Rewards for Innovation, After the Fact

According to the family grapevine, I’m related to a pioneer of the industrial revolution. I’m the (great)ⁿ grandson of Samuel Crompton, inventor of the spinning mule that revolutionized textile production.

Portrait of Samuel Crompton by Charles Allingham (1788–1850), Bolton Library & Museum Services, Bolton Council, CC-BY-NC-ND

What I only recently learned is that Samuel didn’t patent his invention and was instead awarded some money, later, to recognize his contribution.

I was struck by this since it’s exactly what I’ve been writing about recently. A possible way of rewarding entrepreneurs who have worked, and shared, openly. Sustaining entrepreneurs who reject secrecy. A retrospective reward once something has demonstrated its importance and has impacted all our lives.

The story is related briefly in the Wikipedia article and more fully in a book. (French, Gilbert J. (1859). The Life and Times of Samuel Crompton, Inventor of the Spinning Machine Called the Mule. London: Simpkin, Marshall, and Company.)

Samuel Crompton invented the mule, as an improvement on the jenny. The mule allowed for the production of fine cloths.

Spinning Mule, https://commons.wikimedia.org/wiki/File:Mule-jenny.jpg

Samuel didn’t just invent this thing, he made one and actually started making superior cloth in his own home. The quality of the materials attracted a great deal of interest. People wanted to know how he was doing it and tried to ingratiate themselves into his house to see the machine in action. Someone even installed themselves in his attic and drilled a hole in the floor to try to peer through into the room below.

At this point Samuel was in possession of a trade secret. He knew it wouldn’t last. There was the possibility of patenting, but he could not afford this. He said to himself “a few months reduced me to the cruel necessity either of destroying my machine altogether or giving it up to the public. To destroy it I could not think of; to give up that for which I had laboured so long was cruel. I had no patent nor the means of purchasing one”.

Instead he tried a third way that I believe was sometimes used back then (late 18th Century England). In return for a cash contribution (a “subscription”) from a small number of individuals, he would reveal (to them) how the machine worked, and even give up the machine itself. Several people agreed and signed up. The information was duly handed over.

He never received a penny from anyone.

The information was presumably poorly guarded: the design flooded into the public domain, transforming (disrupting, as we would now say) the textile industry and contributing to the industrial might of the North of England (where I’m from, originally. My mother says that the statue of Samuel Crompton in Bolton looks exactly like my grandfather. I will need to investigate).

Statue of Samuel Crompton in Bolton, England. Copyright Kenneth Allen CC-BY-SA, http://www.geograph.org.uk/photo/980458

Samuel died not a rich man. Towards the end of his life the people of Bolton took this issue upon themselves, and raised a petition to parliament that complained Samuel had not received his dues. His invention had changed so much and made many people wealthy, while he was left with essentially nothing. A sum of 5 thousand pounds was awarded. This was seen as pitifully little, and somewhat insulting. Again, from the biography by French: “Thus after having haunted the lobby of the House of Parliament for five wearisome months in hourly expectation of his case being dealt with; leading a life of monotonous anxiety without variety or amusement of any kind … and day by day subjected to that ‘hope deferred which maketh the heart sick’, he returned home to Bolton with this phantom of national reward as the requital for his transcendent invention!”

An interesting situation, of which I would guess there are other examples. A novelty was created, and shared (essentially it “went generic” immediately) and the inventor was not rewarded.

I’m delighted in a way to discover this story. A terrible situation for my forebear, but intellectually fascinating for me as his descendant. I’m left reconsidering this question: is there a way we can work openly (i.e. no patents, no secrecy, no traditional “prizes” given these are typically secretive) and provide inventions to society (in a way that keeps costs down) while still incentivizing the innovators through rewards (i.e. after the fact, once the invention has clearly demonstrated its effectiveness).

I find this question interesting, particularly with respect to the discovery and development of new medicines. I’m reminded of the Health Impact Fund, in which research is done and medicines discovered and where the reward to the discoverer is calculated based on the demonstrated health benefits of the medicine. There is a very nice new representation of this idea by Rufus Pollock and colleagues in the iMed Project, in which it is made more clear that the R&D can be open source. I’m reminded of other kinds of “award” such as data exclusivity in which the R&D can be open and expenses can be reclaimed through the granting (again, from a government, on a piece of paper) of a temporary ability to set a medicine’s price at whatever you like once it’s helping people (a mechanism excitingly being tried by Al Edwards and colleagues in M4KPharma). The distribution of post facto awards to inventors requires high levels of either record keeping or trust or both. In open source everything is clearly laid out – who did what, who suggested what, who drove things forward. Maybe here there is a role for blockchain to industrialise trust – something others are, I think, already looking at.

Samuel Crompton’s story on the surface is one of an innovator not receiving his dues because he didn’t control his intellectual property effectively (he tried!). One can just say “well, so it goes”. But there is a clear, gut-feeling injustice here, and we’re left with a lingering sense of “surely there’s a better way of rewarding innovation that impacts society quickly because it is freely shared.” This makes me impatient to trial bold new funding proposals in real drug discovery and development projects.

 

 

Notes on further reading
1) Rufus Pollock’s essay on the evidence of patents as drivers of innovation in the industrial revolution.

Open Source Mycetoma

Super exciting. Today I’m involved in launching Open Source Mycetoma (“MycetOS”) – an open source drug discovery project aimed at finding new medicines to treat the terrible fungal infection eumycetoma.

The background can be read in the preprint that we’re using to launch the project. In short, this is a disease for which there are no effective medicines. Encouragingly one clinical trial is being run. MycetOS is the backup.

By stepping on a thorn you can contract an infection for which the current best treatment is, well, amputation. It’s an awful, debilitating illness. I’ll refrain here from sharing uncensored images of patients, but please do an image search to see what I mean.

Censored version of https://tinyurl.com/yczdolzd

I remember well the atmosphere in the room at the ECTMIH meeting in Basel in 2015 where a session was run to highlight the clinical trial that had been announced. Listening to the Sudan-based medical expert, Dr Ahmed Fahal, there was shocked silence as he described what he had to do to treat his patients. Emerging from the room, the delegates seemed bewildered, and furious.

Eumycetoma (which we’re calling “mycetoma” just for simplicity, even though there is a bacterial version) is the newest addition to the official WHO list of neglected tropical diseases, and is to some extent the poster child of neglect. The disease is now on the hitlist of the Drugs for Neglected Diseases Initiative (DNDi), with whose leadership this project has materialised – Ben Perry and Jean-Robert Ioset have been driving things. The disease expert is Dr Wendy van de Sande in Rotterdam whose lab can evaluate compounds. My lab has pushed the open source mechanism and we’ve been working on the synthetic chemistry for a year or so.

