Pete Sadler and Robin Ellis from Reddie & Grose explore the different approaches of pharma and tech firms in driving and protecting innovation

The worlds of big tech and big pharma are getting closer and as these relationships deepen and develop, the different approaches that each side takes to both driving and protecting innovation, as well as how they use patents, is coming to the fore.

With the rise in connected medical devices and the emergence of digitally driven healthcare, the two industry sectors are starting to compete for the same space, when in reality there is much more to be gained by working together. For that to happen, a greater understanding of each side’s operating model must emerge.

The challenges being faced by the pharma industry are so complex that new approaches need to be embraced. We are already seeing the use of technologies such as AI starting to bear fruit, for example in its application to perform some of the heavy lifting in new drug development. But AI needs data – lots of it – and obtaining this data tends to require either a willingness to share, or having the technology necessary to gather and process it. For the time being at least, both of these concepts remain alien to much of big pharma.

So how do big tech companies address these issues and what can pharma learn from big tech?

A significant structural difference between the two industries is the role of the standards setting organisations (SSOs).

Industry standards are central to development in the technology, media and telecoms (TMT) space. An SSO will outline a roadmap for the technology development and invites members from industry and academia to contribute to developing the new standard. It requires collaboration and the sharing of ideas. The new standard is a collaboration based on multiple improvements made by its members. This approach is captured in the mobile telecom sector with the evolution of the 2G, 3G, 4G and 5G standards, each one a significant improvement on what came before. The protection that companies have in this kind of environment is based on standard-essential patents (SEPs) but these are not common in the pharma world.

How the technology sector implements patents commercially is also different to the pharma sector. In contrast to the development of medicines, the regulatory requirements in the tech space are less rigorous and to a large extent governed by the SSOs. This means that concepts like patent linkage systems (PLS) and patent term extensions do not exist in the tech world. The tech sector tends to have a greater focus on generating income through licensing its technologies, whereas traditional pharma strives to maintain a monopoly on its blockbuster products and avoid the dreaded ‘patent cliff’.

The licensing model works well for platform technologies which are being more frequently used in drug development. By way of example, AI is being used to help predict the binding of small molecules to proteins. This is achieved by using a statistical approach that extracts the insights from millions of experimental affinity measurements and thousands of protein structures to provide lead optimisation and toxicity predications to a high degree of accuracy. This addresses one of the biggest challenges today in pre-clinical drug discovery and development – that of identifying a drug candidate that is both effective and safe.

Another driving force bringing the two sectors closer together is the rise in big data technologies. Pharma generates masses of data and big tech is geared up to extract value from those massive data sets. By working together to understand the different ways the two industries use data, as well looking into the issues of data sovereignty, data sharing and data security, it will be possible to bring the full value of data analytics to the pharma sector.

There is, however, an institutional issue with data in the pharma industry. It is not used to sharing and is naturally hesitant to share what is perceived as a competitive advantage with third-party platforms. Added to this, the issue of patient confidentiality is often cited as a reason for keeping data ‘in-house’. Although there may be some merit to this, companies should be careful not to keep turning to it as an excuse to avoid embracing the role of big data. An overly cautious approach means that pharma companies will not be able to take full advantage of the technologies available to them and they should be wary of tech companies who will be more than willing to step in and fill the void.

This can be addressed through a better appreciation of how collaboration within big tech can work. The rise in connected medical devices and services will inevitably drive this change as we have already seen in other industries like the automotive sector.

Who knows, the rise in connected medical devices might one day require the need for them to operate to an agreed standard meaning that we could soon be seeing SEPs in pharma. SEPs must be licensed on Fair, Reasonable and Non-Discriminatory (FRAND) terms. They can underpin an environment that continues to reward and protect innovation, while also enabling interoperability and collaboration on a wider scale.

SEPs and FRAND licences could be the key building blocks behind the development of truly personalised medicines. It may sound like science fiction but Aprecia Pharmaceuticals has received approval from the US Food and Drug Administration (FDA) for a 3D-printed drug designed to treat epilepsy. For this process to be scalable, it will require pharmaceutical companies to make the formulations (the ink) while tech companies will provide the printers. With multiple providers of ‘inks’ and ‘printers’ standardisation will be required to avoid each patient, pharmacy or hospital having to have a battery of printers to make each and every medicine.

Every step of the process could benefit from SEPs. The doctor can prescribe a medication according to weight, age and disorder severity for a specific patient but the software ‘ink’ and printers needed to print the prescription will all have to be governed by standards that allow interoperability between drugs from different companies.

This example may seem fanciful now but so was the idea of self-driving cars 20 years ago. So if the promise of truly digital and personalised medicine is to become an everyday reality, then changes in mindset need to happen sooner rather than later.

The speed at which big tech innovates and disrupts is foreign to the pharma sector but it must adapt or there is the real possibility that today’s pharma giants become increasingly side-lined. Pharma companies can respond by adopting a more collaborative approach to development and data sharing by continuing to build partnerships with tech firms. By embracing the technologies and working practices of big tech, pharma can remain at the forefront of an industry that is presently undergoing a seismic transformation.

Pete Sadler and Robin Ellis are both partners at Reddie & Grose LLP, a firm of patent, trade mark and design attorneys