaged with multiple receptors on the cell.  However, the loss in translational and rotational entropies was also important, which was quantified accurately by the model.  Consideration of shear flow and glycocalyx did not alter the computed threshold of antibody surface coverage and the computed trend describing the effect of antibody surface coverage on the nanocarrier binding agreed remarkably well with experimental results of in vivo targeting of the anti-ICAM-1 coated carriers to pulmonary endothelium in mice.  Model results were further validated through close agreement between computed nanocarrier rupture-force distribution and measured values in atomic force microscopy (AFM) experiments.

Scientific Uniqueness:  This work integrates research from four scientific disciplines, namely, Chemical/Bioengineering, Mechanical Engineering, Pharmacology, and Anesthesiology, and has established a true multidisciplinary collaboration.  The driving force of the research is the creation of a mathematical model that interfaces simultaneously with experiments on cell culture, mouse, as well as atomic force-microscopy, thereby providing multiple levels of consistency.

Strategic Outcome Goals include:
 
- 1Discovery:  A mathematical model and framework has been developed in predicting the in vitro as well as in vivo binding characteristics of functionalized nanocarriers to endothelial cells for the purposes of targeted drug delivery.
 
- 2Learning:  One graduate student funded through this project is currently a postdoctoral associate at MIT.  Four other graduate students have been partially funded through this project and are working towards their dissertations.  The project has also involved three undergraduate researchers.

Transformative Research:  This funded research facilitates the engineering of novel nanoscopic targeted drug delivery vehicles for use in cardiovascular diseases and cancer.

Intellectual Merit:  A computational methodology based on Metropolis Monte Carlo has been developed to calculate the absolute binding free energy between functionalized nanocarriers and endothelial cell surfaces.  The model has been quantitatively validated against three different classes of experiments: in vitro in cell culture, in vivo targeting to pulmonary endothelium in mice, and atomic force microscopy; the three-way quantitative agreement with these experiments establishes the mechanical, thermodynamic, and physiological consistency of the research team model.  The calculated binding free energy landscapes yield binding affinities that enable a direct comparison with experiments.  The model suggests that the governing principles in nanocarrier targeting revolve around multivalent interactions and loss of entropy of the carrier as well as the receptors and antibodies, giving the study a rigorous thermodynamic basis.  The computational protocol represents a quantitative and predictive approach for model-driven design and optimization of functionalized nanocarriers in targeted vascular drug delivery.

Broader Impacts of this research include:
 
- ABenefits to society:  While drug-discovery has gotten very sophisticated in the 216 years since Jenner's trial, traditional drug delivery systems such as oral ingestion or intravascular injection do not deviate conceptually from Jenner's techniques in that the medication is distributed throughout the body through the systemic blood circulation, and for most therapeutic agents, only a small portion of the medication reaches the organ to be affected.  Targeted drug delivery seeks to fundamentally alter this approach by preferentially concentrating the drug in the tissues or even cells affected while reducing their relative concentration in the healthy tissues.  The current model developed in this research using functionalized nanocarriers coated with antibodies that specifically recognize biological markers of disease or inflammation, where such carriers are targeted to the sites of inflammation, aids in the improvement of efficacy while reducing side effects of therapeutic protocols.  This approach is gaining ground in the treatment of various pathologies from cancer to inflammation and brings together scientific and biomedical disciplines of chemistry, pharmacology, clinical practice, and engineering.
 
- BBroadening participation of underrepresented groups:  One doctoral student with a disability is being trained in Biochemistry and Biophysics.  One undergraduate under-represented minority student is being trained in Chemical and Biomolecular Engineering research.
 
- CAdvancing discovery and understanding while promoting teaching, training, and learning:  The project has benefited 7 Doctoral students, 2 Postdoctoral scholars, and 3 Undergraduate students in their research and or dissertations.  The models and results of the project have been translated into lectures and in-class demonstrations in two courses at the University of Pennsylvania.  Training modules based on 3-dimensional visualization has also been developed and presented to area high-school students during several summer workshops conducted at the University of Pennsylvania.
 
