Patent Publication Number: US-7900625-B2

Title: Inhaler system for targeted maximum drug-aerosol delivery

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of U.S. Provisional Patent Application Ser. No. 60/711,461, filed Aug. 26, 2005; the disclosure of which is incorporated herein by reference in its entirety. 
    
    
     GOVERNMENT INTEREST 
     The presently disclosed subject matter was made with U.S. Government support under Grant Nos. BES-0201271 awarded by the National Science Foundation, FA 9550-04-1-0422 awarded by the U.S. Air Force Office of Scientific Research, and 1R21GM074651-01 and 8R21EB006717-02 awarded by the National Institutes of Health. As such, the U.S. Government has certain rights in the present subject matter. 
    
    
     TECHNICAL FIELD 
     The presently disclosed subject matter relates to inhaler systems. In particular, the presently disclosed subject matter relates to inhaler systems capable of producing a controlled inhaled aerosol stream which can be directed to a desired lung target area with minimization of parasitic deposition. 
     BACKGROUND 
     Chronic obstructive pulmonary disease was in 1998 the fourth leading cause of death in the United States (see National Center for Health Statistics Report; 48 (11), (1998)). There has also been an astonishing increase over the last 20 years in asthma and cancer cases among children (see EPA Report 240-R-00-006; December 2000). 
     Inhalation of therapeutic particles, such as, but not limited to, drug aerosols, is a standard procedure for the treatment of lung airway inflammations and obstructions. This procedure is also now becoming a novel way to combat cancer, diabetes, AIDS, and other diseases, as well as for rapid pain management as inhalation of therapeutics can provide a very effective mechanism of systemic delivery. Existing drug aerosol delivery devices, however, including those that attempt to target specific areas in the lung, exhibit poor efficiencies (e.g., efficiencies ranging from about 5% to about 20%). Consequently, significant portions of the often-aggressive and expensive therapeutic agent used to combat diseases such as cancer, diabetes, and AIDS can deposit on healthy tissue. 
     For more than 40 years, the most commonly used device for administering therapeutic agents to combat such lung diseases has been the pressurized metered dose inhaler (pMDI). In a pMDI, a propellant (e.g., a non-CFC, such as HFA 134a) ejects, from a pressurized container via a valve, a metered dose of drug in solution (or colloidally suspended) into a spacer where an aerosolized plume is formed and then inhaled. Despite several improvements over the past decades concerning pMDI propellants, actuation mechanisms, and plume modifiers (see Crowder et al., 2001; and Edwards and Dunbar, 2002), pMDI devices suffer from systemic disadvantages (Keller, 1999); for example, the very low target deposition efficiencies, the relatively high aerosol speed, and the requirement for patients to synchronize their breathing inspiration with the actuation of the aerosol device. 
     Jet and ultrasonic nebulizers have also been used for administering therapeutic agents. These devices deliver therapeutic agents in the form of small droplets or a mist, suitable for single or multiple-dose, deep lung penetration of drugs by breath-actuation. Research efforts thus far have focused on the development of portable, battery-powered jet and ultrasonic aerosol generators. Unfortunately, these devices typically provide unsatisfactory deposition efficiencies. 
     Use of powder aerosols, either loaded by the user into a dry powder inhaler (DPI) or stored in the device, is another approach for administering therapeutic agents. In passive DPIs, the motion of the inhaled air generates powder particle entrainment and breakup, whereas in active DPIs, stored energy (e.g., blister packs) assists during inhalation in drug powder dispersion (Dunbar et al., 1998). Again, like pMDIs and jet and ultrasonic nebulizers, DPIs typically do not provide adequate targeted deposition efficiencies. 
     Thus, there is a need in the art for improved aerosol delivery devices, especially aerosol delivery devices that can target specific areas in the lung. 
     SUMMARY 
     This Summary lists several embodiments of the presently disclosed subject matter, and in many cases lists variations and permutations of these embodiments. This Summary is merely exemplary of the numerous and varied embodiments. Mention of one or more representative features of a given embodiment is likewise exemplary. Such an embodiment can typically exist with or without the feature(s) mentioned; likewise, those features can be applied to other embodiments of the presently disclosed subject matter, whether listed in this Summary or not. To avoid excessive repetition, this Summary does not list or suggest all possible combinations of such features. 
     In one embodiment of the presently disclosed subject matter, a method of delivering an active agent to a target area of a lung of a subject in need thereof is provided. In some embodiments, the method comprises providing an inhaler system for directing to a subject a controlled aerosol stream comprising an active agent and regulating a release position of the controlled aerosol stream from the inhaler system to deliver the active agent to a target area of a lung of the subject. In some embodiments, the active agent comprises one or more physical characteristics selected from the group consisting of: a particle size of from about 1 μm to about 20 μm; a substantially spherical shape; and a low density. 
     In another embodiment of the presently disclosed subject matter, an inhaler device for targeted aerosol stream release is provided. In some embodiments, the inhaler device comprises: an outer tube having an inlet at one end, an outlet at an opposing end, and a wall joining the inlet and the outlet comprising one or more air inlet perforations which provide for passage of inhalation airflow into an interior of the outer tube; an adaptive nozzle positioned within the interior of the outer tube and having a nozzle base inlet engaged with the outer tube inlet and a nozzle tip outlet proximal to the outer tube outlet, wherein the nozzle tip outlet and the nozzle base inlet are in flow communication and adapted for passage of an aerosol stream therebetween; and one or more actuators operationally linked to the adaptive nozzle, wherein the one or more actuators can position the nozzle tip outlet and thereby target the aerosol stream release from the inhaler device. 
     In some embodiments, the inhaler device comprises an inhalation airflow control mechanism for varying a cross-section of one or more of the outer tube air inlet perforations, thereby permitting control of the inhalation airflow to generate a desired inhalation waveform. Further, in some embodiments, the inhalation airflow control mechanism is provided in an inhaler device for generating a desired inhalation waveform, in the absence of an adaptive nozzle. In some embodiments, the inhalation airflow control mechanism comprises: an inner tube comprising one or more air inlet perforations, wherein the inner tube is positioned within the interior of the outer tube and slidingly engages an inner surface of the outer tube wall; and one or more actuators operationally linked to the inner tube, wherein the one or more actuators can slidingly position the inner tube to vary the alignment of the one or more inner tube air inlet perforations with the outer tube air inlet perforations, thereby varying the cross-section of one or more of the outer tube air inlet perforations. In some embodiments, the one or more inner tube actuators comprise an active material, such as for example an active material selected from the group consisting of a shape memory alloy (e.g., an alloy of nickel and titanium), a shape memory polymer, a magnetostrictive material, and a piezoceramic material. 
     In some embodiments, the inhaler device comprises one or more micropressure sensors positioned proximal to the outer tube outlet, which can detect an inhalation waveform from inhalation airflow flowing through the outer tube and transmit a signal to the inner tube actuators. The inner tube actuators can vary the position of the inner tube to change the alignment of the inner tube air inlet perforations with the outer tube air inlet perforations, thereby altering the inhalation waveform in response to the signal. The signal from the micropressure sensors can be transmitted to a control logic (e.g. a proportional-integral-derivative (PID) algorithm), which interprets the signal and transmits an actuator control signal to the inner tube actuators. In some embodiments, the control logic is in operational communication with computational fluid-particle dynamics results that determine one or more of the desired inhalation waveform and the desired position of the adaptive nozzle to direct the aerosol stream to a desired target area in a lung of a subject. 
     In some embodiments, the adaptive nozzle comprises a flexible polymer that permits flexing of the adaptive nozzle. In some embodiments, the one or more adaptive nozzle actuators comprise a first set of adaptive nozzle actuators that position the nozzle tip outlet within the outer tube and a second set of adaptive nozzle actuators that flex the adaptive nozzle such that the nozzle tip outlet is axially aligned with the outer tube outlet after positioning. The one or more adaptive nozzle actuators can comprise an active material, such as for example a shape memory alloy (e.g., an alloy of nickel and titanium), a shape memory polymer, a magnetostrictive material, or a piezoceramic material. In other embodiments, the adaptive nozzle can be rotated in an orbit around a central long axis of the outer tube and positioned at one or more desired orbital locations on the orbit. 
     In another embodiment of the presently disclosed subject matter, an inhaler system for targeted aerosol stream release is provided. In some embodiments, the inhaler system comprises: an aerosol source; an aerosol injection system in flow communication with the aerosol source; and an inhaler device in flow communication with the aerosol injection system. The inhaler device can in some embodiments comprise: an outer tube having an inlet at one end, an outlet at an opposing end, and a wall joining the inlet and the outlet comprising one or more air inlet perforations which provide for passage of inhalation airflow into an interior of the outer tube; an adaptive nozzle positioned within the interior of the outer tube and having a nozzle base inlet engaged with the outer tube inlet and a nozzle tip outlet proximal to the outer tube outlet, wherein the nozzle tip outlet and the nozzle base inlet are in flow communication and adapted for passage of an aerosol stream therebetween; and one or more actuators operationally linked to the adaptive nozzle, wherein the one or more actuators can position the nozzle tip outlet and thereby target aerosol stream release from the inhaler device. 
     In some embodiments, the aerosol source comprises a source selected from the group consisting of a pressurized metered dose inhaler (pMDI), a jet nebulizer (JN) and a dry powder inhaler (DPI). 
     In some embodiments, the aerosol injection system comprises a controllable reservoir chamber having an inlet in flow communication with the aerosol source and an outlet in flow communication with the inhaler device. In some embodiments, the aerosol injection system comprises: a pressure sensor that measures pressure within the controllable reservoir chamber; an inlet valve for controlling entry of an aerosol into the controllable reservoir chamber through the reservoir chamber inlet; and an outlet valve for controlling release of the aerosol from the controllable reservoir chamber through the reservoir chamber outlet, wherein the pressure sensor measures pressure within the reservoir chamber and regulates opening and closing of the inlet valve and the outlet valve in order to maintain a desired pressure within the reservoir chamber. In some embodiments, the inlet and outlet valves each comprise an active material actuator, such as for example a thin film actuator. In some embodiments, the active material actuator comprises an active material selected from the group consisting of a shape memory alloy, a shape memory polymer, a magnetostrictive material, and a piezoceramic material. 
     Accordingly, it is an object of the presently disclosed subject matter to provide an inhaler system for targeted drug-aerosol delivery. This object is achieved in whole or in part by the presently disclosed subject matter. 
     An object of the presently disclosed subject matter having been stated above, other objects and advantages will become apparent to those of ordinary skill in the art after a study of the following description of the presently disclosed subject matter and non-limiting examples. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a cut-away perspective view of one embodiment of an inhaler device as disclosed herein. 
         FIGS. 2A and 2B  are cut-away perspective views of one embodiment of an inhaler device as disclosed herein showing the adaptive nozzle in a neutral position ( FIG. 2A ) and in an altered position as a result of repositioning by SMA actuators ( FIG. 2B ). 
         FIG. 3  is a perspective view of one embodiment of an inhaler device and controllable reservoir chamber as disclosed herein. 
         FIG. 4  is a flowchart showing micropressure sensor, control logic, and actuator interactions. 
         FIGS. 5A-5C  are graphs showing sensor properties of SMA materials based on deformation-resistivity relations. 
         FIGS. 6A-6C  are diagrams of a simulation-based drug delivery design for the upper airway, starting from the mouth. A hemispherical tumor was placed in generation G 2 , comparing drug aerosol deposition fractions on the tumor surface for a case utilizing a simulated standard pMDI (normal case) and a simulated smart inhaler system as disclosed herein (controlled case).  FIG. 6A  shows particle release position at the mouth inlet.  FIG. 6B  shows resulting particle deposition patterns in the oral airway.  FIG. 6C  shows resulting particle deposition patterns in the bronchial airway G 0  to G 3  with local tumors. 
         FIG. 7  is a schematic diagram showing examples of nozzle tip outlet particle release positions in inhaler exit plane. 
         FIGS. 8A-8D  are diagrams ( FIGS. 8A-8C ) and a photograph ( FIG. 8D ) showing simulation of particle location at outlet cross section A-A′ for oral airway geometry, airflow rate of 8 standard liters per minute (slpm), and a release location at “top” ( FIG. 8A ). Experimental results confirming simulation predictions are shown in  FIG. 8D . The circle in the photograph of  FIG. 8D  indicates measured particle locations. 
         FIGS. 9A-9D  are diagrams ( FIGS. 9A-9C ) and a photograph ( FIG. 9D ) showing simulation of particle location at outlet cross section A-A′ for oral airway geometry, airflow rate of 8 slpm, and a release location at “bottom” ( FIG. 9A ). Experimental results confirming simulation predictions are shown in  FIG. 9D . The circle in the photograph of  FIG. 9D  indicates measured particle locations. 
         FIGS. 10A-10C  show results of targeted aerosol stream release.  FIG. 10A  is a series of schematic drawings showing nozzle position for targeted release of the aerosol stream.  FIGS. 10B and 10C  are photographs showing particle locations at the outlet of left ( FIG. 10B ) and right branches ( FIG. 10C ) after first bifurcation (B 1 , as labeled in  FIG. 11B ). Flow rate was 8 slpm. 
         FIGS. 11A and 11B  are diagrams showing 3-D views of the oral airway model ( FIG. 11A ) and bifurcation airway model, Generations G 0  to G 3  ( FIG. 11B ). B 1 —first bifurcation, B 21  and B 22 —second bifurcation, B 31 , B 32 , B 33  and B 34 —third bifurcation. The dashed lines indicate the segmental boundaries. 
         FIG. 12  is a diagram showing particles released within a critical radius. 
         FIG. 13  is a diagram showing distributions of particles leaving different tubes of generation G 3  with different given release positions at the mouth inlet (Q in =8 L/min and d p =7 μm; dry air). 
     