But it’s an open source project, so if you want to be an equal partner in this endeavor, you can be. We’ve been running Open Source Malaria on several key principles, and the same ideas apply here. All data and ideas are shared in real time (e.g., as usual, online lab notebooks). Anyone can participate. No patents. You can read the press release for more, and a one-page description of MycetOS.

If you want to get stuck in, there’s a Github community where there are already some live “issues” that need your inputs: what to make next, and do you know of any possible sources of molecules we could screen? There’s a Reddit community too: we’re seeing which of Github or Reddit works best, or whether we can use both in parallel). News/social interactions will be via Twitter.

The worldwide mycetoma community, though small, is bigger than this one project, and we’re hoping people can use MycetOS to collaborate specifically on new small molecules with potential to treat the disease. We’re going to need funding, which is perhaps the largest item on the To Do List. Strength in numbers – if you’d like to be involved, please step forward.

Open Source Malaria’s First Paper

Open Source Malaria (OSM) publishes its first paper today. The project was a real thrill, because of the contributors. I’d like to thank them.

Skepticism about open source research is often based on assumptions: that people will be too busy or insufficiently motivated to participate, or that there will be a cacophony of garbage contributions if a project is open to anyone. I’m not sure where such assumptions come from – perhaps people look first for ways that things might fail. We can draw upon many experiences of the open source software movement that would suggest such assumptions are poor. We can draw on successful examples of open collaboration in other areas of science, such as the Human Genome Project and the projects it has spawned, as well as examples in mathematics and astrophysics. This OSM paper addresses open source as applied to drug discovery, i.e. experimental, wet lab science in an area where we normally expect to need secrecy, for patents. It is based on the experience of 4-5 years of work and describes the first series examined by OSM. The paper argues strongly against these assumptions, since:

1. Many people contributed enthusiastically
2. The contributions came from a wide range of institutions, from Pharma through to Universities, from undergrads through to professors.
3. Those contributions, many of which were unsolicited, were of a high quality.

Roll Credits

So who did what? Time for a bit of a credit reel. This is to express sincere thanks to the contributors, but that conveys the wrong idea of ownership. The philosophy behind the project is shared ownership, with a CC-BY license. We all share the project’s outputs, and we all worked together to get there – that’s the whole point. But still, I am keenly grateful that people got on board a highly speculative project at such an early stage.

Pharma as Open Source Partners

Without GSK Tres Cantos (Francisco-Javier Gamo, Félix Calderón, Benigno Crespo, Maria Lafuente-Monasterio) I’m not sure where we’d be. Their still-astonishing paper in 2010, containing thousands of beautiful hits against malaria, kick-started so much. They continued their inputs to the project, from experiments through to invaluable smaller contributions that take time to make, such as revealing that analogs being suggested by the community had/had not been evaluated by GSK.

GSK’s Transformative Open Dataset for Malaria Drug Discovery

This is a powerful reminder that just because the business model of Big Pharma means it cannot officially countenance open source, the companies are filled with immensely talented people who may be free to contribute, and are interested in doing so. Sanctioned freedom to operate is an enlightened policy and could be a real driver of open source projects through pro bono pharma contributions in the future – something I’ve mentioned before. In fact a referee of the OSM paper asked about this, and the wealth of information that arose from one of Derek Lowe’s posts on this subject was then incorporated into the paper – an interesting example of the new synergy between research papers and community discussions.

Pharma’s involvement is a crucial pillar of open source. I have no desire to obliterate pharma, and I’m not sure any other participant in OSM does – there is extraordinary scientific expertise there that can accomplish astonishing things. The experimental inputs to OSM Series 1 from pharma, such as the Rate of Killing Assay, to pick just one example, have been essential for the project. Frederik Deroose from the company Asclepia designed and costed syntheses and agreed to the sharing of these publicly as part of brainstorming processes. The pharma model has weaknesses, meaning they cannot officially pursue certain projects. I think that open source can provide a powerful competing model. But I hope nobody is surprised to see pharma, or indeed the private sector more generally, as co-authors on the paper.

MMV

The Medicines for Malaria Venture (MMV) has tirelessly supported the project. Back in 2010 I gave a talk at the University of Cape Town hosted by Kelly Chibale. Tim Wells happened to be there, and we got to talking about whether the open source idea I’d previously applied to organic synthesis could work in drug discovery. What was interesting about that conversation was how much Tim had thought about this already. We batted around the arguments for and against open source, and soon reached that point familiar to all scientists where you have to acknowledge that discussion can only get you so far – at some point you have to go into the lab and actually do an experiment. We wanted to establish whether open source drug discovery would “work”, i.e. whether a distributed, self-assembled team could work effectively and leverage inputs from the community. Rather than argue the point any more it was going to be simplest just to try it.

I presented the idea to Jeremy Burrows in Geneva, and MMV became more involved. They provided seed funding which got Paul Ylioja to Australia and into the lab to start the very first reaction (10% yield for a Paal-Knorr, mate?). Paul Willis became the day to day champion at MMV. His pharma experience was clear from the outset – a combination of scientific expertise but also a vigorous pursuit of project milestones that was a striking counterbalance to the rather more relaxed set of objectives we find in many academic research projects. MMV have been pioneers in open data for malaria – the best and most recent example being the Malaria Box initiative driven by Paul himself, and the current work around the Pathogen Box.

Early Days in Sydney

MMV’s backing of the project led to us securing a grant from the Australian Research Council, setting up the core of the project in my lab at The University of Sydney. Murray Robertson came on board, and, later on, Alice Williamson. I could not have asked for a more effective and committed set of postdocs to drive the project core, combining synthesis with a huge amount of technical work in setting up how to run an open source project.

Paul Ylioja, Murray Robertson and Alice Williamson

We benefited greatly from the use of the Labtrove Electronic Laboratory Notebook created by Jeremy Frey at The University of Southampton. This allowed the other contributors at Sydney Uni (students Matin Dean, Matt Tarnowski, Zoe Hungerford and Laura White and crystallographer Peter Turner) to share their raw data with the world, and Sanjay Batra and his team at the CDRI in Lucknow (Harikrishna Batchu, Soumya Bhattacharyya) to add their own syntheses.

We really scrambled for solutions in the early days. How best to solicit inputs? How best to encourage inputs from strangers? How best to disseminate results, on what was becoming an aging platform (The Synaptic Leap, created by Ginger Taylor)? How to ensure people did not use email, but instead communicated publicly? How to guarantee permanence of online data and effective linking between posts? (We were ably shepherded through a ridiculous amount of yak shaving by the talented Mike Robins, a neuroscience major at USyd). How to reassure people that raw data in the ELN could indeed be “wrong” but that science can correct itself iteratively and without shame? I remember an event early on that made me think this could all really work: Paul Ylioja received public advice on a troublesome synthesis from someone who clearly had experience of this reaction far beyond the norm – the idea to “age” a reaction overnight after quenching. It worked a treat. We would not have thought of this, and the anecdotal advice came from someone with high levels of technical expertise reading what we were doing as we were failing.

