WO2006065918A2

WO2006065918A2 - Methods of providing biochemical analyses

Info

Publication number: WO2006065918A2
Application number: PCT/US2005/045269
Authority: WO
Inventors: Andrey J. Zarur; Seth T. Rodgers
Original assignee: Bioprocessors Corp.
Priority date: 2004-12-14
Filing date: 2005-12-14
Publication date: 2006-06-22
Also published as: WO2006065918A3

Abstract

A method of providing information regarding a bioreaction is provided. Information obtained from operation of microbioreactors can be used to design and/or alter and/or operate large-scale bioreactors and large-scale bioreactions.

Description

METHODS OF PROVIDING BIOCHEMICAL ANALYSES

Field of the Invention

The invention relates to methods of providing information regarding a bioreaction and, in particular, to methods for providing information to a client regarding operation parameters for a bioreaction.

Related Art Large scale bioreactions are routinely used to produce a variety of end products including, for example, pharmaceutical agents, such as drugs. The bioreactions typically occur in large scale bioreactors that are used to control environmental factors and to contain the reactants and reaction media. Often, these bioreactions use live cells in a bioreactor to produce an end product. Large scale bioreactors may be designed to work on a continuous flow or a batch process basis and may include a variety of reactor designs including fermentors and fluidized bioreactors.

Variations in conditions in large scale bioreactors such as changes in temperature, pH, shear, nutrient levels, metabolite levels and oxygen concentration can have an affect on the efficiency and the outcome of the process. A slight change in one parameter (reaction condition) can substantially alter the output of a large scale bioreaction. While systems are typically designed to control these parameters within a range, there is often enough variation in a system to reduce or alter yields, shorten cell lifetimes or even to upset the reaction process. Often, an operator of a large scale bioreactor may not know if a system is operating under ideal conditions, and controls the reaction based on previous experience gained with similar large scale processes. If prototype or bench scale bioreactions are used to learn about reaction conditions, these reactions are typically run in flasks, beakers or well plates that cannot accurately model the many different reaction conditions that can be critical in a large scale bioreactor. Thus, trial and error on a large scale is often the method of choice for optimizing a large scale bioreaction. The time and expense involved in doing so is significant and results are often a compromise. A source of reliable predictive information facilitating the design and/or tuning of large scale bioreactors would, for instance, save time, money and energy. SUMMARY OF INVENTION

The subject matter of this application may involve, in some cases, interrelated products, alternative solutions to a particular problem, and/or a plurality of different uses of a single system or article.

Other advantages, features, and uses of the invention will become apparent from the following detailed description of non-limiting embodiments of the invention when considered in conjunction with the accompanying drawings, which are schematic and which are not intended to be drawn to scale. In the figures, each identical or nearly identical component that is illustrated in various figures typically is represented by a single numeral. For purposes of clarity, not every component is labeled in every figure, nor is every component of each embodiment of the invention shown where illustration is not necessary to allow those of ordinary skill in the art to understand the invention. In cases where the present specification and a document incorporated by reference include conflicting disclosure, the present specification shall control.

In one aspect, a method for providing bioreaction information to a client is provided, the method comprising receiving a description of a large scale cellular bioreaction from a client, obtaining microbioreaction output data representative of conditions defining values of different cellular reaction parameters, the outputs being representative of a range of existing reaction parameter values of the large scale bioreaction or adjusted reaction parameter values for potential use in the large scale bioreaction, and reporting at least one output value and/or a corresponding reaction parameter value to the client for use in determining and/or adjusting one or more reaction parameters of the large scale bioreaction. In another aspect, a method for providing bioreaction information to a client is provided, the method comprising receiving a request for cellular bioreaction information from a client, performing at least one bioreaction in a plurality of microbioreactors under a plurality of reaction conditions defined by values of different cellular reaction parameters, determining at least one output value resulting from at least one of the reaction conditions, and reporting the at least one output and/or a value of a cellular reaction parameter to the client for use in design and/or operation of a large scale bioreactor. In another aspect, a method for providing bioreaction information to a client is provided, the method comprising obtaining microbioreaction output data representative of conditions defining values of different cellular reaction parameters, and reporting at least one output value and/or a corresponding reaction condition to a client for use in designing, determining and/or adjusting one or more reaction parameters of a large scale bioreaction.

In another aspect, a method for providing bioreaction information to a client is provided, the method comprising computer-implemented steps of recording, from a plurality of cellular microbioreactions, output values representative of conditions defining values of different cellular reaction parameters and reporting at least one output value and/or a corresponding reaction condition to a client for use in designing, determining and/or adjusting one or more reaction parameters of a large scale bioreaction.

In another aspect, a computer readable medium is provided, the computer readable medium having computer readable signals stored thereon, the signals defining instructions that, as a result of being executed by a computer, control the computer to perform a process for providing bioreaction information, the process comprising acts of tabulating, from a plurality of cellular microbioreactions, outputs representative of conditions defining values of different cellular reaction parameters, and reporting at least one output value and/or a corresponding reaction condition for use in designing, determining and/or adjusting one or more reaction parameters of a large scale bioreaction.

BRIEF DESCRIPTION OF DRAWINGS The accompanying drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component that is illustrated in various figures is represented by a like numeral. For purposes of clarity, not every component may be labeled in every drawing. In the drawings:

FIG. 1 is a schematically illustrated example of a large scale bioreactor; and FIG. 2 is a flow chart illustrating several embodiments of the invention.

FIG. 3 is a block diagram illustrating an example of a computer system on which some embodiments of the invention may be implemented; and Fig. 4 is a block diagram illustrating an example of a storage system that may be used as part of the computer system to implement some embodiments of the invention.

DETAILED DESCRIPTION This invention is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The invention is capable of other embodiments and of being practiced or of being carried out in various ways. Also, the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of "including," "comprising," or "having," "containing," "involving," and variations thereof herein, is meant to encompass the items listed thereafter and equivalents thereof as well as additional items.

The invention relates to a method for providing information to a user to facilitate the operation of a large scale bioreaction. This information can be obtained from a plurality of microbioreactions, such as cellular microbioreactions. Information may also be obtained from archival sources, such as computers and notebooks, in which microbioreaction data has been recorded. The transferred information can include information on reaction parameters that may have an effect on the output of the large scale bioreactor. For example, transferred reaction parameter values may provide values for a specific parameter that can optimize production in a microbioreactor.

Each of the following commonly-owned applications directed to related subject matter and/or disclosing methods and/or devices and/or materials useful or potentially useful for the practice of the present invention is incorporated herein by reference: International Patent Publication No. WO 01/68257 published on September 20, 2001, entitled "Microreactor," by Jury, et al. ; U.S. Patent Publication No. 2003/0077817 published on April 24, 2003, entitled "Microfermentor Device and Cell Based Screening Method," by Zarur, et al. ; U.S. Patent Publication No. 2004/0058437 published on March 25, 2004, entitled "Materials and Reactor Systems having Humidity and Gas Control," by Rodgers, et al. ; U.S. Patent Publication No. 2004/0058407 published on March 25, 2004, entitled "Reactor Systems Having a Light-Interacting Component," by Miller,^ al.; U.S. Patent Publication -No. 2004/0121454 published on June 24, 2004, entitled "Microreactor," by Jury, et al. ; International Patent Publication No. WO 2004/016727 published on February 26, 2004, entitled "Determination and/or Control of Reactor Environmental Conditions," by Miller, et al; U.S. Patent Publication No. 2004/0132166 published on July 8, 2004, entitled "Determination and/or Control of Reactor Environmental Conditions," by Miller, et al; U.S. Patent Publication No. 2005/0106714 published on May 19, 2005, entitled "Rotatable Reactor Systems and Methods," by Zarur, et al ; U.S. Patent Publication No. 2005/0026273 published on February 3, 2005, entitled "Reactor with Memory Component," by Zarur, et al; U.S. Patent Publication No. 2005/0026134 published on February 3, 2005, entitled "Systems and Methods for Control of pH and Other Reactor Environmental Conditions," by Miller, et al; U.S. Patent Publication No. 2005/0032204 published on February 10,

2005, entitled "Microreactor Architecture and Methods," by Rodgers, et al; U.S. Patent Publication No. 2005/0271560 published on December 8, 2005, entitled "Gas Control in a Reactor," by Rodgers, et al; U.S. Patent Application Ser. No. 11/147,413 filed on June 7, 2005, entitled "Reactor Mixing" by Johnson, et al; U.S. Patent Application No. 60/577,987 filed on June 7, 2004, entitled "Reactor Mixing Apparatus and Method," by MacGregor, and Timothy Johnson, et al, U.S. Application Serial No. 11/147,416 filed on June 7, 2005, entitled "Creation of Shear in a Reactor," by Johnson, et al, U.S. Application Serial No. 60/636,182 filed on December 14, 2004, entitled "Microreactor Simulation of Macroreactor," by Zarur, et al. As used herein, a "bioreactor" is a reactor in which a chemical reaction takes place, at least part of that reaction involving the use of a living organism or part of a living organism.

