Abstract:
A method is disclosed for selecting ingredient subsets for evaluation. The method receives a selection of at least one primary clinical effect and selects a plurality of ingredients that have the at least one primary clinical effect. In addition, the method scores for each ingredient a strength of the at least one primary clinical effect and each secondary clinical effect for an average therapeutic dose normalized to body mass for each of a group of subjects. The method further selects for evaluation each subset of the plurality of ingredients satisfying the equation 
     
       
         
           
             
               
                 
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     for each primary clinical effect and 
     
       
         
           
             
               
                 
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     for each secondary clinical effect, wherein n is a number of ingredients, i indicates an ith ingredient, e iP  is a strength of the primary clinical effect of ingredient A i , T p  is a specified primary effect threshold, e iS  is a strength of a specified secondary clinical effect of the ingredient A i , and T s  is a specified secondary effect threshold.

Description:
CROSS-REFERENCES TO RELATED APPLICATIONS 
       [0001]    This application claims priority to U.S. patent application Ser. No. 11/952,866 entitled “METHOD AND APPARATUS FOR COMBINING SUB-THERAPEUTIC DOSES” and filed on Dec. 7, 2007 for W. Matthew Warnock which is incorporated herein by reference and claims priority to U.S. Provisional Patent Application No. 60/874,739 entitled “PORTFOLIO METHOD FOR FORMULATING NEW MEDICINES BY COMBINING SUB-THERAPEUTIC DOSES OF KNOWN MEDICINES” and filed on Dec. 14, 2006 for W. Matthew Warnock, which is incorporated herein by reference. 
     
