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ROCKING THE WORLD NANO-SCALE: FUTURE INTERNET RESEARCH FOR COMMUNICATION NETWORKS IN MEDICINE, HEALTH AND BEYOND, Ian F. Akyildiz, Georgia Institute of Technology
 

ROCKING THE WORLD NANO-SCALE: FUTURE INTERNET RESEARCH FOR COMMUNICATION NETWORKS IN MEDICINE, HEALTH AND BEYOND, Ian F. Akyildiz, Georgia Institute of Technology

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    ROCKING THE WORLD NANO-SCALE: FUTURE INTERNET RESEARCH FOR COMMUNICATION NETWORKS IN MEDICINE, HEALTH AND BEYOND, Ian F. Akyildiz, Georgia Institute of Technology ROCKING THE WORLD NANO-SCALE: FUTURE INTERNET RESEARCH FOR COMMUNICATION NETWORKS IN MEDICINE, HEALTH AND BEYOND, Ian F. Akyildiz, Georgia Institute of Technology Presentation Transcript

    • ROCKING THE WORLD NANO-SCALE: FUTURE INTERNET RESEARCH FOR COMMUNICATION NETWORKS IN MEDICINE, HEALTH AND BEYOND I. F. AKYILDIZ Ken Byers Chair Professor in Telecommunications Georgia Institute of Technology School of Electrical and Computer Engineering BWN (Broadband Wireless Networking) Lab Atlanta, GA, USA
    • REFERENCES I.F. Akyildiz, F. Brunetti, and C. Blázquez, "Nanonetworks: A New Communication Paradigm", Computer Networks Journal, (Elsevier), June 2008. I.F. Akyildiz, J.M. Jornet and M. Pierobon, "Nanonetworks: A New Frontier in Communications”, Communications of the ACM, 2011. IFA’2013 TRONDHEIM 2
    • NANOTECHNOLOGY Enables the control of matter at an atomic and molecular scale: – At this scale, nanomaterials show new properties not observed at the microscopic level – Objective: Exploit these properties & develop new devices and applications 1 nm IFA’2013 TRONDHEIM 3
    • DESIGN OF NANO-MACHINES IFA’2013 TRONDHEIM 4
    • DESIGN OF NANOMACHINES Nanomaterial Based Design Nano-Antenna Bio-inspired Design Nano-EM Transceiver Nano-Transceiver Nano-Antennas Nano-Memory Nano-Processor 100 nm Nanosensors Nano-Processor Nano-Battery 1 μm Nanosensors 2 μm 6 μm Nano-Memory 2 μm Nano-Power Unit 6 μm IFA’2013 TRONDHEIM 5
    • FUTURE LOOK –SILICON TECHNOLOGY ERA IS COMING TO AN END (~ 2020-2030) -MOLECULAR TECHNOLOGY ERA IS STARTING AND WILL BE DOMINATING OUR LIVES FOR THE NEXT 80 YEARS ~(2010-onwards) IFA’2013 TRONDHEIM 6
    • BIOLOGY: A RADICALLY DIFFERENT APPROACH TO NANOMACHINES Cells are nanoscale-precise biological machines Eukaryotic Cell Prokaryotic Cell They communicate and interact/cooperate Eukaryotic Cell Tissue IFA’2013 Bacteria Population TRONDHEIM 7
    • CELLS AS BIOLOGICAL NANOMACHINES Nucleus and Ribosomes = Biological Memory And Processor Gap Junctions = Molecular Transmitters Mitochondria = Biological Battery IFA’2013 TRONDHEIM Chemical receptors = Biological Sensors/Molecular Receivers 8
    • BACTERIA-BASED NANOMACHINES  Reuse of entire biological cells – Through genetic programming of bacteria plasmids (Synthetic Biology) IFA’2013 Communication Functions Actuation Function Cell Membrane = Nano-Power Unit DNA in Nucleoid and Plasmids = NanoMemory/Processor Pili = NanoSensors/Actuator s Sensing Function Protein receptor = Nano-Receivers Ribosomes = Nano-Transmitters Flagellum = Nano-Actuator TRONDHEIM 9
    • BIOLOGICAL NANOMACHINES: BIOLOGICAL BATTERY Mitochondria obtain energy by combining: –Glucose –Amino Acids –Fatty Acids –Oxygen and synthesizing:  Adenosine TriPhosphate or ATP IFA’2013 TRONDHEIM 10
    • BIOLOGICAL NANOMACHINES: BIOLOGICAL MEMORY AND PROCESSOR DNA  DNA in the nucleus contains the information of protein structure (memory)  Ribosomes read and process the DNA information (processor), synthesize the proteins Ribosome Amino Acids  Proteins control functionalities of the cell (e.g., cell signaling (Tx), ligand-binding (Rx), etc.) IFA’2013 TRONDHEIM Protein 11
    • BIOLOGICAL NANOMACHINES: COMMUNICATION THROUGH MOLECULES Tx Eukaryotic Cells Rx Molecules (Proteins, Ions, Hormones) Prokaryotic Cells Tx Rx Rx/Tx Tx/Rx Molecules (e.g., Autoinducer exchange for Quorum Sensing) IFA’2013 Conjugatio n Conjugatio n Chemotaxis Molecules (DNA plasmids) TRONDHEIM 12
    • BIOLOGICAL NANOMACHINES: EXAMPLE OF TRANSMITTER A cell (the transmitter) synthesizes and releases molecules (proteins) in the medium, as a result of the expression of a DNA sequence. Inner concentration Emission of a particle Diffusing particles Gap junction model Outer concentration IFA’2013 Spherical boundary TRONDHEIM 13
    • BIOLOGICAL NANOMACHINE: EXAMPLE OF A RECEIVER Another cell (the receiver) captures those molecules and creates an internal chemical pathway that triggers the expression of other DNA sequences. Incoming particles Particle release LIGAND-RECEPTOR BINDING IFA’2013 Particle binding TRONDHEIM Chemical receptor 14