- DEnhancing the infrastructure for research and education:  A robust research partnership between four laboratories in the School of Engineering and Applied Sciences and the School of Medicine was established based on the research which has led to infrastructure and resources sharing across schools.
 
- EResults disseminated broadly to enhance scientific and technological understanding:  Scientific publications resulting from this research are:
1.  N.J. Agrawal, R. Radhakrishnan, Calculation of Free energies Calculation of free energies in fluid membranes subject to heterogeneous curvature fields, 2009, Phys Rev E, 80, 011925. (Pubmed: 19658747)
2.  J. Purvis, A. J. Shih, Y. Liu, R. Radhakrishnan, Book Chapter: Cancer cell-linking oncogenic signaling to molecular structure, Book title: Multiscale Cancer Modeling, Editors: T. S. Deisboeck, G. Stamatakos, Chapman & Hall-CRC Mathematical and Computational Biology Series, 2010, chapter 2, pages 17-31.
3.  R. Venkatramani, R. Radhakrishnan, Computational Delineation of the Catalytic Step of a High Fidelity DNA Polymerase, 2010, Protein Science, 19(4), 815-825. (Pubmed: 20162624)
4.  F. Shi, S. E. Telesco, Y. Liu, R. Radhakrishnan*, M. A. Lemmon*, The ErbB3/HER3 Intracellular Domain is Competent to Bind ATP and Catalyze Autophosphorylation, 2010, Proceedings of the National Academy of Sciences, 107, 7692-7697. *Co-corresponding authors. (Pubmed: 20351256)
5.  N.J. Agrawal, J. Nukpezah, R. Radhakrishnan, Minimal Mesoscale Model for Protein-Mediated Vesiculation in Clathrin-Dependent Endocytosis, 2010, Plos: Computational Biology, 6(9) e1000926, 2010. (Pubmed: 20838575)
6.  J. Liu, G. E. R. Weller, B. Zern, P. S. Ayyaswamy, D. M. Eckmann, V. Muzykantov, R. Radhakrishnan, A Computational Model for Nanocarrier Binding to Endothelium Validated Using In Vivo, In Vitro, and Atomic Force Microscopy Experiments, 2010, Proceedings of the National Academy of Sciences, 107(38), 16530-16535. (Pubmed: 20823256)
7.  A. Shih, S. E. Telesco, S. H. Choi, M. A. Lemmon, R. Radhakrishnan, Molecular Dynamics Analysis of Conserved Hydrophobic and Hydrophilic Bond Interaction Networks in ErbB Family Kinases, Biochemical Journal, 2011, 436(2), 241-251. Pubmed ID: 21426301.
8.  S. E. Telesco, A. Shih, Y. Liu, R. Radhakrishnan, Investigating Molecular Mechanisms of Activation and Mutation of the HER2 Receptor Tyrosine Kinase through Computational Modeling and Simulation, Cancer Research Journal, 2011, 4(4), 1-35.
9.  A. J. Shih, S. E. Telesco, R. Radhakrishnan, Analysis of Somatic Mutations in Cancer: Molecular Mechanisms of Activation in the ErbB family of Receptor Tyrosine Kinases, Cancers, 2011, 3(1), 1195-1231; doi:10.3390/cancers3011195.
10.  S. E. Telesco, A. J. Shih, F. Jia, R. Radhakrishnan, A Multiscale Modeling Approach to Investigate Molecular Mechanisms of Pseudokinase Activation and Drug Resistance in the HER3/ErbB3 Receptor Tyrosine Kinase Signaling Network, Molecular Biosystems (RSC Journal), 2011, 7 (6), 2066 - 2080. DOI: 10.1039/c0mb00345j. Pubmed ID: 21509365.
11.  B. Uma, J. Liu, R. Radhakrishnan, P. S. Ayyaswamy, D. M. Eckmann, Targeting nanocarriers to vascular endothelium, T. N. Swaminathan, IUBMB Life, 2011, 63(8):640-647. Pubmed ID: 21721099
12.  B. Uma, T. N. Swaminathan, R. Radhakrishnan, D. M. Eckmann, P. S. Ayyaswamy, Nanoparticle Brownian motion and hydrodynamic interactions in the presence of flow fields, Physics of Fluids, 2011, 23, 073602. doi:10.1063/1.3611026.
13.  Generalized Langevin dynamics of a nanoparticle using a finite element approach: Thermostating with correlated noise, B. Uma, T. N. Swaminathan, P. S. Ayyaswamy, D. M. Eckmann, R. Radhakrishnan, J. Chem. Phys., 2011, 135, 114104. DOI: 10.1063/1.3635776; Erratum, 136, 019901, 2012.