A "large scale bioreactor" is a bioreactor that is used to produce a product for sale or for production of an intermediate of a product for sale. These products may be, for example, drugs. Large scale bioreactors typically have volumes in the range of liters or hundreds of liters or more.

A microbioreactor is a microreactor having a volume of less than 1 mL and which is typically used to analyze or evaluate a bioreaction, although, in some cases, microbioreactors can be used for production of a product. A "cellular bioreaction" is a bioreaction, at least. a part of which occurs in, or is facilitated by, a living cell. "Reaction parameters," or reaction conditions, or environmental factors are those factors that can affect a bioreaction. Reaction parameters can be, for example, physical, chemical or electrical. A reaction parameter value is a specific quantitative or qualitative value for the reaction parameter. Examples of exemplary reaction parameters are provided below.

Large scale bioreactor systems may not be truly optimized as it is difficult to independently control many of the parameters affecting output. Typically, when the same reaction as that run in a large scale bioreactor system is run as a prototype reaction on a smaller scale, these parameters can be difficult or impossible to transfer to a large scale bioreactor. This may be because the conditions in a large scale bioreactor are difficult or impossible to reproduce on a small scale, for instance, in a 96 well plate, a flask, or a petri dish. Important parameters such as, for example, oxygen concentration, pH and shear, are either impossible to control or alter in the small-scale environment or are so tightly coupled that a change in one parameter results in changes to one or more additional parameters, making it difficult or impossible to determine what change is responsible for an increase or decrease in production efficiency. For instance, a change in cell nutrient level during a course of a reaction can affect cell metabolism that in turn can alter the pH of the reaction media so that output is altered due to changes much more complex than simply the change in nutrient level. Furthermore, control of some reaction parameters, for example, shear stress on live cells, cannot be achieved in known small scale reactions to an extent where it can accurately replicate the shear stress to which cells are exposed in a large scale bioreaction. The present invention provides the ability to control various reaction parameters, with precision, that can assist in improving or modeling large scale bioreactions. In one aspect, a method is provided in which a client may provide information regarding a large scale bioreaction to an entity that then uses that information in a series of microbioreactions to learn about the effects of changing parameters in the bioreaction. It has been determined that specific microbioreactors, such as those described herein and in documents incorporated herein, can provide a level of control for reaction parameters that can provide for accurate modeling of reactions occurring in large scale bioreactors. The microbioreactors can provide information on reaction parameters that enable or facilitate the client to operate the large scale bioreaction on a more efficient basis than could be achieved without the information and without extensive experimentation with the large scale system. Information received from the client may include, for example, a cell line used to produce the product, the shape and/or size of a reactor, or reaction conditions that are currently in use. The evaluator (the person or entity performing the microbioreactions) can then replicate the suggested reaction, or a similar or representative reaction, on a micro scale and alter a plurality of parameters such as, for example, pH, temperature, shear, CO₂ concentration, O₂ concentration, etc. The use of a plurality of micro-bioreactors can allow individual parameters to be de-coupled from each other to help determine the true effect of changing the value of a single parameter. Using a plurality of microbioreactors, many combinations and permutations of values for these parameters can be tested in order to provide information.

In another aspect, an evaluator may produce data without any prior input from a client. For example, the evaluator may start with a specific cell line capable of producing a desired product such as a peptide or protein. The evaluator can then set up a plurality of cellular microbioreactions in which a common cell type may be used in each reactor while one or more reaction parameters is varied among reactors.

The methods of the present invention may be used to enhance or alter the performance of a variety of large scale bioreactors. In particular, the methods may be used with cellular bioreactions that use vessels and systems for the culture of eukaryotic and/or prokaryotic organisms, and/or cell cultures derived from animals, insects, plants, bacteria, fungi, or yeast.

Cultures may be grown in suspension or attached to solid phase carriers operated in batch, fed batch, extended batch, repetitive batch, draw/fill, rotating- wall, spinning flask, semi-continuous, perfusion or any other continuous mode of operation. Examples of carrier systems include microcarriers (e.g., polymer spheres, microbeads, and microdisks that can be porous or non-porous), cross-linked beads (e.g., dextran) charged with specific chemical groups (e.g., tertiary amine groups), 2D microcarriers including cells trapped in nonporous polymer fibers, 3D carriers (e.g., carrier fibers, hollow fibers, multicartridge reactors, and semi-permeable membranes that can comprising porous fibers), microcarriers having reduced ion exchange capacity, encapsulation cells, capillaries, and aggregates. Carriers can be fabricated from materials such as dextran, gelatin, glass, and cellulose. Examples of large scale bioreactors include stirred tank reactors, roller apparatuses (i.e., benchtop, cart-mounted, and/or automated varieties), vertically-stacked plates, spinner flasks, gentle stirring or rocking flasks, packed-bed reactors, fixed-bed reactors, fluidized bed reactors, shaken multiwell plates, MD bottles, T-flasks, Roux bottles, multiple-surface tissue culture propagators, modified fermentors, and coated beads (e.g., beads coated with serum proteins, nitrocellulose, or carboxymethyl cellulose to prevent cell attachment).

The bioreactions may include culture systems where cells are in contact with moving liquids and/or gas bubbles. Bioreactors of this type include, for example, stirred tank fermentors or bioreactors agitated by rotating mixing devices, chemostats, bioreactors agitated by shaking devices, airlift fermentors/bioreactors, fluidized bed bioreactors, bioreactors employing wave induced agitation, centrifugal bioreactors, roller bottles or other systems for the culture of animal or insect cells attached to polymer (such as plastic) surfaces, and hollow fiber bioreactors. A variety of different cells can be cultured in large- and micro-scale bioreactors and/or in micro-scale bioreactors in comiection with optimization and/or other study or modification of a large-scale process in accordance with the invention. For instance, cell cultures can be derived from sources such as animals (e.g., hamsters, mice, pigs, rabbits, dogs, and humans), insects (e.g., moths and butterflies), plants (e.g., corn, tomato, rice, wheat, barley, alfalfa, sugarcane, soybean, potato, lettuce, lupine, tobacco, rapeseed

(canola), sunflower, turnip, arabidopsis thaliana, taxus cuspidata, catharanthus roseus, beet cane molasses, seeds, safflower, and peanuts), bacteria, fungi, and yeast.

Non-limiting examples of animal cells include Chinese hamster ovary (CHO), mouse Myeloma, MO035 (NSO cell line), hybridomas (e.g., B-lymphocyte cells fused^ with myeloma tumor cells); baby hamster kidney (BHK), monkey COS, African green monkey kidney epithelial (VERO), mouse embryo fibroblasts (NIH-3T3), mouse connective tissue fibroblasts (L929), bovine aorta endothelial (BAE-I), mouse myeloma lymphoblastoid-like (NSO), mouse B-cell lymphoma lymphoblastoid (WEHI 231), mouse lymphoma lymphoblastoid (YAC 1), mouse fibroblast (LS), hepatic mouse (e.g., MC/9, NCTC clone 1469), and hepatic rat cells (e.g., ARL-6, BRL3A, H4S, Phi 1 (from Fu5 cells)). ^' - Cells from humans can include cells such as retinal cells (PER-C6), embryonic kidney cells (HEK-293), lung fibroblasts (MRC-5), cervix epithelial cells (HELA), diploid fibroblasts (WB 8), kidney epithelial cells (HEK 293), liver epithelial cells (HEPG2), lymphoma lymphoblastoid cells (Namalwa), leukemia lymphoblastoid-like cells (HL60), myeloma lymphoblastoid cells (U 266Bl ), neuroblastoma neuroblasts (SH- SY5Y), diploid cell strain cells (e.g., propagation of poliomyelitis virus), pancreatic islet cells, embryonic stem cells (hES), human mesenchymal stem cells (MSCs, which can be differentiated to osteogenic, chondrogenic, tenogenic, myogenic, adipogenic, and marrow stromal lineages, for example), human neural stem cells (NSC), human histiocytic lymphoma lymphoblastoid cells (U937), and human hepatic cells such as

WRL68 (from embryo cells), PLC/PRF/5 (i.e., containing hepatitis B sequences), Hep3B (i.e., producing plasma proteins: fibrinogen, alpha-fetoprotein, transferrin, albumin, complement C3 and/or aplpha-2-macroglobulin), and HepG2 (i.e., producing plasma proteins: prothrombin, antithrombin III, alpha-fetoprotein, complement C3, and/or fibrinogen).