    
     BACKGROUND OF THE INVENTION 
       [0002]    1. Field of the Invention 
         [0003]    This invention relates to methods for formulating new medicines comprising multiple medicinal ingredients. 
         [0004]    2. Description of the Related Art 
         [0005]    Medicines are generally dose-dependent. The effect of a medicine is typically a function of the dose administered. A higher dose produces a greater response than a lower dose. Often a significant dose is required before any response is observed. A lesser dose may elicit no measurable response. The dose required in order to elicit a desired response is referred to herein as a therapeutic dose. 
         [0006]    A sub-therapeutic dose is a dose that is not expected to elicit the desired therapeutic response. For example, if the therapeutic dose of a medicine is two milligrams per kilogram (2 mg/kg) of body weight, a sub-therapeutic dose may be one milligram per kilogram (1 mg/kg) dose. 
         [0007]    Conventional therapeutic doses are determined through statistical analysis of average dose-response curves. However, human bodies are unique, and respond differently to different medicines. Some people respond more or less strongly than the average, making the medicine more or less effective than normal. In addition, almost all medicines have multiple effects, including side effects and possible adverse reactions. These may be stronger in some individuals than in others, but are also often dose-dependent. Since “normal” doses are based on the mean response, there will always be extreme responses, both on the desired or primary effect, and on the undesired secondary or side effects, including allergic and other adverse reactions. 
         [0008]    Because all of these adverse reactions are generally dose-dependent, one way to reduce the incidence and severity of these adverse reactions would be to reduce the normal dose. However, this would also reduce the effectiveness of the medicine, which is also dose-dependent. A sub-therapeutic dose is unlikely to cause significant adverse effects, but is also usually an ineffective medicine. 
         [0009]    Sub-therapeutic doses from multiple ingredients with a desired effect may be combined to achieve the effect of a therapeutic dose. This approach is common in traditional Chinese and Ayurvedic medicine, with many examples of traditional formulas that are commonly used in formulations and doses which, when considering the separate ingredients comprised in the formula, use doses less that those traditionally recommended for that ingredient alone. Some traditional texts explicitly suggest that a practitioner may use less of a given ingredient in a formula, than would normally be used if that same ingredient were used separately. However, these disciplines provide little if any guidance on how much less of an ingredient can be used in a formula, or why, or how to create new formulas from known or newly discovered ingredients. A formula comprising only two ingredients may have infinite variants between 0% and 100% of a normal therapeutic dose of each ingredient, and the complexity increases exponentially with each additional ingredient. Some traditional formulas may contain as many as 50 ingredients, and there are many possible ingredients that could be considered in new formulations. However, screening all possible combinations of sub-therapeutic doses that may be effective is expensive and time consuming. One purpose of the present invention is to reduce the many possible doses and combinations to a manageable number of likely candidates for testing. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0010]    In order that the advantages of the invention will be readily understood, a more particular description of the embodiments will be rendered by reference to specific embodiments that are illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered to be limiting of its scope, the invention will be described and explained with additional specificity and detail through the use of the accompanying drawings, in which: 
           [0011]      FIG. 1  is a graph showing dose/response points; 
           [0012]      FIG. 2  is a graph showing a linear regression of dose/response points; 
           [0013]      FIG. 3  is a graph showing a sigmoid curve model of dose/response points; 
           [0014]      FIG. 4  is a graph showing a distribution of subject responses to a dose; 
           [0015]      FIG. 5  is a schematic flow chart diagram illustrating one embodiment of a screening method; 
           [0016]      FIG. 6  is a schematic flow chart diagram illustrating one embodiment of a ingredient subset selection method; 
           [0017]      FIGS. 7A ,  7 B, and  7 C are table diagrams illustrating a relationship of exemplary ingredients; 
           [0018]      FIG. 8  is a graph showing combined primary and secondary effects of exemplary ingredients; 
           [0019]      FIG. 9  is a graph showing an averaged combined effect of exemplary ingredients; 
           [0020]      FIG. 10  is a graph showing a combined primary effect for a ingredient subsets; and 
