Imagine a world where a contact lens could be used a medical device. A world where tiny sensors in the lenses monitor and measure glucose levels in diabetic patients, alerting them to any dangerous spikes or drops. Thanks to a collaboration between Google and Novartis, these ‘smart lenses’ could become a reality in the next five years. The contact lens project highlights what pharmaceutical companies have the potential to achieve when they collaborate, but such co-operation is not the norm within the life science industry. Pharmaceutical companies tend to lean towards operating in silos, protecting their research and data from competitors. Companies even keep their precompetitive data, which is of very little material value, hidden from others.

This lack of collaboration comes at a huge financial cost to the life science industry; with R&D costs ranging from $2.3 billion to $4.9 billion between the years of 2000 and 2010, for a singular molecular entity. It also has a detrimental impact on productivity, with many companies duplicating the precompetitive data of their competitors. Further, PwC’s Pharma2020 report revealed pharma’s productivity stagnated in the decade between 2000 and 2010. Improved collaboration in the life science industry will help to reduce the time and costs involved with bringing a new drug or medical device to market, benefitting both patients and the industry. Moreover, research from Deloitte has shown that the success of alliances, measured as the average return on investment from alliances, is positively correlated with the number of partnerships an organization engages in. Life science companies that refuse to collaborate with peers in this manner will find themselves falling behind the rest of the more forward-thinking market.

What are the barriers to companies collaborating?

For collaboration to become a widespread practice, it will have to overcome several hurdles. Life sciences is a heavily regulated industry, further bound by the complexity of political oversight. Not only are institutions fiercely protective of what is seen as ‘their’ data, they are also concerned about breaking regulatory rules. Government initiatives (for example, Cancer Moonshot and Precision Medicine Initiative in the US, and the Precision Medicine Catapult in the UK) are also putting more pressure on the life science industry to innovate. The innovation required to achieve the aims of these well-publicized programs will only be met through increased collaboration within the life science industry.

Additionally, the industry is lacking the political and financial incentives to make collaboration an appealing prospect. However, several incentives could be offered through patent reform which would allow further encouragement for companies to collaborate. For example, increased patent life for cures or vaccines where it may not be commercially viable to invest at the present cost of R&D could be an incentive to develop a cure for rare diseases, or increased patents for novel action antibiotics could encourage the industry to work in partnership. Tax breaks for pharma companies who share Intellectual Property, or geographical tax which favours poorer countries unable to afford the cost of treatments or drugs are also potential opportunities to incentivize collaboration.

The key factor in lowering barriers to collaboration is ensuring that precompetitive data is discoverable and sharable between organizations. At present, the industry lacks universal data standards and data formats to make this feasible, with some organizations having purchased data management tools and others investing large sums in creating their own bespoke solutions. Common data standards also have an advantage for proprietary data during mergers and acquisitions (M&A), a regular scenario in the industry. At present, M&As mean a lot of the data value is lost where sharing it between two companies isn’t possible; the introduction of universal data standards can ensure data remains discoverable and of value after a merger or acquisition. Currently, working in silos is costing the life science industry more in the long-run, and slowing the pace of innovation that could improve patients’ lives.

How can we overcome these barriers to make collaboration the norm?

For cooperation, collaboration, and data dissemination to become accepted as the norm, the industry mind-set needs to change drastically. Companies need to be not only willing to share their precompetitive data, but to act upon this proactively. Pooling resources, and allowing access to precompetitive data is vital to ensure the current duplication of data, and waste of resources and money, is avoided by all organizations in the life science industry. However, in order for this to be successful, cross industry standards need to be developed and implemented to allow the easy transfer of information across organizations. Data must become a universal language.

The Hierarchical Editing Language for Macromolecules (HELM) collaborative project is a great example of what collaboration can achieve, with an outcome that will help facilitate future collaboration. The HELM project was initiated after Pfizer realized that there were no open-standard-based solutions on offer to researchers to allow them to computationally handle macromolecules, which the biopharma industry is increasingly using. Pfizer approached The Pistoia Alliance, which discovered that many of its member organizations had the same issue. As a result, a collaborative project ensued under The Pistoia Alliance umbrella, which resulted in the creation of an open source standard for biomolecular language, which is now a recognized submission format by the FDA.

The future of R&D is set to get even more complex

We are reaching the end of the era for blockbuster drugs. Life science companies are therefore now looking to specialize, and are seeking ‘niche-buster’ drugs. But successfully developing niche therapeutics requires considerable amounts of cross-domain data. What is more, this isn’t the only situation leading to vast amounts of data for pharmaceutical companies to contend with. We have seen an explosion in genomic data, as new technology makes it possible to sequence a whole genome for under $1000. Not only will this increase the amounts of data the life science industry has at its fingertips, it also helps to highlight to the public the potential of personal genomics.

Moreover, the rise of the Internet of Things (IoT), will see an increase in real world data provided by the public, from situations including clinical care and clinical trials. Advances in technology will only continue to increase these varied data streams, but the challenge of using and sharing data will continue if the industry does not address it. In order to achieve the great potential and promise that the future of R&D holds, collaboration is vital. The transition to collaboration will not be easy. But there are innumerable issues that will require working together to conquer them, including ensuring patient privacy and data security. Ultimately, the industry must work harder to collaborate, or it will start to see companies become irrelevant.

Steve Arlington
President of the Pistoia Alliance

Steve Arlington, President of the Pistoia Alliance, began his career in the 1970s, and he has worked in the pharmaceutical and diagnostics industry for more than 40 years. Steve began as a research scientist in the field of immunology and developed and launched many products in this arena. He was part of the team that developed and launched Clearblue pregnancy tests. Steve is a retired partner from PwC and led the Pharmaceutical Team in Advisory Services, and also previously led the IBM Life Sciences and Pharmaceutical Global Teams. Steve has grown two global consultancies into billion dollar businesses and launched a biotech company. He has also served on the advisory boards of major pharma and diagnostic companies, start-ups, venture capitalists