14.  J. Liu, N. J. Agrawal, A. Calderon, P. S. Ayyaswamy, D. M. Eckmann, R. Radhakrishnan, Multivalent binding of nanocarrier to endothelial cells under shear flow, Biophysical J., 2011, 101 (2): 319-326. Doi:10.1016/j.bpj.2011.05.063. Pubmed ID: 21767483
15.  V. Ramanan, N. J. Agrawal, J. Liu, S. Engles, R. Toy, R. Radhakrishnan, Systems Biology and Physical Biology of Clathrin-Mediated Endocytosis: An Integrative Experimental and Theoretical Perspective, Integrative Biology (RSC Journal), 2011, 3(8), 803-815. DOI: 10.1039/c1ib00036e. Pubmed ID: 21792431
16.  V. Muzykantov, R. Radhakrishnan, D. M. Eckmann, Dynamic factors controlling targeting nanocarriers to vascular endothelium, Current Drug Metabolism, 2012, 113, 70.
17.  J. Liu, R. P. Bradley, D. M. Eckmann, P. S. Ayyaswamy, R. Radhakrishnan, Multiscale Modeling of Functionalized Nanocarriers in Targeted Drug Delivery, Current Nanoscience, 2011, 7(5): 727-735.
18.  Mesoscale Modeling and Simulations of Spatial Partitioning of Curvature Inducing Proteins under the Influence of Mean Curvature Fields in Bilayer Membranes, J. Liu, R. Tourdot, V. Ramanan, N. J. Agrawal, R. Radhakrishnan, Molecular Physics, 2012, in press. (DOI:10.1080/00268976.2012.664661)
19.  A hybrid formalism combining fluctuating hydrodynamics and generalized Langevin dynamics for the simulation of nanoparticle thermal motion in an incompressible fluid medium, B. Uma, D. M. Eckmann, P. S. Ayyaswamy, R. Radhakrishnan, Molecular Physics, 2012, in press. (DOI: 10.1080/00268976.2012.663510)
20.  A. J. Shih*, S. T. Telesco*, Y. Liu, R. Venkatramani, R. Radhakrishnan, Computational methods related to reaction chemistry, Comprehensive Biomaterials, eds. P. Ducheyne, Elsevier London, 2011, vol. 3, pp155-169. *These authors contributed equally.
21.  S. E. Telesco, A. Shih, Y. Liu, R. Radhakrishnan, Investigating Molecular Mechanisms of Specificity in Regulation of the HER2 Receptor Tyrosine Kinase through Molecular Modeling and Simulation, HER2 and Cancer: Mechanism, Testing and Targeted Therapy, Nova Science Publishers, New York, 2011, Nova Science Publishers, New York, 2011, pp47-80. ISBN: 978-1-61122-274-6.
22.  J. Liu, N. J. Agrawal, D. M. Eckmann, P. S. Ayyaswamy, R. Radhakrishnan, Top-down Mesoscale Models and Free Energy Calculations of Multivalent Protein-Protein and Protein-Membrane Interactions in Nanocarrier Adhesion and Receptor Trafficking, Innovations in Biomolecular Modeling, Royal Society of Chemistry Publishing, 2011, in press.
23.  Modeling of a nanoparticle motion in a Newtonian fluid: A comparison between fluctuating hydrodynamics and generalized Langevin methods, B.Uma, R.Radhakrishnan, D.M.Eckmann and P.S.Ayyaswamy, Proceedings of the ASME 3rd Micro/Nanoscale Heat and Mass Transfer International Conference, Paper No. MNHMT2012-75019, 2012, in press.
24.  Modeling of Binding Free Energy of Targeted Nanocarriers to Cell Surfaces, J. Liu, D. M. Eckmann, P. S. Ayyaswamy, R. Radhakrishnan, The Seventh Interdisciplinary Transport Phenomena Conference, Proceedings of ITP2011, Interdisciplinary Transport Phenomena VII: Fluid, Thermal, Biological, Materials and Space Sciences, 2011, Dresden, Germany, pp6-6 to 6-11.
25.  Fluctuating hydrodynamics approach for the simulation of nanoparticle Brownian motion in a Newtonian fluid, B.Uma, R.Radhakrishnan, D.M.Eckmann and P.S.Ayyaswamy, Proceedings of the 21st National and 10th ISHMT-ASME Heat and Mass Transfer conference, 2012, in press.
26.  Investigating Molecular Mechanisms of Specificity in Regulation of the HER2 Receptor Tyrosine Kinase through Molecular Modeling and Simulation, S. E. Telesco, A. Shih, Y. Liu, R. Radhakrishnan, International Journal of Cancer Research and Prevention (2011), ISSN: 1554-1134, Volume 4, Number 3, 2012.
27.  Structural Systems Biology and Multiscale Signaling Models, S. E. Telesco, R. Radhakrishnan, Annals of Biomedical Engineering, 2012, in press.
 