           [0021]      FIG. 11  is a schematic block diagram illustrating one embodiment of a computer. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0022]    Reference throughout this specification to “one embodiment,” “an embodiment,” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases “in one embodiment,” “in an embodiment,” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment. 
         [0023]    Furthermore, the described features, structures, or characteristics of the invention may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the invention. 
         [0024]      FIG. 1  is a graph  100  showing dose/response points  115 . The graph  100  is illustrative of determining a therapeutic dose for specified ingredient. Ingredients may be herbal, animal, mineral, and/or synthetic ingredients. As depicted, the graph  100  plots the effect  105  of an ingredient administered to one or more subjects in a plurality of doses  110  as dose/response points  115 . 
         [0025]    The effect  105  may be measured as an absolute measure, as observed change, and/or as an effectiveness. For example, the effect  105  may be an absolute measure such as diastolic blood pressure in a subject. In an alternate example, the effect  105  may be observed change such as an observed reduction in pain in the subject. In another example, the effect  105  may be an effectiveness such as observed reduction in diastolic blood pressure as a percentage of the highest observed pressure of the subject. 
         [0026]    The ingredient may be administered to a plurality of individuals with a plurality of doses  110 . In one embodiment, the ingredient is normalized to the body mass of the individual. For example, a specified dose  110  may be normalized to three grams (3 g) for a man with a mass of seventy-five kilograms (75 kg) and four grams (4 g) for another man with a mass of one hundred kilograms (100 kg). 
         [0027]    The graph  100  may be constructed from the results of a clinical trial that is conducted to determine a therapeutic dose for the ingredient. Although for simplicity, a graph  100  is shown with eleven (11) dose/response points  115 , a clinical trial may generate any number of dose/response points  115 . 
         [0028]    Even with the doses  110  normalized to body mass, the reaction of each individual to a dose  110  may vary significantly. Differences in the pharmacokinetics and the pharmacodynamics of an individual and an ingredient result in significant differences in effect. 
         [0029]    As a result, the graph  100  is primarily useful in determining an average therapeutic dose for the ingredient. Although for illustrative purposes the data is shown on the graph  100 , the data may be used by a computer program product. The computer program product may include a tangible storage device such as a hard disk drive having a computer readable program. The computer readable program may be executed on a computer as is well known to those of skill in the art, causing the computer to process and manipulate the data. The data of the graph  100  may be used to determine a therapeutic dose as will be described hereafter. 
         [0030]      FIG. 2  is a graph  200  showing a linear regression  205  of the dose/response points  115  of  FIG. 1 . The description of the graph  200  refers to elements of  FIG. 1 , like numbers referring to like elements. In one embodiment, the linear regression  205  is an expression of the equation y=bx+c where y is the effect  105 , x is the dose  110 , and b and c are calculated constants. The linear regression  205  may be calculated using a least-squares analysis, polynomial fitting, and trend line regression as is well known to those of skill in the art. 
         [0031]    In one embodiment, a minimum effect  210  is established. The minimum effect  210  may be a minimum desired effect. Alternatively, the minimum effect  210  may be an absence of a clinically observed effect  105 . In a certain embodiment, the minimum effect  210  is established at a level where fifty percent (50%) of subjects have the desired minimum effect, a measure referred to hereinafter as EC50. Alternatively, the minimum effect  210  is established at a level where eighty percent (80%) of subjects have the desired minimum effect, a measure referred to hereinafter as EC80. 
         [0032]    A therapeutic dose  215  may be the dose  110  of the ingredient that results in the minimum desired effect that satisfies EC50. The minimum desired effect may be referred to as effective, therapeutic, clinical, or the like. Alternatively, the therapeutic dose  215  may be the dose  110  of the ingredient that results in the minimum desired effect satisfying EC80 
         [0033]    The therapeutic dose  215  may be calculated as the dose  110  that yields the minimum effect  210  when applied to the linear regression equation. In one example, the linear regression equation is Equation 1, where the therapeutic dose  215  x is measured in milligrams, and the minimum effect is a numerical value y, and h is a constant. 
         [0000]        y=gx+h   Equation 1
 