In some instances, cells from insects (e.g., baculovirus and Spodoptera frugiperda ovary (Sf21 cells produce Sf9 line)) and cells from plants and/or food can be cultured. For instance, cells from sources such as rice (e.g., Oryza sativa, Oryza sativa cv Bengal callus culture, and Oryza sativa cv Taipei 309), soybean (e.g., Glycine max cv Williams 82), tomato (Lycopersicum esculentum cv Seokwang), and tobacco leaves (e.g., Agrobacterium tumefaciens including Bright Yellow 2 (BY-2), Nicotiana tabacum cv NT-I, N. tabacum cv BY-2, and N. tabacum cv Petite Havana SR-I) can be cultured in various types of bioreactors as described herein.

In other instances, cells from various sources of bacteria, fungi, or yeast can be cultured in bioreactor systems. Non-limiting examples of bacteria include Salmonella, Escherichia coli, Vibrio cholerae, Bacillus subtilis, Streptomyces, Pseudomonas fluorescens, Pseudomonas putida, Pseudomonas sp, Rhodococcus sp, Streptomyces sp, and Alcaligenes sp. Fungal cells can be cultured from species such as Aspergillus niger and Trichoderma reesei, and yeast cells can include cells from Hansenula polymorpha, Pichia pastoris, Saccharomyces cerevisiae, S. cerevisiae crossed with S. bay anus, S. cerevisiae crossed with LAC4 and LACl 2 genes from K. lactis, S. cerevisiae crossed with Aspergillus shirousamii, Bacillus subtilis, Saccharomyces diastasicus, Schwanniomyces occidentalis, S. cerevisiae with genes from Pichia stipitis, and Schizosaccharomyces pombe.

In some cases, it may be appropriate to add additives (e.g., nutrients and enzymes) to cells being cultured in a bioreactor. Non-limiting examples of additives include amino acids, bovine serum albumin, growth factors (e.g., hepatocyte growth factor), inhibitors (e.g., protease inhibitors), fatty acids, lipids, hormones (e.g., dexamethasone and gibberellic acid), trace elements, inorganic compounds (e.g., reducing manganese), stabilizing agents (e.g., dimethylsulfoxide), polyethylene glycol, polyvinylpyrrolidone (PVP), gelatin, antibiotics (e.g., Brefeldin A), salts (e.g., NaCl), chelating agents (e.g., EDTA, EGTA), and enzymes (e.g., dispase, hyaluronidase, and DNAase).

Reaction parameters can include, for example, chemical concentration, mechanical treatment, temperature and light. Some of the reaction parameters that can be evaluated/determined/transferred include, for example: temperature, pH, shear stress, shear rate, dissolved gases,. such as oxygen concentration and CO₂ concentration, nutrient concentrations, metabolite concentrations, glucose concentration, glutamine concentration, pyruvate concentration, apatite concentration, relative humidity, molarity, osmolarity, color, turbidity, viscosity, a concentration of an amino acid, a concentration of a vitamin, a concentration of a hormone, concentration of an additive, serum concentration, ionic strength, a concentration of an ion, degree of agitation, pressure, and a concentration of an oligopeptide, flow rate, light, cell condition, etc.

These reaction parameters and others may be optimized using microbioreactors and then reproduced in a large scale bioreactor to achieve or approach the results obtained in the microbioreactions. In some large scale bioreactors, and probably in most or all large scale bioreactors, environmental factors may not be consistent throughout the reactor volume. As a result, reaction sites, for example, cells, may be exposed to different conditions that provide for uneven, and sometimes inefficient, operation throughout the reactor. Some environmental factors can be affected due to the specific design and/or operation of the reactor. For example, gravitational forces can serve to separate components of different density, and, even with mixing, the contents of the reactor vessel might not be kept homogeneous. In another example, portions of the reactor contents that are closer to a liquid/gas interface (eg, the surface) may have higher (or lower) gas concentrations than do portions that are not close to the liquid/gas interface. Shear stress forces within a vessel may vary greatly among different locations, depending, in part, on the type of mixer being used. Temperature variations may exist as well, as vessels that require heating or cooling are seldom heated or cooled uniformly. In some cases, these variations in environmental factors at differing locations within a reactor can be determined, or at least estimated.

The nature of a large scale bioreactor can make it difficult to adjust or tune reaction conditions to optimize or improve long term production. This may be particularly true for cellular bioreactions where each cell may provide a reactive site that is not stationary in the large scale bioreactor but rather moves to different locations within the reactor. Each of these locations may exhibit different reaction conditions. Despite designs aimed at producing a homogeneous environment within a large scale bioreactor, there are inherent factors that prevent true homogeneity from being maintained. Differences in pressure, temperature, dissolved gas concentration, shear stress, and light, for example, cannot be totally eliminated. Although these and other reaction conditions can often be measured at different locations within a large scale bioreactor, the measured conditions are often not indicative of the conditions to which cells are exposed over time because cells participating in the reaction typically are present at any specific location for only a very short duration. During a large scale bioreaction process (typically taking longer than several hours, unlike many chemical reactions) any cells taking part in the reaction are exposed to conditions throughout the large scale bioreactor, and any one of these conditions can alter or even cease cell activity. Thus, although conditions at many locations in a large scale bioreaction may be measurable, knowledge of these conditions does not provide the predictive data necessary to optimize production conditions.

Likewise, replication of large scale bioreaction conditions on a traditional small scale, such as in flasks or 96 well plates, falls short of being able to accurately reproduce the'reaction conditions in-large scale reactors and therefore cannot provide data adequate to used to predictively optimize large scale bioreactor conditions. This lack of useful data occurs, in part, because large scale reaction conditions typically cannot be replicated in smaller reaction vessels with a level of control over a time period necessary to determine meaningful effects on output. For instance, attempts to maintain a constant pH in a specific well of a 96 well plate for greater than 1 hour are hampered by external factors such as gas exchange, evaporation, and cellular-induced changes to the medium. In addition, some important reaction conditions, such as shear stress and cell distribution may not be adjustable or controllable at all in traditional small scale reaction vessels or at least not with the precision necessary to learn enough about, or model, large scale reactions to be useful.

The cellular microbioreactors and microbioreactions described herein can provide a level of adjustment and control that allows an operator to obtain data after a meaningful time period. A meaningful time period is a length of time adequate to detect a change in cellular activity that has an effect on the reaction. Reaction conditions can be maintained within ranges that provide results allowing the reaction conditions to be transferred to large scale bioreactors with a corresponding effect on large scale bioreactor results. Using the microbioreactions described herein, discrete conditions occurring at specific locations in a large scale bioreactor can be duplicated on a micro scale. For example, 1,000 different microbioreactions can be run with each of the microbioreactions using different values for the environmental factors that are representative of 1,000 different locations or other factors such as differences in time of reaction, in a large scale bioreactor. As a result, reaction conditions at a specific location in a large scale bioreactor can be predictively adjusted or even optimized, or the overall reaction condition of the large scale reactor can be altered by accounting for the environmental factors at a plurality (eg, 10, 100, 1000 or 10,000) of sites within the large scale reactor, for example. An adjustment based on individual location evaluations within a large scale bioreactor can result in overall improvements to bioreactor efficiency and production. Adjustments may also be made based on average values in the large scale bioreactor.

A variety of different end products can be produced in large- and micro-scale bioreactors and/or in micro-scale bioreactors in connection with optimization and/or other study or modification of a large-scale process in accordance with the invention. Products of a bioreactor can include proteins (i.e., antibodies and enzymes), vaccines, viral products, hormones, immunoregulators, metabolites, fatty acids, vitamins, drugs, antibiotics, cells, and tissues. Non-limiting examples of proteins include human tissue plasminogen activators (tPA), blood coagulation factors, growth factors (e.g., cytokines, including interferons and chemokines), adhesion molecules, Bcl-2 family of proteins, polyhedrin proteins, human serum albumin, scFv antibody fragment, human erythropoietin, mouse monoclonal heavy chain γ, mouse IgG_2b/K, mouse IgG₁, heavy chain mAb, Bryondin 1 , human interleukin-2, human interleukin-4, ricin, human αl - antitrypisin, biscFv antibody fragment, immunoglobulins, human granulocyte, stimulating factor (hGM-CSF), hepatitis B surface antigen (HBsAg), human lysozyme, IL- 12, and mAb against HBsAg. Examples of plasma proteins include fibrinogen, alpha- fetoprotein, transferrin, albumin, complement C3 and aplpha-2-macroglobulin, prothrombin, antithrombin III, alpha-fetoprotein, complement C3 and fibrinogen, insulin, hepatitis B surface antigen, urate oxidase, glucagon, granulocyte-macrophage colony stimulating factor, hirudin/desirudin, angiostatin, elastase inhibitor, endostatin, epidermal growth factor analog, insulin-like growth factor- 1, kallikrein inhibitor, α-1 antitrypsin, tumor necrosis factor, collagen protein domains (but not whole collagen glycoproteins), proteins without metabolic byproducts, human albumin, bovine albumin, thrombomodulin, transferrin, factor VIII for hemophilia A (i.e., from CHO or BHK cells), factor Vila (i.e., from BHK), factor IX for hemophilia B (i.e., from CHO), human- secreted alkaline phosphatase, aprotinin, histamine, leukotrienes, IgE receptors, N- acetylglucosaminyltransferase-III, and antihemophilic factor VIII. Enzymes can be produced from a variety of sources in bioreactors. Non-limiting examples of such enzymes include YepACT-AMY-ACT-X24 hybrid enzyme from yeast, Aspergillus oryzae α-amylase, xylanases, urokinase, tissue plasminogen activator (rt-PA), bovine chymosin, glucocerebrosidase (therapeutic enzyme for Gaucher' s disease, from CHO), lactase, trypsin, aprotinin, human lactoferrin, lysozyme, and oleosines.

