[Audio] BME 695L: Engineering Nanomedical Systems

Guest lecturer: Helen McNally

Guest lecturer: Deborah Knapp.

See references below for related reading.15.1      Overview15.1.1    What does cGMP mean?15.1.2    Why GMP? Controlling processes means more predictable outcomes…15.1.3    Enforcement15.1.4    What can be learned from the semi-conductor industry clean-room and manufacturing?15.1.5    What doesn’t fit this paradigm?15.2      cGMP-level manufacturing15.2.1    Predictable methods lead to predictable products15.2.2    The CFR (Code of Federal Regulations) sections on GMPs15.2.3    What is covered under cGMP?15.3      Bionanomanufacturing15.3.1    So what is special about biomanufacturing?15.3.2    Nano-clean water necessary for nano-pharmaceuticals15.3.3    Contaminants at the nano-level15.3.4    Can you scale up the process?15.4      Some quality control issues – how to test15.4.1    Correctness of size – size matters!15.4.2    Composition – atomic level analyses15.4.3    Monodispersity versus agglomeration15.4.4    Order and correctness of layers215.4.5    Correctness of zeta potentials15.4.6    Does the nanomedical system contain the correct payload?15.4.7    Targeting (and mis-targeting) specificity and sensitivity

See references below for related reading.16.1      Introduction and overview16.1.1    How does the FDA think about nanomedical systems?16.1.2    The 2006 Nanotechnology Task Force16.2      Some details of the Nanotechnology Task Force Report16.2.1    General findings of the report16.2.2    Some initial recommendations of the Task Force16.2.3    Where the FDA may need to meet EPA on nanoscale materials16.2.4    Will FDA re-visit GRAS products containing nanomaterials?16.3      How will the FDA consider nanomedical systems?16.3.1    Nanomedical systems are integrated nanoscale drug and drug delivery devices16.3.2    Either a drug or a device? How about a "Combination Product"?16.3.3    Drug-Biologic combination products16.4      Types of human clinical trials16.4.1    IND16.4.2    “Phase 0”16.4.3    Phase 116.4.4    Phase 216.4.5    Phase 316.4.6    Phase 416.5      EPA and other regulatory agency issues16.5.1    Assessing environmental impact of emerging nanotechnologies16.5.2    Concept of life cycle assessment (LCA)16.5.3    Toxicity of nanomaterials16.5.4    Some recommendations of the 2006 International Conference on Nanotechnology and Life Cycle Assessment16.6      Nanotechnologies and the workplace16.6.1    NIOSH – Formulating workplace safety standards for nanotechnology16.6.2    Protecting workers in the workplace16.6.3    Assessing hazards in the workplace16.6.4    Establishing a Nanotechnology Safety System16.7      The future of nano-healthcare products

See references below for related reading.12.1      Introduction to measures of efficacy for nanomedicine12.1.1    for evaluation purposes, does structure/size reveal function?12.1.2    nanomedical treatment at the single cell level requires evaluation at the single cell level12.1.3    the difficulty of anything but simple functional assays (e.g. phosphorylated “functional” proteins)12.1.4    the need for assays which at least show correlation to functional activity12.2      Quantitative single cell measurements of one or more proteins per cell by flow and image/confocal cytometry12.2.1    cell surface measures of protein expression on live, single cells12.2.2    high-throughput flow cytometric screening of bioactive compounds12.2.3    challenges of measuring protein expression inside fixed, single cells12.2.4    when location is important 2D or 3D imaging is required to get spatial location of proteins inside cells (“locational proteomics” at the single-cell level)12.3      Quantitative multiparameter phospho-specific flow/image cytometry as a single-cell,structural-functional measurement12.3.1    attempts to measure "functional proteins" by detecting phosphorylation12.3.2    example of phospho-specific, multiparameter flow cytometry12.3.3    example of measuring single cell gene silencing by phospho-specific flow cytometry12.4      Quantitative measures of gene expression – the promises and the realities12.4.1    is gene expression at the single cell level really possible?12.4.2    is it even useful to measure a single gene's changes?12.4.3    gene arrays of purified cell subpopulations12.4.4    RNA amplification techniques to attempt to perform single cell gene arrays

