Patent Application
20130124266
The present invention generally relates to a system, method and program product for using a computer system to generate business deals to fund the research and development of innovative technology products, by using a distributed, networked computer system to integrate the elements of a deal from data provided by parties participating in the system; and to establish constructs, standards and protocols for the proper and efficient functioning of the system.
One problem associated with the current approach to research and development funding is that it provides funding for discrete stages of a research and development timeline, which makes research planning and continuity difficult. Funding currently comes from individual sources that often do not communicate or exchange information or align regarding their goals or needs, so funding from each of these “vertical silos” cannot be aligned or aggregated to fund the entire research and development timeline in a continuous, efficient manner. Due to these drawbacks, there is limited certainty for researchers, funders, investors, and other stakeholders, which translates to delayed economic development and job growth and slowdowns in scientific advancement.
According to one implementation, there is provided a method comprising:
accessing, using one or more computers, one or more databases on computer-readable storage media, comprising:
obtaining and storing over time, using the one or more computers, data for product development projects, research and development organizations; funding organizations, and respective organization requirements; securities issuing entities, and respective issuing entity requirements, securities purchasing entities, and pathable development projects;
determining or obtaining a respective technical readiness level for each of a plurality of the product development projects and storing, using the one or more computers, the respective technical readiness levels in the one or more databases;
determining or obtaining for each of a plurality of the product development projects, respective development stages and milestones for a respective pathable development project and one or more entities to perform the respective development stages;
determining, using the one or more computers, an estimated full or partial funding amount for respective of the pathable development projects;
determining in one or more matching steps one or more of:
determining, using the one or more computers, that a level or percentage of funding of the pathable development project is substantially complete relative to the full funding amount for the respective pathable development project or determining a gap in the level or percentage of funding of the pathable development project relative to the full funding amount for the respective pathable development project.
The above and related objects, features and advantages of the present invention, will be more fully understood by reference to the following detailed description of the exemplary embodiments of the present invention, when taken in conjunction with the following exemplary figures, wherein:
The present invention generally relates to systems, methods and, program products for creating and operating a computerized system to identify, align, match, track, report, audit, and conduct and create reports on project deals and comparative deal flow and other activities using an aligned and linked funding approach. In one or more embodiments, the system and method facilitates generation of business deals to fund the research and development of innovative technology products, by using a distributed, networked computer system to integrate the elements of a deal from data provided by participating parties.
In one or more embodiments, a computer system is used to align the financing of innovation to the actual Research & Development (R&D) process of innovation technology organizations, by means of calculating and facilitating bond-based financing deals to overcome vertical siloed barriers among funding organizations and achieve strategic continuity of funding aimed at delivering licensed, usable products.
In one or more embodiments, aligned financing deals may be generated using computerized logic to perform one or more of the following:
Inputs to system 100 generally include product funding organization inputs, research and development and/or technology development inputs, facilitator and/or bond issuer inputs, credit inputs, and bond purchaser inputs. Outputs from system 100 may include processed or unprocessed data based at least in part on the input data and may be specific to at least one request for data received by system 100.
Product funding organization inputs 15 generally relate to data on organizations and on the types of products and/or research and development they would like to promote by facilitating the issuance and purchase of bonds. For example, product funding organizations 10 may include organizations such as governmental agencies that have specific goals with respect to products that would help meet a public need, as well as private groups or foundations that are willing to provide similar support to further their own goals. These identified types of organizations are not intended to limit the scope of what a product funding organization may be, but merely provide illustrative examples for the purposes of the discussion herein. Product funding organization inputs 10 may also provide criteria related to the products the respective organization seeks to promote, along with a specified bond payment pledge or guarantee that would be made available to facilitate the product development. Alternatively, or in addition, the bond payment pledge or guarantee may be made available through other facilitation organizations, as will be discussed below, to research and development organizations that are developing products or technologies related to the product funding organization's goals and that meet the specified criteria. In an exemplary embodiment, these product funding organization inputs 15 may include product needs, scientific criteria to be satisfied, baseline financing terms, and the amount of debt service payment, pledge or guarantee provided. As mentioned previously, these product funding organizations 10 may be public federal agencies or organizations, such as the Department of Health and Human Services, Department of Defense, Department of Agriculture, government-sponsored entities, or may be private foundations or organizations, such as the Gates Foundation. An example data structure for product funding organization inputs in embodiments of the invention may comprise:
Research and development and/or technology development inputs 25, such as pathable research and development for a potential marketable end product, may be provided by a plurality of entities 20 such as research and development organizations, universities, private research and development companies, or individuals and may be related to planned or current research and development. These examples of entities 20 that may provide technology development inputs are not intended to be limiting, and this group may be collectively referred to herein as “research and development organizations.” In one embodiment, technology inputs received from research and development entities relate to ongoing research and development that has been developed to a specific stage by the research and development entity. In one example, the research and development entity may have funded the past research and development with a combination of grant funding, loans, equity investments, debt investments, and/or other forms of financing. The research and development entity may have achieved a specified point with its research and development and may have satisfied certain criteria with its research and development, which enable the research and development entity to take advantage of the features of system 100 for further research and development funding. In an exemplary embodiment, these research and development and/or technology inputs 25 may include the type of product being researched, scientific data supporting a proof of concept (e.g., data supporting how a potential product can be manufactured and turn a profit), and a plan that includes stages with milestones for multiple of the stages, a path to the product or licensing arrangement, a timeline, cost of the path, and a business plan. An example data structure for research and/or technology development inputs 25 in embodiments of the invention may comprise:
Facilitators 70 may be organizations, finance institutions, economic development agencies, individuals, or any other type of organizations that are able to facilitate a funding opportunity between research and technology development organizations 20 and a product funding source 10. In embodiments, facilitators 70 may comprise economic developers 30, strategic investors 40, private-sector co-guarantors 42, or bond purchasers 50.