    
    
     DETAILED DESCRIPTION 
     The presently disclosed subject matter provides a smart inhaler system, which can in representative embodiments fulfill two tasks simultaneously: the provision of substantially maximum drug particle deposition on desired lung target sites and the minimization of deposition of potentially very aggressive drugs on healthy lung tissue by targeted release of an aerosol stream from the inhaler system. Further, by automatically modifying within the inhaler system inhalation airflow produced by a subject&#39;s inhalation, the presently disclosed smart inhaler system generates a controlled inhalation waveform, thereby reducing or even avoiding extra training phases. The avoidance of such extra training phases can be especially beneficial in the treatment of young children and/or the elderly. 
     In contrast to conventional approaches, which use turbulent flow already in the mouth inlet cross section (i.e., the inhaler outlet opening) to increase mixing of inhalation airflow and aerosols (Finley, 2001; Crowder, 2001; and Clark, 2004), computational fluid-particle dynamics (CFPD) analysis utilized by the presently disclosed subject matter predicts a correlation between aerosol characteristics and aerosol stream release position into an inhalation airflow and the deposition location, when powered by a predetermined laminar inhalation waveform. The analysis suggests that three factors should be considered for targeted delivery, i.e., optimal aerosol characteristics (e.g., size, shape, and density of active agent particles), control of the particle release positions, and flow control of inhalation waveform. In some embodiments, the presently disclosed subject matter can address each of these factors, including in particular the second factor and/or the third factor, i.e., control of the particle release positions and/or flow control of the inhalation waveform utilizing a smart inhaler system of the presently disclosed subject matter for targeted delivery of an active agent in an aerosol stream. 
     The first factor, i.e., aerosol characteristics, can in some embodiments, be addressed through the selection or production of an active agent (alone or in combination with a carrier) comprising desired physical characteristics. In some embodiments, desired physical characteristics of the active agent include, but are not limited to a particle size of from about 1 μm to about 10 μm or from about 5 μm to about 20 μm (e.g., 7 μm or 8 μm), a substantially spherical shape, and a low density (e.g., a density comparable to the surrounding carrier medium which can minimize sedimentation and impaction). 
     Accordingly, the presently disclosed subject matter provides in some embodiments a method of delivering an active agent to a target area of a lung of a subject in need thereof. In some embodiments, the method comprises providing an inhaler system (e.g., a smart inhaler system) for directing to a subject a controlled aerosol stream comprising an active agent; and regulating a release position of the controlled aerosol stream from the inhaler system into an inhalation airflow to deliver the active agent to a target area of a lung of the subject. 
     The presently disclosed subject matter provides a “smart inhaler system”, which can increase targeted deposition efficiencies over current inhalers known in the art. Current inhaler systems can at best broadly target lung regions, such as the upper (bronchial) or lower (alveolar) lung. In contrast, the presently disclosed inhalers provide for targeting regions in specific generations (i.e., lung branches) in either the left or the right lobe of the lung, if desired. Together with drastically minimized parasitic wall deposition in the oral airways and on other healthy tissue, the presently disclosed smart inhaler system enables safer and more efficient treatment of lung cancer and other respiratory diseases through targeted drug delivery. In addition, the system also creates a platform for the oral intake of various other kinds of active agents, such as insulin, with desirable efficiency. 
     Further, in some embodiments the presently disclosed smart inhaler system can automatically detect and adapt to a subject&#39;s breathing pattern thereby providing a desired inhalation waveform, and reducing and/or even removing the need for individual training and the associated intake uncertainties. An “inhalation waveform” as the term is used herein refers to a measure of air flow over time (e.g., liters per minute). Normally, inhalation waveforms can vary over the length of a breath, having a peak somewhere toward the middle of a breath and decreasing on either end, which in turn is mirrored in an inhaler outlet where an aerosol stream is injected during an actuation of an inhaler device. In addition, different users, e.g. healthy vs. infirm and children vs. adults, produce different waveforms that can affect targeted delivery of the active agent. As such, a desired, ideal, or optimal waveform can be calculated and the presently disclosed smart inhaler system can measure and adapt an inhalation waveform to a desired inhalation waveform. In some embodiments, a “desired inhalation waveform” is a waveform that can facilitate uniform (e.g., rectangular graphed waveform) laminar flow (e.g., an inhalation flow rate (Q in )≦12 Liters (L)/minute (min)) of the air stream produced by inhalation through the inhaler (i.e., the inhalation airflow) during substantially all of the time period during which the aerosol stream is being directed into the inhalation airflow. For example, in some embodiments, a desired inhalation waveform is one in which the flow rate is substantially constant and from about 6 L/min to about 10 L/min, and in some embodiments about 8 L/min. 
     The performance characteristics of the presently disclosed smart inhaler system can be realized in some embodiments through: (1) a combination of sensors; (2) an adaptive smart inhaler device and a reservoir chamber, both of which can be actuated in some embodiments by shape memory alloy (SMA) actuators; and (3) a control logic, which can be based on experimentally validated predictions of a computer simulation model of targeted lung deposition. 
     In some embodiments, the presently disclosed smart inhaler system implements a controlled air-particle stream, which directs inhaled therapeutic agents, such as drug aerosols, to a desired lung target area with maximum deposition efficiency independent of an individual subject&#39;s inhalation pattern. The inhaler system can work in conjunction with an aerosol source and can comprise in some embodiments two components: (i) an aerosol injection system, which regulates the pressure/velocity and particle distribution of the aerosol source employed; and (ii) an inhaler device, having in some embodiments control mechanisms for (a) producing the desired inhalation waveform independent of a subject&#39;s breathing mode and (b) delivering into the inhalation waveform the embedded particle aerosol stream from an optimal release position. 
     To achieve a desired aerosol efficiency at targeted lung areas, such as for example more than about 45%, the inhaler device, which also can function as a mouth-piece, can be attached, e.g., by a clamp, either directly to an existing aerosol source, for example, a jet nebulizer (JN), a pressurized metered dose inhaler (pMDI) or a dry powder inhaler (DPI), and the like, or to an aerosol injection system, which in turn is attached to an aerosol source. The inhaler device can be regulated for a specific aerosol type and disease and helps to guide the therapeutic agent to the desired lung target area independent of the subject&#39;s breathing pattern. 
     In addition to respiratory therapies, an increasing number of therapeutic agents could benefit from lung delivery via the presently disclosed smart inhaler system, including anti-tubercular agents, vaccines, morphine and other therapeutic agents for pain management, growth hormones, insulin for diabetes therapy, beta-interferon, and oligonucleotides for cystic fibrosis gene therapy, and the like. 
     Accordingly, in some embodiments, a combination of a smart inhaler device and an aerosol injection system can be used to implement the mechanisms for the control of inhalation waveform and particle release position. This modular concept allows for the accommodation of different aerosol sources, e.g., JN, DPI, and pMDI, as well as adaptation of different subject&#39;s breathing patterns. Suitable aerosol sources known in the art, include, but are not limited to, jet and ultrasonic nebulizers, which deliver drugs in form of small droplets or a mist, suitable for single or multiple-dose, deep lung penetration of drugs by breath-actuation. Further, use of powder aerosols, either loaded by the user into a dry powder inhaler (DPI) or stored in the device, is another approach. In passive DPIs, the motion of the inhaled air generates powder particle entrainment and breakup, whereas in active DPIs, stored energy (e.g., blister packs) assists during inhalation in drug powder dispersion (Dunbar et al., 1998). 
     The presently disclosed subject matter provides in some particular embodiments a smart inhaler system comprising an aerosol source, an aerosol injection system and a smart inhaler device, all in flow communication. In some embodiments, the aerosol injection system and inhaler device are attached to a conventional drug-aerosol source, such as a JN, a pMDI or a DPI. 
     The smart inhaler device can comprise an outer tube having an inlet at one end and an open outlet that can act as a mouth piece at an opposing end. The outer tube can further comprise one or more air inlet perforations which provide for passage of inhalation airflow into an interior of the outer tube. 
     In some embodiments, based on in situ pressure measurements, the optimal, computationally predetermined inhalation waveform can be generated in real-time utilizing an inhalation airflow control mechanism for varying a cross-section of one or more of the outer tube air inlet perforations, thereby permitting control of the inhalation airflow to generate the predetermined inhalation waveform within the inhaler device, and in particular, at the location of aerosol stream release. In some embodiments, the inhalation airflow control mechanism comprises an actuated inner tube comprising air inlet perforations, which slides relative to the perforations in the outer tube to vary the cross-sections of the outer tube perforations. 
     The targeted drug-aerosol stream release from a computationally predetermined position/segment of the outlet cross-section of the outer tube/mouthpiece, which can be selected based on a desired target area of the lung of a subject, can be achieved in some embodiments with an adaptive nozzle positioned within the outer tube. 
     In some embodiments, the adaptive nozzle comprises a nozzle tip outlet, which can be deflected by one or more actuators and hence optimally positioned within the outer tube. In another embodiment, targeted drug-aerosol stream release can be achieved utilizing an adaptive nozzle with variable exit diameters and which is positioned substantially and in some embodiments perfectly parallel to the inhaler tube wall. Determination of targeted release positions from correlated positions on orbits with critical radii allows for constructing the nozzle so as to rotate around a central long axis and arrest on the selected orbits and at orbital locations (see  FIG. 12  and Example 5, for example). Changes in nozzle exit diameter and orbital positioning can be implemented via various mechanisms. Non-limiting examples for orbital positioning include ball-and-spring-loaded disk/ratchet or a precision-gear mechanism. Different radial settings can achieve target-specific orbits. 
     The computationally predetermined drug-aerosol stream characteristics and release positions are a function of a subject&#39;s lung morphology, type of drug, and deposition site. As used herein, the term “subject” refers to both human beings and animals (e.g., mammalian subjects) for medical, veterinary, testing and/or screening purposes. 
     The inhaler device can also be equipped with one or more micropressure sensors to detect the inhalation waveform from inhalation airflow flowing through the outer tube, which can be positioned in some embodiments proximal to the outer tube outlet, such as for example in the outlet cross-section. Exemplary micropressure sensors suitable for use with the presently disclosed inhaler device include, but are not limited to, silicon micromachined piezoresistive pressure sensing chips, such as those available from Silicon Microstructures, Inc. (Milpitas, Calif., U.S.A.). Based on this information, the cross-section of the air inlets can be varied, such as by varying the position of the perforated inner sliding tube by actuators receiving a signal from the micropressure sensors to transform the initial inhalation airflow waveform into an inhalation waveform that corresponds to uniform laminar flow necessary for optimal air-particle transport. In some embodiments, the actuators vary the position of the inner tube to change the alignment of the inner tube air inlet perforations with the outer tube air inlet perforations to produce the desired inhalation waveform. 
     In some embodiments, active materials can be utilized. Active materials include for example shape memory alloys (SMA), shape memory polymers, piezoceramic materials or magnetostrictive materials for actuation, and in some embodiments for sensing as well, which allows for the development of highly integrated intelligent systems. 
     An illustrative example of actuation by active materials is the linear actuation capability of an SMA wire actuator. This material is known to exhibit the highest work output per volume of all known actuation mechanisms, see, e.g. Hollerbach et al. (1992). It can easily be stretched at low temperatures, but upon thermal activation, which can be effected by low-voltage electric power, it contracts, very much like a “metal muscle”. Thus, it not only replaces an entire apparatus of gears and other transmission components, but at the same time also provides high actuation force and stroke, is lightweight, and can easily be embedded into structures in a highly flexible way. 
     Moreover, a prominent SMA, nickel titanium alloy (NiTi), is known for its high biocompatibility, and these attractive features have led to a number of applications in the biomedical field, which range from already well-established applications, like stents and orthodontal braces (Duerig et al., 1999), to more advanced systems like smart endoscopes actuated by SMA wires (Reynaerts et al., 1999), and micro drug-dosage systems based on SMA thin film pumps (Benard et al., 1998; Makino et al., 2001; Xu et al., 2001). 
     Now with reference to  FIG. 1 , a particular embodiment of a smart inhaler device  10  is shown. Inhaler device  10  comprises an outer tube  12  having an inlet  14  at one end and an outlet  16  at an opposing end of inhaler device  10 . Outer tube  12  can comprise a plurality of air inlet perforations  18  through the wall of outer tube  12 . Outer tube  12  serves as a mouth piece, in that a subject places their mouth against or over outlet  16  and inhales, drawing air through air inlet perforations  18  to create an inhalation airflow through the interior of outer tube  12  and into the subject&#39;s lungs. 