    • BIOLOGICAL NANOMACHINES Can we create man-made biological nanomachines?  YES!!! Cells can be “reprogrammed” via DNA manipulation (genetic engineering) IFA’2013 TRONDHEIM BioBricks Foundation (MIT) http://biobricks.org/ 15
    • BIOLOGICAL NANOMACHINES: SHORTER-TERM GOAL Genetically program biological cells to perform specific functions Observation of bacteria behavior Biological Circuits to perform specific functions IFA’2013 Extraction of components for specific functions Extraction of genetic code that controls behavior Genetic code with specific functions (Plasmid) Genetically Engineered Bacterium TRONDHEIM Building blocks of biological circuits Genetically Engineered Bacteria Population 16
    • BIOLOGICAL NANOMACHINES: LONG-TERM GOAL (HUMAN CELL ENGINEERING)  To gen. eng. an eukaryotic cell  insert a piece of new DNA code in the lentivirus cell (special type of a virus used in gen. eng.)  Lentivirus is able to infect the eukaryotic cell, and inject the new DNA code in the cell DNA  This technique, upon cell replication, would enable the cell reprog. Lentivirus IFA’2013 TRONDHEIM 17
    • BIOLOGICAL NANOMACHINES APPLICATIONS: ADVANCED HEALTH SYSTEMS Alzheimer, Epilepsy, Depression Monitoring Networks Brain Cells Monitoring Networks Blood Sugar Monitoring Network Heart Monitoring Network Interconnected Intrabody Nanonetworks Glucose Monitoring Nano-sensors Interface with External Networks IFA’2013 Cancer Monitoring Network TRONDHEIM 18
    • PARTICULATE DRUG DELIVERY Y. Chahibi, M. Pierobon, S. O. Song, and I. F. Akyildiz “A Molecular Communication System Model for Particulate Drug Delivery Systems” IEEE Transaction of Biomedical Engineering (2013) Target Location Cardiac Input Injected Particles Drug Particles at Targeted Site Drug Particles Presence in Other Locations Particle Injection Rate Injection Location Spread of Drug Particles Injection Transmitter IFA’2013 Particle Injection Rate Propagation Channel Particle Delivery Rate TRONDHEIM Target location Delivery Receiver 19
    • BIOLOGICAL NANOMACHINES: LONG-TERM APPLICATIONS Biological Computing – Interacting genetically-modified organisms with biological logic gates – Boolean logic operations within the biochemical environment IFA’2013 TRONDHEIM 20
    • BIOLOGICAL NANOMACHINES: LONG-TERM APPLICATIONS  Autonomous Control and Decision Networks in Biochemical Environments – Control of chemical reactions in industrial processes (e.g., drug synthesis, harmful agents removal) – Purification of proteins in biology labs (e.g., quorum sensing-mediated protein copy) IFA’2013 TRONDHEIM 21
    • BIOLOGICAL NANOMACHINES: LONG-TERM APPLICATIONS New genetic code  Biological Sensor Networks – Sensor motes based on genetically engineered bacteria – Natural interconnection through molecular communication IFA’2013 TRONDHEIM 22
    • BIOLOGICAL NANOMACHINES: LONG-TERM APPLICATIONS  Natural Bacteria Environments – Food toxicity monitoring (e.g., yogurt, chicken, etc.) – Environmental monitoring and cleaning (e.g. water pipes, copper mines, radioactivity remediation, etc.) – Intrabody diagnosis and drug delivery networks (e.g., intestine) IFA’2013 TRONDHEIM 23
    • BIOLOGICAL NANOMACHINES: LONG-TERM APPLICATION  Bacteria-based Sensor Network in the Gastrointestinal Tract Bacteria Population Bacteria Motion by Chemotaxis Nanosensor/Actu ator/Transceiver Engineered Bacteria IFA’2013 Propagation of Molecular Signal TRONDHEIM 24
    • COMMUNICATION AMONG BIOLOGICAL NANOMACHINES I. F. Akyildiz, F. Brunetti, and C. Blázquez, "NanoNetworking: A New Communication Paradigm", Computer Networks Journal, (Elsevier), June 2008.  All these applications require nanomachines to communicate with each other for – Relaying and spreading sensory information – Coordinating to perform complex tasks which go beyond the capability of a single nanomachine  For this, we need to better investigate their natural communication paradigm: MOLECULAR COMMUNICATION IFA’2013 TRONDHEIM 25
    • MOLECULAR COMMUNICATION Defined as the transmission and reception of information encoded in molecules An interdisciplinary field that spans Nano, ECE, CS, Bio, Physics, Chemistry, Medicine, and Information Technologies IFA’2013 TRONDHEIM 26
    • MOLECULAR COMMUNICATION Short Range (nm to µm) Molecular Motors IFA’2013 Calcium Ions Medium Range (µm to mm) Bacteria TRONDHEIM Long Range (mm to m) Pheromones and Pollen 27
    • SHORT-RANGE COMMUNICATION USING MOLECULAR MOTORS IFA’2013 TRONDHEIM 28
    • SHORT-RANGE COMMUNICATION USING MOLECULAR MOTORS Node 5 Molecular Rail Node 1 Molecular Motor Node 4 Node 2 IFA’2013 Node 6 TRONDHEIM 29