Economic development inputs 35 relate to potential funding opportunities and allow product funding organization inputs 15 to be aligned in various preliminary sub-matches with research and development and technology development inputs 25 to facilitate further technological development. Economic developers 30 may be organizations, finance institutions, economic development agencies, individuals, or any other type of organizations that are able to facilitate a funding opportunity between research and technology development organizations 20 and a product funding source 10 by issuing or facilitating the issuance of bonds. Economic developers generally have specific criteria regarding the types of innovation for which they would prefer to facilitate funding, with the exact criteria specific to the facilitator. For example, local economic development agency developers may have certain criteria related to local job creation and local investment. Research and technology development organizations that already have operations within the jurisdiction associated with the agency facilitator may be able to satisfy these criteria by expanding their existing operations. Organizations that do not already have a presence in the jurisdiction may qualify as well, for example, by agreeing to establish a presence within the jurisdiction so that it satisfies the criteria set forth by the economic development agency. In an exemplary embodiment, economic development agency inputs 35 may include geographical requirements to locate the operation, company suggestions for particular types of opportunities, job creation goals, financial proffers, and bonding authority. An example data structure for Economic Development inputs in embodiments of the invention may comprise:
Credit inputs 45 provide different information or services to facilitate a matching opportunity between product funding organizations 10 and research and technology organizations 20. In one embodiment, credit inputs comprise an equity investment from strategic investors 40. For example, strategic investors may provide an equity investment in a research and development organization 20 based on the research and development organization's current or future research and development. This investment may also satisfy a criteria specified by the product funding organization 10 or system 100 that allows the research and development organization 20 to qualify for funding opportunities using system 100. Equity inputs from strategic investors are generally direct equity investments made in the research and development organization by investors who are qualified to evaluate the nature of the technology and its relative merits. In some embodiments, equity investors 40 may include organizations associated with governmental agencies, such as DARPA or other funding agencies, and/or may be private investment organizations. Inputs from strategic investors may include types of technologies to be funded, types of financing offered, vetting credentials, and investment amounts. An example data structure for Credit inputs for embodiments of the invention may comprise:
In some embodiments, credit inputs 45 may be received by system 100 from one or more private sector co-guarantors 42. Private sector co-guarantors 42 may be organizations or individuals who provide additional guarantees or pledges related to the guarantee or pledge provided by a product funding organization. In some embodiments, inputs from private sector co-guarantors may impact bond terms provided by one or more facilitators, as discussed previously, by providing an additional guarantee of a bond payment or pledge that allows the economic developers 30 to offer bonds to potential bond purchasers with more attractive terms. In one example, an input from a private sector co-guarantor may provide an additional guarantee related to bonds that are to be offered by a local economic development agency economic developer 30. The credit input 45 may also include a product interest of the private sector co-guarantor, which identifies the types of products or research and development it is willing to promote, as discussed previously with respect to product funding organizations. In an exemplary embodiment, inputs from private sector co-guarantors may include product interest, and monetary amounts that the entity is willing to pledge, and financing terms.
Bond purchaser inputs 55 are also forms of facilitator inputs 70 and may be received by system 100 from individual investors or organizations that express an interest in or provide a commitment to purchase bonds related to research and development being performed by research organizations. These inputs may include bond purchase terms, identification of particular tranches related to stages of an organization's research development path, and amounts that the purchaser is willing to buy through system 100. In an exemplary embodiment, inputs from bond purchasers include purchase terms, such as interest rates, monetary payment amounts, repayment schedules, and other bond-purchase terms (e.g. debt-to-equity conversion terms, warrants, etc.). An example data structure for bond purchaser inputs in embodiments of the invention may comprise:
It should be noted that the method of obtaining the foregoing inputs is not limiting on the invention. For example, one or more of the inputs may be received electronically over a communications network. One or more inputs may also be received by mail, facsimile, or by telephone, or a during a meeting, and then entered or scanned electronically into system 100, or may comprise pulling the data from a database or other entity, or may comprise generating some of the data.
A deal engine 110 is configured to process inputs received from various sources via an input-output interface 105 and may facilitate and calculate matching to generate proposed deal terms, as will be discussed in further detail below. One example of an input-output interface 105 is shown in
Referring again to
An analytics module 130 is configured to provide outputs related to information received by system 100. In some embodiments, analytics module 130 may facilitate basic access to information input to system 100 and stored in database 120 by users. For example, a product funding organization may input data related to a new initiative that may be accessible to all users of system 100, or only to selected users, or only to selected user categories, or only after one or more criteria are satisfied. In some embodiments, analytics module 130 may calculate and provide analytical information in response to one or more requests or queries to the system 100 for information stored by system 100. For example, analytics module 130 may receive a request regarding numbers and types of research and development organizations 20 that are operating in a certain geographic area. In addition, information may be requested regarding amounts and sources of funding received by these research and technology organizations over a specified time period. In embodiments, analytics module 130 may allow financial organizations to identify risks and benefits of specific deals, funding trends in industries, geographic areas, or specific companies, which may allow them to identify additional investment opportunities via system 100 or through other capital markets. In embodiments, analytics module 130 may generate a series of sub-matches of the various inputs using a given input as a starting point. For example, research and development organization 20 may input data into the system 100 to determine scenarios with various combinations of other players to achieve a fully funded product development plan for a pathable product.