See references below for related reading.13.1      Bringing in-vivo considerations into NMS design13.1.1    the in-vitro to ex-vivo to in-vivo paradigm         13.1.1.1 In-vitro - importance of choosing suitable cell lines         13.1.1.2 adding the complexity of in-vivo background while keeping the simplicity of in-vitro         13.1.1.3 all the complexity of ex-vivo plus the “active” components of a real animal13.1.2    In-vivo systems are open, “active” systems with multiple layers of complexity         13.1.2.1 In-vitro and ex-vivo are mostly “closed” systems, but not absolutely         13.1.2.2 What is an “open” system?         13.1.2.3 Attempts to isolate open systems13.1.3    Layers of complexity of in-vivo systems         13.1.3.1 Human cells in nude mice – a mixture of in-vitro and in-vivo         13.1.3.2 “Model” small animal systems         13.1.3.3 better model larger animal systems13.2      Circulation time and biodistribution13.2.1    factors affecting circulation time         13.2.1.1 size/shape         13.2.1.2 "stealth layer" coating         13.2.1.3 zeta potential in-vivo in varying environments         13.2.1.4 filtration and excretion         13.2.1.5 dose/targeting13.2.2    where do the NMS go in-vivo?         13.2.2.1 checking the obvious organs (liver, spleen, kidney, blood…)         13.2.2.2 finding NMS in tissues and organs             13.2.2.2.1 in-vivo             13.2.2.2.2 within dissected tissue sections             13.2.2.2.3 in blood (ex-vivo versus in-vivo flow cytometry)             13.2.2.2.4 what is excreted?13.2.3    Circulation time and dose optimization         13.2.3.1 measure drug concentration over time         13.2.3.2 is there an optimal drug dose?13.4      In-vivo targeting and mistargeting13.4.1    mode of administration (intravenous, oral, intra-tumor…)13.4.2    how can we assess targeting in-vivo? (MRI, fluorescence, …)13.4.3    a rare-cell targeting problem13.4.4    consequences of mistargeting13.4.5    balancing dosing, therapeutic efficacy, and consequences of mistargeting13.5      Evaluating therapeutic efficacy in-vivo13.5.1    advantages of non-invasive measurements13.5.2    measures of tumor load/shrinkage (tumor size, weight,..)13.5.3    other measures of disease effects         13.5.3.1 direct measurement of restoration of lost or compromised functions         13.5.3.2 indirect measures of disease effects (e.g. behavior, weight gain/loss, .)13.5.4    Some examples of in-vivo work with NMS13.6      Summary13.6.1    Choosing an appropriate animal model and getting it approved takes time!13.6.2    Animal experiments are expensive and time-consuming13.6.3    Performing in-vivo measurements of drug delivery and therapeutic efficacy are more challenging and expensive than in-vitro or ex-vivo work!13.6.4    But ultimately you must show that the NMS works in-vivo

