PACKS OF NUTRACEUTICAL,PHARMACEUTICAL OR

COSMECEUTICAL PREPARATIONS FOR INDIVIDUALS

FIELD OF THE INVENTION

[0001] The present invention generally relates to methods, algorithms and systems for searching and selecting combinations of packs of nutraceuticals, pharmaceuticals or cosmeceuticals for individuals.

BACKGROUND OF THE INVENTION

[0002] Nutraceuticals products are available on the market these days. Each nutraceuticals product can be in the intake form of a capsule, drops, pills and the like and may contain various ingredients. Nutraceuticals are either supplements, nutrients, herbal products or any other health related additives or a combination of one or more thereof. Each product includes a formula of known ingredients such as vitamins, herbs and the like.

[0003] Many researches were conducted to study the influence of nutraceuticals on various human subjects of various population groups and for various medical conditions. These studies lead to recommended nutraceuticals in recommended intake dosages for various subjects of various personal subject condition and details such as for various ages, genders and weight or Body Mass Index (BMI) factors of people having different medical conditions.

[0004] There are known in the art methods for calculating and recommending different nutraceuticals to various subjects according to the subject's personal information. These methods receive input personal information of the subject such as age, gender, medical condition, habits and addictions (drugs, drinking or smoking habits), weight or BMI and the like, use the input data to calculate and output a personalized list of recommended nutraceuticals and dosages of each ingredient thereof tailored for the particular individual.

[0005] One such method is described in International Application Publication no. WO 2013/080208 by Aronis et al., which discloses methods for providing a personalized list of dietary nutraceuticals to an individual, wherein at least one of the nutraceuticals affects the bioavailability of at least one other of the nutraceuticals, the methods including adjusting the amount of the affected nutraceutical based on the influence of the affecting nutraceutical on the bioavailability thereof. This application further discloses a computerized system including a database and a processor which includes modules configured for providing the list of nutraceuticals according to the disclosed invention.

[0006] The method disclosed in the above-mentioned application requires producing personal packs such as capsules of nutraceuticals combinations for each person individually and therefore requires investing a substantial amount of time and effort per person and may be costly to the person acquiring the final personalized pack product.

SUMMARY OF THE INVENTION

[0007] According to the present invention, there is provided a computer implemented method for selecting one or more known suitable preparation packs of nutraceuticals, pharmaceuticals and/or cosmeceuticals for an individual, the method comprising: (a) receiving a personalized table of recommended preparations for an individual, said table comprising recommended ingredients of nutraceuticals, pharmaceuticals and/or cosmeceuticals for said specific individual and recommended dosage for each ingredient; and (b) searching through a database stored in a data storage medium, said database comprising a plurality of known preparation packs of nutraceuticals, pharmaceuticals and/or cosmeceuticals along with a pack table of ingredients and quantity of each ingredient of each known preparation pack, for identifying a pack combination of one or more of the known preparation packs that have the best match to the personalized table of the said individual, wherein the search is carried out using a designated algorithm that optimizes the efficiency of the search through the database.

[0008] According to some embodiments, the designated algorithm is configured for operating a weighing process that uses the difference between the ingredients and dosages thereof in the personalized table of the individual and ingredients and quantities thereof as indicated in each pack table of each known preparation pack in the database, wherein the weighing process results in assignment of a weight factor to each preparation pack in the database relevant for the specific individual. [0009] In certain embodiments, the weight factor for each known preparation pack is calculated using a process comprising: (i) calculating for each ingredient of each known preparation pack the difference between recommended dosages of each ingredient in the personalized table and dosage of each ingredient of the known preparation pack; (ii) normalizing each calculated difference; (iii) assigning a deficit weight factor "DF" for each ingredient of each known preparation pack; (iv) assigning a surplus weight factor "SF" for each ingredient of each known preparation pack; (v) summing the product of the normalized difference with the deficit factor of all the ingredients of each known preparation pack resulting in a "deficit sum" (DS) of the known preparation pack; (vi) summing the product of the normalized difference with the surplus factor of all the ingredients of each known preparation pack resulting in a "surplus sum" (SS) of the known preparation pack; and (vii) summing the DS with the SS of each known preparation pack, resulting in the weight factor of the respective known preparation pack. The same process is repeated for each possible combination of known preparation packs to determine the best matching known preparation pack or combination thereof by summing up quantities of the same ingredients, wherein a combination of packs comprises a number of the same known preparation packs and/or different known preparation packs.

[0010] According to certain embodiments, the method further comprises: (i) receiving personal data of the individual; (ii) receiving external conditions; (iii) identifying conditions associated with the individual, using said received personal data; and (iv) filtering out known preparation packs according to the external and identified conditions for searching only through non-filtered known preparation packs in the database.

[0011] Optionally, the identified conditions comprise at least one of: conditions associated with subject's preferences, conditions associated with the individual's medical condition, conditions associated with nutraceuticals, pharmaceuticals and/or cosmeceuticals and/or treatment that the individual receives, conditions associated with behavior of the individual, conditions associated with age, gender, height, weight, medical condition, consumption of other medications, and/or genetic profile of the individual, wherein the external conditions comprise the maximal number of known preparation packs for each subject. [0012] According to some embodiments, the method further comprises a preliminary filtering process for filtering out known preparation packs that are least likely to match the personalized table of the individual, wherein the preliminary filtering process comprising checking coverage rate of the ingredients of each known preparation pack in relation to the personalized table.

[0013] According to certain embodiments, the method further comprises outputting at least one best matching combination of at least one known preparation pack.

[0014] Optionally, the outputting comprises outputting a prioritized table of combinations of known preparation packs that best match the personalized table of the individual ordered according to suitability level thereof.

[0015] According to certain embodiments, the method further comprises providing the database of known preparation packs.

[0016] According to certain embodiments, the provided database of known preparation packs comprises packs with personalized tables for individuals that are registered in the system and the method optionally also includes identifying matching combinations of packs of individuals from the personalized tables in the database using an operational research process, which identifies at least one pack or a combination of packs that will match the largest number of registered individuals. The operational research process may optionally be based on preset or received limitations according to which the at least one matching pack or combination of packs are identified.

[0017] According to certain embodiments, the method further comprises receiving personal data of the individual via a user interface configured to receive personal input data through a predefined user questionnaire.

[0018] Optionally, each table of each known preparation pack comprises the pack ingredients and the quantity of each ingredient in the pack as well as at least one of the following details: measure units for the indicated quantity of each ingredient; pack brand; intake type; container type; number of packs in a container; product ID; retailer ID; pack or container image or link to the image; calories; flavor; surplus factor and deficit factor for each ingredient; one or more condition groups with which the pack is associated.

[0019] The method of the present invention optionally further comprises automatically initiating a purchasing process by automatically transmitting an order message to each retailer of each preparation pack of each identified best matching combination for the particular individual upon receiving the individual's approval and/or purchasing details.

[0020] According to some embodiments of the invention, there is provided a system for selecting one or more known preparation packs of nutraceuticals, pharmaceuticals and/or cosmeceuticals suitable for an individual, said system comprisingf a search engine operable via at least one processor, wherein the search engine is configured for: receiving a personalized table of nutraceuticals,

pharmaceuticals and/or cosmeceuticals for an individual, said tablet comprising one or more recommended ingredients of nutraceuticals, pharmaceuticals and/or

cosmeceuticals for the specific individual and recommended dosage for each ingredient; and searching through a database stored in a data storage medium, wherein the database comprises a plurality of indicators of known preparation packs of nutraceuticals, pharmaceuticals and/or cosmeceuticals along with a pack table of ingredients and quantity of each ingredient of each known preparation pack for identifying a pack combination of one or more of the known preparation packs that have the best match to the personalized table of the said individual. The search is carried out using a designated algorithm, which optimizes the efficiency of the search through the database.

[0021] According to certain embodiments, the system comprises the database as part thereof.

