Bioreactor design

Bioreactor design is a complex engineering task. Under optimum conditions, the microorganisms or cells are able to perform their desired function with 100 percent rate of success. The bioreactor's environmental conditions like gas (i.e., air, oxygen, nitrogen, carbon dioxide) flow rates, temperature, pH and dissolved oxygen levels, and agitation speed/circulation rate need to be closely monitored and controlled.

Most industrial bioreactor manufacturers use vessels, sensors and a control system networked together.

Fouling can harm the overall sterility and efficiency of the bioreactor, especially the heat exchangers. To avoid it, the bioreactor must be easily cleaned and as smooth as possible (therefore the round shape).

A heat exchanger is needed to maintain the bioprocess at a constant temperature. Biological fermentation is a major source of heat, therefore in most cases bioreactors need refrigeration. They can be refrigerated with an external jacket or, for very large vessels, with internal coils.

In an aerobic process, optimal oxygen transfer is perhaps the most difficult task to accomplish. Oxygen is poorly soluble in water--even less in fermentation broths--and is relatively scarce in air (20.8%). Oxygen transfer is usually helped by agitation, which is also needed to mix nutrients and to keep the fermentation homogeneous. There are, however, limits to the speed of agitation, due both to high power consumption (which is proportional to the cube of the speed of the electric motor) and to the damage to organisms caused by excessive [[tip speed](3.14*dia of the impeller in mm * notation of the Speed/60(hr)] causing shear stress.

Industrial bioreactors usually employ bacteria or other simple organisms that can withstand the forces of agitation. They are also simple to sustain, requiring only simple nutrient solutions, and can grow at astounding rates.

Biophotonics

The term biophotonics denotes a combination of biology and photonics, with photonics being the science and technology of generation, manipulation, and detection of photons, quantum units of light. Photonics is related to electronics in that it is believed that photons will play a similar central role in future information technology as electrons do today.

Biophotonics has therefore become the established general term for all techniques that deal with the interaction between biological items and photons. This refers to emission, detection, absorption, reflection, modification, and creation of radiation from biomolecular, cells, tissues, organisms and biomaterials. Areas of application are life science, medicine, agriculture, and environmental science.

Applications

In microscopy, the development and refinement of the confocal microscope, the fluorescence microscope, and the total internal reflection fluorescence microscope all belong to the field of biophotonics.

The specimens that are imaged with microscopic techniques can also be manipulated by optical tweezers and laser micro-scalpels, which are further applications in the field of biophotonics.

Biochemical engineering

Biochemical engineering is a branch of chemical engineering or biological engineering that mainly deals with the design and construction of unit processes that involve biological organisms or molecules. Biochemical engineering is often taught as a supplementary option to chemical engineering or biological engineering due to the similarities in both the background subject curriculum and problem-solving techniques used by both professions. Its applications are used in the food, feed, pharmaceutical, biotechnology, and water treatment industries.

A bioreactor may refer to any device or system that supports a biologically active environment. In one case, a bioreactor is a vessel in which is carried out a chemical process which involves organisms or biochemically active substances derived from such organisms. This process can either be aerobic or anaerobic. These bioreactors are commonly cylindrical, ranging in size from liters to cubic meters, and are often made of stainless steel.

A bioreactor may also refer to a device or system meant to grow cells or tissues in the context of cell culture. These devices are being developed for use in tissue engineering.

On the basis of mode of operation, a bioreactor may be classified as batch, fed batch or continuous (e.g. Continuous stirred-tank reactor model). An example of a continuous bioreactor is the chemostat.

Organisms growing in bioreactors may be suspended or immobilized. The simplest, where cells are immobilized, is a Petri dish with agar gel. Large scale immobilized cell bioreactors are:

* moving media

* packed bed

* fibrous bed

* membrane

Photobioreactor

A photobioreactor (PBR) is a bioreactor which incorporates some type of light source. Virtually any translucent container could be called a PBR, however the term is more commonly used to define a closed system, as opposed to an open tank or pond.

Nanosensor Production methods

There are currently several hypothesized ways to produce nanosensors. Top-down lithography is the manner in which most integrated circuits are now made. It involves starting out with a larger block of some material and carving out the desired form. These carved out devices, notably put to use in specific microelectromechanical systems used as microsensors, generally only reach the micro size, but the most recent of these have begun to incorporate nanosized components.

Another way to produce nanosensors is through the bottom-up method, which involves assembling the sensors out of even more minuscule components, most likely individual atoms or molecules. This would involve moving atoms of a particular substance one by one into particular positions which, though it has been achieved in laboratory tests using tools such as atomic force microscopes, is still a significant difficulty, especially to do en masse, both for logistic reasons as well as economic ones. Most likely, this process would be used mainly for building starter molecules for self-assembling sensors.

The third way, which promises far faster results, involves self-assembly, or “growing” particular nanostructures to be used as sensors. This most often entails one of two types of assembly. The first involves using a piece of some previously created or naturally formed nanostructure and immersing it in free atoms of its own kind. After a given period, the structure, having an irregular surface that would make it prone to attracting more molecules as a continuation of its current pattern, would capture some of the free atoms and continue to form more of itself to make larger components of nanosensors.