In some instances; vaccines can be produced in bioreactors. Non-limiting examples include vaccines for prostate cancer, human papilloma virus, viral influenza, trivalent hemagglutinin influenza, AIDS, HIV, malaria, anthrax, bacterial meningitis, chicken pox, cholera, diphtheria, haemophilus influenza type B, hepatitis A, hepatitis B, pertussis, plague, pneumococcal pneumonia, polio, rabies, human-rabies, tetanus, typhoid fever, yellow fever, veterinary-FMD, New Castle's Disease, foot and mouth disease, DNA, Venezuelan equine encephalitis virus, cancer (colon cancer) vaccines (i.e., prophylactic or therapeutic), MMR (measles, mumps, rubella), yellow fever, Haemophilus influenzae (Hib), DTP (diphtheria and tetanus vaccines, with pertussis subunit), vaccines linked to polysaccharides (e.g., Hib, Neisseria meningococcus), Staphylococcus pneumoniae, nicotine, multiple sclerosis, bovine spongiform encephalopathy (mad cow disease), IgGl (phosphonate ester), IgM (neuropeptide hapten), SIgA/G (Streptococcus mutans adhesin), scFv-bryodin 1 immunotoxin (CD-40), IgG (HSV), LSC (HSV), Norwalk virus, human cytomegalovirus, rotavirus, respiratory syncytial virus F, insulin-dependent autoimmune mellitus diabetes, diarrhea, rhinovirus, herpes simplex virus, and personalized cancer vaccines, e.g., for lymphoma treatment (i.e., in injectable, oral, or edible forms). In some cases, recombinant subunit vaccines can be produced, such as hepatitis B virus envelope protein, rabies virus glycoprotein, E. coli heat labile enterotoxin, Norwalk virus capsid protein, diabetes autoantigen, cholera toxin B subunit, cholera toxin B an dA2 subunits, rotavirus enterotoxin and enterotoxigenic E. coli, fimbrial antigen fusion, and porcine transmissible gastroenteritis virus glycoprotein S.

It may be desirable, in some cases, to produce viral products in bioreactors. Non- limiting examples of viral products include sindbis, VSV, oncorna, hepatitis A, channel cat fish virus, RSV, corona virus, FMDV, rabies, polio, reo virus, measles, and mumps. Hormones are another class of end products that can be produced in large-scale and/or micro-scale bioreactors. Non-limiting examples of hormones include growth hormone (e.g., human growth hormone (hGH) and bovine growth hormone), growth factors, beta and gamma interferon, vascular endothelial growth factor (VEGF), somatostatin, platelet-derived growth factor (PDGF), follicle stimulating hormone (FSH), luteinizing hormone, human chorionic hormone, and erythropoietin. Immunoregulators can also be produced in bioreactors. Non-limiting examples of immunoregulators include interferons (e.g., beta-interferon (for multiple sclerosis), alpha-interferon, and gamma-interferon) and interleukins (such as IL-2).

Metabolites (e.g., shikonin and paclitaxel) and fatty acids (i.e., including straight- chain (e.g., adipic acid, Azelaic acid, 2-hydroxy acids), branched-chain (e.g., 10-methyl octadecanoic acid and retinoic acid), ring-including fatty acids (e.g., coronaric acid and lipoic acid), and complex fatty acids (e.g., fatty acyl-CoA)) can also be produced in bioreactors. In some instances, commercial products, which can be used for treating various conditions, can be produced in bioreactors. Non-limiting examples of such products include Epogen® (i.e., for treating anemia), CamPath® (i.e., for treating chronic lymphocytic leukemia), Herceptin® (i.e., for treating metastatic breast cancer), Mylotarg® (i.e., for treating acute myeloid leukemia), Synagis® (i.e., for treating lower respiratory tract disease caused by respiratory syncytial virus (RSV)), Zenapax® (an immunosuppressive agent, i.e., for preventing organ rejection), Enbrel® (i.e., for treating conditions such as rheumatoid arthritis and ankylosing spondylitis), Humira® (i.e., for treating rheumatoid arthritis), Orthoclone OKT3® (i.e., for preventing organ rejections such as allograft rejections), Remicade® (i.e., for treating rheumatoid arthritis and Crohn's disease), ReoPro® (i.e., for preventing acute thrombosis from percutaneous transluminal coronary angioplasty (PTCA)), Rituxan® (for treating non-Hodgkin's lymphoma), and Simulect® (i.e., for the prophylaxis of acute organ rejection in patients receiving renal transplantation). Different methods of producing end products can be implemented in bioreactors.

In some embodiments, manipulation of gene expression in cells can be performed, and the cells can be cultured in bioreactors to produce one or more products (e.g., proteins) as a result of changes in expression. Different cell types and/or different reaction conditions within the bioreactor, for example, can influence the production of the end product. Methods for manipulation of gene expression can include transfection (i.e., infection of a cell with isolated viral nucleic acid followed by production of the complete virus in the cell), replacement of genes in cells, insertion of genes in cells (e.g., in plants cells using methods such as agrobacterium-mediated transformation, particle bombardment (biolistics), insertion into the separate genome of plastids (e.g., chloroplasts and mitochondria), chloroplast transformation in tobacco, potato, tomato, etc.), and recombinant DNA technologies such as PCR, DNA shuffling, and site-directed mutagenesis.

Other processes including xenotransplantation (e.g., transferring cells, tissues, or organs from an animal to cells, tissues, or organs from a human) and transdifferentiation (i.e., of multipotent stem cells) can also be performed in bioreactors.

FIG. 1 provides a schematic illustration of a conventional large scale bioreactor 100. The large scale bioreactor may include a tank 10, mixing blades 20 and a mixing shaft 30 supporting the blades. Locations P₀ and P₁ illustrate two different points in the reactor. Although the reactor contents may be well mixed and substantially homogeneous, the reaction conditions at points P₀ and P₁ may not be identical, especially in a reaction having a volume of greater than 1 liter, or greater than 10 liters, or greater than 100 liters. For example, the shear stress or another parameter, on a cell at point P₀ may be greater than the shear stress on a cell at point P₁. In addition, there are boundary effects as a vessel wall is approached. Therefore, optimization of reaction parameters at either one of these points may not result in optimization of the same parameters at any other point. In some cases, the conditions to which a cell is exposed at two or more locations can be averaged to arrive at an overall average large scale bioreactor condition, but this may not be an appropriate set of conditions for optimizing overall reaction parameters.

In some embodiments, average reaction conditions in a large scale bioreactor can be replicated or modeled in one or a plurality of microbioreactors. In others, reaction conditions from multiple locations can be modeled or replicated in multiple microbioreactors.

By creating reaction conditions in a series of microbioreactors that can represent the conditions at points throughout a large scale bioreactor, an evaluator can determine precisely the values that are optimal for a number of locations in a specific large scale bioreactor system. For instance, it might be determined that optimizing conditions at point P₁ (FIG. 1) results in a condition at P₀ that may be detrimental or fatal to cells in a bioreaction and vice versa. By testing a large number of reaction parameter values in a series of microbioreactors, conditions at, for example, 2, 3, 10, 100 or more locations in a large scale bioreactor can be evaluated. These evaluations may indicate that an average optimal reaction parameter value may be appropriate for a particular system or that the reaction parameter value should be skewed away from the average.