The Community Builds Itself

It’s exactly this feature of openness (experts coming *to* the project spontaneously) that is so powerful.

Everyone has to be on board with the idea of immediate release of all data – one of the contributors swiftest to understand that mission was Corey Nislow, who together with his team (Guri Giaever, Marinella Gebbia, Anna Lee) contributed a great deal of experimental and computational data arising from a yeast-based mechanism of action assay.

Guiding this community and platform development was a growing set of online contributors specialising in informatics. ChEMBL (John Overington, Iain Wallace, George Papadatos) advised the project on how to manage the growing volume of linked data, published the first interim dataset and carried out numerous analyses such as mechanism of action predictions and isosteric replacement strategies described in the paper. Chris Southan kept a watchful eye on patents, and pushed the importance of the discoverability of the molecules in the lab notebooks and other places (here‘s his list of the molecules from Series 1). An advantage of the openness of the lab notebook is that it can be indexed by search engines. Chris schooled everyone in the ways of the SMILEs, the InChi and the InChiKey, allowing people to find the molecules we were working on (ever tried drawing a molecule in the Google search box? Doesn’t work). Chris Swain provided continual advice on how to create, manage and exploit the dataset of all OSM molecules, and Luc Patiny created a way to visualize the structures and their data – for so long in the early days of OSM our poor capability in compound visualisation was a barrier to community participation.

Favourite Moments

Some events stand out.

1) Patrick Thomson’s synthesis of the sulfonamide analogue. Patrick, working in Colin Campbell’s lab in Edinburgh, took it upon himself to respond to Alice’s challenge to make the “most wanted” compounds in this series. He communicated with us by Twitter, but all the raw data were on the ELN. He made the molecule faster than we did in Sydney and I won’t forget the day when I woke to find a picture of him on Twitter holding the sample, ready to go. He had it evaluated locally at Dundee (thanks to Irene Hallyburton at the DDU). It was inactive, but an important data point needed for the paper. Patrick continued to make other molecules and contribute to other series.

2) Stefan Debbert’s undergrad lab class. Stefan demonstrated the power of crowdsourcing. Open projects work well as a source of undergrad science – all the students can talk about what they are doing and work together on real problems. Stefan managed this with his class, and showed how students can make meaningful contributions to “live” projects. Alice Williamson is now really driving this. That federated lab projects can be run globally, where each lab PI is in total control of the activity but shares data to a core, is a potent idea.

3) Receiving biological data from collaborators and immediately posting the data for community consideration never got old, and remains one of the most exciting aspects of open source. Several leading parasitology labs around the world contributed potency evaluations (e.g. Vicky Avery at Eskitis and her team (Sandra Duffy, Sabine Fletcher), Stuart Ralph at Melbourne Uni and his student James Pham, Kumkum Srivastava in Lucknow, Kip Guy and Julie Clark at St Judes) and evaluations against other parasite stages (Elizabeth Winzeler at UCSD and her team (Stephan Meister, Yevgeniya Antonova-Koch), Michael Delves and Andrea Ruecker at Imperial College). In vivo work, and substantial follow-up analysis was carried out by Sergio Wittlin at Swiss TPHI. In Australia the project benefitted from data and expert guidance from Sue Charman at Monash on solubility and metabolic stability (and her team of Karen White and Eileen Ryan) and Kiaran Kirk’s lab at the ANU (working with his extreme frisbee student Adelaide Dennis) – Kiaran is strongly involved in OSM’s current Series 4, since his favorite antimalarial target, PfATP4, is the target of those compounds. Maybe.

4) The witnessing of productive conversations between professors (Jonathan Baell, who argued strongly for the avoidance of “PAINS”) and undergrads (Zoe Hungerford) to resolve issues quickly within blog posts.

5) The disbelief of witnessing activity cliffs arising from small changes in structure (see the paper itself, Figure 7) – this is something medicinal chemists are all familiar with, but it’s still a shocker when it actually happens to you.

Decision to Park

We communally decided to park the series. It was a tough call – the molecules have striking promise in various ways. If the arylpyrroles had been the last series on the earth, we’d have continued, but there were other series to explore, such as the current in vivo active compounds in Series 4.

But anyone can continue Series 1. There are specific molecules that need to be made, described in the paper, and clear ways forward towards understanding the mechanism of action.

Want In?

The 6th Law of the consortium is about project ownership (see the paper, Figure 1), or rather the lack of it. I started this project with MMV – got it funded, set it up, suggested how it might work best. A core team drove it forwards when it was quiet – open source projects always require leadership. But at heart the OSM consortium is not about ownership, but rather about a way of working. If you cleave to the idea that open data is a good idea, and if you like the idea that when people look over your shoulder they might suggest an improvement to what you’re doing (and that you rise, prospectively, to that challenge) then you’re in. There are no badges, no member dues (there are some T-shirts, actually). Just do an experiment, record the data and expose yourself up to the potential brutality of public improvement.

Other people know this too. The Structural Genomics Consortium is pioneering open data as a stimulus to drug discovery on a large scale. CO-ADD is screening community-contributed compounds for infectious diseases, with a default to public domain data. Sage Bionetworks have pioneered genomics competitions in biomedical research. You can consume your computer’s spare CPU cycles on searching for hits vs. Zika targets using the IBM Grid, or use public data generated by the NIH. I see Open Source Malaria as the necessary extension of open data into the larger, messier place where we all have to roll up our sleeves and make and evaluate real molecules in labs over an extended period.

If you like the idea of Open Source Malaria, then the current series needs work: compound synthesis, biological evaluation and there’s a competition to determine the mechanism of action. There’s also interest in creating an open educational course in medicinal chemistry. And Alice Williamson is keen to work with undergrad lab classes in new analogue synthesis by cloning the course she’s successfully run at The University of Sydney. The current to-do list, a portion of which is shown below, is here. If you have your own series of compounds that you want the community to work on, and you’re happy to share all your data, the platform is for you.