         [0034]    In one embodiment, the computer program product calculates the linear regression  205  of the dose/response points  115 . In addition, the computer program product may calculate the therapeutic dose  215  from a specified minimum effect  210 . 
         [0035]      FIG. 3  is a graph  300  showing a sigmoid curve model  305  of the dose/response points  115  of  FIG. 1 . The description of the graph  300  refers to elements of  FIGS. 1-2 , like numbers referring to like elements. In one embodiment, the sigmoid curve model  305  is an approximation of the dose/response points  115  in the form of Equation 2 where y is the effect  105 , x is the dose  110 , and b and c are calculated constants. 
         [0000]        y=b (1/(1+ e   −x ))+ c   Equation 2
 
         [0036]    A computer program product may derive a therapeutic dose  215  from the sigmoid curve model  305 . In one embodiment, the therapeutic dose  215  is calculated as the dose  110  that yields the minimum effect  210  when applied to the sigmoid curve model  305 . In an alternate embodiment, the therapeutic dose  215  may be selected at the dose  110  at a sigmoid curve model inflexion point  310 . 
         [0037]      FIG. 4  is a graph  400  showing a distribution of subject responses to a dose of an ingredient. The description of the graph  300  refers to elements of  FIGS. 1-3 , like numbers referring to like elements. In one embodiment, the graph  400  illustrates a response  415  to a specified dose of the ingredient by a plurality of subjects. The specified dose may be normalized to the body mass of each subject. 
         [0038]    The response  415  may be analogous to the effect  105  of  FIGS. 1-3 . The graph  400  shows a frequency  410  indicative of a number of subjects that have a specified response  415 . A bell curve  405  is fitted to the clinical data such as the dose/response points  115  of  FIG. 1  as is well known to those of skill in the art. The bell curve  405  yields a mean  420  and first and second standard deviations  425   a ,  425   b  for the subject population. 
         [0039]    In one embodiment, the computer program product calculates the bell curve  405  from the clinical data. The therapeutic dose  215  for the ingredient may be selected for a specified response  415 . For example, the therapeutic dose  215  may be selected at the mean response  420 , satisfying the EC50 criteria. Alternatively, the therapeutic dose  215  may be selected for a one standard deviation response  425 . In one embodiment, the therapeutic dose  215  is selected where eighty percent (80%) of the subjects have the desired response, satisfying EC80. 
         [0040]    An embodiment employs calculations of therapeutic doses for multiple ingredients to combine sub-therapeutic doses of the ingredients as will be described hereafter. One of skill in the art will recognize that the embodiments may use therapeutic doses calculated with other methods. 
         [0041]    The schematic flow chart diagrams that follow are generally set forth as logical flow chart diagrams. As such, the depicted order and labeled steps are indicative of one embodiment of the presented method. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more steps, or portions thereof, of the illustrated method. Additionally, the format and symbols employed are provided to explain the logical steps of the method and are understood not to limit the scope of the method. Although various arrow types and line types may be employed in the flow chart diagrams, they are understood not to limit the scope of the corresponding method. Indeed, some arrows or other connectors may be used to indicate only the logical flow of the method. For instance, an arrow may indicate a waiting or monitoring period of unspecified duration between enumerated steps of the depicted method. Additionally, the order in which a particular method occurs may or may not strictly adhere to the order of the corresponding steps shown. 
         [0042]    Given the potential and likelihood of adverse events for a therapeutic dose of any given ingredient, there may be significant advantage to combining multiple ingredients, creating a therapeutic dose from sub-therapeutic doses of several ingredients. Thus sub-therapeutic dose of a plurality of ingredients with a common primary effect may be combined to produce a combined therapeutic dose. 
         [0043]    These combined ingredients could be different agonists or antagonists of the same receptors, or agonists or antagonists of different receptors that stimulate a common desired primary effect. The ingredients could combine to create, increase, or potentiate a desired primary effect, while also reducing the unwanted secondary effects that might be likely for each individual ingredient because of the reduced dose of each. However, the range and complexity of possible doses increases exponentially with each additional potential ingredient under consideration. 
         [0044]    The embodiments described hereafter screen a plurality of ingredients for combinations of sub-therapeutic doses that may combine to stimulate a desired primary effect. The embodiments may further minimize undesirable secondary effects such as harmful side effects by delivering sub-therapeutic doses of ingredients that do not combine to stimulate a secondary effect. Thus the embodiments screen for combinations of ingredients that may stimulate the primary effect without stimulating secondary effects. 
         [0045]      FIG. 5  is a schematic flow chart diagram illustrating one embodiment of a screening method  500 . The method  500  may be practiced by computer executing a computer program product. The description of the method  500  refers to elements of  FIGS. 1-4 , like numbers referring to like elements. 
         [0046]    The method  500  starts and the computer program product selects  510  a plurality of ingredients that have a primary effect. In one embodiment, the computer program product consults a database of ingredients and selects  510  each ingredient that has the primary effect. 
         [0047]    The primary effect may be a desired subject response. In one embodiment, the primary effect is symptomatic, wherein the symptoms are alleviated. For example, the primary effect may be a reduction in blood pressure. Alternatively, the primary effect may be tonic. A tonic effect strengthens the body of the subject. In one embodiment, the computer program product selects  510  a plurality of ingredients that have one or more symptomatic primary effects and one or more tonic primary effects. 
         [0048]    The primary effect may be specified in response to need, such as a need to reduce blood pressure. In an alternate embodiment, the primary effect is the primary effect of a target ingredient, such as an ingredient that is being prepared as commercial product. For example, the primary effect may be a sedative primary effect when devising a formulation for a product comprising chamomile. Although for simplicity, the method  500  will be described for a single primary effect, one of skill in the art will recognize that the invention may be practiced with a selection of any number of primary effects. 
         [0049]    The computer program product may score  515  a strength of the primary effect and each secondary effect for a dose of each ingredient. The primary effect and secondary effects may be clinical effects. In one embodiment the dose is the therapeutic dose  215  for a specified result. The computer program product may calculate the therapeutic dose  215  as described in  FIGS. 1-4 . Alternatively, the computer program product may consult a database of ingredients and retrieve the strength of the primary effect and the strength of each secondary effect for each ingredient. If an ingredient does not have a specified secondary effect, the strength of the secondary effect may be zero (0). 
         [0050]    A secondary effect may be an undesirable effect, such as a risk of organ damage. However, secondary effects may also be positive though not necessarily sought for the formulation. An embodiment may mitigate the strength of unwanted secondary effects as will be discussed hereafter. 
         [0051]    In one embodiment, the primary and secondary effect strengths are scored  515  using a rate of effect. The rate of effect may be a time interval required for a therapeutic dose  215  of the ingredient to have a desired effect. Alternatively, the primary and secondary effect strengths are scored using a potency. In one embodiment, the potency is a measure of magnitude of the effect. 
         [0052]    In a certain embodiment, the primary and secondary effect strengths are scored using a combination of rate of effect and potency. The strength may be calculated using equation 3, where e is the strength, r is the rate of effect, p is the potency, a is a rate scaling factor and b is a potency scaling factor. 
         [0000]        e=ar+bp   Equation 3
 
