Monetizing R&D intangibles

In my job, I work quite a lot together with medical doctors and professors carrying out research projects where some form of commercialization potential has been identified. Often it is my role to come in as a business developer and by an initial intellectual asset due diligence process distinguish which of the R&D building blocks that are truly value creating and how these potential values may be extracted. As a part of this, I get to see quite a number of grant applications and discuss how these can be re-designed for effective communication of a project's value with a basis in their intellectual assets.

Tacit valuation model for early stage research

I think that it is interesting to think that a grant reviewer will (although probably to a large extent tacitly and indirectly) value the underlying potential of research activities and new technologies, and eventually determine whether the sought amount is a feasible investment. Certainly there are parallels with such an implicit valuation model to patent valuation where a challenge is to identify suitable metrics for estimation of the value of a technology.

So what are some of the soft metrics that could determine the value of a technology for a grant reviewer?

Value of scientific excellence

Most grant reviewers probably would like to say that their sharp eye spotted the Nobel Prize candidate long before its nomination and that it was that particular early-stage grant that enabled the discovery. However, in reality scientific brilliance may be difficult to determine. Especially so, if the grant reviewer's expertise happens to be in another area than what the application is describing. One way to "outsource" this determination is to rely on citations in scientific journals. A citation count corresponds to the number of times other research papers reference the results of a publication-of-interest. But it is not self-evident how to value citations solely based on the number. How would you distinguish between?

• A higher number of citations due to a rather basic discovery
• A low number of citations in highly respected journals
• A high number of citations but none within the same research area
• A low number of citations

Value of personal brands

Another aspect that is often quoted as high perceived value in the eyes of grant reviewers is to have successful competences associated to a project. Metrics to measure the significance of human capital include;

• Curriculum Vitae (e.g. previous positions and experience)
• Academic titles
• Citations (e.g. H-index, citations per year, total citations)
• Publications (e.g. how many, in which journals, co-authors)
• Previously raised financing through grants and commercialization

Value of association to other trademarks

Association of research projects with other entities and initiatives can be interpreted as different identities and perceived values for projects. Here are some examples;

• Market closeness: Letter of intent from a collaborating company
• National/regional importance: Proof of participation in research platform (e.g. IMI, FP7)
• Societal value: Grant approval letter from major foundation (e.g. B&M Gates Foundation)

Value of legal clarity and technology transferability

For grant reviewers that are interested in seeing research results being utilized and commercialized, value metrics may include;

• Patents (e.g. number of patents, coverage, assignee/inventorship)
• Agreements (e.g. consortia agreements - ensuring that rights to results are governed)
• Freedom-to-operate evaluations

However, there are also newer metrics in the knowledge economy such as quotes on how many registered unique users one's database has. Other interesting metrics could for example be generated in open innovation projects such as Folding@Home (where a complex biological computation is distributed on 250 thousand CPUs of personal computers) where the project could claim to have access to 25 000 CPUs (assuming 10% usage of each CPU).

Will we see the numbers of "Digg it"-clicks, twitter hits and LinkedIn connections in future grant applications as metrics for societal interest and networks?

Tobias Thornblad

(Contact via Twitter)

The role of the university - in the Future of Early Innovation

Ulf Petrusson opened up the second day of the Early Innovation and Knowledge City/Region track at CIP FORUM, on Tuesday afternoon. The theme of the talk was about how innovation and openness can be safeguarded in research platforms. The full panel included;

Arundeep Pradhan, President, AUTM and Oregon Health Sciences

Boo Edgar, Chairman, MedCoast Scandinavia and Director, GIBBS

Karen Hersey, fm Senior Counsel IP MIT and Professor, Franklin Pierce Law Center

Michael Cleare, Director TTO, University of Pennsylvania

Philippe Cupers, PhD, IMI European Union

Ulf Petrusson, Professor of Law, University of Gothenburg and Director, CIP

IP as discussion topic is often focused on the commercialization aspect on the underlying technologies but this was a discussion focused on the ability to use instruments such as IPRs, policies and technology transfer functions to stimulate research and knowledge dissemination. Universities face major challenges as increasing complexities of new technologies demands more extensive developments before research results can be readily utilized and provide societal benefits. In order for universities to not being risked to be blocked further down the line of the collaboration, there is an increasing need for intellectual asset management capabilities (e.g. for managing research processes, research collaborations, contract research, research funding, development processes, project selection, etc.).

A model was also presented where the role of the university was tracked over time from being a pure educational platform based on solely contributing to the public domain. Over time, this has also started to incorporate an increasing licensing and collaboration model where its responsibility has also started to include supporting the industry and society by transferring its research. As the importance of providing societal value has increased the university has also engaged in more entrepreneurial activity through a venture creation model. As all of the functions above have been incorporated, a new role for the university has emerged - the Intellectual Asset (IA) platform university.

Tobias Thornblad

(Contact via Twitter)

Utilization models of early-stage research

Long time no blogging...

Switching jobs makes you re-think some of your preconceived theoretical frameworks of how the world works. This was certainly the case for me when I switched from a more traditional intellectual property right (IPR) focused job to one where the core is in identifying intellectual assets (IA) and managing (IAM) these to create knowledge-based business models. Obviously still considering intellectual property and capital, but with an emphasis on the actual core of value creation (i.e. understanding the building blocks that collectively can generate IP/IPRs/IC etc.). With this as a basis, it is interesting to reflect over how early-stage research results (e.g. ideas, technology, etc) can be effectively converted into objects ready for utilization. Since there seems to be no magic recipes, my intention with this blog post is to explore some interesting models that are designed to promote societal utilization and technology dissemination of research results.