There are varied strands of OSM currently needing inputs

Some Predictions

In poker one can sit around for hours winning or losing little pots of money, but the adrenaline flows in cases where you make significant calls, where you place a lot in the middle on a gut reading of the terrain and then watch it play out. I find long bets interesting, when we’re scoping out where we’re all headed long-term, without enough data. I’m a little unpopular with some for saying that the open access debate is over – open access is in my view the future norm, and there’s nothing anyone can do about it (this is a great thing, incidentally). There is now forming a very significant consensus around open data that will impact us all in the next 2 years (Nature’s new policy, for example). I predict open source to be the norm in scientific research in certain areas in 10 years, and if anyone is working secretively in, for example, neglected disease drug discovery by then they will seem perverse. By the time my kids are adults the idea of secrets in scientific research will probably seem perverse – why hold your team back with secrecy when there are so many advantages in collaborating with the world? I say this because the nature of collaboration is only going one way: to be more seamless, to be faster, to be more machine-enabled. To accommodate this change the legal and economic structures that surround research and research funding are going to need to change, beyond all recognition. The impact of that on the development of new medicines is what I find so exciting. I don’t see a solution that doesn’t have holes, but I’d place a bet that there’s a solution set that will in retrospect seem obvious. And I predict that’ll arise from a proper competition between traditional methods of drug discovery and those that are completely transparent. So many good things in this world come from properly formulated competitions.

 

FAQs

1. What do you mean by “Open Source”?
All data and ideas freely shared. Anyone can take part. No patents. See the paper, Figure 1.

2. Where is Open Source Malaria?
Landing page (constructed by the talented, responsive people at CloudCity Development), Lab Notebooks, Wiki, Github To Do List, Twitter. Physically located in many places, and contributors come and go.

3. Isn’t this the same thing as Open Source Drug Discovery, in India?
No. OSDD unfortunately shared only a small amount of its activity publicly, so cannot be considered an open source project. OSDD was described more as a crowdsourcing approach to bioinformatics among groups located in India. A malaria project was mooted but did not ultimately receive funding.

4. Is open source the same as “open access”?
No. “Open access” means you can read the results after publication. In open source you can take part in the research before publication.

5. Is open source the same as “open innovation”?
No. “Open innovation” is about securing solutions in new ways, but there is no requirement to collaborate, or to share what you’re doing and there are controls on the release of data.

6. Aren’t you just getting other people to do a bunch of work for free?
No. People contribute voluntarily for any number of reasons. There is no requirement placed on anyone. The consortium is supported by a mix of core funding (government/NGO), funding to contributing labs (e.g. big pharma inputs, or block-funded academic labs doing other things as well), educational projects (student crowdsourcing as part of official courses) and genuine volunteers (who may or may not be working on employer time).

7. You abandoned the series – I guess open source doesn’t work?
Attrition in drug discovery is high. Open source drug discovery is no different on that score. Given all the data are available it’s clear what to do (and what not to do) next for these molecules. In open source there is no unnecessary duplication and no hiding of bad data, meaning if a series fails, it only needs to fail once.

8. Who’s going to pay for the clinical trials for a patentless drug?
There are known ways of doing this, and many more that are more speculative. As yet, there’s no precedent of a open source drug going all the way through to market.

9. Are you all Communists?
No.

Funding Open Source Drug Discovery

I’ve been speaking to many people about funding open source drug discovery. If there is no secrecy, and no patents, then Who Will Pay? It’s the obvious, central question behind the whole enterprise, particularly around Phase 3 trials. I’ve been asked this probably 20 times in the last 2 weeks of conferences and meetings.

The intellectual arguments in favor of openness are clear – openness means efficiency, inclusiveness, etc etc. It’s a done deal. But what about the money? How do you marry open source and a Big, Sustainable Financing Model?

An answer is to say “Pharma can’t do Open, so the money needs to come from the public sector. Or philanthropy.”

I guess that is true, but when I say this to people, their spark of interest is lost. This just sounds like another drain on the public purse. “These are times of austerity” people will say “where will you find the money for developing new drugs, for clinical trials.” I think people are hoping for something striking and new.

CC-BY https://www.flickr.com/photos/amagill/3366720659

Funding for open source drug discovery will come from many places. But I am left wondering whether there are really new mechanisms we could consider. I’ve previously wondered aloud about retrospective patents and data exclusivity.

Major financing mechanisms have been proposed, such as the Health Impact Fund (“take a drug to market and you’ll be rewarded if it works, then it goes generic”) or Advance Market Commitments (“You can invest since there will be a market”) backed by large financing facilities – essentially permitting GAVI. There are more recent calls for up-front funds e.g. for antibiotics, which is mimicking what has already been achieved with the Global Fund. There are much-maligned Priority Review Vouchers (“develop a medicine for malaria and you’ll save millions developing a new drug for cancer”). There are also prizes and combinations of mechanisms.

(Notice how some of these are meant to work: governments issuing guarantees. We’ll come back to that.)

Question: What unifies these mechanisms? Answer: None has been combined with open source discovery (I think). Why? Because there have not yet been any open source projects that have taken a medicine to clinical trials. This is needed. What happens to these financial tools if you bolt on a commitment to complete transparency and no IP all the way from discovery to market?

I’ve been thinking about this hybrid:

On Day 1 of a drug discovery project you commit to open source principles, and you sell shares. People can buy these and sell them. Initially all shares could be owned by a public body, but could be sold to investors. Perhaps the entity selling the shares could be an organization with a portfolio of projects. Donations could be made, and competitive grants could be awarded, independently of such investor buy-in.

The projects run. Some fail. One hits. When the drug is successfully taken to market, the price is set at a level that ensures investors (including those who contributed key resources) get their money back. This would be achieved by legally-enforcible data exclusivity. The medicine would be made by the generics industry, but the price is initially enforced. Once the money has been recouped, the medicine goes fully generic. Everyone will know how much money needs to be recouped, because the development has been transparent.

So this is rather like the Health Impact Fund: payment for performance – in this case the period of exclusivity ends once the money has been recouped through patient use. A more successful medicine will probably have a shorter period of exclusivity. But here we have the ability to buy and sell shares, which adds the motivational aspects of the market. And with a commitment to zero secrecy.

Obviously also the period of price exclusivity could be shortened by cash donations – a zero-risk investment in global health.

I need economists to please point out the problems with this idea. I don’t know what happens, for example, if the managing organisation is valued, through shares, at $1Bn and Bill Gates gives a cash contribution to the research of $1Bn. If Gates wants money back he’d need to buy the shares, correct? Or he could just donate $1Bn and that would not affect the value of the other shares? Similarly governments could pay for the research in the usual way (“Track 1”: grant funding schemes, pooled funds) that would not need to be repaid. The repayment part (“Track 2”) is an option for people providing private funds?

Does that work?

(Notes: i) I’m posting this in advance of reading this important-but-5-year-old-book on the Health Impact Fund and other mechanisms. ii) I’m grateful for interesting preliminary conversations about this idea in the last 2 weeks with Steve Ward, Tom Higley, Steve Williams, Dave Busha and others (which is not to say they endorse))

World TB Day 2015 – An Open Source Drug Candidate

In recognition of it being World TB day today, and to promote the development of urgently needed new medicines for this terrible disease I’d like to point people to a project they can be involved in from today. We very recently started Open Source TB – a project that will be similar in design to Open Source Malaria. The idea is that, eventually, anyone can run projects and take part in existing ones. No secrecy, no patents. Inclusive research. It’s early days, so please excuse the boxes and bubble wrap.