See references below for related reading.14.1      Introduction to integrated designs14.1.1    “Total design” but there is some order in the design process14.1.2    A brief outline of the total design process14.2      Choose autonomous or non-autonomous design14.2.1    If autonomous, will there be error-checking to correct mistargeting?14.2.2    If autonomous, does the NMS perform all of the multi-step process sufficiently to accomplish the objective?14.2.3    If non-autonomous, what form of external modulation of the in-vivo nanomedical system will be used?14.2.4    If non-autonomous, are the external interactions able to adequately control the actions of the NMS?14.2.5    Evaluate reaction of NMS to external intervention14.2.6    Compare actions of NMS with and without external intervention.14.2.7    How do the actions of the NMS scale (linear? nonlinear? resonance? ) with the size or extent of the external intervention?14.3      Choose core material, size and shape14.3.1    How will the core be used for diagnosis? Therapeutics?14.3.2    Does this dictate the core material? Size?14.3.3    Does shape alter circulation time or target cell penetration?14.3.4    Evaluate size and shape of nanosized core by transmission (TEM) or scanning electron microscopy (SEM), or by atomic force microscopy (AFM)14.3.5    Evaluate size of complete NMS (other parts may not be electron dense) by dynamic light scattering (DLS)14.3.6    Evaluate materials present at each layer of construction by x-ray photoelectron spectroscopy (XPS)14.4      Design NMS targeting and evaluate its effectiveness14.4.1    Choose cell surface biomarker on diseased cell. Is it unique or just elevated in expression (e.g. folate receptors)14.4.2    Choose targeting molecule type (antibody, peptide, aptamer…)14.4.3    Use flow or image cytometry to evaluate correctness of targeting to diseased cell using that biomarker system14.4.4    How much mis-targeting is anticipated? What are the consequences of mistargeting?14.4.5    Determine degree of mistargeting and consider the costs of misclassification (e.g. how many normal cells are mis-targeted for each diseased cell successfully targeted)14.4.6    Based on the costs of misclassification, reconsider additional or alternative diseased cell biomarkers?14.4.7    Evaluate intracellular targeting by TEM if NMS is not fluorescent)14.4.8    Evaluate intracellular targeting by 3D confocal fluorescence microscopy (if NMS is fluorescent)14.4.9    Evaluate intracellular targeting by 2D fluorescence microscopy if confocal microcopy is unavailable14.5      Choose zeta potential14.5.1    Determine required zeta potential for outer/inner layers14.5.2    Determine pH of encountered microenvironments14.5.3    Determine ionic strength of encountered microenvironments14.5.4    Evaluate suitability of zeta potential14.5.5    If signs of agglomeration, modify zeta potential of NMS.14.5.6    Are the NMS sticking to any surfaces or cell types?14.5.7    Are the NMS being rapidly filtered by the kidneys in-vivo?14.6      Choose stealth molecule14.6.1    Determine required time of circulation14.6.2    Circulation time will determine dose needed14.6.3    Evaluate effectiveness of stealth molecule         14.6.3.1 Do the NMS show signs of protein deposition in-vitro or in-vivo?         14.6.3.2 Are the circulation times of the NMS adequate to sufficiently target the diseased cells in-vivo?14.7      Choose type and intracellular target of therapy14.7.1    Eliminate or fix the diseased cells?14.7.2    If choice is elimination, choose appropriate therapeutic molecule that will accomplish this action14.7.3    If choice is to fix the diseased cells, what therapeutic molecule can accomplish this action and how will it be controlled?14.7.4    Choose molecular measure of effectiveness of therapy (induced apoptosis, restoration of normal phenotype, …)14.7.5    Use single cell analysis by flow cytometry to measure that molecular measure, if cells are in suspension.14.7.6    Use scanning image cytometry to measure that molecular measure, if cells are attached14.8      A few final words on design of integrated nanomedical systems14.8.1    We are still in the early days of designing nanomedical systems. Some of the necessary feedback we need for better designs awaits early clinical trials on human patients and volunteers 14.8.2    We do not understand some of the processes well enough to fully control their design. Still it is important to know what is important even if can not yet control it!

Guest lecturer: Dmitry Zemlyanov

See references below for related reading.11.1      Need for single cell measures of nanotoxicity11.1.1    There is more than one way for a cell to die...11.1.2    "Necrosis" vs. "Apoptosis"11.1.3    There are other forms of "toxicity"11.1.4    Some other challenges in measuring toxicity of nanomaterials11.2      Necrosis vs. Apoptosis mechanisms11.2.1    Necrosis is unplanned "cell injury"11.2.2    Apoptosis is planned "programmed cell death"11.2.3    Why it is important to distinguish between necrosis and apoptosis?11.3      Single-cell assays for necrosis and apoptosis11.3.1    Dye exclusion assays for necrosis11.3.2    TUNEL assays for late apoptosis11.3.3    Annexin V assays for early apoptosis11.3.4    COMET assays for DNA damage and repair11.3.5    Light scatter assays11.3.6    Dihydroethidium assays for oxidative stress11.4      Nanotoxicity in vivo – some additional challenges11.4.1    Single-cell nanotoxicity, plus biodistribution measuring challenges….11.4.2  Accumulations and agglomerations of nanoparticles can change toxicity locally totissues and organs11.4.3    Filtration issues of nanoparticles – size matters – toxicity to kidney, liver and lung11.4.4    Functional sensitivity of heart and brain to nanotoxicity largely unknown

See references below for related reading.10.1      Introduction and overview10.1.1    Some of the advantages of therapeutic genes10.1.2    Some of the advantages of molecular biosensor feedback control systems10.1.3    Why a nanodelivery approach is appropriate10.2      The therapeutic gene approach10.2.1    What constitutes a "therapeutic gene" ?10.2.2    Transient versus stable expression modes10.3      Molecular feedback control systems10.3.1    Drug delivery has traditionally not used feedback controls10.3.2    Why feedback control might be a very good idea!10.3.3    Positive or negative feedback?10.4      Molecular Biosensors as a component of a nanomedicine feedback control system10.4.1    What is a molecular biosensor?10.4.2    How a molecular biosensor functions as a therapeutic gene switch10.5      Building integrated molecular biosensor/gene delivery systems –some examples10.5.1    Example of a ribozyme/antivirus system10.5.2    Example of an ARE biosensor/DNA repair system10.5.3    Example of a feedback-controlled system for treatment of retinopathies