Technology Transfer Office (TTO) model

This is the traditional, often totally IPR-focused, model where universities have an internal system where they track inventions and patentable objects and have a number of strategies to ensure utilization and technology dissemination. Typically the personnel at the TTO employs a process to scan the internal R&D activity to identify research results of commercial interest. Protection strategies (e.g. patenting) can then be implemented in close collaboration with the researcher.

Exploitation strategies are then pursued where the three most common probably are;

• Licensing: A license agreement is negotiated to offer rights to the patentable invention (access/ownership) according to the claims made in the written IPR. This is sometimes complemented by a knowledge transfer model where the researcher provides consulting to the licensee to transfer required know-how.
• Spin-out: A startup is formed around the invention where often the inventor is one of the entrepreneurs managing the company or at least gets some sort of ownership stake in the company depending on the circumstances and complexity of the technology. This vehicle often relies on access to external funding, e.g. venture capital.
• Joint-venture: An entity is formed jointly between two (hopefully) complementary partners to create synergies while sharing risks and rewards.

Examples of successful technology transfer offices include; MIT Technology Licensing Office, Harvard University Office of Technology Development,

Examples of spin-out models where the created venture are managed by students educated in innovation and entrepreneurship; Gothenburg International Bioscience Business School, Chalmers School of Entrepreneurship

Cluster of specialized entities

This model can consist of;

1) one entity with multiple specialized divisions,

2) a network of specialized companies/organizations, or,

3) a combination of 1 and 2.

There must be at least one entity dedicated to research that can provide results to the others for commercialization. For utilization effectiveness, it is convenient if certain types of innovations, e.g. all results with medical applications, always goes to the same entity for commercialization. This does not have to mean that ownership is transferred but rather that rights are granted for further development and marketing. As you are probably already thinking, this model builds on proficiency in managing one's business model by using open innovation platforms and platforms can be created on all levels; international-, national-, regional-, company-, project level.

Examples of company models (1) are big corporations such as IBM that has several R&D departments and specialized units to handle commercialization through different applications with activities ranging from aerospace to healthcare.

An example of a network model (2) is SweTree Technologies: IP from 44 cutting-edge researchers is transferred to a privately held holding-company that in turn holds shares in a company specialized in commercializing plant- and forest biotechnologies.
An example of an international combined model (3) is SRI International that creates utilization through licensing, contract research and spin-outs through its specialized divisions and subsidiary Sarnoff.

Combined dissemination and commercialization model

This is a model that can be applied as a strategy to ensure technology dissemination onto the model above (i.e. as a platform strategy or business model) both on multiple and single entities. Core to this model is the separation between commercialization for-profit and technology dissemination for-societal-benefits. However, separation does not mean that only one of these paths should be pursued. On the contrary, a successfully designed model should be able to support simultaneous implementation of both. This is an interesting model from the standpoint of considering how to balance profit-making incentives with knowledge-disseminating incentives, in an ethical way.

An example of this model is the Human Proteome Resource (HPR) program publishes antibody profiles in the Human Protein Atlas based on proteins mapped in the program, while Atlas Antibodies is the commercial vehicle that produces, markets and sells antibody products developed and validated in the HPR Center.

These are all widely different models for utilization of research results but I think that it is interesting to see that some of the same underlying principles of these models can be applied in a number of different settings and contexts (e.g. universities, companies, innovation systems, individuals, networks, etc.). There is obviously also a whole range of pros and cons associated to these models but I won't go into detail in this post. Platform building, technology transfer and management of early innovation is just some of the subjects that will be discussed at CIP FORUM (6th-9th Sep) that I encourage you to register to, for a continued discussion.

Tobias Thornblad

(Contact via Twitter)

Credit Crunch IP

I have a hard time to trying to hide my obsession regarding the financial situation and the worldwide economic downturn. Here are some IP-related thoughts I have absorbed during the last months from various sources.

Venture Capital
Many start ups get funded on the promise and vision of turning their intellectual assets into valuable intellectual property to enable value extraction or be acquired by bigger fish. The current economic climate seems to restrict the flow of new capital to the VC funds. Moreover the model of VC funding is, according to some, about to change. This will probably change the innovation ecosystem and have an effect on IP generating possibilities for start-ups relying on venture capital. According to Bob Kagle and VentureBeat, about half of all VCs going out of business.

IP (patent) liquidation
The strategic focus of the usage of IP will be to generate money to support the operations. The companies have to turn their intellectual capital management to become a profit center instead of a cost center. This includes increased IP transactions and more focus on alternative costs since money in the bank is more attractive then IP assets with no clear purpose except a potential FTO function. To tie on to Marcus' blog post some while ago, perhaps a increased number of transactions can be a driver for a common market place for IP to reduce transaction costs.

Technology transactions
Is this the time where open source and open platforms gets the formal recognition in the corporate world? I am not completely sure that open source solutions, when speaking of software, is less expensive. However, the cost is distributed in another way to reduce upfront costs.

Moreover, open collaborations or outsourcing could be measures to lower costs in development activities or in day-to-day operations. To what extent this will actually happen is yet to see. To manage relationship and results in open platforms are demanding. My view is that not many firms have developed capabilities in relation to this, but I am too inexperienced and lack some insight to do a proper prediction regarding the adoption level dependent on corporate capabilities.

Strategic research
Less capital and commitment to strategic research. Cost cutting means lay-offs. Lay off could implicate loss of knowledge and research momentum . The impact of this will be hard to predict. Some claims that the societal value of having companies doing strategic research will decline vastly during the downturn period. The


That's all for now. Given the media buzz regarding the economic downturn and the effect on our lifestyle and future this topic will be revised in the future.

Mathias Hellman