     An aerosol stream comprising an active agent is delivered from an aerosol source through an adaptive nozzle  20  and into the inhalation airflow for targeted delivery to a target area of lung of the subject. As shown in  FIG. 1 , adaptive nozzle  20  is positioned within the interior of outer tube  12 . Adaptive nozzle  20  has a nozzle base inlet  22  that sealingly engages outer tube inlet  14  and a nozzle tip outlet  24  that is in axial alignment with outer tube outlet  16 . That is, nozzle tip outlet  24  has a long-axis that is parallel to a long-axis of outer tube  12 , which is perpendicularly bisected by outer tube outlet  16 . 
     Nozzle base inlet  22  can be positioned in flow communication, directly or indirectly, with an aerosol source. Nozzle tip outlet  24  is positioned in proximity to outer tube outlet  16  so that the aerosol stream is optimally merged with the inhalation airflow. 
     A sealing member  26  connects nozzle base inlet  22  with outer tube outlet  16  to provide an airtight seal between outlet  16  and nozzle base inlet  22 . Sealing member  26  can be a flexible polymeric O-ring, which can provide both sealing functionality and flexibility to provide mobility to adaptive nozzle  20  within outer tube  12 . 
     As previously disclosed, the smart inhaler system can increase targeted deposition efficiencies over other inhalers known in the art in part through the controlled delivery of the aerosol stream into the inhalation airflow through calculated positioning of nozzle tip outlet  24  within outer tube  12 . Actuators can be utilized to position adaptive nozzle  20 , and in particular nozzle tip outlet  24 , to the desired optimum release position for delivery of the aerosol into the inhalation airflow. Due to space limitations present in some embodiments of inhaler device  10 , it can be desirable in some embodiments to utilize actuators comprising active materials. Exemplary active materials that can be utilized with the presently disclosed subject matter include, but are not limited to, shape memory alloys, shape memory polymers, magnetostrictive materials, and piezoceramic materials. In some embodiments, when shape memory alloys are employed, an alloy of nickel and titanium (NiTi) can be utilized. As shown in  FIG. 1 , shape memory alloys (SMAs) can be fabricated as wires, such as for example FLEXINOL® wires produced by Dynalloy, Inc. (Costa Mesa, Calif., U.S.A.), and thereby act as SMA actuators. For example, as shown in the particular embodiment illustrated in  FIG. 1 , a plurality of SMA actuators are operationally linked to adaptive nozzle  20  near nozzle base inlet  22  and to the inner wall of outer tube  12 . 
     In the embodiment illustrated in  FIG. 1 , a set of three SMA actuators  30  are utilized (only two of which are visible in  FIG. 1 ) to deflect the entire adapter nozzle  20  to a desired position within outer tube  12 . A second set of SMA actuator wires  32  can further be utilized, as shown in  FIG. 1 , to further flex adaptive nozzle  20 , in combination with repositioning the entire structure of adaptive nozzle  20 , as accomplished by SMA actuators  30 . Actuators  32  can be axially bonded to adaptive nozzle  20  along at least a portion of a long-axis of adaptive nozzle  20  and can therefore bend adaptive nozzle  20  such that nozzle tip outlet  24  remains axially aligned with outer tube outlet  16  to ensure aerosol stream release is parallel to (laminar flow) the inhalation airflow. 
     To prevent premature mixing, wall deposition, or particle coagulation, in some embodiments, adaptive nozzle  20  comprises a flexible material, such as a flexible polymeric material, to permit flexing of adaptive nozzle  20  by actuators  32 . Nozzle  20  should present a reasonable compromise between a certain flexibility to enable the necessary deformation and sufficient stiffness to maintain the required shape in the airflow. One non-limiting example of a suitable elastomeric material for use in the construction of flexible nozzle  20  includes silicon rubber. It can be desirable to provide in some embodiments inner surfaces of adaptive nozzle  20 , and in some instances outer tube  12  as well, with higher finish tolerances in order to avoid problems with wall deposition of aerosol particles and turbulence effects. Alternatively, or in combination, the inner surfaces can be coated with compositions that facilitate reduction of turbulence and/or aerosol deposition, as generally known by those of skill in the art. 
       FIGS. 2A and 2B  illustrate the variable positioning of adaptive nozzle  20  within outer tube  12 .  FIG. 2A  shows adaptive nozzle  20  in its original undeflected state when actuators  30  (not seen in  FIG. 2A) and 32  are turned off.  FIG. 2B  shows adaptive nozzle  20  in a deflected configuration resulting from activation of one or several of actuators  30  (not seen in  FIG. 2B ), resulting in constriction of one or two actuators  30 , which pull adaptive nozzle  20  toward the position of activated actuators  30 . The configuration shown in  FIG. 2B , however, leads to a misalignment of the outlet direction, which is no longer coaxial with outer tube  12 . To compensate for this effect, actuators  32  are activated, e.g., contracted under controlled heating by an electrical current, which then bend adaptive nozzle  20  such that nozzle tip outlet  24  can be aligned again coaxially with the long-axis of outer tube  12 . Thus, this mechanism compensates for the axial misalignment error produced by a deflection of adaptive nozzle  20  and promotes a particle release aligned parallel to the inhalation airflow, thereby avoiding undesirable premature mixing effects and early wall deposition. 
     With reference now to  FIGS. 1 ,  2 A and  2 B, smart inhaler device  10  can comprise in some embodiments an inner tube  40  fitted within the interior of outer tube  12  and slidingly engaging the inner surface wall of outer tube  12 . Inner tube  40  further comprises air inlet perforations  42  that can align with outer tube air inlet perforations  18 . One or more actuators, shown as SMA actuators  44  in  FIG. 1 , are linked to inner tube  40 . When activated SMA actuators  44  can position inner tube  40  such that the alignment of inner tube air inlet perforations  42  are aligned or misaligned to varying degrees with outer tube air inlet perforations  18 . By aligning or misaligning inner tube air inlet perforations  42  with outer tube air inlet perforations  18 , the inlet cross-section for air flowing into outer tube  12  to create the inhalation airflow can be controlled depending on the measured and computational fluid-particle dynamics “CFPD”-predicted set point inhalation waveform. Thus, regardless of the breath pattern of the subject utilizing smart inhaler device  10 , a desired inhalation waveform can be attained. 
     In some embodiments, wherein SMA actuators  44  operate under tension, an external restoring force (not shown) can be utilized to return inner tube  40  to its original position once actuators  44  are turned off. In some embodiments, the external restoring force is supplied by a spring washer, against which the actuators  44  work. 
     In some embodiments the smart inhaler system comprises inhaler device  10  in flow communication with an aerosol injection system, which in turn is in flow communication with an aerosol source. In some embodiments, and as illustrated in  FIG. 3 , the aerosol injection system can comprise a controllable reservoir chamber  50 . In some embodiments, controllable reservoir chamber  50 , through a system of microsized pressure sensors, such as for example similar pressure sensors as utilized to measure the inhalation waveform, and valves, allows for the transformation of each aerosol source&#39;s input into a unified controlled state. The aerosol suspension is then directed through adaptive nozzle  20  at nozzle base inlet  22  and out through nozzle tip outlet  24 , where the aerosol stream is injected into the inhalation airflow flowing through the interior of outer tube  12 . For example, in some embodiments a microvalve (e.g., a microvalve available from TiNi Alloy, Inc., San Liandro, Calif., U.S.A.) can be incorporated into controllable reservoir  50 . In some embodiments the microvalve uses a thin film SMA actuator. 
     In some embodiments, an inlet microvalve is placed directly at a reservoir inlet, where it controls entry of the aerosol from the aerosol source into controllable reservoir chamber  50 . A pressure sensor that measures pressure within controllable reservoir chamber  50  is also placed within active reservoir chamber  50 . Depending on the pressure measured by the sensor, reservoir chamber  50  can include an outlet microvalve as well that can open an outlet of active reservoir chamber  50 , which connects with nozzle base inlet  22 , to maintain the level necessary for optimal aerosol injection into the inhalation airflow. 
     In some embodiments, the presently disclosed smart inhaler system comprises a control logic that interlinks sensor signals with the corresponding actuator outputs. In some embodiments, for example, as can be seen in  FIG. 4 , a signal  62  from one or more micropressure sensors  60  is transmitted to control logic  64  which interprets signal  62  and transmits an actuator control signal  66  to one or more inner tube actuators  68  which vary the position of inner tube  40  to change the alignment of inner tube air inlet perforations  42  with outer tube air inlet perforations  18 , thereby altering the inhalation waveform. In some embodiments, control logic  64  responds to signals not only from the micropressure sensors measuring inhalation waveforms, but also from signals  70  originating either from strain gauges or actuators  68  themselves measuring nozzle or inner tube positioning. For example, SMA actuators, due to changes in resistivity, can also act as sensors, and therefore these data can be used to determine adaptive nozzle  20  and inner tube  40  positions before and after actuator changes. 
     Further, control logic algorithm  64  can be in operational communication with a computer model for fluid particle flow  72 , which provides computational fluid-particle dynamics results that determine one or more of the desired inhalation waveforms and the desired position of adaptive nozzle  20  and therefore prescribes the desired actuator set points to direct the active agent to the target area of the lung of the subject. In some embodiments, the control approach is based on a standard proportional-integral-derivative (PID) algorithm. One of ordinary skill in the art would recognize that other algorithms can be suitable for use with the presently disclosed subject matter, upon a review of the same. 
     The presently disclosed smart inhaler system through its modular structure can be used in a number of different applications. Such applications include clinical applications, wherein the presently disclosed inhaler system can be integrated into stationary systems. The presently disclosed inhaler system also can be employed for personal use, such as for use in portable asthma systems, for example, when combined with a microprocessor. Such inhaler systems for personal use are feasible through the miniaturization enabled by the use of shape memory alloys. 
     EXAMPLES 
     The following Examples have been included to illustrate modes of the presently disclosed subject matter. In light of the present disclosure and the general level of skill in the art, those of skill will appreciate that the following Examples are intended to be exemplary only and that numerous changes, modifications, and alterations can be employed without departing from the scope of the presently disclosed subject matter. 
     Disclosed herein are methods and systems for providing “controlled air-particle streams” where most of the drug aerosols reach the desired lung target area (e.g., 45%-92%) based on simulations relying on computational fluid-particle dynamics (CFPD) techniques. The methods and systems were successfully tested for microparticle targeting on a hemispherical tumor located in the third lung generation, using a validated computer simulation model including consideration of optimal particle characteristics, mouth release position, and air/particle velocities (see, for example, Kleinstreuer &amp; Zhang, 2003). Further testing and validation in physical models utilizing embodiments of the smart inhaler system are disclosed in the Examples following. 
     In brief, a suitable physical replica of the upper portion of a human respiratory system is designed and built, and then the smart inhaler&#39;s ability to target specific regions of the lung for particle deposition is quantitatively measured. Although there is variability in exact lung morphology from person to person (based on gender, age, size, etc.) the models built can be representative of a typical lung morphology. The advantage of a tightly coupled computational/experimental approach is that controlled and reproducible experiments can be used to validate the computational models. The computational models can then be used in further assessments to explore the effects of lung morphology variations on particle trajectories and deposition, together with clinical testing. 
     The lung replica and smart inhaler components are combined to show that individual branches of the simplified lung replica can be targeted. The computer prediction model is used to determine the aerosol release position and inlet flow conditions, the nozzle system is used to adjust to the predicted position, and a laser detection system measures aerosol concentration in each of the individual outlets to verify the ability to target individual branches in agreement with the model predictions. 
     The local deposition efficiency is also validated. To this end, the focus can be on one particular branch of the system, in which an artificial tumor of varying size is placed. The aerosol deposition on the artificial tumor is then predicted and measured. 
     Example 1 
     Model Smart Inhaler System Utilizing SMA Actuation 
     The results of the CFPD simulations described herein illustrate the importance of particle characteristics, the location of particle release, and controlled inhalation waveform. Starting with the concept of optimal particle release position, it has been combined with the advantages offered by shape memory alloys (SMA) as disclosed herein in order to design a smart inhaler device. The particle release at a controlled position is enabled in some embodiments by a shape memory actuated flexible adaptive nozzle.  FIGS. 1 ,  2 A and  2 B illustrate the concept of the design, showing the nozzle, which can be deflected by three SMA wires in order to move the nozzle tip to an arbitrary position in the outer tube outlet cross section. The nozzle base is connected to the outer tube by an O-ring, providing sealing functionality and flexibility at the same time. A second set of SMA wires is incorporated into the nozzle and aligned along its long axis. This set of wires can bend the nozzle when contracted under controlled heating by an electric current, and can thus compensate for the axial misalignment error produced by the nozzle tip deflection. This combination assures an aligned particle release, avoiding undesirable mixing effects in this phase of the process. 