The second type of self-assembly starts with an already complete set of components that would automatically assemble themselves into a finished product. Though this has been so far successful only in assembling computer chips at the micro size, researchers hope to eventually be able to do it at the nanometer size for multiple products, including nanosensors. Accurately being able to reproduce this effect for a desired sensor in a laboratory would imply that scientists could manufacture nanosensors much more quickly and potentially far more cheaply by letting numerous molecules assemble themselves with little or no outside influence, rather than having to manually assemble each sensor.

Nanosensor

Nanosensors are any biological, chemical, or sugery sensory points used to convey information about nanoparticles to the macroscopic world. Though humans have not yet been able to synthesize nanosensors, predictions for their use mainly include various medicinal purposes and as gateways to building other nanoproducts, such as computer chips that work at the nanoscale and nanorobots. Presently, there are several ways proposed to make nanosensors, including top-down lithography, bottom-up assembly, and molecular self-assembly.

Predicted applications

Medicinal uses of nanosensors mainly revolve around the potential of nanosensors to accurately identify particular cells or places in the body in need. By measuring changes in volume, concentration, displacement and velocity, gravitational, electrical, and magnetic forces, pressure, or temperature of cells in a body, nanosensors may be able to distinguish between and recognize certain cells, most notably those of cancer, at the molecular level in order to deliver medicine or monitor development to specific places in the body. In addition, they may be able to detect macroscopic variations from outside the body and communicate these changes to other nanoproducts working within the body.

One example of nanosensors involves using the fluorescence properties of cadmium selenide quantum dots as sensors to uncover tumors within the body. By injecting a body with these quantum dots, a doctor could see where a tumor or cancer cell was by finding the injected quantum dots, an easy process because of their fluorescence. Developed nanosensor quantum dots would be specifically constructed to find only the particular cell for which the body was at risk. A downside to the cadmium selenide dots, however, is that they are highly toxic to the body. As a result, researchers are working on developing alternate dots made out of a different, less toxic material while still retaining some of the fluorescence properties. In particular, they have been investigating the particular benefits of zinc sulfide quantum dots which, though they are not quite as fluorescent as cadmium selenide, can be augmented with other metals including manganese and various lanthanide elements. In addition, these newer quantum dots become more fluorescent when they bond to their target cells. (Quantum) Potential predicted functions may also include sensors used to detect specific DNA in order to recognize explicit genetic defects, especially for individuals at high-risk and implanted sensors that can automatically detect glucose levels for diabetic subjects more simply than current detectors. DNA can also serve as sacrificial layer for manufacturing CMOS IC, integrating a nanodevice with sensing capabilities. Therefore, using proteomic patterns and new hybrid materials, nanobiosensors can also be used to enable components configured into a hybrid semiconductor substrate as part of the circuit assembly. The development and miniaturization of nanobiosensors should provide interesting new opportunities.

Other projected products most commonly involve using nanosensors to build smaller integrated circuits, as well as incorporating them into various other commodities made using other forms of nanotechnology for use in a variety of situations including transportation, communication, improvements in structural integrity, and robotics. Nanosensors may also eventually be valuable as more accurate monitors of material states for use in systems where size and weight are constrained, such as in satellites and other aeronautic machines.

Existing nanosensors

Currently, the most common mass-produced functioning nanosensors exist in the biological world as natural receptors of outside stimulation. For instance, sense of smell, especially in animals in which it is particularly strong, such as dogs, functions using receptors that sense nanosized molecules. Certain plants, too, use nanosensors to detect sunlight; various fish use nanosensors to detect minuscule vibrations in the surrounding water; and many insects detect sex pheromones using nanosensors.

Certain electromagnetic sensors have also been in use in photoelectric systems. These work because the specific sensors called, aptly, photosensors are easily influenced by light of various wavelengths. The electromagnetic source transfers energy to the photosensors and energizes them into an excited state which causes them to release an electron into a semiconductor. At that point, it is relatively easy to detect the electricity coming from the sensors, and thus easy to know if the sensors are receiving light. Though more advanced uses of photosensors incorporating other forms of nanotechnology have yet to be implemented into consumer society, most film cameras have used photosensors at the nano size for years. Traditional film uses a layer of silver ions that become excited by solar energy and clump into groups, as small as four atoms apiece in some cases, that scatter light and appear dark on the frame. Various other types of film can be made using a similar process to detect other specific wavelengths of light, including x-rays, infrared, and ultraviolet.

One of the first working examples of a synthetic nanosensor was built by researchers at the Georgia Institute of Technology in 1999. It involved attaching a single particle onto the end of a carbon nanotube and measuring the vibrational frequency of the nanotube both with and without the particle. The discrepancy between the two frequencies allowed the researchers to measure the mass of the attached particle.