The system 100 of
Deal engine 110 facilitates the aligning and grouping of the various inputs to generate one or more sub-matches where in embodiments, a goal may be to obtain a complete funding for all stages of a product development path that may lead to a marketable product. In some embodiments, each input provided by an entity to system 100 and processed by deal engine 110 need not be a “complete” input that satisfies all necessary criteria to fund stages to generate a match for the generation of a marketable product. Each entity's input or inputs may be matched by the deal engine 110 to create one or more sub-matches that may be aligned to create a potentially fully or partially funded development path for a marketable product. For example, a first research and development organization 20 may be performing a research stage that may lead to a marketable vaccine product. A second research and development organization 20 may have the capabilities, resources, and availability to perform a pre-clinical research stage related to a vaccine product. A third research and development organization 20 may have the capabilities, resources, and availability to perform a clinical trial stage. These inputs received from the first, second, and third research and development organizations by system 100 and stored in database 120 may be processed by deal engine 110 to potentially generate a complete path to a marketable product. Alternatively, deal engine 110 may not have identified a complete development path based on these three organizations, it may have generated one or more strings of sub-matches that may be used subsequently, as more inputs are received, to develop a complete product development path. As will be explained in further detail below, such potential sub-matches may be identified by deal engine 110 with respect to the other types of inputs, as discussed above.
Deal engine 110 is operatively coupled to database 120 and is configured to access stored database information to determine whether one or more sub-matches regarding given input data are possible. As discussed previously, the nature of the sub-matches may vary based at least in part on the amount of relevant stored information available to deal engine 110. In some embodiments, the one or more computers may be configured with programming code to implement the deal engine 110 to evaluate input data to determine whether underlying criteria for a development stage have been satisfied and to determine what types of other inputs are needed to generate a complete funded or fundable path for a particular research and development project or technology. The remaining inputs or criteria that need to be satisfied may depend on the respective input that the deal engine 110 is currently evaluating. For example, if deal engine 110 is evaluating an input from a product funding organization 10 that specifies a product need, scientific criteria, proposed financing terms, and a level of guarantee, the remaining information may include facilitator inputs, research organization inputs, bond purchaser inputs, and credit inputs. Various sub-matching operations may be performed based at least in part on the data stored in the database 120 to determine if a complete fundable path for a particular research and development project can be achieved, and if not, what sub-matches are missing. Similarly, in another example, if deal engine 110 is evaluating an input 25 from a research organization 20 that includes a type of product being researched, scientific data related to the research and development, and a partial plan for the development of the product, the remaining information may be product funding organization inputs, facilitator inputs, bond purchaser inputs, credit inputs, and research organization inputs that may complete the development plan. Thus, the remaining pieces of data to obtain a complete funded or fundable path may vary depending upon which pieces of input data may be used as an initial basis of a query looking to create a complete funded or fundable path.
In one embodiment illustrated by
In some embodiments, research and development validation may be based at least in part on such criteria requiring funding by strategic investors, as discussed previously. Although strategic investors provide inputs that include monetary investments with specific types of financing for certain products or technologies, they also serve a validation or certification function because they may have domain-specific knowledge that allows them to identify research and development or technologies that are based on sound scientific practices. As such, they or others may provide certification information as an additional input to the system 100 related to their vetting capabilities that may be associated with research and development or technologies that the strategic investor has evaluated or in which the strategic investor has invested.
As shown in
As shown in
Block 250 comprises an operation of obtaining input data. As discussed previously, in embodiments, the input data may include research and development and technology inputs 25, product funding organization inputs 15, economic development inputs 35, credit inputs 45, and/or bond purchaser inputs 55. In some embodiments, a query may also be received or generated, with one or more of the inputs as base inputs. As discussed, the manner of obtaining the inputs is not limiting on the invention, and may include receiving the input data over a network, and generating some of the input data, or may be in response to Pull queries, and/or some of the data may be received by mail, fax, telephone, and then keyed and/or scanned into the system.
Block 252 comprises determining, using the one or more computers, whether a deal related to any of the received inputs or data previously stored in database 120 of system 100 allows a deal to be generated to fund some, none, or all of the development path to a marketable product. This operation, in some embodiments, may comprise generating one or more initial sub-matches with one or more base inputs. The operation may be followed with one or more secondary and tertiary sub-matches, based at least in part on these initial sub-matches. This sequential sub-matching operation is illustrated in
If a deal is possible, e.g., a complete or substantially complete funding of pathable research and development leading to a marketable product, then the process continues to Block 262. In some embodiments, block 262 may comprise one or more of the steps of publishing the various aspect of the deal, either by display or email or other means, and/or generating a term sheet for the deal, to be discussed.
If no deal is possible, the process proceeds to Block 254. In some embodiments, block 254 comprises determining, using the one or more computers, the data and/or sub-matches that are missing and thus prevent a fully or substantially complete path being funded. Further, block 254 may comprise the steps of identifying the type of input data that was received by determining whether the input data is one of a product funding organization input 15, a research and development and/or technology input 25, an economic development input 35, a credit input 45, or a bond purchaser input 55.