The first set of compounds that were looked at were recently published. The second series of compounds is starting with a very nice looking molecule discovered by GlaxoSmithKline at their Tres Cantos site. It has potency against TB and is not toxic to mammalian cells. It’s an interesting compound – we’re not sure what it’s doing, and could use some help with that, starting from recent predictions of the target.

An Open Source TB hit from GSK – TCMDC143693

We’re still working hard to set up the collaboration platform. Jessica Baiget is a postdoc with me working in Madrid, supervised by Julia Castro-Pichel from GSK. She’s recently resynthesised this compound (here’s the full lab notebook entry – working right now on sharing the whole notebook) so that she can study it further and make some new variations.

This compound needs to be developed more, and any and all data generated will be put into the public domain immediately. We’ll set up more ways we can all work together. If you have a compound series you’d like to install as a new series on the wiki for consideration by the community, please just go ahead – e.g. any “abandoned” series from big pharma, or academic projects needing inputs. For now please check out the Twitter account and follow it for updates. If you’re working in the TB area and want to share ownership of the Twitter account to spread the word about anything open source that is related to TB, please just DM the account so we can be in touch. There’s also a Google+ Community so people can discuss anything.

If you’re a medicinal chemist who would like to make some of these molecules, please get in touch (can use an email account we’ve set up: opensourcetb@gmail.com) – the chemistry for TCMDC143693 is *really nice* in fact, thanks to Jessica’s work. If you are a bioinformatics guru and want to help validate the target for the compound, please also get in touch. If you’d like some of these drug candidates for your own biological work, please just say.

 

The Economics of Open Source Pharma – What about data exclusivity?

This post is about something called data exclusivity. I’m asking whether data exclusivity might be a way to ensure the existence of a financial incentive for open source drug discovery and development.

I am actually asking, since I’m not clear on the language of the relevant law.

I was talking with some people at the SGC in Oxford recently about the possibility of some (any) kind of assurance to investors in open source drug discovery and development (e.g. the state) that they might make their money back when the medicine hits the market. I had been mulling over this idea of a retrospective patent (RP). I was thinking afresh about data exclusivity, which, unlike the RP, is already enshrined in law and which might achieve something similar. Instinctively I’m against exclusivity, but there’s something interesting here.

Data exclusivity is a period following a clinical trial where the funder of the trial (i.e. the people bringing the drug to market) have several years grace to market the medicine: to sell the medicine, you have to have generated the clinical trial data. This exclusivity is nothing to do with a patent – so for example generic versions of a medicine can be produced following the expiry of the period of exclusivity, unless a patent prevents that. Here’s a useful PDF background document. Other miscellaneous background can be seen here, here, a PDF from WIPO, and an argument that data exclusivity is a better incentive for invention than patents.

So: is the 5-10 year exclusivity on the use of clinical trial data a means of protection for an open project? Imagine we run an open source drug discovery/development project, and we run a clinical trial as part of that. We disclose all the data as soon as possible. Would we have some period of exclusivity to act on the data? Would that permit a fully open project to set the drug’s price at a level that covers costs? i.e. can one think of the exclusivity as a positive enabler of an open project, rather than as a necessary evil?

This hinges on whether the data can be public and still not acted upon by anyone else. In other words if you wanted to register your own version of the drug, you’d need to pay for your own trial. You’d have to pretend the original data aren’t there.

You could of course go ahead and pay for your own trial anyway – after all you’d have some confidence that the trial would work out OK.  You could then release a competing medicine. But I can’t imagine any shareholders thinking it would be a good idea to go up against an open consortium, committed to low prices and with a multi-year headstart. (Unless your country’s laws mandate you do this – which is the case in India – in which case the open data would undoubtedly make the trial a lot simpler and cheaper.)

So my conception here of “exclusivity” equates with a “manufacturing license” rather than “secrecy”. The ability to recoup costs might mean there is no need for patent protection and the associated secrecy.

What does the law say? The sticky part is whether the “exclusivity” means that nobody else can see the data or whether nobody else can use the data. The TRIPS agreement on this seems unclear. Article 39.3 of TRIPS says data should be “disclosed” if the disclosure is accompanied by steps to ensure that the data are protected against “unfair commercial use.” It seems to me that this caveat means that the data could be disclosed openly, and that you’d need regulatory vigilance to make sure nobody uses the data to undercut the exclusivity granted to the open project. That shouldn’t honestly be that hard.

Questions.

1) Is this stupid, or has someone made this point before?
2) Is anyone an expert on the letter of the law here? Can the data be seen but not used?

Update (April 14th 2018). More reading materials.
1. Using Market-Exclusivity Incentives to Promote Pharmaceutical Innovation, N Engl J Med 2010; 363:1855-1862.
2. Market Exclusivity Time for Top Selling Originator Drugs in Canada: A Cohort Study, J. Lexchin, Value Health 2017 Sep;20(8):1139-1142.
3. The Role of the FDA in Innovation Policy, R. S. Eisenberg, Michigan Telecommunications and Technology Law Review 2007, 13, 345-388.
4. Data Protection and Data Exclusivity in Pharmaceuticals and Agrochemicals, C. Clift, In Intellectual Property Management
in Health and Agricultural Innovation: A Handbook of Best Practices (eds. A Krattiger, RT Mahoney, L Nelsen, et al.) MIHR: Oxford, U.K., and PIPRA: Davis, U.S.A..

Retrospective Patents as an Incentive to Open Research

Why do we say we need patents?

A patent is a public declaration of knowledge in return for a form of exclusivity. The deal is that by revealing to others what you have achieved, you have some time to profit from the invention, allowing you to recoup expenses incurred in development without being overly pressured by fast followers. Patents are usually promoted as a way to encourage innovation because they are currently a way towards a guarantee that offsets the financial risk of R&D. This seems reasonable. We should all support public disclosure and risk-taking. However, only those who have read a lot of patents will understand how far from the ideal (of being useful documents) patents usually are.

The offset of risk means that patents are seen by many in pharma and global health as a way to guarantee access to new drugs by the greatest number of people – i.e. as being an essential part of equitable access to essential medicines. Thus despite patents often being perceived (I think) as a tool that benefits big pharma, they are seen as being necessary if we want to see medicines developed and distributed. I understand this is broadly the current position of the Gates Foundation, for example.