         [0053]    In one embodiment, the computer program product orders  520  ingredients based on the primary effect. For example, the computer program product may order  520  ingredients in descending order from the ingredient with the strongest primary effect. Similarly, the computer program product may order ingredients with equivalent primary effects in descending order from the ingredient with the weakest secondary effect. 
         [0054]    The computer program product selects  525  a subset of the plurality of ingredients. In one embodiment, the computer program product selects  525  a previously unexamined ingredient subset. The ingredient subset may be selected by giving preference to ingredients at the beginning of the order of ingredients. In addition, the computer program product may remove ingredients from the ingredient subset as described hereafter for  FIG. 6 . 
         [0055]    In one embodiment, the computer program product calculates  530  a sub-therapeutic dose of each selected ingredient in the ingredient subset. The sub-therapeutic dose may be calculated using Equation 4 where d, is the sub-therapeutic dose of the ingredient, d iT  is the therapeutic dose for the ingredient, and m is the sub-therapeutic divisor. In one embodiment, the sub-therapeutic divisor m is a number of the selected ingredients in the ingredient subset. Alternatively, m may be a number of active compounds within all of the ingredients that have the primary effect. In one embodiment, m is a number in the range of 4 to 10. In addition, k may be a constant in the range of 0.6 to 1.3. In a certain embodiment k is 1. The constant k is not zero (0). 
         [0000]        d   i   =d   iT   /km   Equation 4
 
         [0056]    Alternatively, the computer program product calculates  530  a sub-therapeutic dose of each selected ingredient in the ingredient subset using Equation 5, where d T  is a target therapeutic dose for the ingredient subset. 
         [0000]        d   i   =d   T   /km   Equation 5
 
         [0057]    The computer program product determines  535  if the combination of ingredients satisfies Equations 6 and 7, where n is a number of the plurality of ingredients, A i  is an ith single ingredient, e a , is a strength of the primary effect of ingredient A i , T p  is the specified primary effect threshold, e is  is a strength of a specified secondary effect of A i , and T s  is the specified secondary effect threshold. 
         [0000]    
       
         
           
             
               
                 
                   
                     
                       