    • MOLECULAR COMMUNICATION BLOCKS USING MOLECULAR MOTORS Classical Blocks of Communication Theory Encoding Transmission Propagation Reception Decoding Molecular Communication Blocks – Molecular Motors Select Molecules to represent information IFA’2013 Encapsulate molecules into vesicles Molecular motors travel along attach them to molecular motors molecular rails TRONDHEIM Detach vesicles from Molecular motors Extract molecules from vesicles Interpret received information from molecules characteristics 30
    • SHORT-RANGE COMMUNICATION USING MOLECULE DIFFUSION Molecular signals (e.g., CA2+ ions) travel through cells gap junctions ~10 um Cells: Prokaryotic cells -> Bacteria Eukaryotic cells -> Muscular tissue Tx Calcium Signaling Rx Gap junctions IFA’2013 TRONDHEIM Molecules: Auto-inducers Ions (calcium, sodium, potassium) 31
    • SHORT-RANGE COMMUNICATION USING MOLECULE DIFFUSION Molecular signals (e.g., CA2+ ions) travel through cells gap junctions Cells: Prokaryotic cells -> Bacteria Eukaryotic cells -> Muscular tissue Tx ~50 um IFA’2013 Rx TRONDHEIM Molecules: Auto-inducers Ions (calcium, sodium, potassium) 32
    • MOLECULAR COMMUNICATION BLOCKS USING MOLECULE DIFFUSION Classical Blocks of Communication Theory Encoding Transmission Molecular Communication Blocks – Modulate molecule concentration according to the information IFA’2013 Propagation Reception Decoding Molecule Diffusion-based Communication Emit modulated concentration from gap junctions on the nanomachine Modulated concentration propagates via molecule diffusion TRONDHEIM Absorb incoming molecules in the nanomachine Interpret received information Sense their concentration through chemical receptors from variations in concentration 33
    • MEDIUM RANGE MOLECULAR COMMUNICATION THROUGH BACTERIAL CHEMOTAXIS M. Gregori and I. F. Akyildiz, "A New NanoNetwork Architecture using Flagellated Bacteria and Catalytic Nanomotors” , IEEE JSAC (Journal of Selected Areas in Communications), May 2010. Rx Conjugatio n – – – – Conjugatio n Chemotaxis Bacteria are microorganisms composed only by one prokaryotic cell Flagellum allows them to convert chemical energy into motion 4 and 10 flagella (moved by rotary motors, fuelled by chemical compounds) Approximately 2 µm long and 1 µm in diameter. IFA’2013 TRONDHEIM 34
    • INFORMATION ENCAPSULATION … in plasmids or chains of DNA, which contain: – Message to transmit  Approx. 600 KB per plasmid – Active area + Transfer region  Regulate bacteria behavior Active area Message Transfer Region IFA’2013 TRONDHEIM 35
    • MEDIUM RANGE MOLECULAR COMMUNICATION THROUGH BACTERIAL CHEMOTAXIS < 1 mm Plasmid Tx Rx Chemical Attractant TX inserts the information (plasmid) in the bacterium (conjugation) IFA’2013 Bacterium moves in a series of runs and tumbles TRONDHEIM RX releases chemical attractant to “guide” the bacterium until it obtains the information 36
    • MEDIUM RANGE MOLECULAR COMMUNICATION THROUGH BACTERIAL CHEMOTAXIS L.C. Cobo-Rus, and I.F. Akyildiz, “Bacteria-based Communication Networks”, Nano Communication Networks, (Elsevier), December 2010. Classical Blocks of Communication Theory Encoding Transmission Molecular Communication Blocks – Introduce DNA plasmid inside the bacteria’s cytoplasm (conjugation) IFA’2013 Propagation Reception Decoding Bacteria Chemotaxis and Conjugation Receiver releases attractants so the bacteria can reach it Bacteria sense the gradient of attractant particles They move towards the gradient direction (chemotaxis) TRONDHEIM DNA plasmids extracted from incoming bacteria (conjugation) Plasmids are read and information is interpreted 37
    • LONG-RANGE COMMUNICATION USING PHEROMONES L. PARCERISA AND I.F. AKYILDIZ, "MOLECULAR COMMUNICATION OPTIONS FOR LONG RANGE NANONETWORKS," COMPUTER NETWORKS JOURNAL (ELSEVIER), NOV. 2009. Pheromones are larger molecules which can be propagated over longer distances through wind (advection) ~ 1-10 m Pheromone Antenna Pheromones Tx Pheromone Antenna Rx Wind IFA’2013 TRONDHEIM 38
    • LONG-RANGE COMMUNICATION USING PHEROMONES IFA’2013 TRONDHEIM 39
    • MOLECULAR COMMUNICATION THROUGH PHEROMONES L. Parcerisa and I.F. Akyildiz, "Molecular Communication Options for Long Range Nanonetworks“, Computer Networks (Elsevier) Journal, November 2009. Classical Blocks of Communication Theory Encoding Transmission Molecular Communication Blocks – Modulate production of molecules with certain Chemical character. IFA’2013 Propagation Reception Decoding Molecule Advection and Diffusion Release these molecules In the air Molecules propagate thanks Sense incoming to the molecules advection of with air turbulence chemical (wind) and receptors diffusion TRONDHEIM Interpret Received information from chemical charact. of sensed molecules 40