Yet there is a significant downside to patents, which is the associated need for secrecy. To patent something requires that that something has not previously been revealed in the public domain. This means that the novelty in the patent is not merely a novelty, but is a novelty that has not been previously described anywhere. So it is not possible to make something new, start using it, and then later on (when it’s clear that the invention works well) to apply for a patent.

In other words, there is no way to be rewarded for an invention if you have already revealed it to people. “Well done on developing something new that works – here’s a period for you to make your money back.” Colloquially, there is no such thing as a “retrospective patent”.

The terminology of course makes no sense. Why would you need to patent something if it’s already public? Correct. So maybe there is another word for a retrospective patent. A license? A monopoly? What? Does this already exist?

I started looking around at the early history of patent law. I wondered whether, when patents were first created, they were awarded (e.g. by a monarch) for a clearly demonstrated invention already of public/commercial value, and one which needed rewarding through a little market exclusivity. But I can’t find anything of this kind. Was it the case that the first patents were awarded on already-operating objects? I’d love to know.

Nobel Patent, via Wikimedia Commons

 

So as it stands patenting cloaks scientific research in secrecy. This means R&D in pharma and, increasingly, in academia, is a secretive process. The secrecy is infecting university research, where many patents are sought on the off-chance that discoveries could be profitable later. Indeed quite generally patents are seen as necessary if we are to capitalize on discoveries made using public sector funds by using downstream private investment.

The secrecy of this process is the most significant barrier to open research. In many cases people are reluctant to share because there is the expectation that we must patent if we are to avoid jeopardizing the financial structure of the whole research system.

Let’s drill down to pharma for a moment. The secrecy means we don’t share the failed R&D campaigns, the current bottlenecks, the early successes. If a drug will fail, it can fail several times, expensively. There’s much duplication in research, wasting money.

There are non-traditional ways to fund drug discovery that offset some of the risk. One can make a guarantee that funding is available later on in development by amassing commitments up-front, and such things (GAVI, HIF) are being used particularly in the area of neglected tropical diseases. These are not yet mainstream, and the funding just isn’t yet there to replace the current pharma R&D system. But in any case, such instruments are still being used within an inherently secretive R&D system. Patent pooling also clearly requires patents, which are generated using the same secretive R&D system.

So: how can we combine an incentive to work openly (and share all our work) with the possibility we can recoup R&D expenses later?

The retrospective patent (RP) (or whatever it’s called) would mean one could invent something using a completely open R&D process where everything is shared publicly as it’s done, improving efficiency in various ways. Indeed that would be a precondition of being granted the patent – a solid paper trail that demonstrates invention (in much the same way we require this with the current patent process where a patent is challenged). Once the invention is shown to function correctly (and perhaps even to function well) the RP is written as a full, static definition of the scope of the invention (to summarize all the work that has been done and clarify the claim) then a period could be granted of financial exclusivity, by some means i.e. a licensing arrangement, with a period that might depend on the degree to which the invention innovates. Those providing the contributions that led to the invention (rather than those just swooping in at the end) would be granted proportional shares of the exclusivity agreed in the written document. Interestingly this means the State could be an awardee, allowing financial kickback for public investments in research, of the kind argued for by Mariana Mazzucato in her book.

Trying to determine who should benefit from this process (who was responsible for the innovation) when the invention was carried out openly will generate a lot of arguments. But we already have a lot of arguments about patents in the current system.

So an RP wouldn’t be a prize* (just as a patent is not a prize) since it would be something with a value that is determined by market forces during a period of exclusivity.

This proposal for “retrospective patents” is naive, but it gets to the core of the problem: the current need for financial exclusivity promotes secrecy which lowers the efficiency of the research process. If financial return could be guaranteed on condition that the research process is revealed openly in full detail in real time, and that the research needs to be demonstrably effective, and that all who contributed could be eligible for financial reward, we would actually incentivize openness.

So my question is: Does this legal/financial instrument already exist by some other name?

 

(*A note on prizes: Interestingly the kind of post hoc determination described above of who was responsible for past breakthroughs would allow prizes to be run openly, and would allow postmortems on prize funds – i.e. who should get how much of the prize and for what. So the prize could be run with a transparent workflow as a precondition for entry – and after a critical point is reached and a prize awarded the funds could be distributed according to achievement. This would significantly change closed prizes like the Longitude Prize (where people work in isolation in a way that does not change the way the research is done vs. the current system). The need for demonstrating one’s competence as part of an open R&D process should lead to a rather intense level of competition since there is disadvantage to being secretive or doing work that is not reproducible. Open competitions in coding are not mainstream as far as I know, but have shown these intense bursts of creativity. For those used to closed competitions, where one can mull on a problem at leisure without revealing one’s progress, this would be unsettling.)

 

Anatomy of an Open Science Paper

We use lab notebooks to record research. Why not publish lab notebooks alongside papers?

My lab just published a paper on some chemical methodology towards some potential tuberculosis drugs we finished last year. The chemistry was carried out by Kat Badiola, with bio testing courtesy of my colleague Jamie Triccas at Sydney Uni.

In some senses it’s a traditional paper, but it has an interesting feature.

Standard, brief papers are like press releases, conveying the choicest bits of the science. Most manuscripts we often read are a little like this.

Which is useful but of course ridiculous – like icing with no cake. So we often prefer to publish larger pieces of work, where the choicest bits are accompanied by a “Supporting Information” section – stuff you consult if you want to know more. Usually this is a PDF file, usually containing pictures of datasets – in Chemistry this is usually copies of NMR spectra, for example.

Cake
(via https://www.flickr.com/photos/pejrm/7589142384/in/photostream/ (CC BY-NC-SA 2.0))

Which is also ridiculous on its own, since it’s 2014 and megabytes are cheaper than milk now, so we’re able to include raw data files too (though people seldom do, I don’t know why) and we’ve done so with this paper. So you can download the files and reprocess spectra for yourself if you like. Useful for all sorts of obvious reasons I won’t list here.

Which is great but not enough.

What about all the “failed” reactions? What about the repeats, so that one can assess reproducibility? What about the comments and ideas we all put in lab notebooks, such as things to try next? What about the strands of the projects that didn’t quite work out, but may yield to another investigator? What about photos of the science (genuinely useful in organic synthesis), or other data that would help someone wanting to take this research on?

In other words, wouldn’t it be useful to include the lab notebook as part of the paper?

That’s what we’ve done here. The electronic lab notebook Kat used – it’s been zipped up and put on our Uni’s institutional repository. You can download it, unzip it and explore it as a snapshot using a web browser – all the links work, and every experiment is in there.

Components of a Paper

Useful, and easy to do. Very easy for open projects, since you are already sharing everything so why not zip up the notebooks and include them? It’s probably more difficult for closed projects only because if a lab notebook is closed it’s probably not necessarily in the best shape to be shared with others – openness in record keeping can encourage (not guarantee) a way or recording activity that is understandable by others outside the team. Including the notebook is essentially impossible if you’re still using a paper lab notebook (for shame!)