See references below for related reading.9.1      Overview of drug dosing problem9.1.1    Problems of scaling up doses from animal systems9.1.2    Basing dosing on size, area, weight of recipient9.1.3    Vast differences between adults in terms of genetics, metabolism9.1.4    Dosing in children – children are NOT smaller adults!9.1.5    Pharmacokinetics – drug distribution, metabolism, excretion, breakdown9.1.6    Conventional dosing assumes drug goes everywhere in the body9.1.7    Targeted therapies – a model for future nanomedical systems?9.2      From the animal dosing to human clinical trials9.2.1    Importance of picking an appropriate animal model system9.2.2    Does drug dosing really scale?9.2.3    The human guinea pig in clinical trials and beyond9.3      Traditional drug dosing methods9.3.1    Attempts to scale up on basis of area9.3.2    Attempts to scale up on weight/volume9.3.3    Attempts to use control engineering principles9.4      Genetic responses to drug dosing9.4.1    All humans are not genomically equivalent!9.4.2    Predicting on basis of family tree responses9.4.3    SNPs, chips, and beyond…predicting individual drug response9.4.4    After the $ ???? individual genome scan… more closely tailored individual therapies9.5      Dosing in the era of directed therapies – a future model for nanomedical systems?9.5.1    How directed therapies change the dosing equation9.5.2    Current generation directed antibody therapies dosing9.5.3    Some typical side effects of directed therapies9.5.4    Nanomedical systems are the next generation of directed therapies9.6      Most directed therapies are nonlinear processes!9.6.1    Meaning of nonlinear processes9.6.2    Some examples of how a few directed therapies work9.6.3    Side effects of “directed therapies” 9.7      Other ways of controlling dose locally9.7.1    Magnetic field release of drugs9.7.2    Light-triggered release of drugs

See references below for related reading.8.1      Introduction8.1.1    attachment strategies typically depend on core composition8.1.2    but the attachment strategy should not drive the core choice8.1.3    the choice of core should still depend on the desired overall “multifunctional” nanomedical device8.2      “Surface chemistry” strategies for attachment of biomolecules to the core material8.2.1    hydrophobic versus hydrophilic core materials8.2.2    addition of biomolecules for biocompatibility8.2.3    monofunctional versus bifunctional surface chemistry strategies8.2.4    PEGylation as “stealth strategy” to minimize opsonification and increase circulation time8.2.5    pay attention to overall zeta potential during the surface chemistry process!8.3      Two main attachment strategies8.3.1    covalent bonding strategies         8.3.1.1 advantages             8.3.1.1.2 very stable             8.3.1.1.3 can control process of bond disruption for multilayering         8.3.1.2 Disadvantages             8.3.1.2.1 can be too stable and difficult to disassemble             8.3.1.2.2 must be careful to avoid or minimize use of strong organic solvents that can be cytotoxic even at trace concentrations8.3.2    non-covalent (primarily electrostatic) Bonding Strategies         8.3.2.1 advantages             8.3.2.1.1 can use very gentle chemistries for biocompatibility             8.3.2.1.2 chemistry can be very simple layer-by-layer assemblies             8.3.2.1.3 easier to disassemble multilayered structures         8.3.2.2 disadvantages             8.3.2.2.1 instability - different pH and ionic strength environments can cause layers to spontaneously disassemble at undesired times             8.3.2.2.2 zeta potential can suddenly change as layers spontaneously strip off8.4      Special considerations for the final attachment design8.4.1    preparing the nanoparticle for addition of targeting and therapeutic molecules8.4.2    what are the special requirements, if any, for these molecules?         8.4.2.1 how to attach without changing function of molecule         8.4.2.2 does this molecule need to stay attached, or not, to the nanoparticle in order to function8.4.3    testing for targeting and therapeutic efficacy at the single cell level8.5      Attaching different types of targeting molecules (some types and examples)8.5.1    antibodies – which end to attach?8.5.2    peptides – which end to attach, steric hindrance? Spacer arm needed?8.5.3    aptamers - which end to attach, steric hindrance? Spacer arm needed?8.5.4    small molecule ligands - which end to attach, steric hindrance? Spacer arm needed?8.6      Testing the nanoparticle-targeting complex8.6.1    ways of detecting this complex8.6.2    ways of assessing targeting/mistargeting efficiency and costs of mistargeting8.6.3    is the nanoparticle still attached to the targeting molecule?8.7      Attaching/tethering different types of therapeutic molecules8.7.1    antibody therapeutics - need to interact with the immune system to activate8.7.2    peptides (e.g. apoptosis-inducing peptides)8.7.3    therapeutic aptamers8.7.4    transcribable sequences8.7.5    small drugs 8.8      Testing the nanoparticle-therapeutic molecule complex8.8.1    direct and indirect ways of detecting the therapeutic molecules8.8.2    ways of assessing the therapeutic efficacy at single cell level8.8.3    is the nanoparticle still attached to the therapeutic molecule? Is that important?8.9      Nanomedical pharmacodynamics – the great unknown8.9.1    little is known about complex nanoparticle pharmacodynamics8.9.2    obtaining quantitative biodistribution data is extremely difficult!8.9.3    some possible new approaches