Chemical sensors, too, have been built using nanotubes to detect various properties of gaseous molecules. Carbon nanotubes have been used to sense ionization of gaseous molecules while nanotubes made out of titanium have been employed to detect atmospheric concentrations of hydrogen at the molecular level. Many of these involve a system by which nanosensors are built to have a specific pocket for another molecule. When that particular molecule, and only that specific molecule, fits into the nanosensor, and light is shone upon the nanosensor, it will reflect different wavelengths of light and, thus, be a different color

Microarray fabrication

The microarray -- the dense, two-dimensional grid of biosensors -- is the critical component of a biochip platform. Typically, the sensors are deposited on a flat substrate, which may either be passive (e.g. silicon or glass) or active, the latter consisting of integrated electronics or micromechanical devices that perform or assist signal transduction. Surface chemistry is used to covalently bind the sensor molecules to the substrate medium. The fabrication of microarrays is non-trivial and is a major economic and technological hurdle that may ultimately decide the success of future biochip platforms. The primary manufacturing challenge is the process of placing each sensor at a specific position (typically on a Cartesian grid) on the substrate. Various means exist to achieve the placement, but typically robotic micro-pipetting (Schena, 1995) or micro-printing (MacBeath, 1999) systems are used to place tiny spots of sensor material on the chip surface. Because each sensor is unique, only a few spots can be placed at a time. The low-throughput nature of this process results in high manufacturing costs.

Fodor and colleagues developed a unique fabrication process (later used by Affymetrix) in which a series of microlithography steps is used to combinatorially synthesize hundreds of thousands of unique, single-stranded DNA sensors on a substrate one nucleotide at a time (Fodor, 1991; Pease, 1994). One lithography step is needed per base type; thus, a total of four steps is required per nucleotide level. Although this technique is very powerful in that many sensors can be created simultaneously, it is currently only feasible for creating short DNA strands (15-25 nucleotides). Reliability and cost factors limit the number of photolithography steps that can be done. Furthermore, light-directed combinatorial synthesis techniques are not currently possible for proteins or other sensing molecules.

As noted above, most microarrays consist of a Cartesian grid of sensors. This approach is used chiefly to map or "encode" the coordinate of each sensor to its function. Sensors in these arrays typically use a universal signaling technique (e.g. fluorescence), thus making coordinates their only identifying feature. These arrays must be made using a serial process (i.e. requiring multiple, sequential steps) to ensure that each sensor is placed at the correct position.

"Random" fabrication, in which the sensors are placed at arbitrary positions on the chip, is an alternative to the serial method. The tedious and expensive positioning process is not required, enabling the use of parallelized self-assembly techniques. In this approach, large batches of identical sensors can be produced; sensors from each batch are then combined and assembled into an array. A non-coordinate based encoding scheme must be used to identify each sensor. As the figure shows, such a design was first demonstrated (and later commercialized by Illumina) using functionalized beads placed randomly in the wells of an etched fiber optic cable (Steemers, 2000; Michael, 1998) Each bead was uniquely encoded with a fluorescent signature. However, this encoding scheme is limited in the number of unique dye combinations that be can be used and successfully differentiated.

DNA microarray

A DNA microarray is a high-throughput technology used in molecular biology and in medicine. It consists of an arrayed series of thousands of microscopic spots of DNA oligonucleotides, called features, each containing picomoles of a specific DNA sequence. This can be a short section of a gene or other DNA element that are used as probes to hybridize a cDNA or cRNA sample (called target) under high-stringency conditions. Probe-target hybridization is usually detected and quantified by fluorescence-based detection of fluorophore-labeled targets to determine relative abundance of nucleic acid sequences in the target.

In standard microarrays, the probes are attached to a solid surface by a covalent bond to a chemical matrix (via epoxy-silane, amino-silane, lysine, polyacrylamide or others). The solid surface can be glass or a silicon chip, in which case they are commonly known as gene chip or colloquially Affy chip when an Affymetrix chip is used. Other microarray platforms, such as Illumina, use microscopic beads, instead of the large solid support. DNA arrays are different from other types of microarray only in that they either measure DNA or use DNA as part of its detection system.

DNA microarrays can be used to measure changes in expression levels or to detect single nucleotide polymorphisms (SNPs) (see Types of arrays section). Microarrays also differ in fabrication, workings, accuracy, efficiency, and cost (see fabrication section). Additional factors for microarray experiments are the experimental design and the methods of analyzing the data (see Bioinformatics section).

Uses and types

Arrays of DNA can be spatially arranged, as in the commonly known gene chip (also called genome chip, DNA chip or gene array), or can be specific DNA sequences labelled such that they can be independently identified in solution. The traditional solid-phase array is a collection of microscopic DNA spots attached to a solid surface, such as glass, plastic or silicon biochip. The affixed DNA segments are known as probes (although some sources use different terms such as reporters). Thousands of them can be placed in known locations on a single DNA microarray.

DNA microarrays can be used to detect DNA (as in comparative genomic hybridization), or detect RNA (most commonly as cDNA after reverse transcription) that may or may not be translated into proteins. The process of measuring gene expression via cDNA is called expression analysis or expression profiling.

Since an array can contain tens of thousands of probes, a microarray experiment can accomplish that many genetic tests in parallel. Therefore arrays have dramatically accelerated many types of investigation.