[0022] According to some embodiments, the search engine operates a designated user interface for allowing users to input personal details of individuals for identifying the best match packs combination thereby. Optionally, the user interface includes at least one predefined questionnaire for allowing the user to input the individual information according to specific questionnaire fields and setup.

[0023] According to some embodiments, the input individual's data is also used for calculating and outputting the individual's personalized table of nutraceuticals.

[0024] According to other embodiments of the invention, there is provided a computer implemented method for selecting at least one combination of known personalized packs of nutraceuticals, pharmaceuticals and/or cosmeceuticals that suits maximal number of individuals in an optimal manner, wherein this method comprises: (a) providing a database stored in a data storage medium, said database comprising known preparation packs of nutraceuticals, pharmaceuticals and/or cosmeceuticals and a table of ingredients and quantity of each ingredient for each known preparation pack; and (b) identifying at least one most suitable combination of known preparation packs from the database that is suitable for the highest number of registered individuals, using a designated algorithm based on operational research process for optimizing the number of individuals that the combination is suitable for in respect to a suitability level of the combination.

[0025] Optionally, the identification is carried out according to the following steps: (i) calculating a set of grades for each pack in the database, each grade in the grades set being indicative of its suitability to another pack in the database; (ii) calculating a total grade to each pack in the database by summing up all the grades of its respective grades set, said total grade being indicative of the overall suitability level of the respective pack to other packs; (iii) repeating this process of steps (i) and (ii) by calculating the suitability level of a combination of the known preparation pack identified with the best suitability level and all other packs in the database; (iv) recursively repeating the process of steps (ii) and (iii) for a predefined "N" number of times; and (v) selecting the combination with the best suitability level of all iterations of the recursive process identifying the selected combination as the optimally suitable combination of packs of nutraceuticals, pharmaceuticals and/or cosmeceuticals.

[0026] Optionally, the method further comprises a preliminary process in which the original list of packs of the database is enhanced by adding equivalent packs, each equivalent pack is a multiplication of each of the packs from the database, wherein each equivalent pack has the same ingredients as its corresponding original pack with a doubled quantity for each ingredient thereof.

[0027] According to some embodiments, the maximal number of packs per combination is limited such as for two packs.

[0028] The method may further comprise outputting the most suitable combination.

[0029] The method optionally further comprise producing a stock of the identified most suitable combination.

BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Fig. 1 is a flowchart of a process for selecting a matching combination of preparation packs such as nutraceuticals, pharmaceuticals and/or cosmeceuticals packs for a particular individual, according to an inputted personalized table of one or more recommended nutraceuticals and/or pharmaceuticals and/or cosmeceuticals for the particular individual, according to some embodiments of the present invention.

[0031] Fig. 2 is a block diagram showing a system for selecting a matching

combination of preparation packs for a particular individual, according to some

embodiments of the invention.

[0032] Fig. 3 is a flowchart illustrating a process of selecting at least one

combination of known personalized packs of nutraceuticals, pharmaceuticals and/or cosmeceuticals that suits maximal number of individual in an optimal manner,

according to other embodiments of the invention.

DETAILED DESCRIPTION OF SOME EMBODIMENTS OF THE INVENTION

[0033] In the following detailed description of various embodiments, reference is made to the accompanying drawings that form a part thereof, and in which are shown by way of illustration specific embodiments in which the invention may be practiced. It is understood that other embodiments may be utilized and structural changes may be made without departing from the scope of the present invention.

[0034] The present invention provides methods and systems for selecting a

combination of one or more known preparation packs of nutraceuticals,

pharmaceuticals and/or cosmeceuticals from a database, suitable for an individual, according to the individual's personalized table of recommended nutraceuticals, pharmaceuticals and/or cosmeceuticals ingredients and dosages thereof.

[0035] Definitions:

[0036] The term "preparation" (noun) as used herein refers to a pharmaceutical, nutraceutical or cosmeceutical product, substance, composition, formulation, combination or the like.

[0037] The term "pharmaceuticals" as known in the art and used herein refers to a preparation comprising a pharmaceutical product also designated a drug, a medicinal product or a medicine comprising a compound or a combination of compounds that can be used in the treatment of a disease, disorder or condition.. The pharmaceutical preparation can be in any suitable form for administration such as, but not limited to, capsules, tablets, pills, lozenges, sachets, syrups, aqueous solutions or dispersions, ointments, gells, unit dosages for injection, and the like.

[0038] The term "nutraceuticals" as known in the art and used herein refers to a health product that provides health and medical benefits, including the prevention and treatment of diseases. This definition includes nutrients, dietary supplements, herbal products, additives, functional or medical foods, sprays (such as nasal spray) and the like. The nutrients can include dietary nutrients, including micro-nutrients such as vitamins and minerals, for example, vitamin A, vitamin B complex, vitamin C, vitamin D, vitamin E, calcium, iron, magnesium, selenium, zinc, copper, folate, chromium, boron. The dietary supplements are products that contain nutraceuticals derived from food products and may include, for instance, food supplements that are not nutrients, including for example, prebiotics such as dietary fibers, probiotics, omega 3 fatty acids such as eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA), botanical and herbal extracts, multi vitamin, and the like.

[0039] The term "cosmeceuticals" refers to cosmetic products comprising a

combination of cosmetics and biologically active ingredients with purported medical benefits. They may be intended for topical application and may be formulated in form of creams, ointments, lotions, serum and the like. Under the same category of

cosmeceutical products there are Nutricosmetic products that contain nutrients and are employed in cosmetic products, for example, for oxidative damage, photo ageing, skin matrix protection, skin lightening, skin tightening and firming and the like. The

Nutricosmetic products canbe administered orally as supplements in the form of pills, tablets, capsules and the like. Among various examples of cosmeceuticals and

nutricosmetic s are vitamins, proteins, antioxidants such as carotenoids (beta-carotene, lycopene, lutein, zeaxanthin, and astaxanthin) and polyphenols (anthocyanidins, catechins, flavonoids, tannins, and procyanidins), minerals, nutrients, herbs and the like. The term "known preparation pack", "pack" or "preparation pack" used herein refers to any type of the manner in which the preparation is contained and/or delivered. The pack can be for instance a capsule, drops, an edible candy, a tablet, a pill, lotion, cream, ointment, serum or injection, functional and medical foods, and the like.

[0040] The term "pack data", "data set", or "data set of a (known) pack" refers to a data structure unit or data set including information associated with a particular

preparation pack such as the pack ID, a table indicating all ingredients (optionally only active ingredients) of all nutraceuticals, pharmaceuticals and/or cosmeceuticals in the preparation of the pack and quantity of each ingredient and optionally also other information relating to the particular pack such as the pack brand name or code, measures units of all ingredients quantities, side effects, details of its retailer or ordering details and the like.

[0041] The object of the present invention is to effectively search through the database of known preparation packs such as drugs, supplements, nutrients capsules, pills or cosmeceutical creams, ointments, lotions or serums that are available on the market and optionally produced on a mass scale to identify the most suitable combination of such available known preparation packs for the specific individual according to the individual's information that includes a personalized table listing all preparations of nutraceuticals, pharmaceuticals and/or cosmeceuticals recommended for the particular individual. The personalized table of recommended preparations is provided and takes into consideration the individual's personal details such as age, gender, weight, medical condition, allergies, and the like and optionally even the genetic profile of the individual.

[0042] The personalized table lists all ingredients of all recommended preparations of the particular individual and the recommended intake dosage for each ingredient (optionally also indicating the measure units as well). The methods and systems of the present invention are configured for receiving the personalized table of each individual and operate a novel search engine for selecting from the database the most suitable combination of preparation packs. To do so the database is organized such that each known preparation pack (also shortly referred to as "pack") in the database is a data set (data packet) indicative of the nutraceuticals, pharmaceuticals and/or cosmeceuticals in the pack, the pack ID, the ingredients of each nutraceutical, pharmaceutical and/or cosmeceuticals of the preparation and quantity of each ingredient.

[0043] According to some embodiments, the data set of each packet also indicates the brand name of the pack, the intake type (pills, capsules, drops, creams, ointments, lotions, serums, food items etc.) and other related information.