See references below for related reading.6.1      Introduction6.1.1    the general problem of cell entry6.1.2    choosing modes of cell entry6.1.3    how does Nature do it? (biomimetics)6.2      Non-specific uptake mechanisms6.2.1    pinocytosis by all cells6.2.2    phagocytosis by some cells6.2.3    a recent study of Qdot NP uptake6.3      Nanoparticle uptake6.3.1    NP size matters6.3.2    NP shape matters6.3.3    NP agglomeration reduces uptake6.3.4    A sample study6.4      Receptor-mediated uptake6.4.1    Receptor mediated transport of desired molecules6.4.2    How to study uptake mechanisms by inhibiting pathways with specific drugs6.4.3    Some sample studies6.5      Effects of nanoparticle coatings6.5.1    Acrylate-Facilitated Cellular Uptake6.5.2    Polyethyleneimine Coating Enhancement of Cellular Uptake6.6      Effects of microenvironment and external stimuli

See references below for related reading.7.1      Introduction – the importance of the zeta potential7.1.1    nanoparticle-nanoparticle interactions7.1.2    nanoparticle-cell interactions7.1.3     part of the initial nanomedical system-cell targeting process7.1.4     low zeta potential leads to low serum protein binding and potentially longer circulation7.2      Zeta potential basics7.2.1     What is the zeta potential?         7.2.1.1 surface layer potential         7.2.1.2 Stern layer potential         7.2.1.3 slip layer         7.2.1.4 zeta potential layer7.2.2     How is it measured?         7.2.2.1 electrophoresis         7.2.2.2 conversion of electrophoretic mobility to zeta potential7.2.3     Zeta potential is the potential barrier to cell-nanoparticle interactions7.2.4     Optimal zeta potential is complicated but some general advice7.3      Some factors affecting the zeta potential7.3.1    pH7.3.2     ionic strength7.4       Some zeta potential experiences7.4.1     Size and zeta potential changes during LBL assembly of NPs7.4.2     Effects of pH and dilution on NP zeta potential7.5       "Zeta sizing" measuring size on a zeta potential instrument7.5.1     DLS (Dynamic Light Scattering) sizing7.5.2     Relating scattering intensity to diffusion coefficients and hydrodynamic size7.5.3     Computing the hydrodynamic radius from the Stokes-Einstein equation7.5.4     Actual versus measured DLS values

See references below for related reading.5.1      Introduction5.1.1    core building blocks5.1.2    functional cores5.1.3    functionalizing the core surface5.2      Ferric oxide cores5.2.1    paramagnetic cores5.2.2    superparamagnetic cores5.2.3    ferric nanorods5.2.4    advantages and disadvantages5.3      C60 and carbon nanotubes5.3.1    size and structure of C605.3.2    elongation of C60 into carbon nanotubes5.3.3    advantages and disadvantages5.4      Gold cores5.4.1    gold nanoparticles5.4.2    gold nanorods5.4.3    other shapes (e.g. "stars")5.4.4    gold nanoshells5.4.5    advantages and disadvantages5.5      Silica cores5.5.1    silica nanoparticles5.5.2    mesoporous silica NP for drug delivery and biosensing5.5.3    advantages and disadvantages5.6      Quantum dots5.6.1    size determines color5.6.2    good for multicolor fluorescence5.6.3    importance of coatings5.6.4    conjugating targeting molecules5.6.5    examples from studies5.6.6    finding sub-optical nanoparticles5.6.7    cytotoxicity issues5.7      Next generation quantum dots5.7.1    Water-Soluble Doped ZnSe Nanocrystal Emitters5.7.2    Organic quantum dots5.8      Hybrid materials5.8.1    gold-ferric oxide nanoparticles and nanorods5.8.2    NIR fluorescent-chitosan polymer-iron oxide core hybrids5.8.3    dual-modality MRI/NIRF imaging with hybrid nanoparticles