Protein Biochip Array and Other Microarray Technologies

Micro arrays are not limited to DNA analysis; protein microarrays, antibody microarray, Chemical Compound Microarray can also be produced using biochips. Randox Laboratories Ltd. launched Evidence, the first protein Biochip Array Technology analyzer in 2003. In protein Biochip Array Technology, the biochip replaces the ELISA plate or cuvette as the reaction platform. The biochip is used to simultaneously analyze a panel of related tests in a single sample, producing a patient profile. The patient profile can be used in disease screening, diagnosis, monitoring disease progression or monitoring treatment. Performing multiple analyses simultaneously, described as multiplexing, allows a significant reduction in processing time and the amount of patient sample required. Biochip Array Technology is a novel application of a familiar methodology, using sandwich, competitive and antibody-capture immunoassays. The difference from conventional immunoassays is that the capture ligands are covalently attached to the surface of the biochip in an ordered array rather than in solution.

In sandwich assays an enzyme-labelled antibody is used; in competitive assays an enzyme-labelled antigen is used. On antibody-antigen binding a chemiluminescence reaction produces light. Detection is by a charge-coupled device (CCD) camera. The CCD camera is a sensitive and high-resolution sensor able to accurately detect and quantify very low levels of light. The test regions are located using a grid pattern then the chemiluminescence signals are analysed by imaging software to rapidly and simultaneously quantify the individual analytes.

Biochip

The development of biochips is a major thrust of the rapidly growing biotechnology industry, which encompasses a very diverse range of research efforts including genomics, proteomics, computational biology, and pharmaceuticals, among other activities. Advances in these areas are giving scientists new methods for unraveling the complex biochemical processes occurring inside cells, with the larger goal of understanding and treating human diseases. At the same time, the semiconductor industry has been steadily perfecting the science of microminiaturization. The merging of these two fields in recent years has enabled biotechnologists to begin packing their traditionally bulky sensing tools into smaller and smaller spaces, onto so-called biochips. These chips are essentially miniaturized laboratories that can perform hundreds or thousands of simultaneous biochemical reactions. Biochips enable researchers to quickly screen large numbers of biological analytes for a variety of purposes, from disease diagnosis to detection of bioterrorism agents.

Microarray fabrication

The microarray -- the dense, two-dimensional grid of biosensors -- is the critical component of a biochip platform. Typically, the sensors are deposited on a flat substrate, which may either be passive (e.g. silicon or glass) or active, the latter consisting of integrated electronics or micromechanical devices that perform or assist signal transduction. Surface chemistry is used to covalently bind the sensor molecules to the substrate medium. The fabrication of microarrays is non-trivial and is a major economic and technological hurdle that may ultimately decide the success of future biochip platforms. The primary manufacturing challenge is the process of placing each sensor at a specific position (typically on a Cartesian grid) on the substrate. Various means exist to achieve the placement, but typically robotic micro-pipetting (Schena, 1995) or micro-printing (MacBeath, 1999) systems are used to place tiny spots of sensor material on the chip surface. Because each sensor is unique, only a few spots can be placed at a time. The low-throughput nature of this process results in high manufacturing costs.

Fodor and colleagues developed a unique fabrication process (later used by Affymetrix) in which a series of microlithography steps is used to combinatorially synthesize hundreds of thousands of unique, single-stranded DNA sensors on a substrate one nucleotide at a time (Fodor, 1991; Pease, 1994). One lithography step is needed per base type; thus, a total of four steps is required per nucleotide level. Although this technique is very powerful in that many sensors can be created simultaneously, it is currently only feasible for creating short DNA strands (15-25 nucleotides). Reliability and cost factors limit the number of photolithography steps that can be done. Furthermore, light-directed combinatorial synthesis techniques are not currently possible for proteins or other sensing molecules.

As noted above, most microarrays consist of a Cartesian grid of sensors. This approach is used chiefly to map or "encode" the coordinate of each sensor to its function. Sensors in these arrays typically use a universal signaling technique (e.g. fluorescence), thus making coordinates their only identifying feature. These arrays must be made using a serial process (i.e. requiring multiple, sequential steps) to ensure that each sensor is placed at the correct position.

"Random" fabrication, in which the sensors are placed at arbitrary positions on the chip, is an alternative to the serial method. The tedious and expensive positioning process is not required, enabling the use of parallelized self-assembly techniques. In this approach, large batches of identical sensors can be produced; sensors from each batch are then combined and assembled into an array. A non-coordinate based encoding scheme must be used to identify each sensor. As the figure shows, such a design was first demonstrated (and later commercialized by Illumina) using functionalized beads placed randomly in the wells of an etched fiber optic cable (Steemers, 2000; Michael, 1998) Each bead was uniquely encoded with a fluorescent signature. However, this encoding scheme is limited in the number of unique dye combinations that be can be used and successfully differentiated.

Industrial biotechnology

Industrial biotechnology (known mainly in Europe as white biotechnology) is the application of biotechnology for industrial purposes, including manufacturing, alternative energy (or "bioenergy"), and biomaterials. It includes the practice of using cells or components of cells like enzymes to generate industrially useful products. The Economist speculated (as cited in the Economist article listed in the "References" section) industrial biotechnology might significantly impact the chemical industry. The Economist also suggested it can enable economies to become less dependent on fossil fuels.