In addition, the research has been presented in 23 conferences and 18 invited lectures.  The research was also covered by the following media articles:
1.  Calculation of free energies in fluid membranes subject to heterogeneous curvature fields, Virtual Journal of Biological Physics Research, 18 (3), 2009.
2.  Cover Article and Image: Protein Science, 19(4), 2010.
3.  Commentary in Proc Natl Acad Sci, 2010, 107(18):8047, by S. S. Taylor and A. P. Kornev, Yet another "active" pseudokinase, Erb3 on our article Proc Natl Acad Sci, 2010; 107(17):7692. Pubmed ID: 20421461
4.  Editors choice in Cell Biology, Sci. Signal., 2010, 3(120), p. ec133; Rethinking "Pseudo" by A. M. VanHook on our article Proc Natl Acad Sci, 2010; 107(17):7692. DOI: 10.1126/scisignal.3120ec133
5.  Cover Article and Image: Biophysical Journal, 101(2), 2011.
6.  Social Media: Biophysical Society's BLOG and Twitter Feeds: http://biophysicalsociety.wordpress.com/2011/07/19/complex-simplicity-ravi-radhakrishnans-biophysj-cover-art/
7.  Social Media: Integrative Biology's BLOG and Twitter Feed: http://blogs.rsc.org/ib/2011/07/27/review-the-biology-of-clatherin-mediated-endocytosis/
8.  Penn Bioengineering Coverage of Lab Research: http://www.seas.upenn.edu/be/faculty-spotlights/ravi-spotlilght.html
9.  Research at Penn Coverage of Lab Research: http://www.upenn.edu/researchatpenn/article.php?1735&tch
10.  Research Coverage in Penn Engineering Magazine, Fall 2011: https://fling.seas.upenn.edu/~biophys/cv_files/PEmag_2011_cancer.pdf


 
Program Director:
 
 
 
Robert Wellek
CBET Program Director - Interfacial Processes and Thermodynamics
     
NSF Award Number:   0853389
     
Award Title:   Theory and Simulation of Membrane Deformations Orchestrated by Intracellular Molecular Assemblies
     
Principal Investigator:   Ravi Radhakrishnan
     
Institution Name:   University of Pennsylvania
     
Program Element Code:   1414
     
CBET Research Highlight:   Fiscal Year 2012
     
Approved by CBET on:   26 March 2012
     
     


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This CBET Research Highlight was Updated on 25 April 2012.