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  • mattoddchem 11:00 pm on February 6, 2018 Permalink | Reply  

    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

    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.

  • mattoddchem 10:16 pm on September 14, 2016 Permalink | Reply  

    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.


    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.



    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?

  • mattoddchem 1:24 pm on May 29, 2015 Permalink | Reply  

    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.

    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))

    • Thomas Arildsen 7:01 pm on May 29, 2015 Permalink | Reply

      I am not an economist or health professional for that matter, but I cannot help but wonder: what prevents any other generic drug producer from using the openly available documentation of the medicine to produce and sell it at a lower price with no obligation to return any of their earnings to the project that developed it?

      • mattoddchem 9:55 am on May 30, 2015 Permalink | Reply

        Nothing, but, as I understand it, the data exclusivity condition is that if you want to sell a (non-generic) drug, you need to run your own trial in order to generate the clinical data for registration. So: given the available data, you’d be quite confident that the trial would work. But would you really plough money into a trial (that would last years) just to compete with a medicine that is already going to be low cost, and which you know will go generic anyway in a few years? I don’t see this as a strong market incentive.

      • Chris Sampson 5:51 pm on June 2, 2015 Permalink | Reply

        I am an economist, but no expert on this! Hopefully someone in my network will pick this up when I share the link. Economists are generally known for being bad at predicting things, but actually microeconomists are pretty good at predicting how businesses will behave. So it’s good that economists play a central role in HIF et al. For me, the challenge will be getting the regulation right. And the main challenge will be the international context. But pharma will respond to their biggest markets, so if we can get US and EU regulators to work together we’re in with a chance.

    • Nick Dragojlovic 7:10 am on June 3, 2015 Permalink | Reply

      Very interesting post. A few thoughts:

      1) The key issue would seem to be what the permitted ROI for investors is before it goes generic…

      Investors typically aren’t looking just to get their money back, they’re looking to make the best return they can get. If returns in this sector are sub-par, most money will flow to other investments (tech, real estate, whatever) that will yield a higher rate of return.

      2) Buying or selling shares (between investors) won’t really provide an incentive unless the returns are comparable to or better than other asset classes, which probably requires pricing to maximum willingness-to-pay (i.e., current pharma strategy).

      3) The one exception to this is the hypothetical “impact investor” that is motivated primarily by the goal of developing a treatment for a specific disease (say, because their child is affected), and is unwilling to simply donate the money (because they don’t like the idea of donating to a corporation or because they think for-profit entities are more likely to bring a drug to market).

      The problem: no one knows how big this pool of potential investors is and what sorts of resources they command and are willing to invest in this manner. Could be that there is enough impact capital to fund only 1 project in any year, or it could be enough to fund 100. The viability of this type of drug development model crucially depends on that.

      4) In effect, you’re describing equity crowdfunding by impact investors in a “venture philanthropy” model. Again, the viability of this model depends entirely on the number and preferences of impact investors with substantial assets (i.e., accredited investors). Many equity crowdfunding sites focused on healthcare have emerged, and may be good partners in any such venture. For a list, see:

    • mattoddchem 10:13 pm on June 10, 2015 Permalink | Reply

      Hi, Nick, thanks for the comments.
      1) Correct about the typical expectations of investors, but there is more to investing than money – e.g. Corporate Social Responsibility, ethical investments etc.
      2) Ditto – the idea would not necessarily be to maximise returns but to provide modest returns as a feature, i.e. exactly not to accumulate wealth during the course of generating important medicines.
      3) Just as you say – this is the idea. And I agree with you over the level of uncertainty.
      4) To some extent. I would not be prescriptive about the source of the money, if that’s what you mean. I would want to design this thing in a way that money could flow from government grants, philanthropists and simple private investment.

      On reflection I wonder whether I am in effect defining something like a Social Impact Bond?

    • Nick Dragojlovic 7:03 am on June 11, 2015 Permalink | Reply

      Hmmm. Seems like a Social Impact Bond in an R&D context to which anyone could contribute would basically be something like a crowdfunded X-prize, no? I’m all for prize-based incentives, though it’s worth keeping in mind that the participants must still find a way to fund the R&D to actually win the prize (or meet the terms of the Social Impact Bond), which requires either fundraising (status quo) or a large enough return on the SIB to justify early investors (same issue of lots of public money going to corporations, just in this case via SIB returns, rather than via high prices charged to government payors – at least in jurisdictions with pharmacare).