The industrial biotechnology community generally accepts an informal divide between industrial and pharmaceutical biotechnology. An example would be that of companies growing fungus to produce antibiotics, e.g. penicillin from the penicillium fungi. One view holds that this is industrial production; the other viewpoint is that such would not strictly lie within the domain of pure industrial production, given its inclusion within medical biotechnology.

This may be better understood in calling to mind the classification by the U.S. biotechnology lobby group, Biotechnology Industry Organization (BIO) of three "waves" of biotechnology. The first wave, Green Biotechnology, refers to agricultural biotechnology. The second wave, Red Biotechnology, refers to pharmaceutical and medical biotechnology. The third wave, White Biotechnology, refers to industrial biotechnology. In actuality, each of the waves may overlap. Industrial biotechnology, particularly the development of large-scale bioenergy refineries, will likely involve dedicated genetically modified crops as well as the large-scale bioprocessing and fermentation as is used in some pharmaceutical production.

Genencor International and Novozymes are examples of companies that specialize in industrial biotechnology, with particular focuses on specially designed enzymes to catalyze industrially relevant chemical reactions.

Biomaterial - New area of science

The development of biomaterials is not a new area of science, having existed for around half a century. The study of biomaterials is called biomaterial science. It is an exciting field of science, having experienced steady and strong growth over its history with companies such as Smith and Nephew investing large amounts of money in new products. Biomaterials science encompasses elements of medicine, biology, chemistry and materials science.

Definition of a biomaterial

While a definition for biomaterials has been difficult to formulate, a widely accepted definition for biomaterials is that:

"A biomaterial is any material, natural or man-made, that comprises whole or part of a living structure or biomedical device which performs, auguments, or replaces a natural function".

" A Biomaterial is a nonviable material used in medical device, intended to interact with a biological systems (William 1987)"

A biomaterial is essentially a material that is used and adapted for a medical application. Biomaterials can have a benign function, such as being used for a heart valve, or may be bioactive and used for a more interactive purpose such as hydroxy-apatite coated hip implants (the Furlong Hip, by Joint Replacement Instrumentation Ltd, Sheffield is one such example – such implants are lasting upwards of twenty years). Biomaterials are also used every day in dental applications, surgery, and drug delivery (a construct with impregnated pharmaceutical products can be placed into the body, which permits the prolonged release of a drug over an extended period of time).

The definition of a biomaterial does not just include man-made materials which are constructed of metals or ceramics. A biomaterial may also be an autograft, allograft or xenograft used as a transplant material.

Biomaterial Applications

Biomaterials are used in:

* Joint replacements
* Bone plates
* Bone cement
* Artificial ligaments and tendons
* Dental implants for tooth fixation
* Blood vessel prostheses
* Heart valves
* Skin repair devices
* Cochlear replacements
* Contact lenses

Biomaterials must be compatible with the body, and there are often issues of biocompatibility which must be resolved before a product can be placed on the market and used in a clinical setting. Because of this, biomaterials are usually subjected to the same requirements of those suffered by new drug therapies. All manufacturing companies are also required to ensure traceability of all of their products so that if a defective product is discovered, others in the same batch may be traced.

Synthetic biology

The term synthetic biology has long been used to describe an approach to biology that attempts to integrate (or "synthesize") different areas of research in order to create a more holistic understanding of life. More recently the term has been used in a different way, signaling a new area of research that combines science and engineering in order to design and build ("synthesize") novel biological functions and systems. The present article discusses the term in this latter meaning.

History of the term - Synthetic biology

In 1974, the Polish geneticist Waclaw Szybalski introduced the term "synthetic biology", writing: Let me now comment on the question "what next". Up to now we are working on the descriptive phase of molecular biology. ... But the real challenge will start when we enter the synthetic biology phase of research in our field. We will then devise new control elements and add these new modules to the existing genomes or build up wholly new genomes. This would be a field with the unlimited expansion potential and hardly any limitations to building "new better control circuits" and ..... finally other "synthetic"organisms, like a "new better mouse". ... I am not concerned that we will run out exciting and novel ideas, ... in the synthetic biology, in general. When in 1978 the Nobel Prize in Physiology or Medicine was awarded to Arber, Nathans and Smith for the discovery of restriction enzymes, Waclaw Szybalski wrote in an editorial comment in the journal Gene: The work on restriction nucleases not only permits us easily to construct recombinant DNA molecules and to analyze individual genes, but also has led us into the new era of synthetic biology where not only existing genes are described and analyzed but also new gene arrangements can be constructed and evaluated. Nevertheless, the term was largely unused or abandoned until the early 21st century (e.g., SB1.0, the First International Meeting on Synthetic Biology, was held in 2004).

Biology

Biologists are interested in learning more about how natural living systems work. One simple, direct way to test our current understanding of a natural living system is to build an instance (or version) of the system in accordance with our current understanding of the system. Michael Elowitz's early work on the Repressilator is one good example of such work. Elowitz had a model for how gene expression should work inside living cells. To test his model, he built a piece of DNA in accordance with his model, placed the DNA inside living cells, and watched what happened. Slight differences between observation and expectation highlight new science that may be well worth doing. Work of this sort often makes good use of mathematics to predict and study the dynamics of the biological system before experimentally constructing it. A wide variety of mathematical descriptions have been used with varying accuracy, including graph theory, Boolean networks, ordinary differential equations, stochastic differential equations, and Master equations (in order of increasing accuracy). Good examples include the work of Adam Arkin, Jim Collins and Alexander van Oudenaarden. See also the PBS Nova special on artificial life.