[0044] The search is carried out using a designated algorithm, which optimizes the efficiency of the search through the database to have the resulting suitable combination of packets within a realistic timeframe. The search algorithm may also include one or more filtering algorithms for filtering out known preparation packets from the database that have no chance in being relevant to the search, using for instance various predefined conditions that may require using input data including e.g. personal information of the individual such as age, gender, medical condition, weight, height, habits (such as smoking, drinking, drug use and the like), allergies, genetic profile etc.; and/or input preferences of the user such as preferred brands, preferred intake type and the like. Some of the conditions may not depend on input parameters such as the maximum number of packets allowed in a combination and the like to limit the iterations required for the searching process. The aim of the process is to select the best matching packets combination for the specific individual from the available packets.

[0045] According to some embodiments the main search is conducted by assigning a weight factor to each relevant known preparation packet in the database in respect to the specific search session i.e. to the specific individual, according to a weighing calculation process that uses the difference between the ingredients and dosages thereof in the personalized table of the individual and ingredients and quantities thereof as indicated in a packet table of each known preparation packet in the database.

[0046] Reference is now made to Fig. 1, which is a flowchart schematically showing a process for selecting a matching combination of preparation packs for a particular individual, according to an inputted personalized table of preparations recommended for the particular individual, according to some embodiments of the present invention. This process includes first receiving a personalized table of nutraceuticals, pharmaceuticalsand/ or cosmeceuticals preparations of a particular individual 11 including all ingredients of all the preparations in the personalized table and recommended dosages thereof and optionally also personal details of the individual 12 such as the individual's age, gender, weight, height, medical condition, genetic profile, habits, medicines the subject consumes, etc.

[0047] Once the individual's personalized table is received and a search process is initiated using one or more search engines, for searching through at least one predefined database of known preparation packs for a combination of one or more packs that are most suitable for the particular subject, according to the personalized table of the subject 13 and optionally according to other conditions, rules and limitations defined in the search engine. [0048] Optionally, one or more preliminary filtering processes may be conducted 13 before initiating the main search as described in step 14 for filtering out known preparation packs that are not relevant to the search for reducing the number of searchable items in the database and therefore improving efficiency and reducing complexity of the searching process.

[0049] The output of the searching process is the one or more identified packs combinations most suitable to the particular individual 15 optionally presented to the user via one or more presentation means and according to predefined presentation rules.

[0050] Reference is now made to Fig. 2, which is a block diagram showing a system 100 for selecting a matching combination of preparation packs for a particular individual, according to some embodiments of the invention. The system 100 includes a search engine 110, which may be a software and/or hardware module operable through a computer processor 120 for running a software configured for receiving the personalized tables of individual and personal details of each individual and searching through one or more databases such as database 130 stored over a computer storing medium containing information of preparation packs for identifying a combination thereof that is most suitable to the said individual. The system 100 may enable access to a database of combined pharmaceuticals packs, nutraceuticals and/or cosmeceuticals packs, only one of each such packs types or to several databases each associated with a different type of preparations, such as pharmaceutical preparations, nutraceuticals or cosmeceuticals preparations in general or different types of pharmaceutical, nutraceutical or cosmeceuticals preparations. For example, a first database may include information relating to supplements, another database may include information relating to nutrients, another database may refer to data relating to cosmeceuticals and fourth database to medicinal drugs or only drugs associated with a specific disease or disorder and the like.

[0051] According to some embodiments, the search engine 110 operates a designated user interface for allowing users, using an end user 50 device to input personal details of individuals for identifying the best matching combination thereby by communicating with the processor 120 via a network communication link 90.

Optionally, the user interface includes at least one predefined questionnaire for allowing the user to input the subject information according to specific questionnaire fields and setup.

[0052] Additionally or alternatively, the user interface allows the user to purchase the preparation packs of the outputted combination that matches the individual's personalized table by, for example, requiring approval of the user and/or purchasing details and by accessing retailers details already saved in the data set of each known preparation pack in the database. In this way, once the user approves the purchase, an automatic ordering process may be initiated in which each retailer of each known preparation pack of the selected combination is communicated with,e.g., via an automatic ordering messaging process and computerized platform. Once purchased, the packs of the combination are sent either directly by the retailer to the individual or user, which may or may not be the same individual, or to an ordering center that handles distribution of such orders.

[0053] The data- structure of each such database such as database 130 is such that each preparation pack is indicated by at least some of the following (as mentioned above): (i) indication of the pack type (i.e. name of the drug, the nutraceutical or the cosmeceutical or a code thereof that can be identified through a codes index); (ii) table of all ingredients of the preparation pack and quantity of each ingredient; (iii) brand name of the preparation pack; (iv) side effects list; (v) mandatory rules such as ingredients that are forbidden for consumption along with the specific ingredient and the like; and (vi) pack's retailer's details.

[0054] Reference is now made to Fig. 3, which is a flowchart, illustrating a process of selecting a combination of known personalized packs of nutraceuticals,

pharmaceuticals and/or cosmeceuticals that suits maximal number of individuals in an optimal manner, according to some embodiments of the invention. This process includes providing a database stored in a data storage medium that comprises known preparation packs of nutraceuticals, pharmaceuticalsand/ or cosmeceuticals and a table of ingredients and quantity of each ingredient for each known preparation pack 21, each such known pack is associated with a specific individual registered in the system, where the specific known pack thereof includes personalized recommended

preparations and details thereof (ingredients and dosages table) of the particular individual; and identifying the most suitable combination of known preparation packs from the database that is suitable for the highest number of registered individuals 22. The search is done by using a designated algorithm based on operational researc process for optimizing the number of individuals that the combination is suitable for in respect to a suitability level of the combination.

[0055] This means that searching is designed to find a combination from the known preparation packs in the database that is the most "generic" of all so that it will be useful and suitable for the highest number of at least the registered individuals even if this combination will be less suitable to most of these individuals than their own recommended known pack associated therewith.

[0056] The object of this method is to enable large-scale production of generic packs of nutraceutical, pharmaceutical and/or cosmeceutical preparations that will be able to optimally answer the needs of a vast number of potential individuals-customers, without having to personally concoct a different preparations pack to each user individually to increase production efficiency and reduce costs for the individuals.

[0057] According to some embodiments, as shown in Fig. 3, the identified most suitable combination of known preparation packs is then outputted 23 to allow the producer of these packets to create, for example, a stock of the preparation packs of the identified most generic or suitable combinations.

[0058] The below description provides methods that can be used for: (a) producing the personalized table for an individual, receiving user input indicative of an individual's personal details including the individual's personalized table, searching through the database for suitable combinations of preparation packs including preliminary filtering methods and additionally a method for selecting a combination of known personalized packets of nutraceuticals that suits maximal number of individuals in an optimal manner.

[0059] In the below description the term "vector" refers to a data set including a table of nutraceuticals, pharmaceuticals and/ or cosmeceuticals ingredients and quantities or recommended dosages thereof of known preparation packs or

personalized preparation packs, respectively.

[0060] Input

[0061] The end user's answers to a questionnaire will serve as the input to the system. The questionnaire includes questions regarding the individual's/patient's characteristics, medical conditions (including blood tests and genetic sequencing results) and daily menu, which can be either inserted item-by-item or selected from a database of representative menus.

[0062] On-top of the wellness-profiling questions, the user will also be able to submit preferences, such as:

• Desired Brands (may be more than one) OR Brands the user wants to avoid: The user can choose only one option: if the user desires to enter "Desired Brands", only the products that belong to the brands mentioned by the user will be relevant in the search process. If the user desires to enter "Brands to avoid", all brands excluding those mentioned by the users will be relevant in the search process.

• Desired intake forms OR intake forms to avoid: The user can choose only one option: if the user desires to enter "Desire Intake forms", only the intake forms that belong mentioned by the user (e.g. capsules, liquid-drops, tablets...) will be relevant is the search process. If the user desires to enter "Intake forms to avoid", all intake forms excluding those mentioned by the users will be relevant in the search process (e.g. given, all intake forms excluding: sachets and softgels).