      Agree that there is more to investing than money, but the key question is: for whom and how much are they worth? Total impact investment capital as of 2014 is a tiny proportion of total capital ($12.8B globally, by this estimate –

      Is there a lot of untapped potential there? Hard to say without more data.

      In terms of philanthropy, that’s probably the better opportunity at the moment for impact-focused capital to flow into open drug development. Again, the question is: would the ability to invest in a social venture with limited financial ROI increase the total capital put into the sector, or would it simply crowd out philanthropy? Again, hard to say without more data.

      In my opinion, those are the key questions that need to be answered before betting on impact investment as a route to open drug dev instead of or in addition to doubling down on philanthropy.

    • Jack Scannell 4:00 pm on June 16, 2015 Permalink | Reply

      Just so readers know my biases, I have worked in drug and biotech equity investing, drug discovery in a small “bleeding edge” private sector biotech, and in academic research. I now do some work at a translational medicine group at Oxford ( and a life science policy group at Edinburgh (

      I have absolutely zero experience in open source drug discovery (or anything else open source), so apologies in advance if I have misunderstood things or my comments are simply going over old ground. However, with that proviso, here are my reactions.

      (1) Clarify the benefits of open science in drug R&D
      “The intellectual arguments in favour of openness are clear….” They may NOT be clear to a lot of the people who control large sums of private or public sector capital to deploy in drug R&D. Most would probably doubt that any general approach is going to be good for everything.

      Therefore, I think that it would help to educate public and private sector funders (and people like me) if there were some clear statements of where and why open source drug R&D is likely to beat the conventional approach by a long way. I would frame this in terms of “discovery efficiency” before worrying about IP. If you can convincingly argue the approach is more efficient / productive, and for what specific kinds of activities or objectives it is more efficient / productive, then people with money will become more interested in how you overcome some of the obvious challenges (e.g., IP). If you can’t convince people it will be much more efficient/productive, then there is less point doing the work necessary to overcome the IP / funding problem.

      To give a concrete example, I would guess that interactions with the drug regulator would be difficult to do in open source mode. If I read the Second Law of the open source principles to which the blog links, I see that “Anyone can take part at any level.” It would be hard to deal with the FDA or the EMEA on that basis. The FDA wants a named individual who it can send to jail if data are deliberately fabricated. Similarly, there will be manufacturing-related activities during the R&D process; preparing drug for clinical trials where open science would probably not help much.

      Maybe the crisp and clear “open drug R&D – a guide for dinosaurs” already exists. If so, apologies. If not, write one.

      (2) Disease / market choice
      Following a couple of conversations with Mary Moran regarding new antibiotics and the AMR problem, I have become much more sensitive to the distinction between (A) diseases where a good product would, in principle at least, have a commercial market, and (B) diseases where a good product would still never sell very well. because the patients or their governments are too poor, or because the disease is so rare.

      In class (A), charities and governments can support basic research, and may help manage the market, but one can often rely on private sector investment for a lot of the process. In class (B), it seems to be more trouble that it is worth to try to get the private sector involved. Therefore, if you are really doing (B), then there is no point creating complex schemes to pull in private sector/for-profit money. Conversely, if you are really doing (A), you need to be more careful about inadvertently disrupting for-profit efforts (see below).

      (3) Unintended consequences
      As an aside, I worked for a small private sector bio-informatics oriented biotech company in Oxford. We were trying to do what was effectively informatics-driven drug repurposing (or sometimes using re-purposing opportunities as “hits” from which to generate novel chemistry). In some ways, this appears to be a nice, low-cost, high-efficiency business model. We were using large publicly available chemo-proteomic data sets and protein-protein interaction data sets.

      The experience made me sensitive to problems that current patent / IP law presents. The bioinformatics tools might identify something that looked interesting. One would then do a big Pubmed search, and find that a couple of lousy review articles written years ago had speculated (on the basis of other information) that drug class X might be good for disease Y. These lousy review articles would make us think very hard about whether or not we would be able to secure any IP because the patent office might regard them as “Prior Art”. This would tend to be a real disincentive for us to invest any further in the result.

      In a similar vein, drug companies will sometimes publish stuff (either academically or in patent form), not because they think it will be useful to themselves, but because they know it will destroy the IP that their competitors are working on and will reduce competition. This is called “salting the field”.

