As previously discussed, data driven approaches have revolutionised research and R&D in the life sciences sector. As a result, life science IP professionals increasingly have to support projects that involve a large computational component. These generate inventions that they may be less familiar with, and crucially these projects often move at a very different pace from the more traditional molecular biology / biochemistry wet lab driven projects. Indeed, computational projects can generate valuable insights at a relatively fast pace, can result in the development of software tools that are updated every few months, and can even be designed to change after release (i.e. through their use - for example, some machine learning / AI powered tools are designed to continuously learn, resulting in changes in the model that underlies the predictions made by the tool). Altogether, these factors mean that the protection of IP generated by these projects can feel like a “moving target”, raising questions such as what can be protected, what is worth protecting, and when is the right time to “fix” an invention in a patent application. In this post, we provide general tips and tricks to tackle this “moving target problem” using the patent system primarily, based on our experience helping clients handle this subject-matter.
Bioinformatics projects will often result in the creation of various types of potentially valuable assets including data (whether raw or organised as a database), computer implemented methods / tools and new insights generated by the methods (e.g. biomarkers, drug candidate, patient stratification criteria, etc.) Broadly speaking, the latter two categories (computer implemented methods and insights that have direct technical meaning) can be protected by patents in many jurisdictions. These include Europe and the USA, contrary to widespread misconceptions that software is not (or no longer) patentable. Europe in particular is a comparatively favourable jurisdiction for both of these types of IP (as discussed in our blogs: EPO Bioinformatics Roads, Simulations in bioinformatics and A Guide to Patenting Bioinformatics Inventions at the EPO: what is technical and why does it matter?). The subtleties of how to obtain patent protection for computer implemented methods and their resulting insights in the bioinformatics field are beyond the scope of this post. However, it is well worth remembering two things in relation to what can be protected:
Broadly speaking, the question of timing depends on multiple factors that are not dissimilar to those that apply for any type of inventions. However, in a field that moves quickly, these are perhaps more crucial to ask explicitly, and to re-evaluate regularly. Useful questions to ask include:
As discussed above, projects in this field can often generate two types of patent-eligible aspects: computational methods, and insights. Both of these should in general be discussed, and could be made the object of separate protection strategies.
Insights (such as biomarkers, drug candidates etc.) are “traditional” prime candidates for patent protection. They are likely to be familiar to life science IP professionals and patent offices alike, generate IP that is comparatively easy to enforce, and are in general not usefully protected by trade secrets since their commercial exploitation often inherently discloses the invention.
When it comes to software tools, it is often worth having the discussion of whether and to what extent some things should be kept as trade secrets and others should be patent protected. This discussion would typically involve the following questions:
All of these points essentially aim to answer two questions: what patent scope is realistic, and what would be the value of this (i.e. how would it support short and/or long term commercial plans)?
In the software world, competitors and competing products can appear very quickly, and products can become obsolete just as quickly. This can lead to a feeling that the patent system is just too slow to provide any competitive advantage, and too expensive to provide value for money in this context. This does not have to be true, if a patenting strategy is developed and regularly updated with commercial and R&D plans in mind, with the ultimate goal of optimising value in view of these goals. This means applying for patent protection whenever the scope of protection that can reasonably be expected supports short and/or long term commercial plans, and being ruthless about letting go of rights when they no longer provide value. As an example, if a patent (or even a pending application) provides a competitive advantage for 2 years, after which the product has changed enough that the patent/application is no longer useful, then the right has done its job and can be dropped to focus resources on the next wave of innovation. Aging portfolios are expensive to maintain, so looking at the glass half full it’s no bad thing if it makes commercial sense to only protect something for a few years then move on! Finally, it is worth bearing in mind that some patent systems are quicker than others, that acceleration strategies exist in many systems if quick grant is of importance, and that a patent application can have value even before if grants.
In conclusion, it is more important here than ever to have frequent conversations about IP. These should discuss the current state of technology development but also the bigger picture, to understand both the potential for protection and what, for a particular venture, has value now and will have value in the future.
Camille is a Partner and Patent Attorney at Mewburn Ellis. She does patent work in the life sciences sector, with a particular focus on bioinformatics/computational biology, precision medicine, medical devices and bioengineering. Camille has a PhD from the University of Cambridge and the EMBL-European Bioinformatics Institute. Her PhD research focused on the combined analysis of various sources of high-content data to reverse engineer healthy and diseased cellular signalling networks, and the effects of drugs on these networks. Prior to that, she completed a Master’s degree in Bioengineering at the University of Brussels and a Masters in Computational Biology at the University of Cambridge.
Email: camille.terfve@mewburn.com
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