    • NSF MONACO PROJECT I. F. Akyildiz, F. Fekri, C. R. Forest, B. K. Hammer, and R. Sivakumar, “MONACO: Fundamentals of Molecular Nano-Communication Networks,’’ IEEE Wireless Communications Magazine Special Issue on Wireless Communications at the Nano-Scale, October 2012. NSF Funding: This material is based upon work supported by the National Science Foundation under Grant No. 1110947 – $3M in 4 years (2011-2015) – 5 PIs in wireless communication and networks, biology and microfluidic engineering Project webpage: http://www.ece.gatech.edu/research/labs/bwn/monaco/index.html IFA’2013 TRONDHEIM 41
    • NSF MONACO TEAM Principal Investigators I. F. Akyildiz F. Fekri C. R. Forest B. K. Hammer R. Sivakumar Ph.D. Students and Post Docs M. Pierobon IFA’2013 O. Bicen B. Unluturk A. Einolghozati C. Henegar TRONDHEIM P. Bardill B. Krisnaswamy 42
    • NSF MONACO PROJECT: SPECIFIC OUTCOMES Communication Models  Establish the theoretical foundations  Design network architectures, modulation schemes and protocols Network Architecture and Protocols  Develop a molecular communication network based on genetically modified/engineered prokaryotic cells (bacteria) in a microfluidic device IFA’2013 Simulation (NS-3) Generic Physical Experiments TRONDHEIM Bacteria Case 43
    • END TO END MODEL (2 NODES) M. Pierobon, and I. F. Akyildiz, “A Physical End to End Model for Molecular Communication in Nanonetworks,’’ IEEE JSAC (Journal of Selected Areas in Communications), May 2010. Chemical Receptor Diffusing Molecules Input signal Emission Process Emission rate at transmitter Modulates emission rate by controlling the molecule output according to the input signal IFA’2013 Diffusion Process Concentration at receiver Propagates the modulated emission rate from the transmitter to the receiver TRONDHEIM Reception Process Output signal Reads the molecule concentration and returns the output signal 44
    • WHAT DID WE LEARN? Molecular communication system components – Molecule emission (modulates rate of molecule release) – Molecule propagation (diffusion most general) – Molecule reception (based on chemical reactions) Attenuation – As high as 150dB in 50µm distance Delay – In the range of seconds per 50µm IFA’2013 TRONDHEIM 45
    • NOISE MODELS * M. Pierobon, and I. F. Akyildiz, “Diffusion-based Noise Analysis for Molecular Communication in Nanonetworks,’’ IEEE Tr. on Signal Processing, June 2011. * M. Pierobon, and I. F. Akyildiz, “Noise Analysis in Ligand-binding Reception for Molecular Communication in Nanonetworks,’’ IEEE Tr. on Signal Processing, Sept. 2011. Transmitter Input signal Emission Process Sampling Noise Propagation Diffusion Process Counting Noise Receiver Ligand-receptor Kinetic Noise Reception Output signal Process End-to-End Molecular Communication IFA’2013 TRONDHEIM 46
    • INFORMATION CAPACITY M. Pierobon and I. F. Akyildiz, “Capacity of a Diffusion-based Molecular Communication System with Channel Memory and Molecular Noise,” IEEE Tr. on Information Theory, Feb. 2013. (Shorter version appeared in Proc. of IEEE INFOCOM 2011).  Found analytical closed-form expression of the theoretical maximum achievable rate (capacity) in [bits/sec]  Focus on the Diffusion Process propagation Diffusion Process Input signal Emission Process Channel Memory Persistency of emitted molecules in the space IFA’2013 Counting Noise Reception Process Output signal Generated by Molecules subject to Brownian motion TRONDHEIM 47
    • INFORMATION CAPACITY  Theoretical upper bound of the communication performance of a diffusionbased molecular communication Variables Fick’s Diffusion Diffusivity D Temperature T Transmission range Bandwidth W Transmission power Receiver radius R V Molecule Location Displacement K B = Boltzmann's constant G(.) = Gamma function IFA’2013 TRONDHEIM d R 48
    • MC AMONG BACTERIA POPULATIONS A.Einolghozati, M.Sardari, A.Beirami and F.Fekri, “Data Gathering in Networks of Bacteria Colonies: Collective Sensing and Relaying Using Molecular Communication,” Proc. of 1st NetSciCom Workshop at INFOCOM 2012, Orlando, FL, USA, March 2012  Information capacity limits of – Intra-node collective sensing (Quorum Sensing)  How bacteria in a population perform sensing and coordinate their actions – Inter-node communication  How bacteria transfer information from one population to another Bacteria Population IFA’2013 Network of Bacteria Populations TRONDHEIM 49
    • MOLECULAR PROPAGATION OVER MICROFLUIDIC CHANNELS A. O. Bicen, and I. F. Akyildiz, “System-Theoretic Analysis and Least-Squares Design of Microfluidic Channels for Flow-Induced Molecular Communication,” IEEE Tr. on Signal Processing, October 2013. Fluid Flow Chambers contain bacteria Microfluidic Channel Input Molecules Output Molecules  Mathematical modeling of microfluidic channel shapes (Building blocks of microfluidic devices) - Frequency Response and Delay  Framework to design microfluidic devices - Optimize microfluidic channel shapes for a desired spectral output IFA’2013 TRONDHEIM 50