     A third set of SMA wires moves the perforated inner tube with respect to the fixed outer tube in order to adjust the inlet breath air. This part of the system can be used to control the inlet air. 
     The design of the adaptive nozzle, is facilitated by extensive simulation in order to determine suitable geometry, stiffness, and in particular, optimal actuator placement. A very efficient SMA model has been developed, which includes an energy balance for full thermo-mechanical coupling, and therefore is particularly suited for the description of SMA actuators. The model has been further extended to apply to other active materials actuators like piezoceramics (Smith et al., 2003) and magnetostrictives (Smith et al., 2003) as well. The model provides guidance for real-time optimal control for SMA actuators. (Mueller &amp; Achenbach, 1985; Mueller &amp; Achenbach, 1989; Seelecke, 1999; Seelecke &amp; Papenfuss, 1999; Seelecke et al. 2001). 
     For the purpose of structural simulation, a finite element formulation of this model has been developed and successfully implemented into the commercial finite element code ANSYS (Seelecke &amp; Papenfuss, 2000, Frautschi &amp; Seelecke, 2003). Although there is a relatively small number of other FE implementations of SMA models published in the art, these are purely isothermal, focusing on the reproduction of uncontrolled processes and thus do not allow to simulate the behavior of a structure with a SMA actuator. An overview of simulation and controls aspects of SMA actuators in smart systems is disclosed in the review article of Seelecke &amp; Mueller (2004), which is incorporated herein by reference in its entirety. 
     To guide the design process, a series of finite element simulations can be performed. ANSYS can be used as a platform, which allows for geometry import from the 3D solid modeling program used for the smart inhaler system design. The adaptive nozzle can be modeled by appropriate shell elements, and for the SMA wires the FE implementation of a version of the Mueller-Achenbach model can be used. This combination allows for a realistic determination of the time-dependent nozzle deflection together with the necessary forces and related energy consumption. 
     The open loop behavior of several embodiments of the adaptive nozzle can also be investigated. Specifically, the (x,y)-displacement of the nozzle tip in the plane of the outer tube outlet cross section can be measured. Non-contact laser sensors and camera-based methods can be utilized for this purpose. The above measurements can be performed on different embodiments of the adaptive nozzle in order to provide feedback for improvement of both simulations and prototype building. 
     Further, the sensor capabilities of the SMA materials can be investigated at the same time. In addition to the actuator properties due to the temperature-induced contraction, the SMA wires also exhibit a change in electrical resistivity (see  FIG. 5B ). This can be used for sensing purposes, making the material truly multi-functional. A plot of deformation vs. resistivity reveals that the hysteresis can be eliminated, yielding a unique relation between stroke and resistivity. See  FIG. 5C . This feature has received relatively little attention in the art so far except for, e.g., Pitschellis (1998), but it is inherently attractive for the simple reason that there is no need for an additional sensor to determine nozzle and inner tube positions. This becomes particularly important as the non-contact sensors used for initial evaluation can be too big to be incorporated in a miniature system, and other types of devices introduce additional complexity. 
     A device was constructed to develop and verify the algorithms disclosed herein. It comprises an electrically driven SMA wire connected to an elastic cantilevered steel beam. The device can be filled with a fluid in order to achieve higher frequencies due to the improved cooling. 
     Example 2 
     Verification of CFPD Predictions and Smart Inhaler System 
     The experimental model of the human respiratory system utilized for laboratory testing of the smart inhaler system can include highly detailed oral airways, pharynx, larynx, and trachea for verification of the CFPD predictions and smart inhaler. The flow from the trachea can be divided, non-equally, into the left (˜40%) and right (˜60%) primary bronchi. Attached to the right primary bronchus can be a four-generation planar upper bronchi section or a fully three-dimensional upper bronchi section. This laboratory model permits the measurement of flow characteristics and particle depositions. 
     To accurately simulate various modes of breathing, a sophisticated airflow delivery system can be constructed to generate a wide range of inhalation profiles, permitting the investigation of profiles from rest breathing to hypernea. In the following sections, the three different sections of the laboratory lung model are described in detail, followed by a description of the existing airflow delivery system. A brief overview of the diagnostic tools to be employed for the measurement of velocity profiles and particle depositions is also included. 
     The experimental investigations can be tightly coupled with the computations and development of the smart inhaler. An objective of the experimental measurements is to confirm the ability of the smart inhaler to control the trajectory, and hence the deposition location of the drug aerosols. One exemplary measurement of significance in the present Example is the particle flux through each of the sixteen bronchi exits. Particle flux measurements can be used to validate the computational code. Once the computational code is validated for various breathing modes, without the smart inhaler, the inhaler can be added to the geometry. Using the CFD code to guide the smart inhaler deflection, particle flux measurements can be made to validate the smart inhaler&#39;s ability to control the placement of pharmaceutical agents. 
     Construction of an Airflow and Microparticle Delivery System. 
     Supplying the smart inhaler, and hence the human upper airways, is a precisely regulated and filtered airflow system. The upper bronchi models can be incased in an air-tight vessel, upon which a vacuum can be pulled. A calibrated mass flow meter can be used to control the airflow rate into the oral and/or nasal cavity, nominally 10 to 60 standard liters per minute. Between the air tight vessel and the mass flow meters, the airflow can enter into a large plenum. Mounted on two sides of this plenum are large-diameter, solid-cone loudspeakers that are driven by an amplified frequency generator. The loudspeakers act as pistons, and the resulting boundary movement causes a variation in the conducting zone inlet flow rate. 
     Thus, an average mass flux can be maintained with a prescribed oscillation superimposed upon the flow to simulate the time-dependant nature of actual inhalation modes, e.g., normal, pathological, light and heavy exercise. This oscillation has been shown to affect particle deposition in the airway (Finlay and Gehmlich, 2000). A high wattage, solid cone loudspeaker driven with a reasonable amplifier is sufficient to mimic the 3-5 mm Hg intrapulmonary pressure experienced in the lungs. 
     To better simulate human breathing, a voltage-time profile can be generated on a PC supplied to the loudspeakers via an analog I/O board and linear amplifier. Using a PC with LABVIEW® software (National Instruments Corp, Austin, Tex., U.S.A.), virtually any breathing mode can be simulated. If the loud speakers are not sufficient to generate desired, a linear motor with feedback control can be utilized instead. Loud speakers are capable of developing small pressure differentials, whereas a linear motor is capable of generating 100 kPa of pressure, with millisecond time response. 
     Construction of Human Airways Replica and Airflow Measurement. 
     Based on the measured geometric shape of the human oral/nasal passage from actual castings of adult human airways (Cheng et al., 1999), a rigid passageway can be constructed of plexiglass cross-sections, which mimics the actual upper conducting zone very accurately. By seeding the inlet airflow with monodispersed particles, particle-size-dependant fluxes throughout the upper conducting zone can be measured. Constructing the Inlet to Trachea Outlet submodel of stacked cross-sectional pieces allows the model to be sectionalized and permit the exit velocity profile to be measured at any location in the submodel by removing the downstream sections (this can be done via Particle Image Velocimetry and used to validate the computational code). This can allow proper velocity field characterization at three (or more) locations: the entrance to the pharynx; the entrance to the larynx; and the exit of the upper trachea. 
     By using a planar velocity measurement technique that is able to collect the entire flow field instantaneously, time resolved velocity measurements can be made as a function of the temporal location within the prescribed inhalation mode. Particle flux measurements can also be made simultaneously with the velocity measurements. By assuring a uniform particle seeding density at the inlet to this submodel, particle flux measurements downstream of the inlet can provide information on the particle dynamics and transport through the airways of the upper conducting zone. 
     If the particles inhaled are not monodisperse, which is true of all real therapeutic drug aerosols, then it can be desirable to understand the possible effects of particle size on transport through the mouth, larynx, and trachea and into the lung. 
     To model this effect accurately, experimental validation of computational codes can be performed. This Mouth-Trachea submodel can be an ideal code validation tool. Monodisperse particle densities can be determined at the same time that the velocity field is measured, using particle image velocimetry (PIV). However, to measure the density of a polydisperse particle field, particle sizing must be done. This can be accomplished with point measurements using a laser scattering interferometer. The entire field does not need to be mapped; the regions of particular interest can be identified from the planar particle density measurements obtained from the PIV measurements. 
     Additional submodels utilized can be experimental devices that allow the measurement of particle fluxes through the bronchi. An upper bronchi model can be planar in geometry with symmetric bifurcations, corresponding to the Weibel distributions. A fully three-dimensional lung model that contains four generations of bifurcations after the first split between right and left primary bronchus can also be constructed. The right primary bronchus can be developed into the subsequent generations due to its larger volumetric flow rate and the fact that particle deposition is more likely in this bronchus due to its more vertical position. The left primary bronchus and the sixteen bronchi outlets can each be exposed to the sub-atmospheric pressures generated in the air-tight volume. 
     The planar symmetric model can be constructed with glass tubes, allowing visualization of particle deposition. The diameter of each tube throughout the four generations can be based on the measurements of Weibel (1963). The initial diameter, representing the trachea, can be 18 mm, with an unsymmetrical initial bifurcation into the left and right primary bronchus. The right primary bronchus can have a diameter of 12.2 mm. All succeeding bifurcations can be symmetric, with a final tube diameter of 3.5 mm. 
     The more realistic upper bronchi model can be fully three-dimensional and asymmetric. Out-of-plane effects can be quantifiable by varying the degree of departure from two-dimensional in the various generations. 
     Diagnostic Tools to be Employed. 
     Particle Image Velocimetry (PIV) is a planar velocity measurement technique that provides nearly instantaneous velocity fields. The technique employs multiple scatterings of laser light off seed particles. In one PIV technique, the second harmonic radiation (532 nm) from a pair of Nd:YAG lasers is formed into sheets of light which are overlapped in space and offset in time by an adjustable amount. The two Nd:YAG lasers are housed in a single laser head, facilitating alignment. Each Nd:YAG laser is capable of producing 25 millijoule (mJ) in the green in a 8 nanosecond (ns) pulse. The scattered laser light is captured on a Kodak large array (1K by 1K) digital interline transfer camera, specifically designed for PIV measurements. With this experimental setup, the first laser pulse scatters light off seeded hollow spheres and is captured by the digital camera located normal to the sheet. The camera stores this image on the chip and then captures the second laser pulse, which is delayed from a few to a few hundred microseconds, depending upon the mean velocity. The image pair is then downloaded and a cross correlation technique is used to match up particle pairs, which then yield velocity vectors. The advantage of PIV over other velocity measurement techniques is that it measures the entire planar velocity field nearly instantaneously. The advantage of this particular experimental setup is that there is no velocity ambiguity and stagnation flows are resolvable. 
     The particle flux measurements can be made by Mie scattering laser light off the particles as they exit the bronchi tube. This scattered light can be collected via a lens-coupled photomultiplier tube. The intensity of the scattered light can be a quantitative measure of the number of particles passing through the laser probe volume. This is a time resolved measurement and allows the particle flux to be measured throughout the inhalation cycle. This quantitative information can provide validation of the computational code. 
     Example 3 
     Computational Fluid-Particle Dynamics (CFPD) Simulations of the Human Respiratory System and Smart Inhaler Outer Tube Outlet Conditions 
     One goal of the CFPD analysis is to provide particle characteristics and air-particle flow data sets which lead to a smart inhaler system for substantially maximum drug delivery. This can be facilitated by the accurate simulation of air-particle flow in representative human airway models. With the experimentally validated computer simulation model, optimal inhaler outlet conditions equal to the desired mouth inlet conditions can be determined for both the laboratory replica and representative upper airway configurations. The fluid-particle dynamics inside the inhaler system, including possible aerosol deposition, can be more effectively visualized and measured, via a segmental mass balance, in the laboratory. 
     Airflow and Airway Wall Structure Equations. 