Block 256 comprises determining whether a sub-match may be generated within the input type associated with at least one of the received input data. For example, a received research and development and/or technology input 25 may relate to a single stage of a research and development plan. Such received research and development and/or technology input may be sub-matched with existing research and development and/or technology inputs previously stored in database 120 of system 100 to generate a larger sub-match for several stages of the development path.
Block 258 comprises determining whether a sub-match may be generated with data having a different type than at least one of the received input data. For example, a received research and development and/or technology input 25 may be sub-matched with an existing economic development input 35 previously stored in database 120 of system 100 to generate a larger sub-match based on the received research and development and/or technology input 25.
Block 260 comprises storing the received input data in database 120.
Block 262 comprises outputting terms associated with a deal generated by deal engine 110 based on stored and input data.
As shown in
Block 704 comprises obtaining product funding organization data identifying an innovative technology product to be developed, and in some embodiments, at least two product funding organization criteria to be met, wherein the at least two product funding organization criteria may, in embodiments, include at least an amount of a bond payment pledge or guarantee for debt service of bonds, the proceeds designated to fund at least one stage of a complete product development path that comprises a plurality of stages for product development of the innovative technology product.
Block 706 comprises obtaining data on the plurality of stages for the product development, with each of the stages comprising one or more stage requirements.
Block 708 comprises matching or receiving data for a match, using the one or more computers, of one or more organizations that can perform work to meet the stage requirements of one or more of the respective stages of the respective product development.
Block 710 comprises an operation of obtaining requirements data of respective bond issuers for issuing respective bonds for funding one or more of the stages of the complete development path, where the bonds are to receive the product funding organization pledge or bond payment guarantee for partial or complete debt service.
Block 712 comprises an operation of matching, using the one or more computers, one of the stages with the requirements data for one of the bond issuers, and generating data for an allocation of at least part of the amount of the product funding organization bond payment pledge or guarantee to the at least one of the stages.
In some embodiments, the matching and allocating operation may also comprise calculating financial terms related to potential deals. For example, financial terms may comprise interest rates, payment schedules, credit enhancement, insurance, pledges of assets, or other information that would be understood to one of ordinary skill in the art as impacting financial deal terms.
The deal engine 110 may make matching and financial calculations of block 712, including, but not limited to the following:
In some embodiments, block 714 comprises outputting deal terms and requirements. In embodiments, multiple deal terms may be output where multiple potential matches were generated, which then allows for the most favorable set of terms to be selected. In embodiments, the outputted deal terms or proposed or prospective deal terms may include a deal report, as shown in
It should be understood that the equity and debt investments illustrated in
Embodiments may determine, using the one or more computers, based at least in part on the respective requirements data of respective bond issuers 30 for issuing respective bonds, at least one match of a respective one of the bond issuers and a stage of the complete development path and a research organization 20 that meets in whole or in part the requirements data of the one respective bond issuer 30. In some embodiments, bonds may relate to research and development bonds, acquisition and sustainability bonds, or some combination thereof aligned to provide continuous funding of a pathable product.
As noted previously, data obtaining steps may comprise receiving the data electronically via one or more network connections and/or may comprise receiving the data by mail, and/or by facsimile, and/or by telephone, and/or orally, and keying and/or scanning the data into the system 100, or may comprise pulling the data from a database or other entity, or may comprise generating some of the data.
In some embodiments, to achieve computerized generation of deals, additional computerized elements and functions may comprise:
Some embodiments may provide that received funding requirements data comprise at least two of a geographic requirement, a technology requirement, or an economic requirement. For example, received funding requirements data may comprise an identified state or local jurisdiction, biotechnology work, and a requirement to create 100 jobs, respectively.
Some embodiments may provide that obtaining information on a complete development path for the innovative technology product to be developed comprises receiving at least a partial path proposal and a proof of concept. Some embodiments may provide for generating a term sheet based at least in part on a complete development path and an allocation of at least part of an amount of the product funding organization bond payment pledge or guarantee.
Some embodiments may provide for matching or receiving data for a match, using the one or more computers, for at least one purchase commitment to at least one tranche of bonds to be issued by the one bond issuer for the stage of the development. Some embodiments may provide that matching of the purchase commitment occur contemporaneously with the matching of the one of the stages with the requirements data for one of the bond issuers.
A finance method according to an embodiment is described below, with reference to
In embodiments, in stage 920, the one or more computers obtain and store over time, data for: a) product development projects, b) research and development organizations, c) funding organizations, and respective organization requirements, d) securities issuing entities, and respective issuing entity requirements, e) securities purchasing entities, and f) pathable development projects.
In embodiments, in stage 930, a respective technical and/or business readiness level may be determined or obtained for each of a plurality of the product development projects, and the respective readiness levels are stored in the one or more databases. See Table 1 below for a list of representative technology readiness levels and Table 2 below for a list of representative business readiness levels.
In embodiments, in stage 940, for each of a plurality of the product development projects, respective development stages and milestones may be determined by the one or more computers for a respective pathable development project and one or more entities to perform the respective development stages.
In embodiments, in stage 950, an estimated full or partial funding amount for respective of the pathable development project may be determined by the one or more computers.