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         [0058]    In addition, the computer program product may determine if the combination of ingredient satisfies Equation 8, where w i  is a mass of a therapeutic dose of each ingredient and Tm is a mass threshold such as 50 mg. The mass threshold may be in the mass of 10 to 75 mg. 
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         [0059]    If the ingredient subset satisfies Equations 6, 7, and 8 the computer program product selects  540  the ingredient subset for evaluation. The computer program product determines  545  if all possible subsets of the plurality of ingredients have been examined. If all subsets of the plurality of ingredients have not been examined, the computer program product selects  535  a new ingredient subset. If all subsets of the plurality of ingredients have been examined, the method  500  ends. If the ingredient subset does not satisfy Equations 6, 7, and 8, the computer program product determines  610  if all possible subsets of the plurality of ingredients have been examined. 
         [0060]    The method  500  allows the computer program product to screen a significant number of ingredient combinations and select one or more ingredient subsets for further evaluation. Thus the method  500  rapidly identifies promising combinations of ingredients. 
         [0061]      FIG. 6  is a schematic flow chart diagram illustrating one embodiment of an ingredient subset selection method  600  of the present invention. The method  600  may be embodied in step  525  of  FIG. 5 . The method  600  may be performed by a computer executing a computer program product. The description of the method  600  refers to elements of  FIGS. 1-5 , like numbers referring to like elements. 
         [0062]    The method  600  starts and in one embodiment the computer program product creates  605  the ingredient subset. In one embodiment, the computer program product sequentially creates  605  one of all possible combination of the plurality of ingredients as the ingredient subset. The created ingredient subset may be a previously unexamined combination of ingredients of the possible combinations of the plurality of ingredients. 
         [0063]    In one embodiment, the computer program product constructs a multidimensional matrix for each possible combination of ingredients. Alternatively, the computer program product may construct the multidimensional matrix and select two possible combinations of ingredients from the matrix. The computer program product may then evaluate each combination using Equations 6, 7, and 8 and calculate an improvement vector. The improvement vector may indicate changes to the combinations of ingredients that are likely to result in a more favorable combination of ingredients. The computer program product may use the improvement vector to select a third combination of ingredients that satisfies the improvement vector. The computer program product may use the third combination of ingredients to calculate another improvement vector and combination of ingredients, repeating the process until an optimum combination of ingredients is found. 
         [0064]    In one embodiment, the computer program product removes  610  specified ingredients from the ingredient subset. The specified ingredients may flagged as too expensive, too difficult to procure, too difficult to prepare, or the like. 
         [0065]    In one embodiment, the computer program product identifies  615  a secondary effect group of ingredients with a similar secondary effect. The secondary effect may be a clinical effect. For example, if a first and second ingredient shares a first secondary effect, the computer program product may identify  525  a secondary effect group comprising the first and second ingredient. 
         [0066]    The computer program product may remove  620  at least one ingredient of the secondary effect group from the ingredient subset and the method  600  ends. Continuing the example above, the computer program product may remove  620  the first ingredient from the ingredient subset. In one embodiment, only one ingredient of the secondary effect group is not removed. 
         [0067]    In one embodiment, the computer program product does not remove  620  at least one ingredient that mutually potentiates another ingredient. For example, a first ingredient may not be removed for increasing the primary effect strength of a third ingredient. 
         [0068]      FIGS. 7A ,  7 B, and  7 C are table diagrams  700  illustrating a relationship of exemplary ingredients of the present invention. The description of the diagrams  700  refers to elements of  FIGS. 1-6 , like numbers referring to like elements, is illustrative of the methods  500 ,  600  of  FIGS. 5 and 6 . 
         [0069]    In  FIG. 7A , a plurality of exemplary ingredients H1-7 are listed. The practitioner and/or computer program product may select  510  the ingredients H1-7 because of a primary effect. In the diagrams  700 , each of the ingredients H1-7 has the primary effect P 1 . 
         [0070]    The ingredients H1-7 also have a plurality of secondary effects S 1 - 5 . Each of the secondary effects S 1 - 5  of the ingredients H1-7 is listed in the diagram  700 . The practitioner and/or computer program product may score  515  the strength of the primary effect P 1  and each secondary effect S 1 - 5  for each ingredient H1-7. In addition, the practitioner and/or computer program product may order  520  the ingredients H1-7 based on the primary effect P 1 . The ingredients H1-7 are shown ordered from greatest primary effect to least primary effect. 
         [0071]    In  FIG. 7B , the practitioner and/or computer program product identifies  525  a secondary effect subset  720  of ingredients in the diagram  700  with a similar secondary effect S 5 . As shown, ingredients H5 and H6 are identified  525  as belonging to the secondary effect subset  720 . 
         [0072]    The practitioner and/or computer program product may remove  530  at least one ingredient of the subset of ingredients from the diagram. For example, the computer program product may remove  530  ingredient H6 as shown in  FIG. 7C . 
         [0073]    The practitioner and/or computer program product selects  535  a subset of the plurality of ingredients where the average of the primary effect strengths of the selected ingredients exceeds the specified primary effect threshold. For example, if the primary effect threshold is three point six (3.6), the combination of ingredients H1, H2, H3, H4, H5, and H7 has an average primary effect of three point five (3.5) and does not exceed the primary threshold. However, the combination of ingredients H1, H2, H3, H4, and H5 has an average primary effect of three point eight (3.8) and does exceed the primary threshold. Therefore  FIG. 7C  is shown with selected subset of ingredients H1, H2, H3, H4, and H5. 
         [0074]      FIG. 8  is a graph  800  showing combined primary and secondary effects of exemplary selected ingredients H1-5 of  FIG. 7C . The effects  105  of the primary effect  810  and the secondary effects  815  for the selected ingredients H1-5 are shown along a vertical axis. 
         [0075]    Because the primary effect  810  of the selected ingredients H1-5 is additive, the primary effect  810  of the combine selected ingredients H1-5 is significantly greater than any of the secondary effects  815 . Thus the combination of the selected ingredients H1-5 provides the primary effect  810  while mitigating the secondary effects  815 . 
         [0076]      FIG. 9  is a graph showing a combined effect of exemplary ingredients comprising the ingredients H1-5 of  FIG. 8 . The value of the combined effect  905  of the primary effect  810  and the secondary effects  815  for the ingredients H1-5 are shown along a vertical axis. A primary effect threshold  910  and a secondary effect threshold  915  are also shown. The ingredient subset of H1-5 satisfies the Equations 6 and 7 and so is selected for further evaluation. 
         [0077]      FIG. 10  is a graph  1000  showing a combined primary effect for an exemplary first ingredient subset  1005   a  and a second ingredient subset  1005   b  selected for Transient Receptor Potential cation channel subfamily V member 1 (TRPV1) activation. The selected first ingredient subset  1005   a  comprises first ingredients Zingiber officinale H1, Piper nigrum H2, Capsicum annuum H3, and Xanthoxylum piperitum H4. The selected second ingredient subset  1005   b  comprises second ingredients Zingiber officinale H1, Piper nigrum H2, and Capsicum annuum H3. The description of the graph  1000  refers to elements of  FIGS. 1-9 , like numbers referring to like elements. 
         [0078]    The first and second ingredients may be selected for the primary effect of milligrams of Scofield Heat Units (SHU) or SHU mg, wherein SHU is a metric of TRPV1 activation. Each ingredient may include one or more active ingredient with the primary effect. Table 1 lists the first and second ingredients, each active compound of each ingredient, the adjusted SHU for each active compound, a pure SHU potency, a percent of the ingredient that is active, an adjusted SHU potency equal to the Pure SHU multiplied by the percent active, and a secondary effect. 
         [0000]    
       