      One thing that I think people doing open access drug discovery need to think about is the fact that they may be salting the field some of the time, but that the collateral damage will be invisible to them. This is why I think Disease/market choice (above) is important. If you are working in a therapy area where there is unlikely to be much private sector interest, the risk is low. However, once you are working in an area where the public sector is interested as well, then the risk of inadvertently “salting the field” increases.

      One way this can be managed, of course, is by managing the scope of the open science. If, for example, you produce “chemical probes” that might help people find Leads, but which are not Leads, then the risk is probably very low even if you are working in an area that has a lot of commercial interest (as per the Structural Genomics Consortium).

      As you can probably tell, I am not an IP/patent expert, but I think this is a general area that requires real expert thought. Maybe I think it is more important than it really is, given the rather peculiar commercial niche that I was in (bioinformatics-oriented drug re-purposing)? None the less, I have heard other people in the drug industry talk about this problem; where an academic group publishes stuff and simultaneously destroys the IP that would have been required to bring that very stuff to market.

      (4) Selling the idea to for-profit private sector investors
      I have tried to think about selling the idea that Mat sets out to some of the cautious, clever, and critical fund managers that I used to deal with when I worked in investment. If I came to them with the idea as it is presented in the blog, I think I would struggle to part them with their money for the following reasons. Perhaps some of the questions / concerns that the fund managers would have can be answered in the next iteration?

      Here are the kind of things that one or two of the more prickly fund managers would have asked me:

      “Why the hell have you brought me this? You know I can’t invest in this kind of thing?”

      This will be a very niche investment product. You need investors who are healthcare specialists, who can invest in illiquid assets, and who may have to be very flexible about the length of their investment horizon. These kind of people are probably identifiable, but they will be few and far between. Conventional venture capital, for example, typically has predefined holding periods and will need to exit (i.e., sell). It might be better to go after the “commercially-oriented philanthropists” (e.g., the Wellcome Trust translational outfit) and forget about the purely commercial investors.

      “Aren’t you going to promise me a lot more than the prospect of simply getting my money back?”

      Drug R&D has the economics of a lottery. No one buys lottery tickets hoping to “get their money back” because there is a good chance they will get nothing at all. The vast majority of drug R&D projects fail. 9/10 candidates entering clinical trials fail. Around half of the entire economic value of drug industry profits come from the top 10% of marketed drugs (i.e., the top 1% of drugs entering clinical trials) with half of all marketed drugs generating profits that are worth less than the average drug’s fully-allocated R&D cost (i.e., allocating the cost of failures). Therefore, if you cap per-project profits to a “reasonable” level, you destroy – in some peoples’ minds at least – the economics of the industry.

      In my view, for what it is worth, most of the drug industry today is losing money on R&D and some Wall Street analysts agree with me on this. Therefore, if you go to commercial investors promising returns that are at face value going to be lower than the returns from an industry that already has poor returns on R&D, you will struggle to make a sale. If you are promising lower returns, you also need to promise much lower risk. You could only do this if you have a big slug of philanthropic or government money from the start, and the philanthropists or government promise to bail out the shareholders to a large extent if things go wrong. However, this starts to require a very complex investment vehicle.

      “Can you come back and talk to me when you have lined up the money to pay me if it all works?”

      I think the “critical path” that you would need to follow to pull in private sector investors looks long. So, for example, you would first have to get an agreement with whoever was going to cough up the cash at the end of the R&D process. Their commitment would have to be utterly convincing. Only when there was an obvious way of getting paid at the end of the process, would you get any kind of financial pull that would interest commercial investors.

      Given the cost of late stage trials and typical failure rates, you need to get hundreds of millions of dollars committed as an absolute minimum. Not many single agencies will commit that kind of cash, which means you need to build some kind of buyers’ consortium, which will take years to do. Then, of course, R&D projects take 8+ years in clinical development, and 20+ years if you include the basic science. I think you would struggle to build the buyers’ consortium and even if you did build the consortium, private sector investors would be worried that priorities would change and by the time the drug was approved, the cash had been spent on something else.

      “Can I get my money out early if it all looks hopeless?”