Bio-based material

A bio-based material is simply an engineering material made from substances derived from living matter. These materials are sometimes referred to as biomaterials, but this word also has another meaning. Strictly the definition could include many common materials such as wood and leather, but it typically refers to modern materials that have undergone more extensive processing. Unprocessed materials may be called biotic material.

Bio-based materials are often biodegradable, but this is not always the case.

Examples include:

* casein- A phosphoprotein extracted from milk during the process of creating low fat milk, it is processed in various ways to make: plastic, dietary suppliments for body builders, glue, cotton candy, glue, protective coatings, paints, and occurs naturally in cheese, giving it a creamy texture.
* polylactic acid - a polymer produced by industrial fermentation
* bioplastics - including a soy oil based plastic now being used to make body panels for John Deere tractors
* engineered wood products such as oriented strand board and particle board
* zein - a natural biopolymer which is the most abundant corn protein
* cornstarch - the starch of the maize grain, used to make packing pellets

Specific uses of the term Bionics

In medicine

Bionics is a term which refers to flow of ideas from biology to engineering and vice versa. Hence, there are two slightly different points of view regarding the meaning of the word.

In medicine, Bionics means the replacement or enhancement of organs or other body parts by mechanical versions. Bionic implants differ from mere prostheses by mimicking the original function very closely, or even surpassing it.

Bionics' German equivalent "Bionik" always takes the broader scope in that it tries to develop engineering solutions from biological models. This approach is motivated by the fact that biological solutions will always be optimized by evolutionary forces.

While the technologies that make bionic implants possible are still in a very early stage, a few bionic items already exist, the best known being the cochlear implant, a device for deaf people. By 2004 fully functional artificial hearts were developed. Significant further progress is expected to take place with the advent of nanotechnologies. A well known example of a proposed nanodevice is a respirocyte, an artificial red cell, designed (though not built yet) by Robert Freitas.

Kwabena Boahen from Ghana was a professor in the Department of Bioengineering at the University of Pennsylvania. During his eight years at Penn, he developed a silicon retina that was able to process images in the same manner as a living retina. He confirmed the results by comparing the electrical signals from his silicon retina to the electrical signals produced by a salamander eye while the two retinas were looking at the same image.

Other uses

In a more specific meaning, it is a creativity technique that tries to use biological prototypes to get ideas for engineering solutions. This approach is motivated by the fact that biological organisms and their organs have been well optimized by evolution. In chemistry, a biomimetic synthesis is a man-made chemical synthesis inspired by biochemical processes.

Another, more recent meaning of the term "bionics" refers to merging organism and machine. This approach results in a hybrid systems combining biological and engineering parts, which can also be referred as cybernetic organism (cyborg). Practical realisation of this was demonstrated in Kevin Warwick's implant experiments bringing about ultrasound input via his own nervous system.

In 2006 Mercedes-Benz introduced its Bionic concept car.

Examples of Biomimetics

* Velcro is the most famous example of biomimetics. In 1948, the Swiss engineer George de Mestral was cleaning his dog of burrs picked up on a walk when he realized how the hooks of the burrs clung to the fur.

* Cat's eye reflectors were invented by Percy Shaw in 1935 after studying the mechanism of cat eyes. He had found that cats had a system of reflecting cells, known as tapetum lucidum, which was capable of reflecting the tiniest bit of light.

* Leonardo da Vinci's flying machines and ships are early examples of drawing from nature in engineering.

* Julian Vincent drew from the study of pinecones when he developed in 2004 "smart" clothing that adapts to changing temperatures. "I wanted a nonliving system which would respond to changes in moisture by changing shape", he said. "There are several such systems in plants, but most are very small — the pinecone is the largest and therefore the easiest to work on". Pinecones respond to warmer temperatures by opening their scales (to disperse their seeds). The smart fabric does the same thing, opening up when it is warm, and shutting tight when cold.

* "Morphing aircraft wings" that change shape according to the speed and duration of flight were designed in 2004 by biomimetic scientists from Penn State University. The morphing wings were inspired by different bird species that have differently shaped wings according to the speed at which they fly. In order to change the shape and underlying structure of the aircraft wings, the researchers needed to make the overlying skin also be able to change, which their design does by covering the wings with fish-inspired scales that could slide over each other. In some respects this is a refinement of the swing-wing design.

* Some paints and roof tiles have been engineered to be self-cleaning by copying the mechanism from the Nelumbo lotus.

* Nanostructures and physical mechanisms that produce the shining color of butterfly wings were reproduced in silico by Greg Parker, professor of Electronics and Computer Science at the University of Southampton and research student Luca Plattner in the field of photonics, which is electronics using photons as the information carrier instead of electrons.

* The wing structure of the blue morpho butterfly was studied and the way it reflects light was mimicked to create an RFID tag that can be read through water and on metal.

* Neuromorphic chips, silicon retinae or cochleae, has wiring that is modelled after real neural networks. S.a.: connectivity

* Synthetic or "robotic" vegetation, which aids in conservation and restoration, are machines designed to mimic many of the functions of living vegetation.