[0063] Ingredients

[0064] Ingredients are active materials present in the preparations that can be pharmaceuticals, nutrients, supplements,cosmeceuticals or other active substances. The Ingredients table will include the following data:

• Ingredient name.

• Unit ID (which may be mg or μg).

• NormalizationFactor (represents a value by which the amount of this ingredient should be divided in order to get a normalized amount representation).

• Importances urplus (a factor which represents how important it is not to exceed too much of this ingredient).

• ImportanceDeficit (a factor which represents how important it is not to miss too much of this ingredient).

[0065] Another table (IngredientEquivalents) will group ingredients that refer to the same active material, but at different formulation-types, to adjust quantities according to a common ground. The table will consist of the following data:

• Ingredient Group ID. • Ingredient ID.

• Percentage.

[0066] All of the ingredients under the same group-ID are equivalent to one- another (e.g. different formulas for the same active materials of the preparation). The percentage will indicate the factor by which the amount of the material (as it appears in the column "OriginalAmount" in the table "FormulasToIngredients" mentioned later in this application) will be multiplied in order to normalize it according to its active materials. For example: the following materials may belong to the same group:

Gymnema 80% (which may be the leading most common form of the material, for which the "percentage" will be set to 100%), Gymnema 5: 1 (for which the

"Percentage" will be set to 80%, compared to the 100% of the first formula) and Gymnema 40 (for which the "percentage" will be set to 50%).

[0067] Dynamic rule-book

[0068] The rule-conditions database will consist of a table similar to the current table of conditions: a set of conditions according to the patient's questionnaire-items.

[0069] The rule-results database will consist of a table similar to the current table of results, with some minor modifications: the "Result Type" column will include types relevant to preparations such as nutrients and supplements (no formulas). The column "ResultPeriod" can be removed. Two other columns that will be added are

" Importances urplus" and "ImportanceDeficit". These columns are also present in the "Ingredients" data for every ingredient (and nutrient) - and will be further elaborated later in the application. However, if the values in the columns in the current

"RulesResults" table are left at null, the default values in the "preparations" table are relevant, and if the columns in the "RulesResults" table have positive values, these values override the default values of the "preparations" table.

[0070] Another new column is "Nextls Alternative". If the value in this field is set to true, then the current ingredient (at its recommended dose) and the ingredient in the next line in the table (at its recommended dose) are considered as alternatives to each other, meaning that theoretically both will result in similar outcomes for the same condition. If several succeeding lines are set to true in this field, all of them (up to and including the last line that is set to false) are considered as alternatives to one another.

[0071] The method to choose the right alternative: If one of the alternatives appears under a different rule-result for the

individual/patient as a forbidden material (mandatory 0-amount), then this alternative is removed.

If the alternative ingredients include several nutrients, all nutrients will be included in the personalized vector. The next step is for choosing an alternative from a set of ingredients that are not nutrients.

If the individual/customer should receive a Multi- Vitamin as well (for nutritional balance), ingredients which are nutrients will be compared to instances in the multivitamin as well (the existence of the same nutrient as an alternative in one of the rules-results and in the multi-vitamin will be considered as two instances in which the same ingredient appears, under the same logic. The amount of each nutrient in the multi-vitamin will be treated as if it were a value under "resultMinValue"). If the same ingredient is present in more than one row relevant to the patient's condition-results, for example: material x is present as alternative number 4 of one condition-result satisfied for the patient, as well as alternative number 2 of another condition-result satisfied for the same patient, then this ingredient may be chosen for both condition-result sets - at the higher dose between the two (the same as the current process: the highest of the "resultMinValue" is the chosen value, unless there is a value in "resultMax Value", in which case the lowest of the

"resultMax Value" is chosen - and overcomes all other values for the same ingredient).

The material that appears most often between all alternatives is preferred as an alternative.

If more than one material shares the same number of appearances, the chosen alternative is the one whose chosen quantity (which is the highest between all appearances of the same materials) is the lowest. This also means that if all alternatives appear only once, the preferred alternative is the one with the lowest value in "resultMinValue".

If all alternatives (which are not nutrients, assuming that there are at least two non- nutrient alternative ingredients) are not shared with any other condition the patient may suffer from (thus, paragraphs 4-6 are irrelevant), the system will construct several alternative vectors, each containing a different alternative (non-nutrient) ingredient. The process of matching a best-fit package of formulas, as will be described further on, will be conducted on each alternative vector, and the best-fit vector will be the one that includes the lowest amount of intake-forms. If several alternative packages consist of the same amount of intake-forms, the preferred package will be the one that includes the lowest variability of intake-forms, and if all packages include the same variability of intake forms as well, the preferred package will be the one that contains the total lowest weight of formulas.

[0072] If an ingredient appears in more than one instance in the Rules-Results for the same individual/patient, and the quantity of one instance is chosen (e.g. the one with the higher quantity of the ingredient), the " Importances urplus" and

"ImportanceDeficit" parameters of the same chosen instance are the ones chosen as well for that ingredient.

[0073] Ingredients for which the value under "resultMaxValue" is set to 0 - are referred to materials with mandatory zero amount, meaning that these materials should not be included at all in the package the customer will receive (as opposed to 0 which result simply from not needing the ingredient, but it may be present at some small quantities in the final package if the overall offering is graded as a good-enough fit for the customer's needed vector).

[0074] A new additional type of result is "forbidden intake form", which will mention the ID of an intake-form (e.g. capsule, tablet, softgel...) that should not be given to the patient if a specific condition (according to the original questionnaire) is fulfilled.

[0075] User-specific Vector

[0076] The user specific vector is a table of all the preparation materials (such as nutrients and other supplements) required for the individual, resulting from both the personal multi-vitamin and the rules-results as mentioned above. Each ingredient appears only once in this Vector.

[0077] Each ingredient of the vector will be accompanied by 3 parameters:

NormalizationFactor (from the Ingredients table), Importances urplus and

ImportanceDeficit (either from the ingredients table - if these columns are set to NULL in the rules-results table, or replaced by the positive values appearing in the rules- results table). [0078] The user specific vector is also divided to several sections, as each section is assigned to a specific conditions-group. For example: a vector can include positive values (as well as a few mandatory zeros) of a total of 22 ingredients. The first 12 ingredients belong to the conditions-group "Nutritional Balance" (which are essentially nutrients), 2 more ingredients belong to the conditions-group "Cancer", 5 additional ingredients belong to the conditions-group "Cardiovascular", 2 ingredients belong to "Diabetes", and the final ingredient is a mandatory-zero. Mandatory-Zeroes do no need to belong to any specific conditions-group, as they will be used to filter forbidden products, contrary to other ingredients which will be referenced in order to locate appropriate product combinations. It should be noted that if a specific ingredient appeared originally (in the Rules-Results) in more than one instance, and only one instance was finally chosen (for example: the one with the highest quantity of the ingredient), then the ingredient will appear in the user's-vector under the conditions- group for which the chosen instance belonged to.

[0079] Formulas

[0080] A table of formulas (chemical or trivial names) of ingredients of

preparations that are available in the market will consist of the following fields:

• Formula Name.

• Brand.

· IntakeType (for example: capsule, tablet, softgel, drop, sachet, rounded teaspoon, rounded scoop etc.).

• ContainerType (for example: Bottle, Pack, Bag etc.)

• ServingsQuantity (for example: how many capsules in one bottle).

• DSLD-ID (Internal ID of the NIH preparations Database).

· Optional: the products ID numbers at different retailers (when applicable, for example- the product's ID in Amazon, in Vitamin-Shop, in Wallgreens, etc.) or Barcode number.

• IsActive (false means that the preparation does exist in the database, but the system will ignore its existence when searching for product-packages for the customers). · A possible link to an image/label of the product.