The evaluations may also show that a different large scale bioreactor design would result in improved yield, for instance, and may lead to partial or total re-design of the large scale reactor. It is notable that accurate reaction data from microscale bioreactors, as provided in the present invention, can provide information that is not obtainable from the large scale reactor itself. For example, a microbioreactor can provide data modeling the status of a cell subjected to the shear stress at point P₀ because the microbioreactor can apply those shear conditions for an amount of time (eg, > 1 minute or > 1 hour or > 1 day) that allows the effect on the cell or cells to be measured and quantified. A sampling of cells or reaction media from point P₀ in a large scale bioreactor would unlikely be able to provide this data because of the transient nature of the cells in the large scale bioreactor. For instance, any cell drawn from point P₀ during the bioreaction process would not have been subjected to conditions at point P₀ for an extended length of time (e.g., greater than 1 s or 1 min) and therefore the cell's status would not reflect the conditions at point P₀, but rather the result of the conditions at many different points throughout the large scale bioreactor. Conditions at point P₀ might, in fact, be detrimental to the cell but analysis of a sample drawn from point P₀ in a large scale reactor would not provide this information because, for example, the sample and its components are not stationary at point P₀ in a large scale bioreactor. However, extended testing in a microbioreactor under the same conditions would provide this information as the conditions and time under those conditions can be precisely controlled. Conditions at this point (and many others) may be critical to the overall output and viability of the system. Microbioreactors and techniques provided in accordance with the present invention can provide this information.

In another set of embodiments a large scale reactor can be designed from the ground up using information obtained from a plurality of microbioreactions. For example, after completing 10,000 microbioreactions with differing reaction parameter values, it might be determined that control of one, two, three or more factors is the most important for maximizing large scale product output. A large scale reactor design can then be chosen to optimize these values throughout. For instance, if oxygen concentration is found to be critical, an aeration system can be employed to improve oxygen content throughout the large scale reactor. In another instance, if a narrow temperature range is found to maximize cell life, several smaller large scale bioreactors may be used to decrease temperature variation within the reactor(s) or a different heat exchange system can be employed. Thus, the use of multiple microbioreactions to evaluate the effect of a large number of input parameter-values can be used to provide reaction information with a degree of certainty that can allow for the confident production of large scale bioreactors while minimizing the risk that major alterations to the^" large scale bioreactor or bioreaction will be required. Parameters such as pH, temperature, shear, CO₂ concentration, O₂ concentration, ionic strength etc. can be varied individually across an array of microbioreactors so that the effect of a slight change in any one of these parameters can be realized In some embodiments, an individual parameter can be varied across an array of microbioreactors while maintaining all other parameters, or a select group of parameters, substantially constant. By "substantially constant," it is meant that any measured changes in the value of these parameters are within a specific range that includes any error attributable to the measurement techniques used. See Table 1. Thus, if CO₂ concentration is a substantially constant parameter, then over a chosen time period, for example one hour, the measurement of the CO₂ concentration will be consistently within a range, such as, for example, +/- 0.1%, or another precision value.

In one embodiment, pH may be controlled to within 0.05 pH units. Similarly, oxygen and/or CO₂ concentrations can be controlled within a range of +/- 1% or +/- 0.1%. Shear stress may also be controlled within a range of +/- 10%, +/- 5%, +/- 1%, or +/- .1%. Many of these parameters can be controlled within a range that has been unattainable with other types of small scale reaction vessels. For example, reactions run in 96 well plates, reaction flasks, or Petri dishes have been unable to maintain these parameters at constant levels for extended time periods such as >10 minutes, >1 hour, or >1 day. As a result, methods previously known to those skilled in the art have been unable to achieve a level of precision that provides for the production of information that is useful in designing or operating a large scale microbioreactor. For instance, bioreactions run in 96-well plates do not present a level of control where a single parameter, for example, pH, can be varied without upsetting other parameters such as, for example, alkalinity or CO₂ concentration. Thus, these different parameters cannot be de-coupled using conventional techniques. Furthermore, on a micro scale, some parameters such as shear and/or pH and/or O₂ concentration and/or CO₂ concentration have been difficult to maintain in a-fixed range for a time period adequate to provide meaningful results. Bioreactions, and particularly cellular bioreactions, typically require substantial reaction times to produce measurable product or change in condition. If only short term results can be measured, these short term results are typically not indicative of results achievable over a longer term. Thus, to provide meaningful results that can be transferred to a large scale reaction, reactions typically should be run for extended time periods, for example, greater than 1 hour, 12 hours, 1 day, two days, five days, one week, two weeks, one month, or longer periods of time. In other embodiments, parameters may be controlled or varied over time within a particular range and need not be substantially constant. It is notable that the methods provided herein can provide more than just general information about how to run a bioreaction. Rather, the information that can be provided is specific information that can be directly replicated on a macro scale. For example, other methods are known that can determine from a Petri-dish or a 96-well plate that a particular cell thrives with a particular nutrient or over a specific temperature range, for example. But these methods are unable to control cellular reaction parameters at specific levels for extended periods of time. They might provide a broad pH range or oxygen concentration without knowing what point in that range is optimal or without knowing the effect of moving within that range or the effect on other reaction parameters due to movement in that range. As a result, the information is of limited use in large scale reactor operation, and trial and error in the large scale operation is typical used in an attempt to tune the system. However, the present invention includes methods to provide precise information gathered over time about a number of input parameters that provide information adequate to commence a large scale bioreaction resulting in successful production of cells, compounds or other end products. For example, the information provided may include a pH value maintained in a range of +/- 0.05 pH units for one hour, as well as an oxygen concentration maintained at a concentration range of +/- 0.1 millimolar for greater than 1 hour. If the effect on output is positive, these cellular reaction parameter values can be transferred to a large scale bioreactor and will contribute to the success of the bioreaction. The type of precise repeatable information that is useful in these circumstances can be provided, in some embodiments, by operating one or more cellular microbioreactors, such as a cellular microreactor array. A microbioreactor array allows for a plurality of reactions to be run simultaneously. For example, more than 10, more than 100, more than 1,000, or more than 10,000 microbioreactions can be run and/or monitored simultaneously or during overlapping time sequences. These microbioreactors can provide a level of control that is unobtainable with previously- known techniques. And it has now been found that information obtained using these microbioreactors can be transferred to a macrobioreaction to improve the performance of the macrobioreaction. The usefulness with large scale bioreactors is greatly increased by the ability to de-couple a large number of input parameters. For example, a series of 100 cellular microbioreactors may be run in parallel with all reaction parameters being identical except for one, for example, oxygen concentration. Thus, the oxygen concentration in each of the microbioreactors may differ from another microbioreactor by a small but detectable or predictable amount, for example, 0.1%. Other parameters, such as pH, ionic strength, CO₂ concentration, sheer, temperature, and nutrient level may be kept constant across the entire array. This level of control, unobtainable in 96-well plates or Petri-dishes or flasks, provides a dataset that reveals the true effect of varying the oxygen concentration (and only the oxygen concentration) in the reaction medium. While other techniques may purport to accurately vary or control the oxygen concentration, such variation or control cannot be transferred to macrobioreactors and may be accompanied by other uncontrollable changes, for example, changes in pH or CO₂ concentration. Thus, the oxygen data obtained from such a set of results may be of minimal'Use when applied to a large scale bioreactor because the effect of changes in oxygen concentration cannot be decoupled from changes due to other input parameters.

In some embodiments, these microbioreactor reaction parameter values can be held stable or consistent for an extended period of time (see, for example, Table 1). For example, an array of 100 microbioreactors can each retain a pH within a window of plus or minus 0.05 pH units over a period of greater than 1 hour, greater than one day, or greater than one week. This level of control for an extended period of time can provide valuable information as to cell viability and/or production efficiencies under these conditions. In some embodiments, the level of control is improved by knowing how many cells or how many live cells are in each microbioreactor. Other methods that may be able to hold these tolerances for seconds or even minutes cannot provide meaningful long-term results because output values, e.g., cell death, cell reproduction, product output, etc., are difficult to measure with any degree of accuracy over these limited time periods. ^'"^{• ■}" Adjustment of conditions in a large scale bioreactor, based upon information learned in activity carried out in a microbioreactor in accordance with the invention, can be carried out by those of ordinary skill in the art without undue experimentation. As one example, it may be that reaction in a large scale bioreactor is not occurring optimally. Via a series of reactions run in a microbioreactor array, it might be determined that within a particular temperature range, pH can vary by no more than a particular amount, but in another temperature range pH can vary more widely, while still resulting in good yield of product (and/or other good result). Or in another example it may be determined that within a particular range of balance of oxygen/carbon dioxide content, both pH and temperature can vary within particular ranges while still providing ^■good yield, but at a particular point in the oxygen/carbon dioxide ratio relationship, pH must be confined within a particular range and/or temperature must be confined within a particular range. While these are only hypothetical examples, they illustrate the type of information that can be learned using techniques and apparatus of the invention. Using that information, those of ordinary skill in the art, without undue experimentation, can readily adjust conditions within a large scale bioreactor to control oxygen/carbon dioxide balance, pH, temperature, and/or any other particular variable within whatever particular range is required throughout most of or all of the large scale bioreactor to maximize yield or otherwise optimize a particular process as desired. Those of ordinary skill in the art have, available to them, apparatus and knowledge for relatively precisely controlling temperature; pH, and content of various elements and compositions in a relatively uniform way throughout a large scale reactor for this purpose. The methods described herein may be computer implemented. Software and data can be stored on computer readable media and can be executed or accessed at a later date. Software can be used, for example, to obtain data, store data, organize data, correlate data and to provide information to a client. Data may include input parameters and/or output data from microbioreactions such as cellular microbioreactions. For example, in one embodiment, microbioreactor output data can be stored on computer readable media, correlated with corresponding reaction parameter values, processed to determine optimal values and can then be reported to a client in computer readable or human readable format. Microbioreaction output data representative of conditions defining values of different cellular reaction parameters may be obtained from sources such as a database on computer readable media. Output values and/or corresponding reaction conditions retrieved from the same database can then be reported to a client who may in turn use the data to determine and/or adjust parameters of a large scale bioreaction. Data stored on computer readable media may include, for example, time and date, location, client name, and input parameters such as temperature, pH, shear stress, shear rate, dissolved gases, such as oxygen concentration and CO₂ concentration, nutrient concentrations, metabolite concentrations, glucose concentration, glutamine concentration, pyruvate concentration, apatite concentration, relative humidity, molarity, osmolarity, color, turbidity, viscosity, a concentration of an amino acid, a concentration of a vitamin', a_^concentration of a hormone, serum concentration, ionic strength, a concentration of an ion, degree of agitation, pressure, and a concentration of an oligopeptide, flow rate, light, cell condition, etc. Also included may be output data such as cell viability, product output, product purity, cell reproduction, cell life, cell death, etc.