     In order to capture the isothermal airflow pattern in realistic upper lung airways and to check for possibly transitional airflow, i.e., the laminar-to-turbulent flow regimes, the low-Reynolds-number (LRN) k-ω model of Wilcox (1998) has been selected and adapted. It has been demonstrated that the modified LRN k-ω model is appropriate for such internal flows (Zhang &amp; Kleinstreuer, 2003a). All air transport equations, including the heat transfer equation, as well as initial and boundary conditions are given in Zhang &amp; Kleinstreuer (2003a, b) and Kleinstreuer &amp; Zhang (2003), each of which is incorporated by reference herein in their entireties. 
     As part of these Examples, different types of inhalation conditions, especially particle size, particle density, particle release position, and inhalation waveform, can be considered. The laboratory airway replicas including oral cavity, pharynx, larynx and tracheobronchial airways, as provided herein, can be used to generate meshes for the air-particle flow simulations. In addition three different airway cast models can be selected to give information to investigate inter-subject variations. The boundary conditions for different surface and wall configurations, e.g., roughness effects, cartilageous rings, mucus film etc., including constant or variable temperature conditions (cf. Daviskas et al., 1990; Morris, 1988; among others) can be implemented. The optimal fluid-particle stream and maximum aerosol deposition analyses can provide the actual inhaler air-particle exit conditions and can be used in the laboratory as mouth inlet conditions. 
     The airway wall structure equations utilized are the standard conditions of equilibrium, stress-strain relations, and conditions of compatibility (see, for example, Ugural &amp; Fenster, 1995 or Fung, 1994). Wall material properties and airway expansion measurements are given in Fung (1981) and Kamm (1999). Computational fluid-structure interaction simulations can be readily implemented. 
     See Zhang et al. (J. Aerosol Science (2005), vol. 36, pp. 211-233) for governing transport equations, boundary conditions, and solution procedure, including computer model validations. 
     The numerical solutions of the continuity, momentum, and turbulence transport equations, along with scalar advection equations can be carried out with a parallelized finite-volume based code (CFPD code), which was developed especially for laminar-transitional-turbulent flows in bio-fluid applications. The numerical program uses a structured, multiblock, body-fitted coordinate discretization scheme. The complex meshes are generated with GRIDPRO® (PDC, White Plains, N.Y., U.S.A.). High-resolution upwinding techniques can be used to model the advective terms of the transport equations. To achieve higher-order spatial accuracy, interface flux reconstruction can be performed using either second order total variation—diminishing (TVD) or third order (fifth order in smooth regions) weighted essentially non-oscillatory (WENO) interpolations of the solution variables. Any inhalation waveform can be accommodated, including aerosol inhaler outlet conditions. 
     The particle transport equations can be solved with an off-line F90 code with parallelized algorithms (Longest et al., 2004). 
     Airway Geometries. 
     The airway geometries can include the oral cavity, pharynx, larynx, trachea, and 13 generations of bronchi (G 0 -G 12 ). Comparisons of the deposition efficiencies between the numerical simulations and experimental observations (i.e., mouth to G- 9 ) can be made to verify the computer model. Once the validity of the numerical technique is established, the numerical simulation of the conducting airway can be extended to generation  12  (G 12 ), considering both symmetric Weibel configurations for ease of model validation and international data transfer as well as asymmetric configurations as tabulated by Raabe et al. (1976), Horsefield et al. (1971), and Ley et al. (2002), among others. Geometric variations can also be included for double and triple bifurcations (cf. Corner et al., 2001 a, b; Zhang &amp; Kleinstreuer, 2002; Zhang et al., 2001). 
     Additional airway features to be considered include cartilaginous rings, especially in the trachea, shape and openings of vocal folds, and movement of liquid (mucus) layers. The simulations of airflow and particle deposition in parallel and series with triple-bifurcation unit are proposed to consider as completely as possible the geometric effects due to intra- and inter-subject variability, particle characteristics as well as inlet conditions obtained from the exit of inhalers or the upstream airway units. Clearly, particles which make it past G 12  deposit either in the alveolar region or are being exhaled. 
     Determination of Optimal Inhaler Outlet Conditions. 
     Appropriate particle-release locations and timing, suitable particle characteristics, and an ideal inhalation waveform can transport drug aerosols, on a case-by-case basis, to desired lung target areas.  FIG. 6  shows the present methodology in virtual reality for normal vs. controlled micro-particle releases from Generation  3  and the mouth via a back-tracking method (disclosed in detail hereinbelow). Specifically, in selecting micro-particles, i.e., 5≦d p ≦7 μm, and strictly laminar flow, quasi-deterministic particle trajectories can be achieved; hence, airway landing area and particle release position at the aerosol delivery entrance correlated directly. 
       FIG. 6  (top) shows the example of a tumor located in generation G 2 , which under currently used, uncontrolled inhalation conditions (homogenized throughout mouth inlet cross section) receives only a minute fraction of the inhaled aerosol. Utilizing the presently disclosed computations for targeted delivery, it is shown that as a result of a localized particle release within the mouth inlet cross section a) the undesired particle deposition along the airway walls is basically eliminated, and b) the fraction of particles depositing on the tumor is drastically increased ( FIG. 6 , bottom). 
     In reality, variations in lung morphology, breathing mode, particle size, and specific lung target area for drug aerosol deposition complicate the task of achieving a controlled air-particle stream which results in optimal drug aerosol deposition. These variations can be addressed, at least in part, by considering the following exemplary criteria: 
     (a) broadening the particle release area; 
     (b) selecting the best particle characteristics; and 
     (c) determining an optimal inhalation waveform. 
     In order to accommodate different airway geometries, e.g., children, adults, the elderly, and to be able to target different desirable lung areas, the mouthpiece cross section (outer tube outlet) can be, for example, divided into eight particle release sections that allow for targeting of, for example, G 3 -G 6  or G 9 -G 12  independently (see  FIG. 7 ). Alternatively, or in combination, “critical radii” can be utilized, as disclosed hereinbelow, to position aerosol stream release. The back-tracking methodology as well as trial and error runs can match the optimal release segment with maximum deposition in the predetermined target region. Some well-defined particle release areas (see  FIG. 7 , striped regions) can be always excluded because aerosols from such locations deposit typically in the oral airway. 
     To address (b), the correct effective diameter and density of (probably solid spherical) micro-particles can be determined to achieve the goal of maximum drug aerosol deposition. 
     Regarding (c), any active or passive inhalation waveform generated by a patient or an existing device (pMDI, DPI, or SMI) can be modified. Specifically, a laminar flow, Q in ≦15 L/min, and a rectangular, i.e., uniform) inhalation waveform can be objectives to generate the highest deposition results. 
     In summary, the exit conditions of a smart inhaler system can be determined, which, for example, could be attached to off-the-shelf inhalers. A smart inhaler system disclosed herein can ultimately: (i) modify a given waveform (or air stream) to an ideal, e.g., uniform and strictly laminar, waveform, and (ii) direct and concentrate the drug aerosol stream to the test release section ( FIGS. 6 and 7 ) in order to achieve maximum deposition in the desired lung target area. 
     Example 4 
     Demonstrated Targeted Delivery of Particles Utilizing The Smart Inhaler System 
     An objective of the present Example is to fabricate a smart inhaler system disclosed herein and to set up an experimental facility to validate in the laboratory the computer simulations. For this purpose, a replica of the human lung, comprising a glass model, which starts from the oral airways, and continues all the way to the fifth generation lung structure was constructed. The smart inhaler system was implemented into this glass model, and laser-based Mie scattering imagery was used to visualize the particles at various outlets. 
     In the first phase of the present Example, attention was confined to the steady case, where a continuous air stream was directed through a “lung box”, to which various components of a glass model of the airway system can be attached. In order to track the potential dispersion of injected particles with the travel distance, several straight glass tubes of various lengths were used (5 cm, 15 cm, and 20 cm), along with a 90-degree-bend and a 1:1 model of the human oral airway system. Particles are injected initially through a small seeding tube in the outlet cross-section of the lung box. The tube can be placed at any desired or arbitrary position in the cross section. 
     A laser sheet is then formed at the outlet cross-section of the various components, and Mie scattering provides an instantaneous image of the particle locations. The above system was used initially to optimize the set up of the laser system and image acquisition, along with the seeding system for the particles. Initially, spherical particles obtained from the burning of incense with a nominal diameter of 0.6 μm used. A new seeding system, yielding a wide range of sizes and distributions can be used to accurately simulate a wide variety of pharmaceutical agents. For example, polystyrene spheres of various diameters can be utilized. 
     In a second phase of the present Example, the initial seeding system was then replaced by a nozzle injector, which had been fabricated using rapid prototyping technology. This first nozzle generation features a static, yet deformed shape, such that the outlet cross section is off-center. Rotation of the nozzle allows adjusting to several different release locations along the perimeter of a circle. Results of the computer-modeling simulations and laboratory experiments are disclosed as follows. 
     Laboratory Experiments 
     The first objective is to show that particles do not disperse over the entire airway cross section, but rather stay confined so that they can potentially be directed to desired deposition areas. The second objective is to show that variations in the release position have a deterministic effect on the trajectory of these particles such that their deposition area can in effect be predicted. 
     For this purpose, stationary experiments were performed at various airflow rates ranging from 40 standard liters per minute (slpm) down to 8 slpm. The injection of the particles was velocity matched to this co-flow to minimize the effect of shear layers, which are expected to lead to premature dispersion. At higher flow rates, transition to turbulent flow can occur which also leads to undesired dispersion. 
     For each flow rate the particle behavior was studied for a variety of glass pipes of different length in order to document the amount of dispersion as a function of the travel distance. A portion of the large body of results are disclosed below. 
     When particle injection occurs at a “top” region of the inlet cross section for an air flow rate of 12 slpm, after 20 cm through a straight pipe, the particles are still very close together, and almost no dispersion was observed. After a 90-degree bend, the particles were slightly driven to the outside due to the action of centrifugal forces, but they were still very coherent. After the particles had traveled roughly 40 cm and passed several cross-section variations, a flattened shape was observed. However, it is noteworthy that the particles were still coherent and had not dispersed over the cross-section at all. 
     The flow rate of 12 slpm also represents the case where the peak Reynolds number exceeds the value of 1800 in the larynx, potentially causing transition to turbulent flow in the trachea. 
     A similar trend was observed for the case of release at a “bottom” region of the inlet cross-section. Here, the particles stayed even closer together. It is worth noting that it was possible to not only prevent dispersion of particles, but importantly, to also control the trajectory of the particles even over great distances downstream through the choice of release location. 
     Computer-Modeling Simulations 
     The results from the laboratory experiments confirmed the general feasibility of the method. Further implementations can utilize predictions from numerical simulations to increase the accuracy of targeted-delivery. Exemplary calculations were run with the CFD code CFX-4 and an in-house particle tracking code, and results for the 8 slpm case are disclosed below. 
     The comparisons between the simulated and measured particle distributions with different inlet release positions for the oral airway model are shown in  FIGS. 8 and 9 , assuming a steady inspiratory flow rate of 8 slpm and a spherical particle diameter of 1 μm. 1000 particles were released at the oral inlet. In a comparison of the simulated results for top and bottom release shown in  FIGS. 8B and 9B , respectively, with the experimental results for top and bottom release shown in  FIGS. 8D and 9D , respectively, the simulated particle distributions agree well with the experimental visualizations. 
     This effect becomes even clearer for the case of the oral airway model with the first bifurcation attached to it (B 1  of  FIG. 11 ).  FIGS. 10A-10C  compare three cases, which differ only by the angular position of the nozzle in the mouth inlet cross section ( FIG. 10A ). In the left column of  FIGS. 10A-10C , particles are released at an angle of 60° with the vertical and occur exclusively in the left branch of the first bifurcation as seen in  FIG. 10B , while the right column (release at 240°) shows the opposite result as seen in  FIG. 10C . The center column documents that this behavior can be finely controlled to the degree that a fraction of the particles occurs in each branch ( FIGS. 10B and 10C ). 
     Minor discrepancies may be attributed to: (i) slight differences in inlet release positions between the simulations and experiments; (ii) differences in visualization locations; (iii) differences in the geometries (for example, there is a transition tube in the experimental setup and the airway geometry becomes slightly different after manufacturing); and (iv) the difference in particle size, i.e., particle distributions are sensitive to factors (i) and (ii). 
     Conclusions 
     The above results provide convincing evidence that:
         1. Particle dispersion can be avoided for laminar flow conditions; and   2. Particle trajectories, and consequently, deposition at targeted sites in the airway system can be controlled by appropriately choosing the aerosol release location.       