         
               
               
               
               
               
               
             
               
               
               
               
               
               
             
           
               
                 TABLE 1 
               
               
                   
               
               
                   
                   
                   
                   
                 Ad- 
                 Sec- 
               
               
                   
                 Active 
                   
                 Percent 
                 justed 
                 ondary 
               
               
                 Botanical name 
                 Compound 
                 SHU Pure 
                 Active 
                 SHU 
                 Effect 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 Zingiber officinale 
                 6-gingerol 
                 60,000 
                    6% 
                 3,600 
                   
               
               
                   
                 6-shogaol 
                 160,000 
                    6% 
                 9,600 
                   
               
               
                   
                 Total 
                   
                   
                 13,200 
                 Settles 
               
               
                   
                   
                   
                   
                   
                 Stomachs 
               
               
                 Piper nigrum 
                 piperine 
                 100,000 
                 7.15% 
                 7,150 
                 Reduce  
               
               
                   
                   
                   
                   
                   
                 drug 
               
               
                   
                   
                   
                   
                   
                 effects 
               
               
                 Capsicum annuum 
                 capsaicin 
                 16,000,000 
                 0.25% 
                 40,000 
                 Burning 
               
               
                 Xanthoxylum 
                 α-sanshool 
                 80,000 
                 0.45% 
                 368 
                   
               
               
                 piperitum 
                   
                   
                   
                   
                   
               
               
                   
                 β-sanshool 
                 70,000 
                 0.07% 
                 49 
                   
               
               
                   
                 γ-sanshool 
                 110,000 
                 0.19% 
                 209 
                   
               
               
                   
                 δ-sanshool 
                 110,000 
                 0.02% 
                 22 
                   
               
               
                   
                 α-hydroxy- 
                 26,000 
                 2.38% 
                 619 
                   
               
               
                   
                 sanshool 
                   
                   
                   
                   
               
               
                   
                 β-hydroxy- 
                 13,000 
                 0.27% 
                 35 
                   
               
               
                   
                 sanshool 
                   
                   
                   
                   
               
               
                   
                 Total 
                   
                   
                 1,302 
                 Numbing 
               
               
                   
                   
                   
                   
                   
                 Effect 
               
               
                   
               
             
          
         
       
     
         [0079]    The Zingiber officinale is shown with a side effect of settling stomachs, the Piper nigrum with a side effect of reducing drug effects, Capsicum annuum with a side effect of causing burning, and the Xanthoxylum piperitum with the side effect of causing numbing. Because each ingredient has a different secondary effect, the combined ingredients do not increase any one secondary effect. 
         [0080]    The target therapeutic dose d T  for the ingredient subset  1005   a  is 300,000 SHU mg. In Table 2, the therapeutic dose d iT  in SHU mg for each ingredient is the first ingredient subset  1005   a  is shown, along with a sub-therapeutic SHU mg dose d i  is calculated for each first ingredient using Equation 4, where k=1 and m=4, the number of active compounds. 
         [0000]    
       
         
               
               
               
               
             
               
               
               
               
             
           
               
                   
                 TABLE 2 
               
               
                   