* Medical adhesives involving glue and tiny nano-hairs are being developed based on the physical structures found in the feet of geckos.

Bionics

Bionics (also known as biomimetics, biognosis, biomimicry, or bionical creativity engineering) is the application of biological methods and systems found in nature to the study and design of engineering systems and modern technology. The word "bionic" was coined by Jack E. Steele in 1958, possibly originating from the Greek word "βίον", pronounced "bion", meaning "unit of life" and the suffix -ic, meaning "like" or "in the manner of", hence "like life". Some dictionaries, however, explain the word as being formed from "biology" + "electronics".

The transfer of technology between lifeforms and synthetic constructs is, according to proponents of bionic technology, desirable because evolutionary pressure typically forces living organisms, including fauna and flora, to become highly optimized and efficient. A classical example is the development of dirt- and water-repellent paint (coating) from the observation that the surface of the lotus flower plant is practically unsticky for anything (the lotus effect).

Examples of bionics in engineering include the hulls of boats imitating the thick skin of dolphins; sonar, radar, and medical ultrasound imaging imitating the echolocation of bats.

In the field of computer science, the study of bionics has produced artificial neurons, artificial neural networks, and swarm intelligence. Evolutionary computation was also motivated by bionics ideas but it took the idea further by simulating evolution in silico and producing well-optimized solutions that had never appeared in nature.

It is estimated by Julian Vincent, professor of biomimetics at the University of Bath in the UK, that "at present there is only a 10% overlap between biology and technology in terms of the mechanisms used".

History

The name biomimetics was coined by Otto Schmitt in the 1950s. The term bionics was coined by Jack E. Steele in 1958 while working at the Aeronautics Division House at Wright-Patterson Air Force Base in Dayton. However, biomimicry or biomimetics is more preferred in technology world in efforts to avoid confusion between the medical term bionics.

Classification of biopharmaceuticals

* Blood factors (Factor VIII and Factor IX)
* Thrombolytic agents (tissue plasminogen activator)
* Hormones (insulin, glucagon, growth hormone, gonadotrophins)
* Haematopoietic growth factors (Erythropoietin, colony stimulating factors)
* Interferons (Interferons-α, -β, -γ)
* Interleukin-based products (Interleukin-2)
* Vaccines (Hepatitis B surface antigen)
* Monoclonal antibodies (Various)
* Additional products (tumour necrosis factor, therapeutic enzymes)

Uses

* Erythropoietin - Treatment of anaemia
* Interferon-α - Treatment of leukaemia
* Interferon-β - Treatment of multiple sclerosis
* Monoclonal antibody - Treatment of rheumatoid arthritis
* Colony stimulating factors - Treatment of neutropenia
* Glucocerebrosidase - Treatment of Gaucher's disease


Large scale production

Biopharmaceuticals may be produced from microbial cells (e.g. recombinant E. coli or yeast cultures), mammalian cell lines (see cell culture) and plant cell cultures in bioreactors of various configurations.

Important issues of concern are cost of production (a low volume, high purity product is desirable) and microbial contamination (by bacteria, viruses, mycoplasma, etc). Alternative platforms of production which are being tested include whole plants (plant-made pharmaceuticals).

Biopharmaceutical

Biopharmaceuticals are medical drugs produced using biotechnology. They are proteins (including antibodies), nucleic acids (DNA, RNA or antisense oligonucleotides) used for therapeutic or in vivo diagnostic purposes, and are produced by means other than direct extraction from a native (non-engineered) biological source.

The first such substance approved for therapeutic use was biosynthetic 'human' insulin made via recombinant DNA technology. Sometimes referred to as rHI, under the trade name Humulin, was developed by Genentech, but licensed to Eli Lilly and Company, who manufactured and marketed the product starting in 1982.

The large majority of biopharmaceutical products are pharmaceuticals that are derived from life forms. Small molecule drugs are not typically regarded as biopharmaceutical in nature by the industry. However members of the press and the business and financial community often extend the definition to include pharmaceuticals not created through biotechnology. That is, the term has become an oft-used buzzword for a variety of different companies producing new, apparently high-tech pharmaceutical products.

When a biopharmaceutical is developed, the company will typically apply for a patent, which is a grant for exclusive manufacturing rights. This is the primary means by which the developer of the drug can recover the investment cost for development of the biopharmaceutical. The patent laws in the United States and Europe differ somewhat on the requirements for a patent, with the European requirements are perceived as more difficult to satisfy. The total number of patents granted for biopharmaceuticals has risen significantly since the 1970s. In 1978 the total patents granted was 30. This had climbed to 15,600 in 1995, and by 2001 there were 34,527 patent applications.

Within the United States, the Food and Drug Administration (FDA) exerts strict control over the commercial distribution of a pharmaceutical product, including biopharmaceuticals. Approval can require several years of clinical trials, including trials with human volunteers. Even after the drug is released, it will still be monitored for performance and safety risks.

The manufacture of the drug must satisfy the "current Good Manufacturing Practices" regulations of the FDA. They are typically manufactured in a clean room environment with set standards for the amount of airborne particles.