See references below for related reading.4.1      Overview: targeting nanosystems to cells4.1.1    antibody targeting4.1.2    peptide targeting4.1.3    aptamer targeting4.1.4    ligand-receptor targeting4.2      Antibodies – polyclonal and monoclonal4.2.1    Where do antibodies come from – in nature?4.2.2    How do we make them in the laboratory?4.2.3    Monoclonal antibodies – some details you need to know!4.2.4    Labeling strategies4.2.5    Therapy problems with mouse monoclonal antibodies4.2.6    “Humanizing” monoclonal antibodies to reduce adverse host immune reactions4.2.7    Why antibodies may not be a good overall choices for targeting nanosystems to cells 4.3      Peptide targeting4.3.1    How does a peptide target?4.3.2    Examples of peptide targeting4.3.3    Creating new peptides by random peptide phage display libraries4.3.4    High-throughput screening of those peptide libraries4.3.5    Advantages and disadvantages of peptide targeting4.4      Aptamer targeting4.4.1    What are aptamers and how do they target?4.4.2    Some different types of aptamers4.4.3    How do you make aptamers?4.4.4    How do you screen for useful aptamers?4.5      Ligand-receptor targeting4.5.1    What are ligands?4.5.2    What are their advantages/disadvantages?4.5.3    Example – folate receptors4.6      How do we quantitatively evaluate targeting?4.6.1    Technologies for evaluating targeting         4.6.1.1 Flow cytometry         4.6.1.2 Scanning image cytometry4.6.2    Evaluating targeting specificity4.6.3    Evaluating targeting sensitivity

See references below for related reading.3.1      Nanomedical systems – levels of challenges3.1.1    Diagnosis - difficult3.1.2    Therapy – more difficult3.1.3    Both ("Theragnosis") – most difficult!3.2      How theragnostics relates to Molecular Imaging3.2.1    conventional imaging is not very specific3.2.2    types of In-vivo Imaging         3.2.2.1 X-rays, CAT (Computed Axial Tomography) scans         3.2.2.2 MRI (magnetic Resonance Imaging)         3.2.2.3 PET (Positron Emission Tomography) scans3.2.3    "molecular imaging" of nanoparticles in-vivo for diagnostics/monitoring of therapeutics3.3      Engineering nanomedical systems for simultaneous molecular imaging3.3.1    using nanomedical cores for MRI contrast agents3.3.2    difficulties in using PET probes for nanomedical devices3.3.3    using cell-specific probes for molecular imaging of nanomedical devices3.3.4    breaking the "diffraction limit" – new nano-level imaging modalities3.4      Theragnostic nanomedical devices3.4.1    using nanomedical devices to guide separate therapeutic device3.4.2    when might we want to combine diagnostics and therapeutics?3.5      Requirements for specific cell targeting3.5.1    must be cell surface biomarker that at least partially identifies that cell3.5.2    OR a Boolean set of several biomarkers whose composite "signature" identifies a cell3.5.3    OR a set of biomarkers that excludes all other cells3.5.4    challenge – how to "multiplex" a Boolean set of targeting molecules3.6      Consequences of mis-targeting3.6.1    “side effects” to innocent bystander (normal) cells3.6.2    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 same3.6.3    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 threatening3.7      Engineering around the consequences of mis-targeting3.7.1    measure number of good (normal) cells destroyed to eliminate a diseased cell3.7.2    put a weighting factor on the relative “goodness” or “badness” of normal cells and diseased cells3.7.3    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 cells3.8.1    lower numbers of nanoparticles3.8.2    improve specificity of targeting molecules according to what is learned about the identity of the mis-targeted cells3.8.3    if possible, require an AND condition requiring simultaneous presence of two target molecules on the same cells being targeted3.8.4    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).