Thanks to the Labtrove team at the Uni of Southampton for capturing the snapshot and generally being great.

(Related links: Some suggestions as to how we might change journal articles in future are here. More on the browser-based notebook Labtrove here and here. Please comment below if I’ve missed anything.)

Crowdsourcing Drug Discovery

Open Source Malaria has completed an experiment in crowdsourcing for open drug discovery.

Identifying and developing medicines is a labour-intensive process, particularly in the discovery and optimization phases, and most particularly in the physical preparation of samples of new molecules for testing: a phase that consumes large amounts of time and money and is often a roadblock. One of the obvious things to do is to crowdsource the synthetic chemistry using students.

In open source projects there is the tantalizing additional possibility that student teams can assemble to work on those problems because what’s needed can be fully described in the open. The openness means that the teams could learn from each other, share data and receive peer review and mentorship from interested experts based elsewhere, such as in the pharmaceutical industry.

There have obviously been examples of crowdsourcing in various scientific arenas such as genomics (e.g., 1, 2) and there have been closed groups of students operating in the area of drug synthesis. There are examples of crowdsourcing initiatives in attempts to identify biologically active natural products (1, 2), Joerg Bentzien ran a Kaggle competition in in silico small molecule modeling, Urmi Bajpai is working with students in her lab on some biochemical projects (see also this earlier story) and there are other preparative activities of many kinds dating back to things as diverse as the AIDS quilts. I wasn’t aware of any students participating in crowdsourced synthetic chemistry as part of a project that was open source, though Patrick Thomson provided a spectacular example of how openness can lead to high quality scientific contributions from individuals. Mass recruitment of synthetic expertise is going to be one cornerstone of any scaled-up vision for Open Source Pharma, and I was very keen to see if we could complete this exercise in OSM as a precedent, and maybe learn how to make sure it works most effectively.

We just completed this precedent. Around 50 students from Lawrence University in the US midwest worked on the synthesis of six new analogs in the “Near Neighbour” (NN) branch of Series 1 of OSM. The compounds were mailed to a different lab in the US for biological evaluation. Active compounds were discovered – one of them new to the project and quite potent. I find the closure of this loop tremendously exciting.

Data for the Lawrence University Compounds – check out the red value for OSM-A-3!

Here’s how it worked. I was contacted a few days before the end of 2012 by two US-based academics asking whether their undergraduate cohorts could contribute to OSM. This had been an aim of the project way back in the design phase and not something we’d gotten round to. For one of the academics, Stefan Debbert, Murray Robertson and I wrote up a description of a synthetic route we’d been using for the NN compounds. The chemistry is not trivial, but possesses the advantage that the compounds are typically solids that can be easily purified and are stable under ambient conditions. Stefan looked into this and came up with some analog structures he felt his students would be able to access, and without any further input from us he got this working in his lab class in early 2013. Around June/July he wrote to say his students had finished the syntheses, and in November he uploaded all the data to the online lab book. After some quality control checking of the data by others, the compounds were shipped to Kip Guy’s lab at St Jude’s where Julie Clark performed the assessment of potency and the data were put up online last month, thereby closing the loop on this part of the project. This whole process took longer than it should have since we were all feeling our way a little on this one.

The data have come in just in time for the writing of the first OSM paper, which is at an advanced stage. We are now faced with the interesting challenge of how to credit this student cohort with authorship. What a great problem to have.

A Student Hard at Work in the Debbert Undergrad Lab

The take-home: a cohort of undergraduates successfully made new molecules that are potent in killing the malaria parasite. The data are valuable as part of a larger project of current research that will be published in the peer-reviewed literature.

 The students were able to make an impact because:

1) A current/future research need was openly described

2) The rules behind the project clearly stated that anyone could participate

3) The student team was locally and carefully mentored by a dedicated individual (Stefan) willing to engage in an unusual activity

4) The details of what was needed were described in full, i.e. previous, related research that made it clear the activity would not be open-ended

5) The outputs were actively used, i.e. data deposited in the relevant lab notebook for the benefit of the wider project and molecules tested by a laboratory willing to do so.

This is scaleable. Any team of undergraduates can engage in real research in this way, and perform scientific activities that are valuable to a “live” project and which might result in the undergraduates being able to publish their work. The work could be out-of-hours or, more excitingly (and as in Stefan’s case) part of a formal lab class for which the students receive credit – more on this below. I don’t know about you, but if I’d had the chance to make real molecules for a real research project as an undergrad, I would have found that quite motivating.

One of the neatest aspects about doing this openly is the quality control. A cynical onlooker might say “Well, these are just a bunch of undergrads – how can we trust the work?” You don’t have to. In an open source project, you have access to the raw data, so you can check the quality for yourself. Many people don’t trust data in synthetic chemistry journals in any case (trust is a problem across the discipline) but raw data in open projects solves this problem in as much as it can be solved.

So what would I change next time?

1) Fully Independent Contribution. The collaboration was set up because Stefan contacted me to ask if he could help out. That’s fine, but in an ideal world it would be clear to a lab director what was required without asking – that’s the aim of the Github To Do List that has since been introduced to OSM. But even there it’s sometimes not obvious what’s required and I think we can use Github more effectively. As much as possible in an open project one needs to promote independent contributions and an interlinked mentorship structure (the “Linus doesn’t scale” problem). Having said that, after the initial communications, Stefan ran the whole class independently, which is a testament to his achievement.

The OSM Consortium has a public to do list

2) Direct Data Deposition. The students did not deposit data into the lab notebook directly – Stefan himself aggregated the work and deposited the data for each compound himself. I think this arose because using the lab notebook presented a barrier to participation that was just slightly too large, and there was a concern that students might copy each other. I want to make sure the lab notebook is so easy to use that next time the students are happy to put the data up themselves as they are working – which is the standard practice in OSM. This means making sure that everyone understands that the data they are reading is like any data in any lab book and just because it’s on the internet doesn’t mean it’s correct or final.

One of Stefan’s ELN Entries

3) Global Lab Buddies. Ideally we would have two teams in different places communicating with each other on a synthetic route and not via the central project hub. I have in mind something that ought to be of interest to funding agencies like Fogarty, USAID or Wellcome – a lab class in a developed country pursues a synthetic route and a lab class in a developing nation pursues the same or related experiments, with direct collaboration between students and with mentorship in both places. This has the potential to be an inexpensive way of creating a “lab buddy” scheme where students can share what they learn with each other directly (with only light guidance from a PI, so that the collaboration scales well) and there is no need to spend money moving people around or organizing bench fees; effective lab-based crowdsourcing is significant in terms of how we think about organizing “networks” between universities (e.g. the APRU or WUN) – you can do a lot more for a lot less money if you don’t have to buy airplane tickets.