[0081] Another table (FormulasToIngredients) will detail the internal contents of each Formula, and will consist of the following: • Formula ID

• Ingredient ID

• Unit ID

• Original Amount (the amount as it appears on the label of the product, or retrieved from the original Database).

• Adjusted Amount.

• GradeS urplus

• GradeDeficit

[0082] If a formula consists of several ingredients, each ingredient will be mentioned in a different row, for the same Formula- ID.

[0083] The Adjusted- Amount is the Original- Amount multiplied by the Percentage for the same ingredient as mentioned in the "IngredientEquivalent" table.

[0084] GradeSurplus is the result of the following formula:

[0085] { (Original Amount)/(NormalizationFactor) } * Importances urplus

[0086] GradeDeficit is the result of the following formula:

[0087] { (Original Amount)/(NormalizationFactor) } *ImportanceDeficit

[0088] Another table will mention the condition-groups each formula is applicable for, and will consist of the following:

• Formula ID

· Condition Group ID

[0089] The same formula can be correlated to several different conditions. For example, one formula can be related for the following condition-groups: Nutritional- Balance, Diabetes, Gastro, Oxidative damage, Photo ageing, skin matrix protection, skin lightening, skin tightening and firming. In this case, the same Formula-ID will appear in three rows, each indicating the corresponding Condition-group-ID.

[0090] Filtering

[0091] If the user submitted in the questionnaire several desired brands, all formulas assigned to the brands that weren't chosen will be filtered out. Alternatively, if the user chose specific brands to avoid, the formulas belonging to these brands will be filtered out. [0092] If the user submitted in the questionnaire several desired intake forms, all formulas assigned to intake forms that weren't chosen will be filtered out.

Alternatively, if the user chose specific intake forms to avoid, the formulas assigned to them will be filtered out.

[0093] The table "IntakeRules" will consist of the following:

• Condition Group ID

• IntakeGroup

• IntakeType

• MaxDifferent

• MaxSame

• MaxTotal

[0094] IntakeType can be, for example, capsules, tablets, sachets etc. Several intake-types can be mixed together (for example, capsules and tablets) if they belong to the same IntakeGroup. Otherwise, intake types belonging to different groups cannot be intermixed in the same combination.

[0095] MaxDifferent represents the maximal number of different compositions of the same intake-type can be mixed together. For example, is the IntakeType is capsules, and MaxDifferent is set to 2, it means that a combination can include a maximal number of two different capsules. MaxSame represents the maximal amount of intake-units of the same composition. For example, if IntakeType is Drops, and IntakeSame is set to 8, then it is possible for a combination to include up to 8 drops of the same composition. MaxTotal is the maximal total amount of the basic units allowable. For example, if the IntakeType is Drops, MaxDifferent=2, MaxSame=8 and MaxTotal=8, it means that a total of 8 drops is allowable in one combination, from up to two different compositions. Some possible combinations may include: 8 drops of the same composition, 4 drops from one composition and 4 drops from a second composition, 2 drops from one composition and 6 drops from another composition, as well as number that are below the maximal limitation: 2 drops of one composition, 4 drops of one composition and one drop of a second composition, 3 drops of one composition and 2 drops of another composition and so on.

[0096] If an individual (also referred to herein as patient or user ) suffers from multiple condition groups (e.g. Cardiovascular and Diabetes, and maybe Gastro as well), the combination of preparations can include different intake types for each condition group, but a different table will indicate which intake-types can be mixed together across the entire combination. For example, one possible option will be the possibility to mix capsules, tablets, soft gels and sachets together (in this case, syrup drops cannot be mixed in the same combination with capsules, for example). A possible example is a combination that includes 2 capsules for the Cardiovascular condition group, along with one sachet for the Physical Activity condition group.

[0097] Combinations

[0098] For each condition group, the system will look up for all preparations relevant to the condition, wherein said preparations contain at least one ingredient present in the vector under said condition.

[0099] A list of all possible preparations that contain ingredients present in the customer's vector thus is generated.

[00100] Each preparation may contain, apart from ingredients present in the user's vector, also ingredients that are not present in the user's required vector. For each available preparation pack, e.g., capsule, the system will store two summed numbers: the sum of "GradeDeficit" for all ingredients in the preparation that are present in the user's vector, and the sum of "GradeSurplus" for all ingredients in the preparation that are not present in the user's vector. The following condition should be kept:

[00101] Let U be the set of all possible ingredients in the system, V the set of ingredients present in the user's personal vector, such that V c U , and n is the number of ingredients in N, where N is the subset of all ingredients present in a specific preparation currently examined or a combination of preparations under examination.

N e t/

[00102] Thus, the updated list of ingredients will reduce to the preparations that meet this criterion. [00103] The next steps are conducted for each ingredient in V, starting with the ingredient with the highest ImportanceDeficit value. If several ingredients share the same ImportanceDeficit value, the choice of which ingredient will be dealt with first and which afterwards may be random. For each ingredient, a mini-list which consists of all preparations that include this ingredient (at any amount) will be generated, and all possible combinations will be examined. The first combinations to be examined are the combinations of only one preparation. For these combinations, the following condition will be checked:

[00104] Let Z be the set of ingredients in a preparation or a combination of preparations, that are present in V, i.e.Z c V such that Ζ=Χ·Ν

[00105] If the current ingredient under examination (the ingredient with the highest ImportanceDeficit value) is y. j £ n:

( True if Z - <^ v ^■

Next combination of current supplement = } J J J

False otherwise

[00106] Where z _j is the ingredient j in the currently examines preparation, and v _j is the ingredient j in V. Thus, if the amount of the ingredient under examination in the current combination (which is initially - one intakeForm of the current preparation) is lower than the required amount of the ingredient in V, then a higher combination should be also considered, which can be either the next multiple of intakeForms of the same preparation, or a combination of the current preparation with another spreparation that contains the same ingredient.

[00107] The order of conditioning is such that first all single (and relevant) intakeForms are checked - only if maxDifferent, maxSame or maxTotal is higher than the quantity of IntakeForms in the currently examined combination, combination of two intakeForms are checked next, and so on (if intakeForms is set to 1, the condition is irrelevant. Also, if the currently examined combination is 2 capsules of the same preparation, for example, and maxSame is set to 3 capsules, then there is no need to check the condition for 3 capsules since even if it will be met, 4 capsules is not an option. Similarly, if maxDifferent is set to 2, maxSame is also set to 2, but maxTotal is set to 3, the combination can include a maximum of two identical capsules with another single different capsule, but not 2 identical capsules with another 2 similar capsules, since in that case the total number of capsules, 4, will be higher than maxTotal). If the criterion of Zj<Vj is met (where for a combination of more than one preparation, Zj is the total sum of the ingredient in all preparations contained in the combination), and maxSame for the current intakeForm is higher than the current number of intakeForms checked (initially it is 1, then it is 2 etc.), then the next combination that will be checked is the same preparation at the next quantity (last examined quantity + 1). If maxDifferent is also higher than the current number of intakeForms checked, then combination of different preparations will be checked as well. Such combination will include only preparations for which the criterion Zj<Vj is still valid, at quantities for which it is still valid. Each combination may include identical preparations at different quantities up to maxSame, combined with other different preparations at quantities which are not higher than maxDifferent, keeping the condition that the total number of preparations is not higher than maxTotal.

[00108] Combination-Grading

[00109] For each combination (which may include a single preparation or more), the absolute value of the difference between the amount of each ingredient in the

combination and the required amount in the personal Vector is divided by the normalizationFactor, and then multiplied by importances urplus is the existing amount in the combination is higher than the required amount, or multiplied by

importanceDeficit otherwise. The sum of these results is the grade of the combination. The combination with the closest grade is the chosen one.

[00110] Thus, the Grade G _k for each combination k is:

importanceSurplusi if z _t > Vi importanceDeficitt if z _t < v _t

Where K is the set of all examined options (keK), and the chosen combination is:

min G _h

keK ^K

[00111] If more than one combination results in the same minimal G value, then the chosen combination will be the one with fewer total amount of preparations. If more than one combination results in the same minimal G value, and the combinations consist of the same total amount of preparations, then the chosen combination will be the one with fewer total amount of different preparations. In any other case, the choice may be arbitrary.