     It is further important to note that the two documented release locations termed “top” and “bottom” have received their names because of the specific orientation of the oral airway system, which is positioned in the horizontal plane in order to simplify the imaging system set up. In a real human lung, however, these would be left and right hand side, respectively, and, hence, the above experiments have also shown that it is clearly possible to target right and left lobe of the lung separately. 
     Additionally, it can be seen from the results that, as a by-product of the controlled air-particle stream release, wall deposition in the critical oral airway region has been virtually eliminated. This feature can considerably improve targeted deposition efficiency and reduce significantly potential side effects. 
     In summary, this Example illustrates the capabilities of the smart inhaler system to enable targeted treating of lung cancer as well as a number of other respiratory diseases. A number of additional therapeutic applications, such as insulin for diabetics, inflammation treatments, blood disorders, pain management, chemotherapy, gene manipulation, etc. are also possible utilizing the presently disclosed smart inhaler system. 
     Example 5 
     Drug-Aerosol Release Points From Orbits of Critical Radii 
     As confirmed by experimental visualizations disclosed hereinabove, micro-particle trajectories can be tracked and are controllable under laminar flow conditions. Thus, given suitable air-inhalation waveforms, particle characteristics and particle release positions, the therapeutic aerosols inhaled via a smart inhaler system can reach the targeted lung areas at large mass fractions to effectively combat different diseases. In turn, deposition of aggressive drugs on healthy lung tissue is avoided. 
     The adaptive nozzle disclosed herein has thus far been utilized in the above Examples to target particle release. In an alternative embodiment, the concept of “orbital point release with critical radii” is introduced and tested with CFPD simulations in the present Example. It is noted, however, that although the orbital point release methodology can be implemented utilizing targeted-release mechanisms other than the adaptive nozzle disclosed herein, the presently disclosed subject matter is not intended to be limited thus, but rather the present subject matter specifically includes implementing the orbital point release methodology utilizing the presently disclosed adaptive nozzle as well as other targeted-delivery mechanisms. 
     Airway Geometries 
     An upper airway model (see  FIGS. 11A and 11B ) comprising an oral airway cast replica and Weibel Type A triple-bifurcation lung airways, representing generations G 0  (trachea) to G 3 , was employed to investigate the inhalation and transport of drug aerosols. 
     Numerical Method 
     The airflow and particle transport were simulated with a commercial finite-volume code CFX4 (ANSYS, Inc., Canonsburg, Pa., U.S.A.) and an in-house off-line F90 particle trajectory code. The computations were conducted on an IBM p575 machine with multiple POWER5® processors (IBM, Armonk, N.Y., U.S.A.). 
     Model Validations 
     The comparisons between the simulated and measured particle distributions with different inlet release positions for the oral airway model were utilized as disclosed in detail in Example 4 and shown in  FIGS. 8-10 . Additional computer model validations and relevant applications can be found in Kleinstreuer &amp; Zhang (2003) as well as Zhang et al. (2002f, 2005), each of which is incorporated herein by reference in their entireties. 
     Back-tracking and Particle Release Positions 
     The specific inlet positions of aerosols which land on different targeted sites are determined via “back-tracking,” and then release-controlled air-particle streams are generated so that most aerosols deposit in the desired lung regions, e.g., inflamed left or right lower airways, etc. 
     Release positions of particles deposited in the upper airways as well as those which exit airways of generation G 3  vary depending in part on particle diameter (d p ). Simulations were run with Q in =8 L/min and d p =7, 10, or 20 μm. The depositions of particles with d p =7 and 10 μm are minor in the upper airways due to relatively low inertial impaction. Most of them can enter the deeper lung regions. In general, particles released from the left and right sides of the circular mouth entrance enter the left and right lungs, respectively. However, the inlet positions of particles leaving different portions of G 3  vary irregularly due to the effects of secondary flows. 
     If the targeted regions are located in the upper airways, larger-size particles (e.g., 20 μm) can be employed to enhance the deposition when utilizing a low inhalation flow rate (e.g., 8 L/min). 
     Release from Orbits with Critical Radii 
     It has been determined, as disclosed herein, that particles released from different fixed regions can enter different parts of the lower airways (i.e., after G 3 ). Targeting can be achieved by calculated positioning and aligning an adaptive nozzle disclosed herein in the inhalation tube for different patients and diseases. Positioning can be potentially simplified by calculated particle release from orbital points, i.e., from circles with critical radii. In this case, a tube-aligned nozzle with adjustable outlet diameters can rotate following the predetermined orbit of a critical radius (see  FIG. 12 ). The nozzle can be positioned at a specific angle (or orbit location) so that most of the released particles can reach the desired areas. 
     As an example, the targeted regions for inlet-release positions  1  to  4 , as shown in  FIG. 12 , are the four outlets in the lower airways after generation G 3  (see Table 1 and  FIG. 13 ). Particles leaving from G 31  and G 34  may enter side and central parts of the left lung, respectively, while they transport into side and central portions of the right lung after exiting from G 35  and G 38  (see  FIG. 11 ). Specifically, with the controlled inlet points, the capture efficiency of particle deposition in the targeted areas can increase from about 10% to 60%-100% (see Table 1). 
     Distributions of particles entering targeted (outlet) airways are depicted in  FIG. 13 . Some particle dispersion occurs for Inlet Positions  2  to  4  because of the influence of secondary flows. In contrast, Inlet Position  1  is located in a larger particle release area, reaching the G 31  airway outlet without any local dispersion. Dispersion can further be decreased when using drug aerosols with attractive surface charges/properties. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Regional Percentage of Inhaled Aerosols (%) 
               