Techniques in systems biology

According to the interpretation of System Biology as the ability to obtain, integrate and analyze complex data from multiple experimental sources using interdisciplinary tools, some typical technology platforms are:

* Transcriptomics: whole cell or tissue gene expression measurements by DNA microarrays or serial analysis of gene expression
* Proteomics: complete identification of proteins and protein expression patterns of a cell or tissue through two-dimensional gel electrophoresis and mass spectrometry or multi-dimensional protein identification techniques (advanced HPLC systems coupled with mass spectrometry). Sub disciplines include phosphoproteomics, glycoproteomics and other methods to detect chemically modified proteins.
* Metabolomics: identification and measurement of all small-molecules metabolites within a cell or tissue
* Glycomics: identification of the entirety of all carbohydrates in a cell or tissue.

In addition to the identification and quantification of the above given molecules further techniques analyze the dynamics and interactions within a cell. This includes:

* Interactomics which is used mostly in the context of protein-protein interaction but in theory encompasses interactions between all molecules within a cell
* Fluxomics, which deals with the dynamic changes of molecules within a cell over time
* Biomics: systems analysis of the biome.

The investigations are frequently combined with large scale perturbation methods, including gene-based (RNAi, mis-expression of wild type and mutant genes) and chemical approaches using small molecule libraries. Robots and automated sensors enable such large-scale experimentation and data acquisition. These technologies are still emerging and many face problems that the larger the quantity of data produced, the lower the quality. A wide variety of quantitative scientists (computational biologists, statisticians, mathematicians, computer scientists, engineers, and physicists) are working to improve the quality of these approaches and to create, refine, and retest the models to accurately reflect observations.

The investigations of a single level of biological organization (such as those listed above) are usually referred to as Systematic Systems Biology. Other areas of Systems Biology includes Integrative Systems Biology, which seeks to integrate different types of information to advance the understanding the biological whole, and Dynamic Systems Biology, which aims to uncover how the biological whole changes over time (during evolution, for example, the onset of disease or in response to a perturbation). Functional Genomics may also be considered a sub-field of Systems Biology.

The systems biology approach often involves the development of mechanistic models, such as the reconstruction of dynamic systems from the quantitative properties of their elementary building blocks. instance, a cellular network can be modelled mathematically using methods coming from chemical kinetics and control theory. Due to the large number of parameters, variables and constraints in cellular networks, numerical and computational techniques are often used. Other aspects of computer science and informatics are also used in systems biology. These include new forms of computational model, such as the use of process calculi to model biological processes, the integration of information from the literature, using techniques of information extraction and text mining, the development of online databases and repositories for sharing data and models (such as BioModels Database), approaches to database integration and software interoperability via loose coupling of software, websites and databases the development of syntactically and semantically sound ways of representing biological models, such as the Systems Biology Markup Language.

Systems biology

Systems biology is a relatively new biological study field that focuses on the systematic study of complex interactions in biological systems, thus using a new perspective (integration instead of reduction) to study them. Particularly from year 2000 onwards, the term is used widely in the biosciences, and in a variety of contexts. Because the scientific method has been used primarily toward reductionism, one of the goals of systems biology is to discover new emergent properties that may arise from the systemic view used by this discipline in order to understand better the entirety of processes that happen in a biological system.

Systems biology can be considered from a number of different aspects:

* Some sources discuss systems biology as a field of study, particularly, the study of the interactions between the components of biological systems, and how these interactions give rise to the function and behavior of that system (for example, the enzymes and metabolites in a metabolic pathway).

* Other sources consider systems biology as a paradigm, usually defined in antithesis to the so-called reductionist paradigm, although fully consistent with the scientific method. The distinction between the two paradigms is referred to in these quotations:

"The reductionist approach has successfully identified most of the components and many of the interactions but, unfortunately, offers no convincing concepts or methods to understand how system properties emerge...the pluralism of causes and effects in biological networks is better addressed by observing, through quantitative measures, multiple components simultaneously and by rigorous data integration with mathematical models" Science.

"Systems biology...is about putting together rather than taking apart, integration rather than reduction. It requires that we develop ways of thinking about integration that are as rigorous as our reductionist programmes, but different....It means changing our philosophy, in the full sense of the term" Denis Noble

* Still other sources view systems biology in terms of the operational protocols used for performing research, namely a cycle composed of theory, computational modelling to propose specific testable hypotheses about a biological system, experimental validation, and then using the newly acquired quantitative description of cells or cell processes to refine the computational model or theory. Since the objective is a model of the interactions in a system, the experimental techniques that most suit systems biology are those that are system-wide and attempt to be as complete as possible. Therefore, transcriptomics, metabolomics, proteomics and high-throughput techniques are used to collect quantitative data for the construction and validation of models.

* Finally, some sources see it as a socioscientific phenomenon defined by the strategy of pursuing integration of complex data about the interactions in biological systems from diverse experimental sources using interdisciplinary tools and personnel.

This variety of viewpoints is illustrative of the fact that systems biology refers to a cluster of peripherally overlapping concepts rather than a single well-delineated field. However the term has widespread currency and popularity as of 2007, with chairs and institutes of systems biology proliferating worldwide.