[00112] Another parameter may adjust the result G _k according to the preparation's Product-Quality (PQ). This parameter is an indicator for the products quality, in the range 0<PQ≤1, where 1 indicates the highest quality, and lower numerical fractions represent an attenuation of the result according to this parameter. If PQ is accounted for as well, then G _k is calculated as follows:

[00113] This choice of preparations or combinations of preparations will be conducted for each ingredient in the required vector V, starting from the ingredient with the highest importanceDeficit value to the lowest (in any case where more than one ingredient has the same importanceDeficit value, the choice may be arbitrary). If for a specific ingredient, all possible combinations were already calculated during the comparison process for other ingredients, the process of calculation and choice of combinations will be skipped for this ingredient.

[00114] After each choice of preparation (or set of preparations) is chosen to be added to the current package, the amount of ingredients existing in this set of preparations (and present in the user's personalized vector) will be subtracted from the vector, so that the new personalized vector will include updated value of these ingredients. If an ingredient exists in the chosen preparation or set of preparations at a quantity which is higher than the one in the vector, then the updated quantity in the vector will be zero. Thus, negative quantities are not allowed for the vector.

[00115] The combinations chosen due to each ingredient's comparison process will be added together to form the personal cart for the user, representing the complete set of preparations that would be the best fit for the personalized required vector.

[00116] Combination's Fitness Grade

[00117] A grade G _v will be calculated in a similar manner to G _r , only that instead of a subtraction between a required and proposed composition for each nutrient, only the required amounts of each nutrient in the personalized vector, normalized by the normalization factor and multiplied by importance deficit will be summed up. The contribution of each nutrient to the summation will be defined as G > _v v,r.

G _v — / G _{v i} = ; importanceSurpluSi — I ' — I normalizationFactori

i=i÷v i=i÷v

[00118] Dividing G _{v /} of each nutrient i by the total grade G _v will yield the relative contribution (in percentage) of each nutrient in the personalized vector - NP .

[00119] The final fitness grade of a cart Ft _c , representing an estimation (in

percentages) of the fitness of a selected combination to the originally require

personalized vector, will be as follows: onF actori

< ^c i AND v _t < c _t < 2 ^■ v _t < ^c i AND 2 ^■ ι¾ < c _;

where c, represents the total amount of a nutrient i in the examined cart, resulting from the summation of the amounts of this nutrient from all of the combinations present in this cart.

[00120] Multiple Cart Presentation

[00121] It is possible to work in a multiple-cart mode, where the customer will be presented with several different choices in order to choose a selected cart according to his/her preferences.

[00122] In this mode, several different carts will be constructed as follows: for each ingredient, the second-best combination (i.e. the combination with the second lowest G _r value) will be chosen as an option. Thus, the total number of options is limited to twice the total number of ingredients. All possible combinations of different cart that include either the original lowest G _r or the second lowest G _r value will be constructed. For each cart, the fitness grade Ft _c will be calculated (subscript c stands for the cart under examination) and presented to the user next to the contents of the cart.

[00123] Additional parameters, such as the price of each cart (which can be further broken down to prices offered from different retailers) might also be presented.

[00124] Prefixed Combinations Choices

[00125] The following passages will describe the methodology for choosing a small subset of preparation combinations that represent the best suitability to a much wider set of required compositions of actual individual. The system manager will input the desired number of preparation packs (e.g. capsules).

[00126] Step 1: [00127] A basic list of vectors will include vector-compositions which fit in volume into one preparation pack type such as one capsule of predefined dimensions (or tablet). If a composition for a specific patient includes, for example, nutrients that may only fit into two capsules due to its overall volume, exactly half of the nutrients' amount will be stored as a basic vector in the list of vectors. Otherwise, the complete composition will serve as a basic vector by itself.

[00128] Step 2:

[00129] The list will also include all combinations of the same basic vectors at double quantities. Thus, if the original list contained n vectors, the new list L will include 2n vectors.

[00130] Step 3:

[00131] For each of the vectors in the list, a grade will be computes as following: the grade according to the formula G _k will be calculated between said vector and each of the customers-required compositions. The vector's total grade GRv will be the result of summing all of these grades (between the currently examined vectors and every other required composition) together.

Zi — v _{k l} \ (importanceSurplus if z _l > v _l normalizationF actor I importanceDeficit if z _t < v _t

[00132] where M represents the number of customer-required compositions, and Vk,i is the value of nutrient i in the required composition v for customer k.

[00133] Step 4:

[00134] The minimal value of all GR _V options is chosen.

min GR _V

VEL

[00135] If the chosen vector is based on a single basic vector, then this basic vector is added to the results list. If the chosen vector is composed of a double quantity of a basic vector, then the basic vector from which it has been constructed is added to the results list.

[00136] The basic vector added to the results list, as well as the vector based on a doubled amount of the same basic vector, will be removed from the original list.

[00137] Step 5: [00138] For a combination that may include up to two different or identical capsule- compositions, the list of vectors is extended to include all combinations of the last basic vector added to the results list, with any other vector - excluding a combination with itself (as such combination has already been accounted for in Step-2).

[00139] Step-6:

[00140] The grade GR _V is calculated for all of the newly added combinations to the list.

[00141] Step 7 (repeat step 4):

[00142] The minimal value of all GR _V options (between the complete list of original list and the newly added combinations) is chosen.

[00143] Once again, if the chosen vector is based on a single basic vector, then this basic vector is added to the results list. If the chosen vector is composed of a double quantity of a basic vector, then the basic vector from which it has been constructed is added to the results list. However, if the minimal GR _V value is that of a combination of the last- added basic vector with another basic vector, then the second basic vector will be added to the results list.

[00144] All combinations that include the last added basic vector (including the basic vector itself, or its double amount) will be removed from the current list.

[00145] Step 8 (repeat step 5):

[00146] The list of vectors is extended to include all combinations of the last basic vector added to the results list, with any other vector - excluding combinations with any of the basic vectors already present in the results list.

[00147] Steps 6-8 will be repeated until the results list includes the amount of basic vectors as the number of capsules desired by the system manager.

[00148] Mandatory Zeros Integration

[00149] For patients that have mandatory zero-amounts for certain nutrients in their compositions, the process can be conducted in the similar manner as described in steps 1-8. The system manager needs to provide the specific nutrient for which the mandatory zero will be examined. In this case, the list of customer-required compositions will include only the subset of compositions of costumers for whom such mandatory zero amount of the specific nutrient was originally advised, meaning that these compositions do not include said nutrient. The list of basic vectors will be generated from all compositions which do not include any amount of the mandatory- zeroed nutrient (including compositions that not necessarily exclude this nutrient due to a mandatory zero, but simply because it was not required for a specific customer), as described in Steps 1-2 above.

[00150] Another option is for the system manager to define several nutrients for which mandatory zeroes will be defined simultaneously. In that case, the system will conduct the same procedure, while the list of customer-required compositions and the list of basic vectors will include only compositions in which all such nutrients are absent.

[00151] Uploading current inventory

[00152] A list containing a subset of basic vectors can be uploaded to the system. The basic list as described in steps 1-2 will be originated in the same manner.

However, for any basic vector that exists in the uploaded list but doesn't exist in the newly generated basic list, it will be added to the list both as a basic vector and as a double-quantity vector.

[00153] The rest of the calculation procedure will behave in the same manner.

However, if a basic vector is chosen to be added to the results list, and it already is included in the uploaded list, the procedure will continue its regular process (including adding all combination of this chosen vector with all other basic vectors to the list) without actually adding the basic vector itself to the results list.

[00154] In case a list is uploaded under the mandatory-zeroes mode, only the vectors that do not include the filtered nutrient will be added to the list.