    • MOLECULAR COMMUNICATION THROUGH MICROFLUIDIC CHANNELS 0,1,1,0,0,1… Source Input t CHANNEL TRANSMITTER 0,1,1,0,0,1… RECEIVER Destination Output t  Establish the fundamentals of practical molecular nanonetworks  Analyze the channel and information capacity  Design information encoding/decoding techniques, and modulation schemes IFA’2013 TRONDHEIM 51
    • VALIDATION PLATFORM Engineered DNA plasmid  Bacteria (E. coli) are genetically modified in order to produce: – Transmitter bacterium (Tx) Can only release molecules (autoinducers) – Receiver bacterium (Rx) Glows upon the detection of autoinducers IFA’2013 TRONDHEIM 52
    • VALIDATION PLATFORM A bacteria-based molecular communication link Molecule diffusion Chemical Message Transm. Signal IFA’2013 Recv. Signal Transmitter Bacteria Population TRONDHEIM Fluorescence Message Receiver Bacteria Population 53
    • VALIDATION PLATFORM WHAT CAN WE MEASURE? Growth of bacteria in the chamber after seeding (left) and after 11 hours (right) Fluorescence microscope images after seeding (left) and after 11 hours (right) IFA’2013 TRONDHEIM 54
    • NSF MONACO PROJECT: SPECIFIC OUTCOMES Communication Models  Establish the theoretical foundations  Design network architectures, modulation schemes and protocols  Develop a molecular communication network based on genetically modified/ engineered prokaryotic cells (bacteria) in a microfluidic device IFA’2013 Network Architecture and Protocols Simulation (NS-3) Generic Physical Experiments TRONDHEIM Bacteria Case 55
    • FUTURE WORK (I) For each MC option (e.g., molecular motors, pheromones, calcium ions) – End-to-end system design and modeling Transmitter Design (e.g., how pheromones are released) Receiver Design (e.g., pheromone antenna with MIMO technology) Channel Modeling (e.g., model of meteorological conditions for pheromone air transport) and study of attenuation and delay. IFA’2013 TRONDHEIM 56
    • FUTURE WORK (II)  For each MC option (e.g., molecular motors, pheromones, calcium ions) – Noise Analysis (e.g., misrecognition of pheromone types) – Capacity Analysis (e.g., maximum rate of delivery of pheromone messages) – Interference Analysis (e.g., how different pheromone sources interfere) IFA’2013 TRONDHEIM 57
    • FUTURE WORK (III)  For each MC Option (e.g., molecular motors, pheromones, calcium ions) – Energy Modeling (e.g., energy for pheromone emission/recognition) – Modulation/demodulation (e.g., pheromone pulses) – Addressing (e.g., different pheromone types) – Packetizing (e.g., information in bursts of pheromones) IFA’2013 TRONDHEIM 58
    • NSF MONACO PROJECT: BROADER IMPACT  Significant impact on research in – Nanotechnology – Biology – Information and communication technologies  Define the first steps towards real implementable solutions  Great impact in almost every field of our society – E.g., healthcare, homeland security and environmental protection, ... IFA’2013 TRONDHEIM 59
    • ANOTHER APPLICATION OF MOLECULAR COMMUNICATION RESEARCH Particulate Drug Delivery System (PDDS) – Drug particles are released in the body – They propagate in the cardiovascular system – Upon reception at the targeted site, they perform their healing action  Utilize the tools and techniques learnt in the MoNaCo project to study and enhance Particulate DDSs IFA’2013 TRONDHEIM 60
    • ORIGINS OF PDDS Paul Ehrlich (1854-1915): – He imagined the concept of “magic bullets” (Magische Kugeln) which are the ideal therapeutic agent killing the targeted diseases without affecting the other healthy parts of the body IFA’2013 TRONDHEIM Paul Ehrlich Nobel prize in Medicine (1908) 61
    • DEFINITION OF THE PDDS Method to direct drug nanoparticles to the exact location of the disease at the right concentration while minimizing the effects on other healthy parts of the body IFA’2013 TRONDHEIM 62
    • PDDS: WHY NANO-PARTICLES?  Easy to reach the diseased parts  Do not affect healthy cells and body fluids 1 nm – 100 nm IFA’2013 TRONDHEIM 63
    • HOW ARE NANOPARTICLES FOR DDS FABRICATED? J. Kost and R. Langer, "Responsive Polymeric Delivery Systems" Advanced Drug Delivery Reviews, 2012. Biochemists can put pharmaceutical agents inside nanoparticles Microscopic view of clusters of drug-loaded nanoparticles IFA’2013 TRONDHEIM 64
    • DRUG LOADED NANO-PARTICLES Biochemists can engineer drug-loaded nanoparticles of any size, shape, and chemical properties (reaction rates, absorption rates, affinity with disease parts)  PDDS are engineered in such a way that they – – – – Target the diseases with cell precision Survive long enough in the human body Not be excreted from the body quickly Attach themselves to the diseased cells by ligand-targeting IFA’2013 TRONDHEIM 65