                   
               
               
                   
                   
                   
                 Sub- 
               
               
                   
                   
                   
                 therapeutic 
               
               
                   
                   
                 Therapeutic  
                 Dose d i   
               
               
                   
                   
                 Dose d iT   
                 (SHU mg) 
               
               
                   
                 Botanical name 
                 (SHU mg) 
                 m = 4 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                   
                 Zingiber officinale 
                 198,000 
                 49,500 
               
               
                   
                 Piper nigrum 
                 107,250 
                 26,813 
               
               
                   
                 Capsicum annuum 
                 600,000 
                 150,000 
               
               
                   
                 Xanthoxylum 
                 19,528 
                 4,882 
               
               
                   
                 piperitum 
                   
                   
               
               
                   
                 Total 
                   
                 231,194 
               
               
                   
                   
               
             
          
         
       
     
         [0081]    The graph  1000  shows the combined primary effect for the first ingredient subset  1005   a . The first ingredient subset  1005   a  has a combined primary effect less than the primary effect threshold  910  of 300,000 SHU mg. 
         [0082]    In Table 3, the therapeutic dose d iT  for each ingredient in the second ingredient subset  1005   b  is shown, along with a sub-therapeutic SHU mg dose d i  is calculated for each first ingredient using Equation 4, where k=1 and m=3, the number of active compounds. 
         [0000]    
       
         
               
               
               
               
             
               
               
               
               
             
           
               
                   
                 TABLE 3 
               
               
                   
                   
               
               
                   
                   
                   
                 Sub- 
               
               
                   
                   
                   
                 therapeutic 
               
               
                   
                   
                 Therapeutic  
                 Dose d i   
               
               
                   
                 Botanical name 
                 Dose d iT   
                 m = 4 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                   
                 Zingiber officinale 
                 198,000 
                 66,000 
               
               
                   
                 Piper nigrum 
                 107,250 
                 35,750 
               
               
                   
                 Capsicum annuum 
                 600,000 
                 200,000 
               
               
                   
                 Total 
                   
                 301,750 
               
               
                   
                   
               
             
          
         
       
     
         [0083]    The graph  1000  shows the combined primary effect for the second ingredient subset  1005   b . The second ingredient subset  1005   b  has a combined primary effect greater than the primary effect threshold  910  of 300,000 SHU mg. Thus using the screen method  500 , the second ingredient subset  1005   b  is selected  540  for evaluation while the first ingredient subset  1005   a  is not selected. 
         [0084]      FIG. 11  is a schematic block diagram illustrating one embodiment of a computer  1100  in accordance with the present invention. The computer  1100  includes a processor module  1105 , a cache module  1110 , a memory module  1115 , a north bridge module  1120 , a south bridge module  1125 , a graphics module  1130 , a display module  1135 , a basic input/output system (“BIOS”) module  1140 , a network module  1145 , a Universal Serial Bus (USB) module  1150 , an audio module  1155 , a peripheral component interconnect (“PCI”) module  1160 , and a storage device  1165 . 
         [0085]    The processor module  1105 , cache module  1110 , memory module  1115 , north bridge module  1120 , south bridge module  1125 , graphics module  1130 , display module  1135 , BIOS module  1140 , network module  1145 , USB module  1150 , audio module  1155 , PCI module  1160 , and storage device  1165 , referred to herein as components, may be fabricated of semiconductor gates on one or more semiconductor substrates. Each semiconductor substrate may be packaged in one or more semiconductor devices mounted on circuit cards. Connections between the components may be through semiconductor metal layers, substrate-to-substrate wiring, circuit card traces, and/or wires connecting the semiconductor devices. 
         [0086]    The memory module  1115  stores software instructions and data. The processor module  1105  executes the software instructions and manipulates the data as is well known to those skilled in the art. The software instructions and data may be configured as one or more computer readable programs. The computer readable programs may comprise a computer program product and be tangibly stored in the storage device  1165 . The storage device  1165  may be a hard disk drive, an optical storage device, a holographic storage device, a micromechanical storage device, a semiconductor storage device, or the like. In one embodiment, the computer  1100  executes one or more computer program products that carry out the methods  500 ,  600  of the present invention. 
         [0087]    The present invention may be embodied in other specific forms without departing from its spirit or essential characteristics. The described embodiments are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.