BME 695L Lecture 3: Theranostics and Molecular Imaging

By James Leary

Biomedical Engineering, Purdue University, West Lafayette, IN

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See references below for related reading.

3.1      Nanomedical systems – levels of challenges
3.1.1    Diagnosis - difficult
3.1.2    Therapy – more difficult
3.1.3    Both ("Theragnosis") – most difficult!

3.2      How theragnostics relates to Molecular Imaging
3.2.1    conventional imaging is not very specific
3.2.2    types of In-vivo Imaging X-rays, CAT (Computed Axial Tomography) scans MRI (magnetic Resonance Imaging) PET (Positron Emission Tomography) scans
3.2.3    "molecular imaging" of nanoparticles in-vivo for diagnostics/monitoring of therapeutics

3.3      Engineering nanomedical systems for simultaneous molecular imaging
3.3.1    using nanomedical cores for MRI contrast agents
3.3.2    difficulties in using PET probes for nanomedical devices
3.3.3    using cell-specific probes for molecular imaging of nanomedical devices
3.3.4    breaking the "diffraction limit" – new nano-level imaging modalities

3.4      Theragnostic nanomedical devices
3.4.1    using nanomedical devices to guide separate therapeutic device
3.4.2    when might we want to combine diagnostics and therapeutics?

3.5      Requirements for specific cell targeting
3.5.1    must be cell surface biomarker that at least partially identifies that cell
3.5.2    OR a Boolean set of several biomarkers whose composite "signature" identifies a cell
3.5.3    OR a set of biomarkers that excludes all other cells
3.5.4    challenge – how to "multiplex" a Boolean set of targeting molecules

3.6      Consequences of mis-targeting
3.6.1    “side effects” to innocent bystander (normal) cells
3.6.2    these side effects may be lethal to bystander cells, or they may change the overall state of the patient so that the treatment problem is no longer the same
3.6.3    Side effects may be unpredictable and may lead to dangerous non-linear patient responses what are difficult to correct and potentially dangerous or even life threatening

3.7      Engineering around the consequences of mis-targeting
3.7.1    measure number of good (normal) cells destroyed to eliminate a diseased cell
3.7.2    put a weighting factor on the relative “goodness” or “badness” of normal cells and diseased cells
3.7.3    example: How many stem cells are you willing to lose to purge tumor cells during a bone marrow transplantation?

3.8      Some ways to lower mis-targeting to non-diseased cells
3.8.1    lower numbers of nanoparticles
3.8.2    improve specificity of targeting molecules according to what is learned about the identity of the mis-targeted cells
3.8.3    if possible, require an AND condition requiring simultaneous presence of two target molecules on the same cells being targeted
3.8.4    if necessary, design a non-specific targeting control switch on a secondary non-specific target molecule which inactivates subsequent nanomedical device action (off control switch upon detecting an error in targeting).


Copyright © 2011, James F. Leary, All rights reserved.


Omid C. Farokhzad, Sangyong Jon, Ali Khademhosseini, Thanh-Nga T. Tran, David A. LaVan, and Robert Langer. “Nanoparticle-Aptamer Bioconjugates: A New Approach for Targeting Prostate Cancer Cells” CANCER RESEARCH 64, 7668–7672, 2004.
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Ralph Weissleder, Kimberly Kelly, Eric Yi Sun, Timur Shtatland, Lee Josephson. “Cell Specific targeting of nanoparticles by multivalent attachment of small molecules”. Nature Biotechnology 23(11): 1418-1423, 2005.
Jesus M. de la Fuente, Catherine C. Berry, Mathis O. Riehle, and Adam S. G. Curtis. “Nanoparticle Targeting at Cells”, Langmuir 22, 3286-3293, 2006.
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Shen Baozhong, Wang Kezheng, Sun Xilin and Wu Lina “Development of molecular imaging and nanomedicine in China” WIREs Nanomedicine and Nanobiotechnology 2011.

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