    • HOW DOES PDDS WORK? I. Brigger, C. Dubernet P. Couvreur "Nanoparticles in Cancer Therapy and Diagnosis" Advanced Drug Delivery Reviews (2012)  Nanoparticles accumulate in diseased parts but not in healthy parts Healthy parts Diseased parts Normal vessel walls  Nanoparticles are able to travel from the blood to the diseased parts through damaged vessel walls Damaged vessel walls Drug-loaded nanoparticles  Drug-loaded nanoparticles can go inside the diseased cells and deliver the drug IFA’2013 TRONDHEIM 66
    • MODELING THE PDDS DIAGNOSIS Diagnosis: IFA’2013 INJECTION PROPAGATION DELIVERY Type of the diseases and its location is identified TRONDHEIM 67
    • MODELING THE PDDS DIAGNOSIS Injection: IFA’2013 INJECTION PROPAGATION DELIVERY Appropriate nanoparticles for the disease are injected in the body TRONDHEIM 68
    • MODELING THE PDDS DIAGNOSIS INJECTION PROPAGATION DELIVERY Propagation: Nanoparticles get dispersed throughout the human body IFA’2013 TRONDHEIM 69
    • MODELING THE PDDS DIAGNOSIS Delivery: IFA’2013 INJECTION PROPAGATION DELIVERY Nanoparticles deliver their content to the disease while avoiding healthy parts TRONDHEIM 70
    • CHALLENGES  Modeling must capture realistic phenomena: – Time-variance of the blood flow – Reaction and dispersion of drug particles in the blood – Individual specificities – Body clearance mechanisms – Physiological abnormalities, etc. IFA’2013 TRONDHEIM 71
    • MEDDS: MOLECULAR COMMUNICATION FOR DRUG DELIVERY SYSTEMS SAMSUNG SAIT (2012-2015) Objective: To establish the molecular communication fundamentals of intra-body particle propagation in order to design the PDDS MOLECULAR COMMUNICATION FOR NANOPARTICLES PROPAGATION (Year 1 and 2) MOLECULAR COMMUNICATION FOR ACTION-POTENTIAL PROPAGATION (Year 2) ACTION POTENTIALTRIGGERED PARTICULATE DRUG DELIVERY (Year 3) • E2E PDDS Model • Neuron Model • • Network Performance • Peripheral Nervous System (PNS) Model Electrical Stimuli Optimization • PNS Interference Study • Joint Action-Potential and Drug Propagation Optimization • • Validation (COMSOL/KMC) Use case: Pharmacokinetics IFA’2013 • Network Performance TRONDHEIM 72
    • SAMSUNG MEDDS TEAM Principal Investigator Ph.D. Students Y. Chahibi IFA’2013 I. F. Akyildiz O. Bicen Collaborators M. Pierobon Univ. of Nebraska-Lincoln TRONDHEIM S. O. Song Samsung SAIT 73
    • END-TO-END PDDS MODEL Y. Chahibi, M. Pierobon, S. O. Song, and I. F. Akyildiz “A Molecular Communication System Model for PDDS”, IEEE Trans. on Biomedical Engineering, 2013. Receiver Diseased Part Interferers Walls Absorption  We abstract elements of targeted drug delivery systems as components of a molecular communication system. Transmitted signal Drug Injection Pattern Packets Drug-loaded Nanoparticles Received Signal Drug Delivery Pattern Interferers Body Tissues Channel IFA’2013 Human Body TRONDHEIM Interferers Liver and Kidney Clearance 74
    • END-TO-END PDDS MODEL Target Location Cardiac Input Injected Particles Drug Particles at the Targeted Site Particle Injection Rate Injection Location Drug Particles Presence in Other Locations Spread of the Drug Particles Injection Transmitter Particle Injection Rate Target Location Propagation Channel Particle Delivery Rate Delivery Receiver  RESULTS: Transfer function, delay and attenuation of Drug Concentration from Injection to Delivery IFA’2013 TRONDHEIM 75
    • PROPAGATION (CHANNEL) MODEL  Blood Velocity Network – – Models the blood velocity in blood vessels Derived from the Navier-Stokes equations  Drug Propagation Network – – Injection Models the spread of drug in blood vessels Stems from the advection-diffusion equation Blood Velocity (BV) Network Blood velocity Drug Propagation (DP) Network Propagation Delivery IFA’2013 TRONDHEIM 76
    • BLOOD VELOCITY NETWORK  Drug propagates in the body thanks to the blood velocity  Blood velocity network models the time–varying blood velocity – Everywhere in the body – For any individual (Different persons have different blood flows) IFA’2013 TRONDHEIM 77
    • BLOOD VELOCITY NETWORK  A complex network comprised of: – – – – Cardiac Input (Blood velocity at the output of the heart) Large and Small Arteries Veins Other Organs  Final expression of the blood velocity is derived using tools from transmission line theory IFA’2013 TRONDHEIM 78
    • DRUG PROPAGATION NETWORK  Predicts the drug concentration in the cardiovascular system Injection Rate (Blood Velocities) (Injection Site) (Delivery Site) (Drug Properties) Drug Propagation Network Drug Delivery Rate Concentration of particles flowing in the blood per second. Unit is [mol/(m^3)]. IFA’2013 TRONDHEIM 79