See references below for related reading.1.1      Nanotechnology – Why is something so small so big?1.1.1    Definitions of nanotechnology based on size1.1.2    A “bottoms up” rather than “tops down” approach1.1.3    The nanoworld challenges our perspectives on size1.2      The Progression of Medicine1.2.1    Conventional "modern" medicine1.2.2    "Personalized" or "molecular" medicine1.2.3    Nanomedicine "single-cell" medicine1.3      How Conventional Medicine Works for Diagnosis of Disease1.3.1    Identification of the "diseased state"1.3.2    Simple measurements of body structure and function1.3.3    Follow-up clinical tests1.3.4    Internal examinations by non-invasive in-vivo imaging1.3.5    Molecular tests for specific gene properties1.3.6    Comparison of individual results with "normal ranges"1.4      How Conventional Medicine Works for Treatment of Disease1.4.1    Stabilization of patient – "heal thyself"1.4.2    Surgical repair of injuries1.4.3    Treatment with drugs locally1.4.4    Treatment with drugs systemically1.4.5    Treatment with targeted therapies1.5      Factors Limiting the Progress of Medicine1.5.1    Economics1.5.2    Politics1.5.3    Regulation1.6      Some Specific Problems with Conventional Medicine1.6.1    Consequences of waiting for patient symptoms1.6.2    Trained people and modern drugs are expensive1.6.3    Diagnostic technologies, if available, are still relatively primitive and/or expensive1.6.4    Crude targeting of drugs1.7      What is the Basis for Nanomedicine?1.7.1    Creation of nano-sized tools1.7.2    These nanotools permit single-cell medicine1.7.3    These “nanomedical systems” can be “smart” devices1.8      Some ways that nanotechnologies will impact on healthcare1.8.1    Nanomedicine will be “pro-active” rather than “reactive” medicine1.8.2    Possibility of "regenerative medicine"1.8.3    Blurring of distinction between prevention and treatment

See references below for related reading.2.1       Elements of good engineering design2.1.1    Whenever possible, use a general design that has already been tested2.1.2    Whenever possible, take advantage of “biomimicry” – Nature has tried many designs!2.1.3    Avoid “general purpose” design. Use multiple specific molecules to do specific tasks.2.1.4    Control the order of molecular assembly to control the order of events2.1.5    Therefore, perform the nano assembly in reverse order to the desired order of events2.2      Building a nanodevice2.2.1    Choice of core materials2.2.2    Add drug or therapeutic gene2.2.3    Add molecular biosensors to control drug/gene delivery2.2.4    Add intracellular targeting molecules2.2.5    Result is multi-component, multi-functional nanomedical device2.2.6    For use, design to de-layer, one layer at a time2.2.7    The multi-step drug/gene delivery process in nanomedical systems2.3      The challenge of drug/gene dosing to single cells2.3.1    Precise targeting of drug delivery system while protecting non-targeted cells from exposure to the drug2.3.2    How to minimize mis-targeting2.3.3    How to deliver the right dose per cell2.3.4    One possible solution – in situ manufacture of therapeutic genes2.4      Bridging the gap between diagnostics and therapeutics2.4.1    how conventional medicine is practiced in terms of diagnostics and therapeutics2.4.2    the consequences of separating diagnostics and therapeutics2.4.3    a new approach – "theragnostics" (or "theranostics")2.5      Examples of current theragnostic systems2.5.1    example 1: Rituxan ("Rituximab)(an example of not using diagnostics to guide the therapy)2.5.2    example 2: Herceptin ("terastuzumab")2.5.3    example 3: Iressa ("Gefitinib)2.5.4    other examples2.6      How theragnostics relates to Molecular Imaging2.6.1    conventional imaging is not very specific2.6.2    types of In-vivo Imaging         2.6.2.1 X-rays, CAT (Computed Axial Tomography) scans         2.6.2.2 MRI (magnetic Resonance Imaging)         2.6.2.3PET (Positron Emission Tomography) scans2.6.3    "molecular imaging" of nanoparticles in-vivo for diagnostics/monitoring of therapeutics2.8      Engineering nanomedical systems for simultaneous molecular imaging2.8.1    using nanomedical cores for MRI contrast agents2.8.2    difficulties in using PET probes for nanomedical devices2.8.3    using cell-specific probes for molecular imaging of nanomedical devices2.8.4    breaking the "diffraction limit" – new nano-level imaging modalities2.9      Theragnostic nanomedical devices2.9.1    using nanomedical devices to guide separate therapeutic device2.9.2    when might we want to combine diagnostics and therapeutics?