[00155] Analyzing mixed set of input data (regular and mandatory zeros)

[00156] If a data file of customer-required compositions include subset of

compositions in which several mandatory zeroes are present (for some customers, it may be only one specific mandatory zero, for other several mandatory zeroes) as well as regular compositions without mandatory zeroes, the system will segment the data as follows:

I. A segment of all regular compositions (without any mandatory zeroes).

II. For each different single nutrient with a mandatory zero (for compositions that include only one single mandatory zero within them) - a different segment.

III. For each set of several nutrients with mandatory zeros (more than one) - a different segment designated only for compositions that exclude only these mandatory zeros. [00157] The percentage of each segment from the total number of compositions in the original complete list of compositions will be calculated, and the number of required-capsules entered by the system-manager will be segmented as well according to the same percentages. The actual resulting number of capsules for each segment will be rounded up.

[00158] The system will conduct the search process for each segment separately, stopping at the resulting calculated number of capsules for each segment. The lists of customer-required compositions will be mutually exclusive between all segment (meaning that if a customer's required composition includes several mandatory zeroes, it will be present only in the segment of these mandatory zeroes, and it will not appear in the segments that include only smaller subset of these mandatory zeroes, or a one of the single mandatory zeros). The list of original basic vectors (as describes in step 1) for each segment that includes one or more mandatory zeroes, will be limited to all compositions that do not include these specific nutrients. A list of basic vectors for a segment at a lower order - for example, one that consists of only a single mandatory zero, will also include basic vectors that are present in other segments due to the fact that they exclude not only this nutrient, but other nutrients as well. Thus, for the segment the segment of regular compositions (without any mandatory zeroes), the list of customer-required compositions will include only compositions that do not include any mandatory zeroes, but the list of basic vectors will include all basic vectors

(including those that exclude several nutrients and are also present in other segments).

[00159] The order by which the process will be executed will start with the segment with the least restrictions (the segments of regular compositions and no mandatory zeroes, for example) and ends with the segment with the highest number of restrictions (the highest number of mandatory zeroes). The order of execution of segments that consist of the same number of restrictions may be chosen arbitrarily.

[00160] Functional / Medical Foods Incorporation

[00161] A preliminary personalized vector (referred to as the "First Stage

Personalized Vector") will be constructed for the patient, which will include the required micro -nutrients and preparations, as well as macro-nutrients (e.g. carbs, fats or proteins). Utilization of the First Stage Personalized Vector will result from several possible scenarios:

A. The patient needs to consume medical foods. B. The patient's medical profile in the Expert System suggests a need to utilize medical/functional foods within the recommended dietary menu.

C. The patient wants the dietary menu to include such foods.

These foods are categorized into the following food subgroups:

· Medical Foods

• Functional Foods

• Sports Foods

[00162] Each such food item will contain the complete data and attributes as in the rest of the food items (e.g. nutrients, serving sizes etc.), as well as a breakdown to other nutraceuticals they may include. Some medical foods may have reimbursement codes implemented as well. If a patient indicates in the system's questionnaires

reimbursement-entitlement, the search process will be limited only to medical foods that have a proper reimbursement code.

[00163] Once one of the above scenarios for medical / functional (including sports) foods have been met, the same matching process described between the personalized vector and proper preparations, will apply to matching the best- fit medical / functional foods and a First Stage Personalized Vector.

[00164] After adjusting and submitting a final menu, the algorithm will recalculate the final personalized vector, including required amount of ingredients still absent, accounting for all foods included in the final menu. A matching process between this personalized vector and the variety of preparations will be executed as described above.

[00165] Example:

V - Required User's Vector

Norm - NormalizationFactor

IS - Importances urplus

ID - ImportanceDeficit

GS - GradeS urplus

GD - GradeDeficit

[00166] In the current example, U consists of 12 ingredients, of which 7 are present if the user's required vector - V. ingredient I ron Zinc Vit.C B12 Cr Gym MT NA1 NA2 NA3- NA4 NAS

V 5.3 5.4 44 2 200 400 600 - - - - -

Norm 18 15 60 2 30 200 400 5 70 100 3 12

IS 60 50 10 1 1 20 20 1 20 10 1 30

ID 80 75 50 60 40 90 90 10 100 50 30 60

[00167] The complete database consists of 11 supplements (in this example, all of which are capsules, Capl - Capl l).

[00168] Caps 8-11 don't include any ingredients that are present in V, thus the list of relevant supplements is reduced to Caps 1-7.

[00169] Next we compute for each Cap the sum of "GradeDeficit" and the sum of " GradeS urplus" for the relevant ingredients. For Capl : tron Zinc Vit.C B12 Cr Gym (MAI NA2 NA3 NA4 HAS

Ca I 10 100 30 200 1000

G D 44.4 833 40

GS 57 333

^ GD = (44.4 + 83.3 + 40) ^ GS = (57 + 333)

[00170] Thus, since∑GS >∑GD, Ca l does not meet the required criteria and is filtered out. In a similar way, Cap3 is also filtered out, leaving the relevant list of supplements with 5 options: Cap2, Cap4, Cap5, Cap6, Cap7.

[00171] Next, each ingredient is examined in turn, staring with the ingredient with the highest ID (ImportanceDeficit) value. In this case, 2 ingredients share the same maximal ID value of 90: Gymnema (Gym) and Milk-Thistle (MT). The choice between the two is arbitrary. For example, the system may start by examining the ingredient GYM, which is present in 2 different supplements: Cap4 and Cap5. It is assumed in the current example that all supplements (for all conditions) may be given as one or two capsules, i.e.:

maxDifferent = 2

maxSame = 2

maxTotal = 2

[00172] Thus, the options are one Cap4 capsule, 2 Cap4 capsules, 1 Cap4 capsule combined with Cap5 capsule, 1 Cap5 capsule, and 2Cap5 capsules. However, the system checks for each supplement if it doesn't exceed the required amount in V, and only if this condition is met, a higher multiple or combination of this supplement is examined. In the current case:

(Cap4l _G YM=600)>(VI _G YM=400)

Thus, the option 2*Cap4 or Cap4+Cap5 are irrelevant.

(Cap5l _GYM =200)<(VlGYM=400), thus 2*Cap5 is also a relevant option. Next each combination will be graded. The first grade for a combination that includes only Cap4 is:

600 - 400 0 - 600

! — ^L■ 20 + - ^■

200 400

= 28 + 27 + 36.66 + 60 + 266.66 + 20 + 135 = 573.32

[00173] The second grade for a combination that includes only Cap5 is:

Q - l£ Hl . go _ _| _ l£^ [ . 75 _|_ l£^44| _ ₊ | 0-2| _ ^ ₊ | 100-200| _ ₊ 1200-4001

18 15 60 30 200

90 + 12_ ££1 . go + !^-2l - 20 = 28 + 27 + 36.66 + 60 + 133.33 + 90 + 135 +

400 70

8.57 = 518.57

And the third grade for a combination that includes two Cap5 supplements is:

5.4| - 44| |0 - 2 | |200 - 200|

G ₃ = - - 50 + - ^■ 60 + -

15 60 30

|400 - 400| 10 - 6001 |60 - 0|

— x + 90 + 20

200 400 70

= 28 + 27 + 36.66 + 60 + 0 + 0 + 135 + 17.14 = 303.8

[00174] The minimal chosen grade is G ₃ , which includes two Cap5 supplements.

This combination is added to the user's cart.

[00175] The new Vector:

[00176] The next ingredient with the same maximal ID value of 90 is Milk-Thistle (MT), which is present in 2 different supplements: Cap6 and Cap7. It is assumed in the current example that all supplements (for all conditions) may be given as one or two capsules.

[00177] Again, the options are one Cap6 capsule, 2 Cap6 capsules, 1 Cap6 capsule combined with Cap7 capsule, 1 Cap7 capsule, and 2 Cap7 capsules. Again, the system checks for each supplement if it doesn't exceed the required amount in V, and only if this condition is met, a higher multiple or combination of this supplement is examined.

[00178] In the current case:

(Cap6l _M T=800)>(VI _M T=600)

Thus, the option 2*Cap6 or Cap6+Cap7 are irrelevant.