               
                 (Q in  = 8 L/min, d p  = 7 μm) 
               
            
           
           
               
               
               
            
               
                   
                 Controlled Inlets 
                   
               
               
                   
                 Positions 
               
            
           
           
               
               
               
               
               
            
               
                   
                 1 
                 2 
                 3 
                 4 
               
            
           
           
               
               
               
            
               
                   
                 Targeted area 
                   
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                   
                 Normal 
                 G31 
                 G34 
                 G35 
                 G38 
               
               
                   
                 Region 
                 Inlet 
                 outlet 
                 outlet 
                 outlet 
                 outlet 
               
               
                   
                   
               
            
           
           
               
               
               
               
               
               
               
            
               
                   
                 Deposition 
                 2.23 
                  0 
                  0.22 
                 2.09 
                 0.08 
               
               
                   
                 in the oral 
               
               
                   
                 and G0-3 
               
               
                   
                 Exit G31 
                 12.36 
                 100 
                 — 
                 — 
                 — 
               
               
                   
                 Exit G32 
                 14.29 
                 — 
                 — 
                 — 
                 — 
               
               
                   
                 Exit G33 
                 12.48 
                 — 
                 35.63 
                 — 
                 — 
               
               
                   
                 Exit G34 
                 8.93 
                 — 
                 64.15 
                 — 
                 — 
               
               
                   
                 Exit G35 
                 13.23 
                 — 
                 — 
                 89.51  
                 0.81 
               
               
                   
                 Exit G36 
                 14.75 
                 — 
                 — 
                 8.38 
                 — 
               
               
                   
                 Exit G37 
                 11.85 
                 — 
                 — 
                 0.02 
                 — 
               
               
                   
                 Exit G38 
                 9.88 
                 — 
                 — 
                 — 
                 99.11  
               
               
                   
                   
               
            
           
         
       