In embodiments, in stage 960, a matching may be performed, using the one or more computers, of a respective one of the pathable development projects with one or more of the funding organizations, based at least in part on matching the organization requirements of the respective funding organization to at least one selected from the group of: a) the technical and/or business readiness level of the product development project associated with the respective pathable development project, b) a target product profile, c) an amount of available funds for a given target product profile, an d) approximate timeframe for completion of the pathable development project, and e) a requested co-funding amount.
In embodiments, in stage 965, a matching may be performed, using the one or more computers, of one or more of the funding organizations with one or more of the securities issuing entities, based at least in part on the respective issuing entity requirements of the respective issuing entities relating to at least one selected from the group of: a) jobs projected to be created by the respective pathable development project, b) location of work for the respective pathable development project, and c) technology type.
In embodiments, in stage 970, a matching may be performed, using the one or more computers, of one or more of the securities issuing entities with one or more of the pathable development projects, based at least in part on at least one selected from the group of: a) a projected financial return, b) a schedule of tranches for the stages of the pathable development project, and c) a surety arrangement.
In embodiments, in stage 975, a matching may be performed, using the one or more computers, of one or more of the securities purchasing entities with one or more of the securities issuing entities, based at least in part on at least one selected from the group of: a) level or percentage of funding relative to the funding amount for the respective pathable development project, b) a projected financial return, c) a schedule of tranches for the stages of the pathable development project, and d) a surety arrangement.
In embodiments, in stage 980, a determining may be performed, using the one or more computers, of whether funding of the pathable development project is substantially complete relative to the full funding amount for the respective pathable development project or determining a gap in the level or percentage of funding of the pathable development project relative to the full funding amount for the respective pathable development project.
In embodiments, in stage 985, selected entities' data relating to the pathable development project that has substantially complete funding and/or comprise results of individual matching steps may be published to at least one selected entity.
In embodiments, in stage 990, tranche data may be generated and selected, using the one or more computers, for a respective one of the pathable development projects, to one or more entities that are to perform the development stages for the respective pathable development project.
The deal engine 110 is configured to process data and inputs received from various sources and to calculate matching to generate proposed deal terms, as will be discussed in further detail below.
According to one or more embodiments, deal engine 110 may use data regarding Technology Readiness Levels (TRLs) and Business Readiness Levels (BRLs) to match product funding organizations and investors with research and development companies through all stages of product development.
Table 1 lists TRLs that may be used for biotechnology products (similar ratings may be used for other technical fields, such as space systems, weapons development, etc.), according to one or more embodiments. In particular, nine (9) separate TRLs are illustrated in Table 1, which are used by the deal engine 110 to match investors with research and development companies through all stages of product development. The TRLs may correspond to various portions of the scientific & implementation stages shown in
Table 2 lists BRLs that may be used for biotechnology products, in which similar ratings can be used for other technical fields. In particular, nine (9) separate BRLs are listed in Table 2, which can be used by the deal engine 110 to match investors with research and development companies through all stages of product development. The BRLs may correspond to various organizational capacities and capabilities which may be needed and/or advisable to have in order to perform the corresponding scientific & implementation stages shown in
In some embodiments, product funding organization inputs 15 provided by product funding organizations are matched to the various nine TRL stages (see
An example is provided below with respect to inputs to a deal engine 110 according to one or more embodiments, and the processings performed by the deal engine 110. Tables 3A, 3B and 3C below shows example inputs to a deal engine 110 according to one or more embodiments.
Table 4 below shows an example of project stage calculations performed by a deal engine according to one or more embodiments. In this example, there are six (6) project stages.
In Table 4, the first row corresponds to a Project Stage Number, the second row corresponds to a Project Stage Description, the third row corresponds to a Project Stage Duration, the fourth row corresponds to a Project Stage Cost, the fifth row corresponds to a Technology Level at Start of Project Stage, the sixth row corresponds to a Technology Level at End of Project Stage, the ninth row corresponds to a Match to Funding Organization (True or False), the tenth row corresponds to a Funder for Stage, the twelfth row corresponds to a Funding Link Committed for Next Stage, and the thirteenth row corresponds to a Funder for Next Stage.
Continuing with the above example, the deal engine then performs a project continuity test to determine whether there is continuity with respect to funding of the various stages of a project, which in this case is shown below in Table 5.
Continuing with the above example, the deal engine then performs financial calculations, and in this example that is shown below in Table 6 for a six stage project (each stage is represented by a separate column in Table 6):
In Table 6, the first row corresponds to an Advance Market Commitment Amount, the second row corresponds to an AMC Committed, the fourth row corresponds to a Baseline project duration, the fifth row corresponds to a Co-investment discount rate, the sixth row corresponds to a NPV (Net Present Value) of AMC for co-investment, the eighth row corresponds to a Baseline project cost, the ninth row corresponds to an Overall co-investor share (maximum), the twelfth row corresponds to a Funding by project stage, the fourteenth row corresponds to a Baseline stage cost, the fifteenth row corresponds to a Funder share, the sixteenth row corresponds to a Co-investor share, the seventeenth row corresponds to a Research organization share, the nineteenth row corresponds to a Funder amount, the twentieth row corresponds to a Co-investment amount, the twenty-first row corresponds to a Research organization amount, the twenty-third row corresponds to a Co-investment NPV remaining, the twenty-fifth row corresponds to a Total co-investment, the twenty-sixth row corresponds to a Total research organization investment, the twenty-seventh row corresponds to a Co-investor ratio, the twenty-ninth row corresponds to a Co-investor return from AMC, the thirtieth row corresponds to a Research Organization return from AMC, and the thirty-second row corresponds to a Ratio of co-investment to AMC.