    • DRUG PROPAGATION NETWORK  Comprised of Network Links (Vessels) and Network Nodes (Bifurcations)  DP depends on the: – Topology of the cardiovascular system – Body temperature – Drug radius – Drug shape – Blood viscosity Network Link = Blood Vessel Drug Propagation Network (Advection-Diffusion) Drug Delivery Rate Drug Injection Rate Network Source IFA’2013 Network Node = Bifurcation TRONDHEIM Network Destination 80
    • DRUG PROPAGATION NETWORK  Derived the impulse response of a blood vessel, bifurcation, and junction as expressions of: – Blood velocity – Diffusion coefficient – Temperature – Viscosity – Length – Radius Drug Injection Rate IFA’2013 Bifurcation Link Drug Injection Rate Drug Delivery Rate Drug Injection Rate TRONDHEIM Drug Delivery Rate Junction Drug Delivery Rate 81
    • END-TO-END PDDS MODEL  By combining the Drug Propagation Network and Blood Velocity Network we obtain the transfer function of the overall network  Predict the Drug Delivery Rate Injection Blood Velocity (BV) Network Blood Velocity Drug Propagation (DP) Network Propagation Delivery IFA’2013 TRONDHEIM 82
    • WHAT DID WE LEARN ? – Molecular Communication is a flexible, accurate, and efficient paradigm to model the PDDS  Flexible  Impulse responses are easy to manipulate analytically  Efficient  Analytical solutions are much faster than Monte-Carlo or finite element methods  Accurat  Good agreement with finite element and Monte-Carlo results Implications: - Drug delivery can be optimized – It provides better insight about intra-body communication IFA’2013 TRONDHEIM 83
    • IMPACT ON HEALTH AND MEDICINE Controlling the quantity and the timing of the drug injection to optimize the healing Developing personalized drug delivery systems Providing an alternative to in-vivo testing of drugs using the drug propagation simulation tool IFA’2013 TRONDHEIM 84
    • MEDDS: MOLECULAR COMMUNICATION FOR DRUG DELIVERY SYSTEMS SAMSUNG SAIT (2012-2015) Objective: To establish the molecular communication fundamentals of intra-body particle propagation in order to design PDDS MOLECULAR COMMUNICATION FOR NANOPARTICLES PROPAGATION (Year 1 and 2) MOLECULAR COMMUNICATION FOR ACTION-POTENTIAL PROPAGATION (Year 2) ACTION POTENTIALTRIGGERED PARTICULATE DRUG DELIVERY (Year 3) • E2E PDDS model • Neuron Model • • Network Performance • Peripheral Nervous System (PNS) Model Electrical Stimuli Optimization • PNS Interference Study • Joint Action-Potential and Drug Propagation Optimization • • Validation (COMSOL/KMC) Use case: Pharmacokinetics IFA’2013 • Network Performance TRONDHEIM 85
    • COMMUNICATION ASPECTS OF PDDS Y. Chahibi, I.F. Akyildiz and S. O. Song, “Molecular Communication Noise and Capacity Analysis for Drug Delivery Systems” Submitted for journal publication. – Noise: Brownian Motion – Information-Theoretical Capacity: the maximum amount of drugs that can reliably be delivered from injection point to the target point – Delay: Time required for a drug to attain the delivery location IFA’2013 TRONDHEIM 86
    • MEDDS: MOLECULAR COMMUNICATION FOR DRUG DELIVERY SYSTEMS SAMSUNG SAIT (2012-2015) Objective: To establish the molecular communication fundamentals of intra-body particle propagation in order to design PDDS MOLECULAR COMMUNICATION FOR NANOPARTICLES PROPAGATION (Year 1 and 2) MOLECULAR COMMUNICATION FOR ACTION-POTENTIAL PROPAGATION (Year 2) ACTION POTENTIALTRIGGERED PARTICULATE DRUG DELIVERY (Year 3) • E2E PDDS model • Neuron Model • • Network Performance • Peripheral Nervous System (PNS) Model Electrical Stimuli Optimization • PNS Interference Study • Joint Action-Potential and Drug Propagation Optimization • • Validation (COMSOL/KMC) Use case: Pharmacokinetics IFA’2013 • Network Performance TRONDHEIM 87
    • CASE: PHARMACOKINETICS Y. Chahibi, I.F. Akyildiz and S. O. Song, “Pharmacokinetics use case of Molecular Communication for Drug Delivery Systems” Submitted for journal publication.  Allow to map our communication model to pharmacologists – Where does the drug go? – How much of it reacts? – How much is absorbed by healthy parts? Reacted Particles (%?) Healthy Vessel (%?) Diseased Vessel (%?) Wall Absorption (%?) Wall Adsorption (%?) – How do cardiovascular diseases affect the drug distribution? IFA’2013 TRONDHEIM 88
    • CASE: PHARMACOKINETICS  Blood vessel damage can severely affect the drug delivery  Electrical equivalents for cardiovascular diseases:  How can we model the damaged vessels?  A healthy blood vessels can be modeled as an electrical circuit with:  Resistance  Blood Viscosity  Inductance  Blood Inertia  Capaciance  Vessel Elasticity Healthy (No leakage) (No conductance)  We propose equivalent electrical circuits for damaged blood vessels and studied their effect on drug propagation IFA’2013 TRONDHEIM  Tumorvessels small holes  Fluid leakage  Conductance Diseased part (With leakage) Add a parfallel conductance to the helthy model  Arteriosclerosis  Hardened vessel walls  No (remove) capacitance Arteriosclerosis (No elasticity) (No conductance) 89