(CC image from https://www.flickr.com/photos/zachstern/2852218181/sizes/m/)

The experience makes me wonder about best practice:

1) Mentorship. How many mentors are needed for a class? There needs to be a committed local champion like Stefan, and the class size can be left up to the lab director, who also manages local health/safety requirements. There needs to be a central mentor (me, in this case) to help with any snafus. I think there is real potential here for additional mentorship from pharma professionals who could ensure that the molecules being made are reasonable for a drug discovery/development project. Such mentorship could be provided directly pro bono, or organized through a PDP (e.g. MMV, DNDi) or learned organization (e.g. the RSC). Pharma experts in a given location could contribute to their community in this way – e.g. Merck could mentor students working in schools in New Jersey.

2) Replication. It makes sense to me for two students to run each experiment, as a form of replication check. This is real research, so there should be controls, particularly if the students are not very experienced. It’s also probably a good idea for the students to make known compounds as part of the synthetic cluster. The need for positive controls of this kind is particularly keen in open projects since biological evaluation may well be performed in different labs where protocols will inevitably differ. A modest degree of replication makes everyone happier with the numbers ultimately obtained.

3) End-to-End. The work the students do needs to be incorporated into the larger project (at least on a wiki or in a paper) which may require that the molecules are evaluated in some way. If this is needed, then it’s crucial that it happens, so that student effort is not wasted or merely archived. Never ask a crowd to do anything that is not then used. This needs to be factored in to the planning of project resources and means that before the synthesis starts, there needs to be a commitment from somewhere that the molecules will be taken on (in this case, to kill a nasty).

4) How to Assess – or The Brown Oil Problem. I think the greatest power of crowdsourcing lab work lies in incorporating this into the undergraduate curriculum. Imagine that you’re planning a lab class, and you check online to find 38 different current project needs in open malaria, TB and Ebola projects. Let’s say the Open Source Pharma vision is made real and there is a repository of such projects that are known to be active that very day. This is not very far-fetched. You would, I think, be very keen to use one of these real research needs in your class, to fire up your students about how cool research is. If the syntheses were well-designed you could get started as soon as the starting materials were in. But the complication is: How to Assess the Project? What happens if a student fails to prepare a molecule that ought, in theory, to be preparable? How do we assess a project outcome if the outcome is novel, as part of a research project? I have no good answer to this, but feel that there are steps that can be taken:

i) Clarity of Design. The designer of the synthetic route to be undertaken must provide as much detail as possible about the ease of the synthesis. This honesty is simple in open projects – in the NN synthesis undertaken by Stefan it was possible for him to see all of the mis-steps and failures that the OSM team had wrestled with previously, and it was therefore possible for us to provide a lot of advice about key steps. Students themselves can even cite previous attempts as mitigating circumstances (“Though the molecule could not be prepared it was noted that Mat Todd similarly failed to generate this key intermediate in experiment 34-6 (13th Oct 2012)…” etc)

ii) Emphasis on Approach. The marking scheme used by the lab director needs to focus more on the approach used by the student and the quality of the scientific record produced than on the final outcome. This is in any case good academic practice. There remains an issue of plagiarism if students are posting items into the public domain, but one has to wonder about the value of having the students write reports that are vulnerable to this in the modern age.

iii) Time-resistance. The marking scheme needs to be immune to later discoveries. If it is ultimately found that a particular compound is unstable, a student who has earlier made this compound and found the same phenomenon cannot have their efforts re-marked, just because this makes the assessment too conditional and complex.

OSM is supported financially and scientifically by the Medicines for Malaria Venture and the Australian Government

If people want to get involved in this kind of activity, and it’s not clear from the OSM To Do List or the wiki what is needed, then don’t hesitate to get in touch directly. It’d be great to generate some more synthetic schemes suitable for students. If you are planning a research project yourselves, and are writing a proposal, consider including some element of crowdsourcing+open source so we can have lots more students contributing to real research in the public domain.

The High Line and the Public Good

The High Line is perhaps the most beautiful urban object I know. A former railroad track snaking through Manhattan, it has been repurposed as a garden and architectural haven, above the streets and passing within feet of the surrounding buildings, which are revealed, close up, like canyons to a fighter pilot.

The High Line in New York City

The line started out as private enterprise. I wonder if the development was originally publicly subsidized. It any event the line failed, since trucking made it industrially obsolete. You can still pick out the original ironwork in amongst the grasses. More recently the line was saved by an initiative based on community action, seeded with public money, followed by private money. The funding that has made the High Line incredible is shown by plaques near the middle of the trail to be this mix of public and private influence. I’m in awe of those who had the original vision to see what the line would become.

Public Leadership for the High Line

Private and Corporate Support for the High Line

I first visited the High Line four years ago, then again a few weeks back. What a difference those years have made. So much new private industry has emerged along the sides of the tracks in the streets below – cafes, bars, shops where before there was little. Another example, should we need another, that public works can act as a seed for rapid private investment.

The High Line is also free. It’s a marvel. I read that London is planning a garden bridge. To be great places, cities need inspirational works. We will rarely achieve that from public or private sector alone, but instead a combination without a predictable recipe.

Start of the Newer Section of the High Line

I couldn’t help but extrapolate to pharma.

Medicines sustain people – enabling them to do great things. A society profits enormously if its population is healthy. Effective medicines are a public good, produced by public and private enterprise. Yet we’re not currently producing the medicines we need, and we need to ask why. Perhaps we have become overly reliant on the private sector (which currently funds about 2/3 of all biomedical R&D). Probably no single system will work in producing what we need: every disease is different. The private sector needs the public sector to do what it can’t, and to do that it needs more R&D funds.

But the public sector can do something genuinely radical that it’s not currently doing and which the private sector cannot – embrace an open source approach where all data and ideas are freely shared, anyone may participate and there are no patents. This is the idea behind Open Source Pharma. Such an open, meritocratic arena achieves something quite astonishing: it promotes competition and collaboration at the same time.

Scaffolding at the End of the Line

The effect of going open source in the development of new therapeutics might simply be to de-risk some avenues of enquiry – to take discovery far enough that the private sector can accommodate the risk. The effect might be to enable genuinely new medicines to be discovered, developed and marketed completely from scratch. And the effect might be to provide a shocking and competing business model, if it’s done right. My money is on all three of these.

The High Line Opens New Spaces

But let’s not be lazy and assume that public R&D needs to operate just like private R&D. It would be a serious mistake to spend public money like we’re spending private, pretending that we need to use the same research model. If we’re funding it differently, we can do it differently. So why not play to the strengths of what entrepreneurial public financing can do – and open it up.