      Mixing private sector money that is chasing financial returns with philanthropic money that is seeking to make the world a better place may cause governance problems. What if, half way through the project you find out that your drug is bad for malaria (a lousy commercial market) but good for, say, male pattern baldness (a great commercial market). Do you ditch the malaria plan and go hell for leather for baldness? But maybe you can’t because if it is open source so there is no IP. What if another great malaria drug beats you to market, and you are worried that governments will no longer honour the agreement on data exclusivity and cost recovery because they no longer need your drug as much. The private sector shareholders may want to wind up the project and get their remaining cash out before it is spent, but the philanthropists would want to push on.

      “Who is in charge if we find something that will be useful for some big commercial market?”

      A similar but slightly different point is that a standard commercial R&D project has all sorts of option value, because you can chop and change the objectives to match the emerging science or changing market conditions. An open innovation project with some kind of long term commitment from governments or public sector bodies around endpoints / regulatory approval for malaria or another disease has none of this kind of option value, because you can’t easily repurpose the science if there looks to be a better opportunity to address. This is true even if there turns out to be science that could have been turned into IP for a commercial market.

      This kind of on-the-fly repurposing is very common. Many of the world’s most successful drugs or drug classes were invented for something else (e.g. the anti-TNFs, Viagra, SFUs for diabetes, MAO inhibitors for depression, the anti-VEGF drugs used in AMD, etc. etc.). Because you have tied payment to a specific outcome, many years in advance, while at the same time foregoing opportunities to re-purpose the project if other outcomes look better, the “option value” is much lower than a typical R&D project.

  • mattoddchem 9:33 am on March 24, 2015 Permalink | Reply  

    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.

    Open Source TB Hit

    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: – 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.


    • Bheemara G. Ugarkar 2:33 pm on March 25, 2015 Permalink | Reply

      The molecule you have shown is an excellent Hit and if it has potent MIC against H37Rv and non toxic to mammalian cells, it is a plus. What else is done on this molecule? Any SAR and SPR information? Just curious. I am part of the Open Source Drug Discovery in India and we have pursued a couple of hits from GSK. Best wishes: Bheemarao

    • Jessica Baiget 11:19 pm on March 25, 2015 Permalink | Reply

      Hi Bheemara, thank you for your interest. This hit is our starting point and we are currently working towards obtaining data for some analogues that we may have access to. However, our initial work has been focused on the synthesis of some related compounds (see link) that have been sent recently for biological evaluation. This information and our lab notebook will be fully accessible in a few weeks. Best wishes


  • mattoddchem 1:20 pm on February 23, 2015 Permalink | Reply
    Tags: data exclusivity, economics, , , patents, TRIPS   

    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.


    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?

  • mattoddchem 9:46 am on January 13, 2015 Permalink | Reply  

    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

    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.)


  • mattoddchem 9:51 am on December 15, 2014 Permalink | Reply
    Tags: academia, Electronic Laboratory Notebook, ELN, open access, , publishing, tuberculosis   

    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.

    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

    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.)

  • mattoddchem 10:31 pm on October 3, 2014 Permalink | Reply
    Tags: , Crowdsourcing, Education, , MMV, , , Open Source Malaria, ,   

    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!

    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

    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

    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

    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.

    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.

    • mattoddchem 10:31 pm on June 11, 2015 Permalink | Reply

      Example of the use of undergraduates in research: long standing program at California State: though clearly a difference here is that the research is open access (i.e. to read) rather than necessarily open source (open ELN, visible as it happens).

  • mattoddchem 8:34 am on October 2, 2014 Permalink | Reply
    Tags: biomedical R&D, open source, , , private sector, The High Line   

    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.

    High Line in NYC

    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

    Public Leadership for the High Line

    Private money for the High Line Development

    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.

    High Line - New Section

    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

    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 up new spaces

    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.

  • mattoddchem 10:31 pm on June 25, 2014 Permalink | Reply  

    Sabbatical Day 1 

    Today I’m starting a 6-month sabbatical. Sabbaticals are a perk of academia (though every profession should have them) allowing the sabbaticalee to learn something new, start up a new project or mull over a large problem, freed of administrative and teaching responsibilities. It also provides time to finish papers, write grant proposals etc. Some people, for pragmatic reasons, take sabbaticals at their home institution, a staybattical if you will, but nothing beats the disruption of a move, and talking to new people, for thinking about tough problems in a new way.

    So what am I doing? I’m in Boston till September then in Oxford till January.