(Cap7l _M T=400)<(VI _M T=600), thus 2*Cap7 is also a relevant option.

Next each combination will be graded. The first grade for a combination that includes only Cap6 is:

13 - 6.31 10-5.41 |0 - 44| |0-2| |0— 0|

|0-0| |800 - 600|

^♦ W **— ϊδδ— ²⁰

= 14.66 + 27 + 36.66 + 60 + 0 + 0 + 10 = 148.37

[00179] The second grade for a combination that includes only Cap7 is:

10 -6.31 10-5.41 |60 -44| |0-2| |0— 0|

G ₅ = _Λη ^■ 80 + „ _r ^■ 75 + -——— - ^■ 10 +—— - ^■ 60 +—— - ^■ X

⁵ 18 15 60 2 30

|0-0| |400 - 600| |100-0| |25 - 0|

+ ^■ X + ^■ 90 + ^■ 10 + ^■ 30

200 400 100 12

= 28 + 27 + 36.66 + 2.66 + 0 + 0 + 45 + 10 + 62.5 = 211.85

[00180] And the third grade for a combination that includes two Cap7 supplements is:

10 -6.31 10-5.41 |120-44| |0 - 2| |0— 0| G ₆ = ^■ 80 + —— ^■ 75 + ^■ 10 + ^■ 60 + ^■ X

⁶ 18 15 60 2 30

|0-0| |800 - 600| |200 - 0| |50 - 0|

+ _^ „ ^■ X + 77^: ^L■ 20 + _Ληη ^■ 10 +— -—— ^■ 30

200 400 100 12

= 28 + 27 + 36.66 + 12.66 + 0 + 0 + 10 + 20 + 125 = 259.32

[00181] The minimal chosen grade is G4, which includes one Cap6 supplement.

This supplement is added to the user's cart.

[00182] The new Vector: ) ron Zinc Vit.C B12 Cr Gym MX

V 6,3 5,4 44 2 0 0 600

Ca p6 3 800

V" 3.3 5.4 44 2 0 0 0

[00183] The next ingredient with the same highest ID value of 80 is Iron, which is present in 2 different supplements: Capl and Cap2. Capl has been filtered out since in its case∑GS >∑GD, which leaves only Cap2 as candidate. The options are one Cap2 capsule or two Cap2 capsules:

[00184] thus 2*Cap2 is a relevant option.

[00185] The first grade for a combination that includes only Cap2 is:

_{G7 =} H_ . ₈ o ₊ ^_^. _{50 +} ^.50 +^-60 +^- + ^- +

18 15 60 2 30 200

+ i^. _{1 +} |20

5.77 + 115.33 + 36.66 + 60 + 0 + 0 + 0 +

400 5 70

2.2 + 5.71 =225.67

[00186] The second grade for a combination that includes two Cap2 supplements:

14- 3.31 180 - 5.41 |0 -44| |0 -2| |0— 0|

G ₈ = -— ~— ^■ 60 + — ^■ 50 + „ ^■ 50 + „ ^■ 60 + ^■ X

18 15 60 30 lo - oi lo - oi |22 - 0| 140 - 0|

+

200 x + 400 x + 1 + 20

5 70

= 2.33 + 248.66 + 36.66 + 60 + 0 + 0 + 0 + 4.4 + 11.42

= 363.47

[00187] The minimal chosen grade is G ₇ , which includes one Cap2 supplement. This supplement is added to the user's cart.

[00188] The new Vector:

[00189] The next ingredient with the highest ID value of 75 is Zinc, which is present only in Cap2. However, Cap2 has already been examined (both at one or two capsules). Thus, there is no need to repeat these calculations, so the system will move on to the next ingredient with the highest ID value of 60 which is Vitamin B 12. However, this ingredient is present only in Cap3 which has been filtered out. Since it is not present in any valid supplements, the system will move on to the next ingredient with the highest ID value of 50 which is Vitamin C. Capl which includes this ingredient has been filtered out, and Cap7 has already been examined and calculated, so the system will move on to the last ingredient with the ID value of 40 which is Chromimum. The ingredient is present in Capl and Cap3 which have been filtered out, and in Cap5 which has already been calculated. Thus, the calculation process stops here, and the final cart includes: Two Cap5 supplement + one Cap6 supplement + One Cap2 supplement.

[00190] The personalized vector's grade is:

6.3 5.4 44 2 200 400 600

G _v = 80 +— ^■ 75 +— ^■ 50 + - ^■ 60 + 30 + 90 + 90 v 18 15 60 2 40 200 400

= 28 + 27 + 36.66 + 60 + 150 + 180 + 135 = 613.66

[00191] The relative contribution NP of Iron is:

28

= 4.56%

613.66

[00192] Similarly, the relative contribution of the rest of the ingredients is:

[00193] The calculation of each of the members of the fitness grade Ft is:

6.3-5

Iron: 5<6.3, thus: 4.56% = 0.94%

6.3

Zinc: 40>15 AND 40>2*5.4, thus: 1 ^■ 4.4% = 4.4%

44-0

Vit. C: 0<44, thus: 5.97% = 5.97%

44

2-0

Vit. B 12: 0<2, thus: 9.77% = 9.77%

2

Chromium: 200<200, thus: ² °° ^~200■ 24.44% = 0

200

400-400

Gymnema: 400<400, thus: 29.33% = 0

400 Milk-Thistle: 800>400 AND 600<800<800 ^* 2, thus: 22% = 7.33%

600

[00194] The total fitness grade therefor is:

Ft _c = 100 - (0.94 + 4.4 + 5.97 + 9.77 + 0 + 0 + 7.33) = 71.59%

[00195] Many alterations and modifications may be made by those having ordinary skill in the art without departing from the spirit and scope of the invention. Therefore, it must be understood that the illustrated embodiment has been set forth only for the purposes of example and that it should not be taken as limiting the invention as defined by the following invention and its various embodiments and/or by the following claims. For example, notwithstanding the fact that the elements of a claim are set forth below in a certain combination, it must be expressly understood that the invention includes other combinations of fewer, more or different elements, which are disclosed in above even when not initially claimed in such combinations. A teaching that two elements are combined in a claimed combination is further to be understood as also allowing for a claimed combination in which the two elements are not combined with each other, but may be used alone or combined in other combinations. The excision of any disclosed element of the invention is explicitly contemplated as within the scope of the invention.

[00196] The words used in this specification to describe the invention and its various embodiments are to be understood not only in the sense of their commonly defined meanings, but to include by special definition in this specification structure, material or acts beyond the scope of the commonly defined meanings. Thus if an element can be understood in the context of this specification as including more than one meaning, then its use in a claim must be understood as being generic to all possible meanings supported by the specification and by the word itself.

[00197] The definitions of the words or elements of the following claims are, therefore, defined in this specification to include not only the combination of elements which are literally set forth, but all equivalent structure, material or acts for performing substantially the same function in substantially the same way to obtain substantially the same result. In this sense it is therefore contemplated that an equivalent substitution of two or more elements may be made for any one of the elements in the claims below or that a single element may be substituted for two or more elements in a claim. Although elements may be described above as acting in certain combinations and even initially claimed as such, it is to be expressly understood that one or more elements from a claimed combination can in some cases be excised from the combination and that the claimed combination may be directed to a sub-combination or variation of a subcombination.

[00198] Insubstantial changes from the claimed subject matter as viewed by a person with ordinary skill in the art, now known or later devised, are expressly contemplated as being equivalently within the scope of the claims. Therefore, obvious substitutions now or later known to one with ordinary skill in the art are defined to be within the scope of the defined elements.

[00199] The claims are thus to be understood to include what is specifically illustrated and described above, what is conceptually equivalent, what can be obviously substituted and also what essentially incorporates the essential idea of the invention.

[00200] Although the invention has been described in detail, nevertheless changes and modifications, which do not depart from the teachings of the present invention, will be evident to those skilled in the art. Such changes and modifications are deemed to come within the purview of the present invention and the appended claims.