Some of the methods described herein and various embodiments and variations of the methods and acts, individually or in combination, may be defined by computer- readable signals tangibly embodied on or more computer-readable media, for example, non- volatile recording media, integrated circuit memory elements, or a combination thereof. Computer readable media can be any available media that can be accessed by a computer. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM,^' ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, other types of volatile and non- volatile memory, any other medium which can be used to store the desired information and which can accessed by a computer, and any suitable combination of the foregoing. Communication media typically embodies computer- readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct- wired connection, wireless media such as acoustic, RP, infrared and other wireless media, other types of communication media, and any suitable combination of the foregoing.

Computer-readable signals embodied on one or more computer-readable media may define instructions, for example, as part of one or more programs, that, as a result of being executed by a computer, instruct the computer to perform one or more of the functions described herein, and/or various embodiments, variations and combinations thereof. Such instructions may be written in any of a plurality of programming languages, for example, Java, Visual Basic, C, C#, or C++, Fortran, Pascal, Eiffel, Basic, COBOL, etc., or any of a variety of combinations thereof. The computer-readable media on which such instructions are embodied may reside on one or more of the components of any of systems described herein or known to those skilled in the art, may be distributed across one or more of such components, and may be in transition therebetween. - The computer-readable media may be transportable such that the instructions stored thereon can be loaded onto any computer system resource to implement the aspects of the present invention discussed herein. In addition, it should be appreciated that the instructions stored on the computer-readable medium, described above, are not limited to instructions embodied as part of an application program running on a host computer. Rather, the instructions may be embodied as any type of computer code (e.g., software or microcode) that can be employed to program a processor to implement the above-discussed aspects of the present invention.

It should be appreciated that any single component or collection of multiple components of a computer system, for example, the computer system described in relation to Figs. 3-4, that perform the functions described herein can be generically considered as one or more controllers that control such functions. The one or more controllers can be implemented in numerous ways, such as with dedicated hardware and/or firmware, using a processor that is programmed using microcode or software to perform the functions recited above or any suitable combination of the foregoing. Each of systems described herein and illustrated in FIG. 2, and components thereof, may be implemented using any of a variety of technologies, including software (e.g., C, C#, C++, Java, or a combination thereof), hardware (e.g., one or more application-specific integrated circuits), firmware (e.g., electrically-programmed memory) or any combination thereof. One or more of the components may reside on a single device (e.g., a computer), or one or more components may reside on separate, discrete devices. Further, each component may be distributed across multiple devices, and one or more of the devices may be interconnected.

Further, on each of the one or more devices that include one or more components of the systems, each of the components may reside in one or more locations on the system. For example, different portions of the components of these systems may reside in different areas of memory (e.g., RAM, ROM, disk, etc.) on the device. Each of such one or more devices may include, among other components, a plurality of known components such as one or more processors, a memory system, a disk storage system, one or more network interfaces, and one or more busses or other internal communication links interconnecting the various components. The systems, and components thereof, may be implemented using a computer system such as that described below in relation to Figs. 3 and 4.

• Various embodiments according to the invention may be implemented on one or more computer systems. These computer systems, may be, for example, general-purpose computers such as those based on Intel PENTIUM-type and XScale-type processors, Motorola PowerPC, Motorola DragonBall, IBM HPC, Sun UltraSPARC, Hewlett- Packard PA-RISC processors, any of a variety of processors available from Advanced Micro Devices (AMD) or any other type of processor. It should be appreciated that one or more of any type of computer system may be used to implement various embodiments of the invention.

A general-purpose computer system according to one embodiment of the invention is configured to perform any of the functions described above. It should be appreciated that the system may perform other functions and the invention is not limited to having any particular function or set of functions.

For example, various aspects of the invention may be implemented as specialized software executing in a general-purpose computer system 1000 such as that shown in Figure 3. The computer system 1000 may include a processor 1003 connected to one or more memory devices 1004, such as a disk drive, memory, or other device for storing data. Memory 1004 is typically used for storing programs and data during operation of the computer system 1000. Components of computer system 1000 may be coupled by an interconnection mechanism 1005, which may include one or more busses (e.g., between components that are integrated within a same machine) and/or a network (e.g., between components that reside on separate discrete machines). The interconnection mechanism 1005 enables communications (e.g., data, instructions) to be exchanged between system components of system 1000. Computer system 1000 also includes one or more input devices 1002, for example, a keyboard, mouse, trackball, microphone, touch screen, and one or more output devices 1001, for example, a printing device, display screen, speaker. In addition, computer system 1000 may contain one or more interfaces (not shown) that connect computer system 1000 to a communication network (in addition or as an alternative to the interconnection mechanism 1005.

The storage system 1006, shown in greater detail in Fig. 4, typically includes a computer readable and writeable nonvolatile recording medium 1101 in which signals are stored that define a program to be executed by the processor or information stored on or in the medium 1101 to be processed by the program. The medium may, for example, be a disk or flash memory. Typically, in operation, the processor causes data to be read from the nonvolatile recording medium 1101 into another memory 1102 that allows for faster access to the information by- the processor than does the medium 1101. This memory 1102 is typically a volatile, random access memory such as a dynamic random access memory (DRAM) or static memory (SRAM). It may be located in storage system 1006, as shown, or in memory system 1004, not shown. The processor 1003 generally manipulates the data within the integrated circuit memory 1004, 1102 and then copies the data to the medium 1101 after processing is completed. A variety of mechanisms are known for managing data movement between the medium 1101 and the integrated circuit memory element 1004, 1102, and the invention is not limited thereto. The invention is not limited to a particular memory system 1004 or storage system 1006.

The computer system may include specially-programmed, special-purpose hardware, for example, an application-specific integrated circuit (ASIC). Aspects of the invention may be implemented in software, hardware or firmware, or any combination thereof. Further, such methods, acts, systems, system elements and components thereof may. be implemented as -part of the- computer system described above or as an independent component. Although computer system 1000 is shown by way of example as one type of computer system upon which various aspects of the invention may be practiced, it should be appreciated that aspects of the invention are not limited to being implemented on the computer system as shown in Fig. 3. Various aspects of the invention may be practiced on one or more computers having a different architecture or components that that shown in pig,.3.

Computer system 1000 may be a general-purpose computer system that is programmable using a high-level computer programming language. Computer system 1000 may be also implemented using specially programmed, special purpose hardware. In computer system 1000, processor 1003 is typically a commercially available processor such as the well-known Pentium class processor available from the Intel Corporation. Many other processors are available. Such a processor usually executes an operating system which may be, for example, the Windows® 95, Windows® 98, Windows NT®, Windows® 2000 (Windows® ME), Windows® XP, Windows CE® or Pocket PC® operating systems available from the Microsoft Corporation, MAC OS System X available from Apple Computer, the Solaris Operating System available from Sun Microsystems, Linux available from various sources, UNIX available from various sources or Palm OS® available from Palmsource, Inc. Many other operating systems may be used. , ^ The processor and operating system together define a computer platform for which application programs in high-level programming languages are written. It should be understood that the invention is not limited to a particular computer system platform, processor, operating system, or network. Also, it should be apparent to those skilled in the art that the present invention is not limited to a specific programming language or computer system. Further, it should be appreciated that other appropriate programming languages and other appropriate computer systems could also be used.