     
     Nozzle Positioning 
     As disclosed herein, a specific disease, lung tumor location, and/or suitable treatment determine the desired lung target site or region. Some of these predetermined deposition areas can be reached as demonstrated in  FIG. 13  and Table 1. Implementation can be achieved as follows. 
     A nozzle with variable exit diameter and substantially, or in some cases, perfectly parallel to the inhaler-tube wall rotates and arrests on selected orbits and at orbital points (see  FIG. 13 , for example). Changes in nozzle exit diameter and orbital positioning can be implemented via various mechanisms. Examples for varying the nozzle exit diameter include SMA ring-wire control near the flexible nozzle tip or mechanical (camera-like) nozzle aperture changes. Examples for orbital positioning include ball-and-spring-loaded disk/ratchet or a precision-gear mechanism. Different radial settings achieve target-specific orbits. 
     REFERENCES 
     The references listed below, as well as all references cited in the specification, are incorporated herein by reference to the extent that they supplement, explain, provide a background for, or teach methodology, techniques, and/or compositions employed herein.
     Achenbach M and Müller I (1985). Simulation of material behavior of alloys with shape memory. Arch Mech, 37(6), 573-585.   Achenbach M (1989). A model for an alloy with shape memory. Int J Plast, 5, 371-395.   Benard W L, Kahn H, Heuer A H, and Huff M A (1998). Thin-film shape-memory alloy actuated micropumps. Journal of Microelectromechanical Systems, 7(2), 245-251.   Cheng, Y. S., Zhou, Y., &amp; Chen, B. T. (1999). Particle deposition in a cast of human oral airways.  Aerosol Sci. Technol.,  31, 286-300.   Corner, J. K., &amp; Kleinstreuer, C (1995). A numerical investigation of laminar flow past nonspherical solids and droplets,  Journal of Fluids Engineering—Trans. of ASME  117, 170-175.   Corner, J. K., Kleinstreuer, C., &amp; Zhang, Z. (2001a). Flow structures and particle deposition patterns in double bifurcation airway models. Part 1. Air flow fields.  Journal of Fluid Mechanics,  435, 25-54.   Corner, J. K., Kleinstreuer, C., &amp; Kim, C. S. (2001b). Flow structures and particle deposition patterns in double bifurcation airway models. Part 2. Aerosol transport and deposition,  Journal of Fluid Mechanics  435, 55-80.   Crowder, T. M., Lousy, M. D., Sethuraman, V. V., Smyth, H. D. C., and Hickey, A. J. (2001). An Odyssey in Inhaler Formulation and Design,  Pharmaceutical Technology, July  2001:99-113.   Daviskas, E., Gonda, I., &amp; Anderson, S. D. (1990). Mathematical modeling of heat and water transport in human respiratory tract,  J. Appl. Physiol.  69(1), 362-372.   Duerig T, Pelton A, and Stöckel D (1999). An overview of Nitinol medical applications. Mat Sci Eng A, A273-275, 149-160.   Dunbar, C. A., Hickey, A. J., and Holzner, P. (1998) Dispersion and Characterization of Pharmaceutical dry Powder Aerosols,  KONA  16:7-44.   Edwards, D. A. &amp; Dunbar, C. (2002). Bioengineering of therapeutic aerosols,  Annual Review of Biomedical Engineering,  4, 93-107.   Finlay, W. H. (2001).  The Mechanics of Inhaled Pharmaceutical Aerosols: An Introduction . London, UK: Academic Press.   Finlay, W. H., &amp; Stapleton, K. W. (1995). The Effect on Regional Lung Deposition of Coupled Heat and Mass Transfer between Hygroscopic Droplets and their Surrounding Phase.  J. Aerosol Sci.  26(4), 655-670.   Frautschi, J.; and Seelecke, S. (2003), Finite Element Simulation of Adaptive Aerrospace Structures with SMA Actuators, SPIE Smart Structures and Materials 2003, Modeling, Signal Processing, and Control, San Diego, Calif., 2003, to appear.   Hollerbach J M, Hunter I W, and Ballantyne J, (1992) A Comparative Analysis of Actuator Technologies for Robotics, vol. 2. MIT Press, 299-342.   Keller, M. (1999) Innovations and Perspectives of Metered Dose Inhaler in Pulmonary Drug Delivery,  Int&#39;l J. Parm.  186:81-90   Kleinstreuer, C. (2003).  Two - Phase Flow: Theory and Applications . Taylor &amp; Francis, New York.   Kleinstreuer, C., &amp; Zhang, Z. (2003a). Laminar-to-turbulent fluid-particle flows in a human airway model.  Int. J. Multiphase Flow,  29, 271-289.   Kleinstreuer, C., and Zhang, Z. (2003b). Targeted drug aerosol deposition analysis for a four-generation lung airway model with hemispherical tumors,  ASME Journal of Biomechanical Engineering,  125(2), 197-206.   Ley, S., Mayer, D., Brook, B. S., Van Beek, E. J. R., Heussel, C. P., Rinck, D., Hose, R., Markstaller, K., &amp; Kauczor, H.-U. (2002). Radiological imaging as the basis for a simulation software of ventilation in the tracheo-bronchial tree.  Eur. Ragiol.,  12, 2218-2228.   Longest, P. W., Kleinstreuer, C. &amp; Buchanan, J. R. (2004). Efficient computation of micro-particle dynamics including wall effects.  Computers  &amp;  Fluids  (in press).   Makino E, Mitsuya T, and Shibata T (2001). Fabrication of {TiNi} shape memory micropump.  Sensors and Actuators A,  88, 256--262.   Morris, I. R. (1988). Functional Anatomy of the Upper Airway,  Emerg. Med. Clin. North Am.  6: 639-669.   Pitschellis R, Mechanische Miniaturgreifer mit Formgedachtnisantrieb (1998). No. 714 in Fortschr.-Ber. VDI Reihe 8. VDI Verlag Dusseldorf   Raabe, O. G., Yeh, H. C., Schum, G. M. &amp; Phalen, R. F. (1976),  Tracheobronchial Geometry: Human, Dog, Rat, Hamster, LF- 53. Lovelace Foundation Report, Albuquerque, N. Mex.   Reynaerts D, Peirs J, and van Brussel H (1999). Shape memory micro-actuation for a gastro-intestinal intervention system.  Sens Act,  77, 157--166.   Schlesinger, R. B., Gurman, J. L. &amp; Lippmann, M. (1982). Particle deposition within bronchial airways: Comparisons using constant and cyclic inspiratory flows,  Ann. Occup. Hyg.  26, 47-64.   Seelecke S. Adaptive structures with SMA actuators—modeling und simulation (in German), Habilitation Thesis, TU Berlin, 1999.   Seelecke S. and Müller I. Shape memory alloy actuators in smart structures—modeling and simulation, Applied Mechanics Review, vol 57, no 1, 2004   Seelecke S. and Büskens C. Optimal control of beam structures by shape memory wires. In S. Hernandez and C. A. Brebbia, editors, Opti 97, Computer Aided Optimum Design of Structures, Rome, Italy, Sep. 8-10, 1997, pages 457-466, Rome, Italy, Sep. 8-10, 1997, Comp. Mech. Press, 1997.   Seelecke S. and Papenfuβ N. (1999). Simulation and Control of SMA Actuators, in  Proceedings of the  6 th SPIE Conference on Smart Structures and Materials , Vol. 3667, Newport Beach, USA, 1-5 Mar. 1999   Seelecke S., Papenfuβ N., A Finite Element Formulation for SMA Actuators, Journal of Applied Mechanics and Engineering, Vol. 5, No. 1, 2000   Seelecke S., Büskens C., Müller I., and Sprekels J., Online Optimization of Large Systems: State of the Art, chapter Real-Time Optimal Control of Shape Memory Alloy Actuators in Smart Structures, Springer Verlag, 2001.   Smith R. C. Inverse compensation for hysteresis in magnetostrictive transducers. Mathematical and Computer Modelling, 33:285-298, 2001.   Smith R. C., Seelecke S., Ounaies Z. and Smith J., A Free Energy Model for Hysteresis in Ferroelectric Materials, Journal of Intelligent Material Systems and Structures, 2003, submitted.   Smith R. C., Seelecke S., Dapino M. J. and Ounaies Z., Unified Model for Hysteresis in Ferroic Materials, SPIE Smart Structures and Materials 2003, Modeling, Signal Processing, and Control, San Diego, Calif., 2003, to appear.   Weibel, E. R. (1963).  Morphometry of the Human Lung . New York: Academic Press.   Wilcox, D. C. (1998).  Turbulence Modeling for CFD  ( Second Edition ), DCW Industries, Inc., LA Canada, CA.   Xu D, Wang L, Ding G, Zhou Y, Yu A, and Cai B (2001). Characteristics and fabrication of NiTi/Si diaphragm micropump. Sensors and Actuators A, 93, 87-92.   Zhang, L., Asgharian, B. &amp; Anjilvel, S. (1996). Inertial and interceptional deposition of fibers in a bifurcating airway.  J. Aerosol Medicine  9, 419-430.   Zhang, Z., &amp; Kleinstreuer, C. (2002). Transient airflow structures and particle transport in a sequentially branching lung airway model.  Physics of Fluids,  14, 862-880.   Zhang, Z. &amp; Kleinstreuer, C. (2003a). Modeling of low Reynolds number turbulent flows in locally constricted conduits: A comparison study.  AIAA Journal,  41, 831-840.   Zhang, Z. &amp; Kleinstreuer, C (2003b). Species heat and mass transfer in a human upper airway model,  International Journal of Heat and Mass Transfer,  46, 4755-4768.   Zhang, Z. &amp; Kleinstreuer, C (2003c). Airflow structures and nano-particle deposition in a human upper airway model,  Journal of Computational Physics , Submitted for publication.   Zhang, Z., Kleinstreuer, C. &amp; Kim, C. S. (2001). Effects of curved inlet tubes on particle deposition in bifurcating lung airways.  Journal of Biomechanics,  34, 659-669.   Zhang, Z., Kleinstreuer, C. &amp; Kim, C. S., (2002a). Cyclic micron-size particle inhalation and deposition in a triple bifurcation lung airway model.  J. Aerosol Science  33, 257-281.   Zhang, Z., Kleinstreuer, C. &amp; Kim, C. S., (2002b). Aerosol deposition efficiencies and upstream release positions for different inhalation modes in an upper bronchial airway model.  Aerosol Science  &amp;  Technology,  36, 828-844.   Zhang, Z., Kleinstreuer, C., Kim, C. S. &amp; Hickey, A. J. (2002c). Aerosol transport and deposition in a triple bifurcation bronchial airway model with local tumors.  Inhalation Toxicology,  14, 1111-1133.   Zhang, Z., Kleinstreuer, C. &amp; Kim, C. S. (2002d). Micro-particle transport and deposition in a human oral airway model,  J. Aerosol Science,  33, 1635-1652.   Zhang, Z., Kleinstreuer, C. &amp; Kim, C. S. (2002e). Computational analysis of micron-particle deposition in a human triple bifurcation airway model,  Computer Methods in Biomechanics and Biomedical Engineering,  5, 135-147.   Zhang, Z., Kleinstreuer, C. and Kim, C. S. (2002f). Gas-Solid Two-Phase Flow in a Triple Bifurcation Lung Airway Model,  Int. J. Multiphase Flow , Vol. 28, pp. 1021-1046.   Zhang, Z., Kleinstreuer, C., Kim, C. S. &amp; Cheng, Y. S. (2003a). Vaporizing micro-droplet inhalation, transport and deposition in a human upper airway model,  Aerosol Science and Technology , (in press).   Zhang, Z., Kleinstreuer, C &amp; Donohue, J. F. (2003b). Comparison of micro- and nano-size particle depositions in a human upper airway model,  Journal of Aerosol Science , Submitted for publication.   Zhang, Z., Kleinstreuer, C, Donohue, J. F. and Kim, C. S. (2005). Comparison of Micro- and Nano-Size Particle Depositions in a Human Upper Airway Model,  Journal of Aerosol Science , Vol. 36, 211-233.   

     It will be understood that various details of the presently disclosed subject matter may be changed without departing from the scope of the present subject matter. Furthermore, the foregoing description is for the purpose of illustration only, and not for the purpose of limitation.