In Table 6, the AMC Committed logic value (True, Row 2) is determined based on whether the Advance Market Commitment amount is greater than zero (which it is in this example). The Baseline Project Duration (Row 4) is the sum of the Project Stage Durations (see Table 4). The NPV of AMC for Coinvestment value (Row 6, $42,104,948.47) corresponds to the NPV of the Commitment Amount value (Row 1, $112,000,000) at the Coinvestment Discount Rate (Row 5, 15%). The Baseline Project Cost value (Row 8) is the sum of the Project Stage Costs (see Table 4). The Coinvestment DMV Remaining value (Row 23) is calculated as the NPV of AMC for Coinvestment value ($2,104,948.47) minus the Coinvestment Amount for a particular stage. The Coinvestor ratio (Row 27) is calculated as the Total Coinvestment value divided by the Total Research Organization Investment value. The Coinvestor Return for AMC value (Row 29) is calculated as the Advance Market Commitment amount multiplied by {(Coinvestor ratio)/(Coinvestor ratio+1)}. The Research Organization Return from AMC value (Row 30) is calculated as the Advance Market Commitment amount divided by (Coinvestor ratio+1). Lastly, the Ratio of Coinvestment to AMC (Row 32) is calculated as Total Coinvestment divided by Advance Market Commitment amount.
Based on the example shown in Table 6, for the entire six project stages, the total funding is: $147,000,000 funder amount, $42,000,000 coinvestment amount, and $21,000,000 research organization amount.
In some embodiments, the deal engine may analyze the proposed project in comparison to traditional government contracting, and provide a report with such comparison analysis to investors and R&D companies seeking funds from investors. Table 7 below shows an example of this analysis, for a deal engine according to some embodiments. In the example shown in Table 7, due to the innovative financing techniques proposed by the deal engine, there is much less financing needed from investors to fund a project based on the deal proposed by the deal engine (in this case, about $86,000,000 less funding needed).
In Table 7, the Links Between Funders value is calculated as the Project Funders value minus 1. The Project Delay Due to Proposed Cycles value is calculated as the Links Between Funders value multiplied by the Proposed Cycle Duration value. The Total Additional Costs value is calculated as the Business Project Cost value (see Table 6) multiplied by (Business Development Cost+Non-project Administrative Cost). The Total Contribution of Funding Organizations if Project Performed Under Traditional Contracting value is calculated as the Baseline Project Cost value plus the Total Additional Costs Plus Fees value. The Total contribution of funding organizations under innovation finance approach value is calculated as the sum of the Funder Amounts for each of the project stages.
Also, the deal engine according to one or more embodiments may perform bond calculations for possible financing of various stages of a project. An example of such bond calculations is provided below, with reference to Table 8.
For the above example, for stages 4 and 5 of the project, the R&D work is performed in 2.5 years, following the science schedule. The co-investors contribute and the Research Organization contribute their funds at the start of stage 4, the funding agency 2 contributes its funds as debt service over 7 years, paying $14,037,153 per year, thereby allowing it to stretch out and smooth its cash flow.
In Table 8, the project cost value of $70,000,000 is calculated as a sum of the funder amounts $17,500,000 and $52,500,000 in the financial calculations performed by the deal engine (see Table 6). The “bond proceeds” value corresponds to the total uses of funds value of $80,000,000. The “estimated annual debt service” value of $14,077,153 is calculated based on the 5.5% interest rate, the 7 year amortization term, and the $80,000,000 bond proceeds (debt) amount. The “less earnings on debt service reserve fund @0.50%” value of $40,000 is calculated as 0.005*the debt services reserve fund value of $8,000,000. The “net annual debt service” value of $14,037,053 is calculated as the “estimated annual debt service” value minus the “less earnings on debt service reserve fund” value. Lastly, the “total outlay by funding agency” value of $90,260,074 is calculated as the “net annual debt service” value (14,037,153) multiplied by the “amortization term” value (7), minus the “debt service reserve fund” value (8,000,000).
Based on the above example, the deal engine according to one or more embodiments provides information that is very useful in determining whether or not investors should invest in various stages of projects that request funding, and that provides the tools for both investors and R&D companies to contract with each other and to find the appropriate financing for all stages of a project.
In some embodiments, an Innovation Finance Risk Index (IFRI) may be obtained based at least in part on IFRI factors. The IFRI Factors may be computed based on: a) TRLs, b) Business Readiness Level (BRL), and c) Financial (or Capital) Readiness Level (F/CRL). In more detail, F/CRL=(Amount of Federally-provided (or other-entity-provided)Capital)/(Total Capital Required to Complete the Project).
IFRI may then be computed in some embodiments as: IFRI=TRL*BRL*F/CRL.
In other embodiments, IFRI is computed as: IFRI=TRL+BRL+F/CRL. In either implementation, a larger IFRI value signifies a lesser financial risk assessment for a particular product to be considered for funding, and vice versa.
In some embodiments, each of the factors used to compute IFRI may be benchmarked to external comparables data sets based on and extrapolated from publicly available public and private sector funding and financing data, in which each of the factors can be updated periodically, such as monthly, quarterly, or annually.
Based on the computed IFRI, investors may determine whether or not a particular research and development for which funding is requested by a particular entity, for one or more research and development stages poses an acceptable risk to those investors.