One or more portions of the computer system may be distributed across one or more computer systems (not shown) coupled to a communications network. These computer systems also may be general-purpose computer systems. For example, various aspects of the invention may be distributed among one or more computer systems configured to provide a service (e.g., servers) to one or more client computers, or to perform an overall task as part of a distributed system. For example, various aspects of the invention may be performed on a client-server system that includes components distributed among one or more server systems that perform various functions according to various embodiments of the invention. These components may be executable, -intermediate (e.g., IL) or interpreted (e.g., Java) code which communicate over a communication network (e.g., the Internet) using a communication protocol (e.g., TCP/IP).

It should be appreciated that the invention is not limited to executing on any particular system or group of systems. Also, it should be appreciated that the invention is not limited to any particular distributed architecture, network, or communication protocol.

Various embodiments of the present invention may be programmed using an object-oriented programming language, such as SmallTalk, Java, C++, Ada, or C# (C- Sharp). Other object-oriented programming languages may also be used. Alternatively, functional, scripting, and/or logical programming languages may be used. Various aspects of the invention may be implemented in a non-programmed environment (e.g., documents created in HTML, XML or other format that, when viewed in a window of a browser program, render aspects of a graphical-user interface (GUI) or perform other functions). Various aspects of the invention may be implemented as programmed or non-programmed elements, or any combination thereof. Further, various embodiments of the invention may be implemented using Microsoft.NET technology available from Microsoft Corporation.

EXAMPLES Example 1

In a first prophetic example, a client (large scale bioreactor operator) may provide an evaluator (microbioreactor service provider/vendor) with background information about a specific large-scale bioreaction. As shown in the flow chart illustrated in Fig. 2, the client can provide the information to the evaluator who can then proceed with a series of cellular microbioreactions. In different embodiments, many of the steps shown in

FIG. 2 are optional and, of course, additional steps may be added. In this illustration, the client wishes, for example, to produce a specific drug using a genetically-engineered cell line. The evaluator can obtain cells representative of the cell line, possibly from the client, and can then proceed to evaluate the performance of the cells under a variety of conditions in a plurality of microbioreactors. For instance, in one microbioreactor array, pH may be increased by .05 pH units from reaction chamber to reaction chamber, while other parameters such as shear, temperature, viscosity, nutrient level, ionic strength, evaporation, and gas concentrations, such as CO₂ and O₂ are maintained at constant levels. At the completion of the evaluation, or during the evaluation, the cells can be examined to determine the health of the cells and/or any output of the cells can be detected, quantitatively or qualitatively, using methods either described herein or known to those skilled in the art. Other microbioreactor arrays may be operated, for example, using the same cell line but by varying alternative parameters. These additional evaluations may be run concurrently or at different times. For example, in another 100 unit microbioreactor array, shear stress can be varied while all parameters except for sheer stress are retained at constant levels. This will provide information regarding the effect of sheer stress on the bioreaction, independent of changes in other parameters. Likewise, one or more optimum values or ranges can be determined for each parameter independently from all other parameters.

Additional rounds of microbioreactions may be run by presetting one or more microbioreaction parameters to different values, such as optimal levels determined previously. Then, with one or more parameters maintained at this value, a different second parameter can be varied to determine how the variation of the second parameter affects the reaction in light of the new value for the first parameter. In this way, a matrix or matrices or parameters can be investigated where any number of parameters can be individually investigated independently of all other parameters. In some cases, it may be preferred to vary the second parameter over a smaller range than was utilized in the first set of reactions. In this way, optimum ranges can be narrowed down as the evaluation continues, and shifts in optimum ranges for one parameter due to changes in a second parameter can be determined. When changes to a first reaction parameter affect the output expected with a second reaction parameter value, this effect can be determined and therefore accounted for. In other words, the effects of each of the two reaction parameters can be de-coupled and applied independently. The effect of one parameter on another can be accounted for. At any point during the procedure, values such as output values or reaction parameter values can be reported to the client. For instance, first round values for all parameters may be provided prior to receiving second or later rounds of values that may provide more refined information. After receipt of initial information the client may ask the evaluator to alter one or more parameters to determine any possible additional effects of these later alterations. For example, if a particular design of a large scale bioreactor is chosen, the evaluator may be asked to run reactions by varying parameter values over a specific range of shear values that can be replicated within the chosen large scale bioreactor. Following optimization of these shear values, another parameter, eg, temperature, may be tested over a specific temperature range, for example, a 5 degree range divided into 0.05 degree increments in individual microbioreactors. These additional results and associated reaction parameters may then be provided to the client. Together, these results, and possibly others, can result in a "best case" scenario for a given large scale bioreactor having a fixed volume and shape. By using microbioreaction data, a set of optimal large scale bioreactor reaction conditions can be provided that could not have been obtained from the large scale bioreactor itself, due, in part, to the inherently different reaction conditions that cells in a large scale bioreactor are subjected to. Specific thresholds for reaction conditions may also be determined that can provide limits within which a given reactor should be run in order to maintain an active system.

In other embodiments, only output values are supplied to the client. Values for reaction conditions need not be supplied. These output values may be useful independently if, for example, the client has specifically directed the evaluator on how to proceed and is simply waiting for results. ^■ When microbioreactions are run without knowledge of a specific predetermined large scale bioreactor design, the parameter values may be varied over ranges that could be replicated on a large scale when a large scale reactor can be designed from scratch.

Table 1 illustrates examples of some of the parameters that can be controlled using the microbioreactors and methods described herein. Column 2 provides ranges within over which these parameters can be controlled for a period of 1 hour, 1 day, 30 days, 60 days or more for a cellular^' microbioreaction. The third column provides methods that may be used to perform the measurements. Table 1

Example 2

In a second prophetic example, a producer of a specific protein is designing a large scale bioreactor to produce protein A in large quantities at the greatest possible yield and best purity obtainable. The producer (client) asks the evaluator/microbioreactor service provider/vendor to provide optimum value ranges for ten different reaction parameters.

In this example, 10 different input parameters are evaluated using 1,000 microbioreactors. The 10 parameters (environmental factors) being evaluated could include, for example, relative humidity, pH, oxygen concentration, glucose concentration, amino acid concentration, shear stress, temperature, carbon dioxide concentration, light intensity and light wavelength. In this example, the microbioreactors are divided into groups of 100 and in each group all parameter values are maintained constant except for one. In other embodiments, different numbers of microbioreactors may be subjected to different reaction parameter values. In this case, output values for purity and quantity of the target protein are determined for each of the 1,000 microbioreactions. In some cases, the microbioreactions may be re-run, substituting new reaction parameter values for previous ones. The new values may be, for example, those values that were found to be optimal for each individual reaction parameter in the previous set of microbioreactions. Ranges of reaction parameter values may be evaluated, for example, based on the yield and/or purity values obtained for each reaction parameter input value. Reaction parameter ratings may depend on the relative importance of yield and purity. Of course, other output values may also be considered. The determined values can play a role in both the physical design of a large scale reactor as well as in the operation of the reactor during production. For instance, if a low shear stress is shown to be preferred, the reactor can be constructed with a mixing device designed to minimize shear. If a high oxygen concentration is required, the reactor may be equipped with multiple aerators that can provide oxygen to many locations in the large scale bioreactor without significantly increasing the shear stress to which the cells are subjected. If precision in a particular parameter is found to be of relatively great importance, then the reactor can be constructed to very precisely control that parameter (e.g., with more robust, complete, or extensive heat exchange; greater control of pH via pH sensing and adjustment at additional/multiple locations within the reactor, etc.). In such a manner, the large scale bioreactor can be constructed and/or operated to reflect the optimal values that were revealed in the parallel microbioreactions that were previously performed. Many of these values may have never been achievable through trial and error with a large scale reactor due to the interdependence of the parameters in the large scale bioreactor.

Example 3

In another prophetic example, microbioreaction data can be provided to a client without operating a microbioreactor. For instance, microbioreactor data can be obtained from a database of previously determined input parameter and output values. The database can be computer implemented, using, for example, computer systems and methods described herein.

