Patents and translational research in genomics

From Big Data to Precision Medicine

For over a decade the term "Big data" has been used to describe the rapid increase in volume, variety and velocity of information available, not just in medical research but in almost every aspect of our lives. As scientists, we now have the capacity to rapidly generate, store and analyse data that, only a few years ago, would have taken many years to compile. However, "Big data" no longer means what it once did. The term has expanded and now refers not to just large data volume, but to our increasing ability to analyse and interpret those data. Tautologies such as "data analytics" and "data science" have emerged to describe approaches to the volume of available information as it grows ever larger. New methods dedicated to improving data collection, storage, cleaning, processing and interpretation continue to be developed, although not always by, or for, medical researchers. Exploiting new tools to extract meaning from large volume information has the potential to drive real change in clinical practice, from personalized therapy and intelligent drug design to population screening and electronic health record mining. As ever, where new technology promises "Big Advances," significant challenges remain. Here we discuss both the opportunities and challenges posed to biomedical research by our increasing ability to tackle large datasets. Important challenges include the need for standardization of data content, format, and clinical definitions, a heightened need for collaborative networks with sharing of both data and expertise and, perhaps most importantly, a need to reconsider how and when analytic methodology is taught to medical researchers. We also set "Big data" analytics in context: recent advances may appear to promise a revolution, sweeping away conventional approaches to medical science. However, their real promise lies in their synergy with, not replacement of, classical hypothesis-driven methods. The generation of novel, data-driven hypotheses based on interpretable models will always require stringent validation and experimental testing. Thus, hypothesis-generating research founded on large datasets adds to, rather than replaces, traditional hypothesis driven science. Each can benefit from the other and it is through using both that we can improve clinical practice.

Impact of gene patents on diagnostic testing: a new patent landscaping method applied to spinocerebellar ataxia

Recent reports in Europe and the United States raise concern about the potential negative impact of gene patents on the freedom to operate of diagnosticians and on the access of patients to genetic diagnostic services. Patents, historically seen as legal instruments to trigger innovation, could cause undesired side effects in the public health domain. Clear empirical evidence on the alleged hindering effect of gene patents is still scarce. We therefore developed a patent categorization method to determine which gene patents could indeed be problematic. The method is applied to patents relevant for genetic testing of spinocerebellar ataxia (SCA). The SCA test is probably the most widely used DNA test in (adult) neurology, as well as one of the most challenging due to the heterogeneity of the disease. Typically tested as a gene panel covering the five common SCA subtypes, we show that the patenting of SCA genes and testing methods and the associated licensing conditions could have far-reaching consequences on legitimate access to this gene panel. Moreover, with genetic testing being increasingly standardized, simply ignoring patents is unlikely to hold out indefinitely. This paper aims to differentiate among so-called 'gene patents' by lifting out the truly problematic ones. In doing so, awareness is raised among all stakeholders in the genetic diagnostics field who are not necessarily familiar with the ins and outs of patenting and licensing.

The impact of human gene patents on genetic testing in the United Kingdom

PURPOSE

This article reports the results of an empirical study examining the impact of human gene patents on the development and delivery of genetic tests in the public sector in the United Kingdom.

METHODS

Semi-structured qualitative interviews.

RESULTS

The study found that, despite the potential for gene patents to have significant negative consequences for genetic testing, in fact, human gene patents have little or no impact on practice for those developing genetic tests in the public sector in the United Kingdom. This is not because patents are managed optimally; rather, gene patents are essentially ignored. This article reports the factors that motivate this behavior.

CONCLUSIONS

At least insofar as there seems to be no apparent problem of lack of patient access, there is no significant public health problem. However, there is divergence between the legal and the practical situation. Complacency about the lack of impact of patents on access to diagnostics is risky, and concerns about patents should be addressed proactively, rather than reactively.