    • CASE: PHARMACOKINETICS WHAT BODY DOES TO THE DRUG?  We extend the drug propagation network to account for realistic phenomena that occur in nanoparticles Injection 1 Tree of blood vessels – Reaction – Absorption – Adsorption 2 3 7  We derived expressions for the quantity of drugs that is absorbed by tissues, the quantity that reacts with the blood, etc. IFA’2013 5 4 Healthy TRONDHEIM 6 Fractions of drugs reacting, absorbed by tissues and, remaining in the blood. 90
    • IMPACTON HEALTH AND MEDICINE  Predicting what happens to drug-loaded nanoparticles on their way to the diseased parts  Studying the effect of abnormal body conditions (damaged blood vessels, high blood pressure, etc.) on drug delivery  Evaluating how much of the drug is excreted from the body IFA’2013 TRONDHEIM 91
    • MEDDS: MOLECULAR COMMUNICATION FOR DRUG DELIVERY SYSTEMS SAMSUNG SAIT (2012-2015) Objective: To establish the molecular communication fundamentals of intra-body particle propagation in order to design PDDS MOLECULAR COMMUNICATION FOR NANOPARTICLES PROPAGATION (Year 1 and 2) MOLECULAR COMMUNICATION FOR ACTION-POTENTIAL PROPAGATION (Year 2) ACTION POTENTIALTRIGGERED PARTICULATE DRUG DELIVERY (Year 3) • E2E PDDS model • Neuron Model • • Network Performance • Peripheral Nervous System (PNS) Model Electrical Stimuli Optimization • PNS Interference Study • Joint Action-Potential and Drug Propagation Optimization • • Validation (COMSOL/KMC) Use case: Pharmacokinetics IFA’2013 • Network Performance TRONDHEIM 92
    • CHALLENGES OF MOLECULAR COMMUNICATION MODELING FOR ACTION-POTENTIAL PROPAGATION  Mathematical modeling is complex because of the nonlinear effects in neural cells  Propagated action-potential should not affect the normal biological functions of the body  Many neural mechanisms are not deeply understood because action-potentials are difficult to measure on the human body IFA’2013 TRONDHEIM 93
    • MOLECULAR COMMUNICATION FOR ACTION-POTENTIAL PROPAGATION Y. Chahibi, I.F. Akyildiz and S. O. Song, “An Action-Potential Molecular Communication Model”, in preparation – Transmitter:  The signal is transmitted by potential stimulation by an electrical excitation – Channel:  First, the electrical propagation in ion-channels along the neuron cell  Second, the diffusion of neurotransmitters in the gap between two neuron cells – Receiver:  The signal is received by voltage induction at the receiver neuron cell IFA’2013 TRONDHEIM 94
    • MOLECULAR COMMUNICATION FOR ACTION-POTENTIAL PROPAGATION  Outcomes: – Transfer function, attenuation, delay, between two extremities of a neural network – Optimization of the electrical stimuli, and the location of the source and the destination – Triggering of the chemical activity of drugs through the action potential IFA’2013 TRONDHEIM 95
    • IMPACT OF MC ACTION-POTENTIAL PROPAGATION ON THE MEDICAL WORLD  Targeting neural diseases (Epilepsy, Depression, Alzheimer, …) using the action-potential  Combining particulate drug delivery with actionpotential triggering  Analyzing human cells that produce electrical signals (action-potentials), such as heart and brain cells IFA’2013 TRONDHEIM 96
    • RECOGNITION OF THE WORK ON INTERCELLULAR COMMUNICATION  2013 Nobel Prize in Medicine or Physiology – J. E. Rothman, R. Schekman and T. C. Südhof: – Distinguished for “their discoveries of machinery regulating vesicle traffic, a major transport system in our cells” Laureates of the Nobel prize in Medicine or Physiology (2013) IFA’2013 TRONDHEIM 97
    • RECOGNITION OF THE WORK ON INTERCELLULAR COMMUNICATION  2013 Nobel Prize in Chemistry – Arieh Warshel, Martin Karplus and Michael Levitt: – Distinguished for “the development of multiscale models for complex chemical systems” Laureates of the Nobel prize in Chemistry (2013) IFA’2013 TRONDHEIM 98
    • CONFERENCE ACTIVITIES IEEE Int. Workshop on Molecular and Nano-scale Communication (MoNaCom) 1. IEEE Infocom Conf., in Shanghai, China, April 2011. 2. IEEE ICC 2012 Conf., in Ottawa, Canada, June 2012. 3. IEEE ICC 2013 Conf., in Budapest, Hungary, June 2013. IFA’2013 TRONDHEIM 99
    • 1st ACM Annual International Conference on Nanoscale Computing and Communication (ACM NANOCOM 2014) – Atlanta, USA, May 2014 IFA’2013 TRONDHEIM 100
    • A NEW “ELSEVIER” JOURNAL http://www.elsevier.com/locate/nanocomnet IFA’2013 TRONDHEIM 101
    • OUR RESEARCH CENTERS * N3Cat: NaNoNetworking Research Center, (since 2007) UPC, Barcelona, Spain. * NANO-KAU, (since 2011) NanoCom Center at King Abdulaziz University, Jeddah, KSA. * FiDiPro: Finnish Distinguished Professorship for NANOCOM, TUT, Tampere, Finland. (since Sept. 2012) IFA’2013 TRONDHEIM 102