In one embodiment, a client may request information regarding certain conditions, such as optimal input parameters, for a bioreaction such as a cellular bioreaction. Upon receiving the request, the evaluator can search or review data in its possession or available from third parties. The data may have been generated by previous microbioreactions and cellular microbioreactions. The bioreaction may be identical to the bioreaction inquired about, but in many instances the retrieved data may be for a reaction that is similar to or possesses some commonality with the requested reaction. For instance, the results may be from a reaction wherein the cell or cells tested are known or suspected to react in a manner similar to cells which the client is inquiring about. For example, if the client inquires about input parameters for cell line A, the evaluator may report results from cell line B microbioreactions if cell line B is known or suspected to react similarly to cell line A. In one embodiment, if cell line B is suspected to react to changes in pH in a manner similar to cell line A, the output data for cell line B at various pH input values may be provided. Alternatively, a single pH value or range, eg, an optimal value or range, can be provided to the client. In another embodiment, output values for various shear stress input parameter values for a generic class of cells can be provided in response to a request for shear stress results for a specific cell type that can be considered to be a member of the class. Microbioreactor databases can also be developed independently of specific requests and the data may be used at a later date in response to a specific inquiry. Thus, databases of input parameter values and corresponding output values can be developed with or without a specific request from a client, and these databases may be accessed at a later time to provide information internally or to a client.

The information may be specific to a particular cell, or bioreactor or cellular product, for example. The information may also be more generic, such as directed to a class of cells or bioreactors or cellular products. For example, classes of cells may be genetically engineered E. CoIi cells or cells producing peptides or proteins. A class of bioreactors may be, for example, stirred tank fermentors or fluidized bed bioreactors or other classes of bioreactors known to those skilled in the art or described herein. A class of cellular product may be, for example, proteins or peptides or enzymes or drugs. A screening test to determine if output values are appropriate across a specific class may be run by using a microbioreactor to test, for example, 2, 3 or 4 different members of the class using common input parameters. For example, each of 3 different protein producing cells can be subjected to different shear stress values across a range of interest. If the 3 cell types react similarly under different shear stress conditions then the shear stress data may be useful across the class. If reactions are dissimilar, then the data might not be useful across the class and more specific, individualized testing may be preferred.

In a variation, output data or reaction parameters can be provided to a client without first receiving an inquiry. An evaluator may independently identify a bioreactor operator (client) as active in a specific field and may then provide data regarding output results or input parameters that may be applicable to that field. For example, an evaluator may obtain shear stress data generated from microbioreactors used to evaluate a specific protein-producing bacterial cell line and can provide the data or a portion of the data to a client that operates large scale cellular bioreactors to produce proteins. While several embodiments of the present invention have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the functions and/or obtaining the results and/or one or more of the advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the present invention. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications- for which the teachings of the present invention is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, the invention may be practiced otherwise than as specifically described and claimed. The present invention is directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the scope of the present invention.

All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.

The indefinite articles "a" and "an," as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean "at least one."

The phrase "and/or," as used herein in the specification and in the claims, should be understood to mean "either or both" of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Other elements may optionally be present other than the elements specifically identified by the "and/or" clause, whether related or unrelated to those elements specifically identified unless clearly indicated to the contrary. Thus, as a non-limiting example, a reference to "A and/or B", when used in conjunction with open-ended language such as "comprising" can refer, in one embodiment, to A without B (optionally including elements other than B); in another embodiment, to B without A (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc. As used herein in the specification and in the claims, "or" should be understood to have the same meaning as "and/or" as defined above. For example, when separating items in a list, "or" or "and/or" shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as "only one of or "exactly one of," or, when used in the claims, "consisting of," will refer to the inclusion of exactly one element of a number or list of elements. In general, the term "or" as used herein shall only be interpreted as indicating exclusive alternatives (i.e. "one or the other but not both") when preceded by terms of exclusivity, such as "either," "one of," "only one of," or "exactly one of." "Consisting essentially of, when used in the claims, shall have its ordinary meaning as used in the field of patent law.

As used herein in the specification and in the claims, the phrase "at least one," in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase "at least one" refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, "at least one of A and B" (or, equivalently, "at least one of A or B," or, equivalently "at least one of A and/or B") can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one act, the order of the acts of the method is not necessarily limited to the order in which the acts of the method are recited. In the claims, as well as in the specification above, all transitional phrases such as

"comprising," "including," "carrying," "having," "containing," "involving," "holding," and the like,.are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases "consisting of and "consisting essentially of shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03. What is claimed is:

Claims

1. A method for providing bioreaction information to a client, the method comprising: receiving a description of a large scale cellular bioreaction from a client; obtaining microbioreaction output data representative of conditions defining values of different cellular reaction parameters, the outputs being representative of a range of existing reaction parameter values of the large scale bioreaction or adjusted reaction parameter values for potential use in the large scale bioreaction; and reporting at least one output value and/or a corresponding reaction parameter value to the client for use in determining and/or adjusting one or more reaction parameters of the large scale bioreaction.

2. The method of claim 1 wherein the reaction parameters are selected from temperature, pH, shear stress, shear rate, dissolved gases, such as oxygen concentration and CO₂ concentration, nutrient concentrations, metabolite concentrations, glucose concentration, glutamine concentration, pyruvate concentration, apatite concentration, relative humidity, molarity, osmolarity, color, turbidity, viscosity, a concentration of an amino acid, a concentration of a vitamin, a concentration of a hormone, serum concentration, ionic strength, a concentration of an ion, degree of agitation, pressure, and a concentration of an oligopeptide, flow rate, light, cell condition, etc.

3. The method of claim 1 wherein greater than 3 reaction parameters are varied among the plurality of micfobioreacto^'rs.

4. The method of claim 1 wherein greater than 4 reaction parameters are varied among the plurality of microbioreactors.

5. The method of claims 3 or 4 wherein the bioreactions are performed in the microbioreactors in parallel.

6. The method of claim 1 wherein reporting includes providing values or value ranges for at least 3 reaction conditions.

7. The method of claim 1 wherein reporting includes providing at least 3 output values.

8. The method of claim 1 wherein the description includes values or value ranges for reaction conditions from more than one location in a large scale bioreactor.

9. The method of claim 1 comprising: adjusting at least one cellular reaction parameter after obtaining the microbioreaction data; and obtaining a second set of microbioreaction output data representative of conditions after adjusting the at least one cellular reaction parameter.

10. The method of claim 9 comprising adjusting the at least one cellular reaction parameter an additional time; and obtaining a third set of microbioreaction output data representative of conditions after adjusting the at least one cellular reaction parameter the additional time.

11. The method of claim 9 comprising adjusting a second cellular reaction parameter; and obtaining a third set of microbioreaction output data representative of conditions after adjusting the at least one cellular reaction parameter.

12. A method for providing bioreaction information to a client, the method comprising: receiving a request for cellular bioreaction information from a client; performing at least one bioreaction in a plurality of microbioreactors under a plurality of reaction conditions defined by values of different cellular reaction parameters; determining at least one output value resulting from at least one of the reaction conditions; and reporting the at least one output and/or a value of a cellular reaction parameter to the client for use in design and/or operation of a large scale bioreactor.

13. The method of claim 12 wherein the reaction conditions are selected from pH, temperature, nutrients, drugs, shear, ionic strength, [O₂], and [CO₂].

14. The method of claim 12 wherein the at least one output value is selected from cell growth, cell survival, cell reproduction and biochemical production.

15. The method of claim 12 wherein at least 100 bioreactions are performed in parallel.

16. The method of claim 12 wherein at least 1000 bioreactions are performed in parallel.

17. The method of claim 12 wherein only a single reaction condition is varied in at least 100 bioreactions and other reaction conditions are constant in the at least 100 bioreactions.

18. The method of claim 12 wherein reporting includes correlating at least one value of a cellular reaction parameter or condition with its corresponding output value.

19. The method of claim 18 wherein the output value is an optimal output value.

20. The method of claim 13 wherein the reaction condition is hydrodynamic shear.

21. A method for providing bioreaction information to a client, the method comprising: obtaining microbioreaction output data representative of conditions defining values of different cellular reaction parameters; and reporting at least one output value and/or a corresponding reaction condition to a client for use in designing, determining and/or adjusting one or more reaction parameters of a large scale bioreaction.

22. The method of claim 21 wherein the cellular reaction parameters are selected from pH, temperature, nutrients, drugs, shear, ionic strength, [O₂], and [CO₂].

23. A method for providing bioreaction information to a client, the method comprising computer-implemented steps of: recording, from a plurality of cellular microbioreactions, output values representative of conditions defining values of different cellular reaction parameters; and reporting at least one output value and/or a corresponding reaction condition to a client for use in designing, determining and/or adjusting one or more reaction parameters of a large scale bioreaction.

24. A computer readable medium having computer readable signals stored thereon, the signals defining instructions that, as a result of being executed by a computer, control the computer to perform a process for providing bioreaction information, the process comprising acts of: tabulating, from a plurality of cellular microbioreactions, outputs representative of conditions defining values of different cellular reaction parameters; and reporting at least one output value and/or a corresponding reaction condition for use in designing, determining and/or adjusting one or more reaction parameters of a large scale bioreaction.