Examples as to how IFRI may be computed according to some embodiments are provided below.
IFRI=f({P}), where {P} is a set of input parameters. In some embodiments, {P} can be the set of input parameters TRL, BRL, Capital Committed, and Capital Required to Project Completion. TRL is the project's Technology Readiness Level, which may range in some embodiments from a value of 1 up to a maximum value TRLmax (see Table 1, whereby in that example TRLmax is 9). BRL is the Business Readiness Level of the organization conducting the project, which may range in some embodiments from a value of 1 up to a maximum value BRLmax (e.g., BRLmax=9). Capital Committed is the amount of capital committed from various sources to perform the project, and may be expressed as a monetary value. Capital Required to Project Completion is the amount of capital estimated to be needed to complete the project from its current state.
Financial Readiness Level, or FRL, is a parameter that may be calculated according to the following expression:
FRL=100%*(Capital Committed/Capital Required to Project Completion)
With the above input parameters, in one embodiment, IFRI can be calculated as:
IFRI=3−(K1*(TRL/TRLmax)+(K2*(BRL/BRLmax)+K3*FRL)), where
K1 is a Technology Readiness Weighting Factor that can be assigned as a nominal value of 1 or that can be set to a fractional value between 0 and 1 as determined from past technology readiness performance data of a selected set of previous projects,
K2 is a Business Readiness Weighting Factor that can be assigned as a nominal value of 1 or that can be set to a fractional value between 0 and 1 as determined from past business readiness performance data of a selected set of previous projects,
K3 is a Finance Readiness Weighting Factor that can be assigned as a nominal value of 1 or that can be set to a fractional value between 0 and 1 as determined from past finance readiness performance data of a selected set of previous projects.
Using the above function f, and an example set of parameter and weighting factors, IFRI can be calculated for an example project as follows:
TRLmax=9,
BRLmax=9
K1=1,
K2=1,
K3=1
From the above data, IFRI can be computed for the six projects to be: IFRI for Project 1=1.833, IFRI for Project 2=2.663, IFRI for Project 3=2.317, IFRI for Project 4=2.061, IFRI for Project 5=1.267, and IFRI for Project 6=0.389.
In some embodiments, using the form of the IFRI function as described above, IFRI can take on a value from zero to three, with zero equaling the lowest risk and three indicating the highest risk. Thus, in the above examples, Project 6 has the lowest risk and Project 2 has the highest risk.
In some embodiments, using the form of the IFRI function as described above, the Technology Readiness Level, Business Readiness Level, and Financial Readiness Level are given equal weight in calculating the risk, but this need not necessarily always be the case (e.g., the weighting may be empirical, based on past performance data that may affect the weightings K1, K2, K3).
The computed value IFRI, which corresponds to the risk index for a project, may be used in some embodiments to select a preferred project for funding from a set of projects. In the above examples, based on the amount of risk that an investor may wish to take, the investor may choose to invest in Project 6 if the investor is not willing to take on much risk, and the investor may choose to invest in Project 2 and/or Project 3 if the investor is willing to take on much risk.
In other embodiments, using for example empirical values for the weighting factors K1, K2, K3, based on various analyses of various sets of historical data from actual performance of historical projects, the weights of the Technology Readiness, Business Readiness, and Financial Readiness factors K1, K2, K3 may be different, which will affect the computation of IFRI.
In addition, analyses of the empirical data on historical projects for various different industry sectors may be used to indicate that each industry sector has its own sector-specific weighting factors K1, K2, K3, indicating different relative weights of the importance of the Technology Readiness, Business Readiness, and Financial Readiness aspects in different industries.
In some embodiments, IFRI may be calculated using other functions f. For example, in some embodiments, IFRI may be computed using Step functions, where the output f({P}) is defined by values enumerated by a user.
In other embodiments, IFRI may be computed using Probabilistic functions, where the output f({P}) is given not as a single value but as a probability distribution for risk based on the input parameters such as TRL, BRL, and FRL, and it either may be calculated from sets of values or may be provided from a table of empirically encountered probability distributions based on historical data.
In yet other embodiments, IFRI may be computed using non-linear functions, where the output f({P}) is calculated using non-linear functions of the input parameters {P}, such as polynomial functions, exponential functions, power-law functions, integral or derivative functions.
In other embodiments, IFRI may be computed using Composite functions, where the input parameters {P} are themselves functions of other sets of subparameters {Q}.
In yet other embodiments, IFRI may be computed using another mathematically valid function or combination of functions.
Additional embodiments for computing IFRI can use Commitment Risk Factors to evaluate the reduction of risk of a project if an Advance Market Commitment and Funding Links are made. An example of computing IFRI using Commitment Risk Factors is described below, which uses elements of commitment by one or more product funding organizations to compute reduction in risk as linked funding commitments are made.
Example for Computing IFRI Using Commitment Risk Factors:
IFRI=f({P}), where {P} is a set of input parameters.