    The focus is on open source drug discovery. My lab ran an open science project in drug synthesis in tropical diseases with WHO, and is now at the centre of a fascinating experiment in open source drug discovery known as Open Source Malaria (OSM), with MMV. The first malaria papers will be written up in the coming months. There is a huge amount to do in OSM, but the project has achieved some key objectives already, in terms of demonstrating how open drug discovery can function efficiently, leveraging the power of a nimble and distributed group and identifying new, potent anti-malarial drug candidates. More on OSM in future posts. One of my main objectives during the sabbatical is to look at how we can scale-up OSM in the next 3 years, since it needs to be made larger if it is to compete effectively with established, large, closed projects operating elsewhere.

    University of Sydney contributors to OSM - me, Tom MacDonald, Jo Ubels and Alice Williamson

    University of Sydney contributors to OSM – me, Tom MacDonald, Jo Ubels and Alice Williamson

    My lab is starting up a project in Open Source Tuberculosis, with GSK Tres Cantos. This is exciting for lots of reasons, and I’ll be writing more on this project soon too, but with TB we move slightly closer to a disease area where drugs have a positive net present value, jargon for the idea that there is a profit incentive to TB drug discovery that makes an open approach more difficult to conceptualize end-to-end: how can an open source approach compete with commercial or academia/industry projects where future profits (guaranteed through patents) are used to off-set up-front funding of the research?

    So here are the two questions I’ll be looking at:

    1) How can we scale-up open source drug discovery precedents like OSM to become part of a new pharma industry?

    2) Could we use open source drug discovery in areas normally associated with a profit, such as cancer, Alzheimer’s or diabetes?

    These are great questions because it’s not clear how to answer them. My expertise is organic chemistry, and that is the important technical discipline I bring to such questions. The experience of previous open science projects has I think taught us a lot about how to run them. But I don’t want to contribute anything to a research effort that is either sub-par, or which is not maximally efficient. I don’t think we’re doing drug discovery (or, indeed, organic chemistry) efficiently. Indeed I think we’re hemorrhaging resources in the way we’re currently doing science. It is, to be frank, toe-curling. So I want to look at the two questions above so that I and my students can contribute only to the very best projects with the best structure and the most likelihood of finding a new medicine.

    To start to answer question 1, I’m helping run this unique meeting. The outcomes will be written up and extensively disseminated. It’s very exciting to get this group of people together, all of whom are in touch with an even wider network of talented people who are interested in trying something new. We’ll be discussing prizes, for example – the idea that if you award large sums for research performed you can separate out the costs of research from the price of a medicine. I’m very excited to see what comes out of the meeting.

    To answer question 2 I am visiting two institutes, both leading the field in data sharing for drug discovery in areas such as epigenetics. So from late June to mid-September I’ll be in Boston working with Brian Hubbard’s team at the Harvard/MIT Broad Institute – this is a great fit because Brian and his colleagues have extensive industry experience, but have moved to the Broad to try out something genuinely new.

    Boston, on the morning of Day 1

    Boston, on the morning of Day 1

    Then from late September to early January I’ll be at the Structural Genomics Consortium at the University of Oxford, working with Chas Bountra. (The chief medicinal chemist there, Paul Brennan, is a buddy of mine from postdoc days at Berkeley). Chas has been a leader in open science for some time, securing extensive funds for the SGC’s activities and working effectively with the pharma industry to share data that underpins much of the structural biology that fuels rational drug design. The aim in both places: to collect together a group of people willing and able to try a project in open source drug discovery in an area such as cancer. i.e. to define a target, a hit compound, a scientific project structure and a governance/financial plan for how something like this might work. Both the Broad and the SGC lead the world in sharing data related to biomedicine, but neither have an open source project currently operating – i.e. one where anyone from outside those institutes may contribute, and it is clear what the project will do tomorrow. Collecting such a group together is really tough, and I don’t know how to do this, which is why I need a sabbatical. The aim is a project that is properly federated – labs in several countries working on the same project, using local funds, acting as a kernel, to which anyone else may contribute should they have the expertise. How?

    So I’m in Boston till September, then Oxford till the end of the year. Ping me if you want to talk about open drug discovery or organic chemistry. Even better, if you’re interested in trying out something in open drug discovery, by contributing to a consortium of loosely affiliated scientists who share what they do each day, please get in touch.

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