Skip to content

Accellerating decentralized innovation in biotech

Anthony Butler
5 min read

Most people will have heard of Moore's Law as it relates to the computer industry but there's a similar – though diametrically opposed -- law that governs the pharmacutical indusry known as Eroom's Law.  Eroom's Law states that the speed of drug development declines and costs double every nine years.

This is troubling for a number of reasons but, not least of all, because it means that potentially life-saving drugs are not getting to the people who need them as fast as they should – nor as fast as they perhaps might have before.  This is perhaps counter-intuitive given all the advances that hae been in technology, such as artificial intelligence, which can accellerate drug design.  However, these delays are, for the most part, due to systemic issues such as regulatory burden and complexity in bringing drugs to market, misallocation of capital, and inefficiencies in the sharing of knowledge.

A lot of these issues can be attributed to the structure of the industry itself where there are large companies who use monopolistic intellectual property models as a moat.

As with other industries, there is some emergent thinking about how some of these systemtic inefficiencies can be addressed using new technologies.  For example, how can the principles of the open source communities – which have been responsible for tremendous advances in technology – also be applied to the biotech space; how can we reimagine pharma as a more decenteralised, network structure; and how can we rethink some of the funding models to address the well-known inefficiencies in how researchers must seek government funding grants.

There has been some fascinating work to think about a new organisational structure for biotech research modeled on the Decenteralized Autonomous Organisation (DAO) concept that has emerged out of the blockchain world.   In a Biotech DAO, the founders would set a particular mission – such as, to use a real world example, funding pre-clinical drug development for longevity (VitaDAO).   The DAO would then attract talent, seek funding (such as through a token issuance or some other mechanism), and would implement an open governance structure.  In many cases, the intent is for the DAO to also be self-sustainining through, for example, also receiving IP revenues from the commercialisation of any DAO-funded research that might then be distributed to the members and/or used to fund successive research and development efforts.

The tokenisation of IP – as an IP NFT – represents one of the more useful and interesting applications of NFTs.   It enables a researcher to "mint" NFTs for different aspects of their work, such as data, in order to fund their research.  DAOs or individuals would buy these NFTs in order to support the researcher in their activities.   As their research progresses through commercialisation, these funders (whether DAOs or humans) can receive revenues, based on their IP NFT holdings, from the licensing of the research or sale of the resulting pharmacutical products.  Aside from fundamentally transforming the funding model for research, this also creates new liquidity around IP and allows collateralisation and even borrowing against it.  

Molecule, who have been leading a lot of the work in this space, have a good primer on IP-NFTs at the link below:

IP-NFTs for Researchers: A New Biomedical Funding Paradigm
TL;DR: This week, the first university biomedical intellectual property (IP) and research project was funded as an NFT (non-fungible…

Whilst this would solve for the funding challenges, this new approach to decenteralised science could address other inefficiencies.

Firstly, with funding largely tied to reputation as represented by publishing metrics – such as h-index – it's possible that some ideas by brilliant but not well-known scientists is not getting funded.  It is possible, using decenteralised technologies, to envision a world where reputation is also tokenised so that activities, such as participation in conferences, peer value, training or similar, all become visible in a scientist's "wallet" such that funding decisions by the DAO can be informed by a broader and richer set of data points.

Secondly, the peer-review process has been widely targeted in the context of a broad set of criticisms of the academic publication industry.  For example, academics – mostly funded by taxpayers – write papers that are then submitted to for-profit journals who subsequently engage other academics – also funded by taxpayers – to review the research; with the resulting paper subsequently published in a journal that is then sold back to the taxpayer-funded universities that these same academics work for.  There's some work being done, such as described in this paper, on how peer reviewers can be economically rewarded and incentivized.  

Thirdly, the speed at which a DAO can fund research is orders of magnitude faster than what we have seen from governments.  If we use VitaDAO as an example, their latest Community and Treasury Report shows they funded approximately $2,000,000 in research projects within less than a year of operation.  

Fourth, whilst the cloud abstracted away a lot of the complexity in developing new software by making the atomic building blocks of digital innovation available to the world, there is no equivalent in biotech.  There are, of course, economic reasons for this but, through the emergence of these new decenteralised approaches to science, there is also a possibility to fund the development of new scientific infrastructure, such as lab services and data sharing paltforms.  LabDAO is an example of this where they are seeking to establish shared tools, platforms, and "cloud labs" that can be accessed by researchers in return of shared IP or tokens.   The idea being that scientists can get access to lab capabilities with the same ease of instantiating an EC2 instance on Amazon Web Services.  This video from earlier this year provides a good introduction to LabDAO.

Lastly, it is interesting to think about the interconnection between these new digital-native institutional forms, such as DAOs, and the physical world.  A large part of the challenge is regulatory as a drug passes through pre-clinical, phase 1 and phase 2 trials.  Indeed, this period where the innovation is "translated" from research into something that can ultimately be commercialised is called the "valley of death" in the industry.  As many studies have observed, it costs a lot, takes a long time to pass through the regulatory gates, and the chances of succcess are low.      As more governments consider special economic zones (SEZs) or charter cities as an enabler of economic growth, there is an opportunity for future-oriented and science-friendly cities or jurisdictions to partner with BioDAOs to help streamline and accellerate clinical trials – and eventually manufacturing and commercialisation.  

Anthony Butler Twitter

Anthony Butler is based in Riyadh, Kingdom of Saudi Arabia where he currently Chief Technology Officer for IBM Middle East and Africa. He is focused on emerging technologies and applications.