In this example, {P} may comprise the following set of input parameters: AMC Committed, AMC Amount, Project Stages, Funding Link Committed, Funding Link Amounts, TRL, BRL, Capital Committed, and Capital Required To Project Completion, where:
a) AMC Committed is a fuzzy boolean parameter (true/false, or fuzzy values in between), indicating whether a Product Funding Organization has made a binding Advance Market Commitment to purchase products which reach approval for use,
b) AMC Amount is the amount of the binding Advance Market Commitment,
c) Project Stages is the number of stages in the project, d) Funding Link Committed is an array of fuzzy boolean parameters, with one value per stage of the project, indicating whether a Product Funding Organization has made a binding commitment to fund the next stage of the project,
e) Funding Link Amounts is an array of currency values, with one value per stage of the project, indicating the amount committed to the link from each stage of the project to the next stage,
f) TRL is the project's Technology Readiness Level, ranging from 1 to a maximum, denoted as TRLmax (e.g., TRLmax=9),
g) BRL is the Business Readiness Level of the organization conducting the project, ranging from 1 to a maximum, denoted as BRLmax (e.g., BRLmax=9), h) Capital Committed is the amount of capital committed from various sources to perform the project,
i) Capital Required To Project Completion is the amount of capital estimated to be needed to complete the project from its current state, and
j) FRL is the Financial Readiness Level and is a calculated parameter, calculated as 100%*(Capital Committed/Capital Required To Project Completion).
With these input parameters, as one example IFRI can be calculated as:
IFRI=AMC Committed*Funding Link 1*Funding Link 2*(K1*(TRL/TRLmax)+K2*(BRL/BRLmax)+K3*FRL)), where
K1 is a Technology Readiness Weighting Factor which may be assigned a nominal value of 1 or can be determined from past performance data of a selected set of previous projects,
K2 is a Business Readiness Weighting Factor which may be assigned a nominal value of 1 or can be determined from past performance data of a selected set of previous projects, and
K3 is a Finance Readiness Weighting Factor which may be assigned a nominal value of 1 or can be determined from past performance data of a selected set of previous projects.
Using this function f, and an example set of parameter and weighting factors, IFRI can be calculated for an example project as follows:
Based on the above numbers, IFRI may be calculated for a set of projects as follows:
In this manner of computing the IFRI function according to some embodiments, IFRI may take on a value from zero to three, with zero equaling the highest risk and three indicating the lowest risk.
Note that examples have been provide of pharmaceutical and biotech research and development and products, but the invention is not so limited. The invention may be applied for generating a series of sub-matches and partial sub-matches for any type of product or research and development.
As described earlier, and referring to
If debt financing such as bonds or loans is being used in a project, then the deal engine according to some embodiments may generate an additional subset of documents to support the negotiation and issuance of such debt instruments. An example of such additional subsets of documents are described below in an example, with reference to Table 10.
Embodiments within the scope of the present invention include program products comprising machine-readable media for carrying or having machine-executable instructions or data structures stored thereon. Such machine-readable media may be any available media which may be accessed by a general purpose or special purpose computer or other machine with a processor. By way of example, such machine-readable media may comprise RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which may be used to store desired program code in the form of machine-executable instructions or data structures and which may be accessed by a general purpose or special purpose computer or other machine with a processor. Combinations of the above are also included within the scope of machine-readable media. Machine-executable instructions comprise, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing machines to perform a certain function or group of functions. Note that the machine-executable instructions/programming code may comprise algorithms embedded in Excel or other spreadsheets.
Embodiments of the invention have been described in the general context of method steps which may be implemented in embodiments by a program product including machine-executable instructions, such as program code, for example in the form of program modules executed by machines in networked environments. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular data types. Multi-threaded applications may be used, for example, based on Java or C++. Machine-executable instructions, associated data structures, and program modules represent examples of program code for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represent examples of corresponding acts for implementing the functions described in such steps. As noted, the machine-executable instructions/programming code may comprise algorithms embedded in Excel or other spreadsheets.
Embodiments of the present invention may be practiced with one or multiple computers in a networked environment using logical connections to one or more remote computers (including mobile devices) having processors. Logical connections may include a local area network (LAN) and a wide area network (WAN) that are presented here by way of example and not limitation. Such networked environments are commonplace in office-wide or enterprise-wide computer networks, and include intranets and the Internet, and may use a wide variety of different communication protocols. Those skilled in the art will appreciate that such network computing environments will typically encompass many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. Embodiments of the invention may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination of hardwired and wireless links) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.
It should be noted that although the flow charts provided herein show a specific order of method steps, it is understood that the order of these steps may differ from what is depicted. Also two or more steps may be performed concurrently or with partial concurrence. Such variation will depend on the software and hardware systems chosen and on designer choice. It is understood that all such variations are within the scope of the invention. Likewise, software and web implementations of the present invention could be accomplished with programming techniques with rule based logic and other logic to accomplish the various database searching steps, correlation steps, comparison steps and decision steps. Artificial intelligence tools, such as inference, neural network logic, and other tools known to one of skill in the art may be used to accomplish searching, calculating, matching, or other computational steps. It should also be noted that the word “component” as used herein and in the claims is intended to encompass implementations using one or more lines of software code, and/or hardware implementations. It should also be noted that the phrase “a plurality” is intended to mean more than one, and is not intended to refer to any previous recitation of the word “plurality,” unless preceded by the word “the.”
While this invention has been described in conjunction with the exemplary embodiments outlined above, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, the exemplary embodiments of the invention, as set forth above, are intended to be illustrative, not limiting. Various changes may be made without departing from the spirit and scope of the invention.
This application claims priority to provisional patent application 61/499,810, entitled “Systems, Methods, and Program Products for Innovation Finance,” filed on Jun. 22, 2011, which is incorporated in its entirety herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| 61499810 | Jun 2011 | US |
