Open-source drug discovery

Todd started by noting that he must normally begin his talks by selling open source to a room that is hostile to the idea; that tends not to be a problem at LCA. The chemistry community, he said, is playing catch-up, trying to mimic some of the things that the open-source community has done. The first step was to apply these principles to basic research before moving on to drug discovery; the latter proved to be harder, since it's typically a process that is shrouded in secrecy.

There are hazards around using terms like "open source" when it comes to chemistry. Todd mentioned a 2013 article in the Guardian discussing his work; the first comment came from a certain "rmstallman" asserting that "open source" does not apply in this setting. An inconclusive argument followed. Todd still wonders whether he should be using "open source", but alternatives like "free drugs" have their own pitfalls, he noted.

The first project started in 2005, working on a drug called Pranziquantel. It is given to some 100 million people each year to deal with a particularly nasty freshwater parasite infestation. The molecule comes in two forms (enantiomers), one of which is effective while the other only serves to leave a nasty metallic taste in the mouth. That taste is evidently so bad that many people given the drug refuse to take it; there is thus a solid reason to want to create just the effective form of the molecule, but that was an expensive thing to do. Todd's group took on this problem, and decided to ask the world for help — something that is rarely done in the chemistry field.

Thus started a community called "Synaptic Leap", which was useful for a while but has now gone dormant. The group asked for ideas, but didn't get much until it brought in some grant money and started an online lab notebook. That was the crucial component; it reveals what is happening in the lab every day, shows that the group is actually leading the effort rather than just asking others to do free work, and makes the world take the effort seriously. Synaptic Leap was featured on a prominent chemistry blog, with mixed reactions overall, but a lot of people started to contribute. A company called Syncom did a lot of lab work and accelerated the work considerably.

A post to a LinkedIn room containing 1,000 process chemists brought in more help; as a side benefit, Todd said, it also found an actual reason for LinkedIn to exist. In the end, they solved the problem quickly, making good use of input from outside. The solution is working its way toward the market now.

The scientific community tends to talk a lot about "open innovation", but that has nothing to do with open source. In the former, a company with a problem will post it publicly, then buy a solution if somebody presents it. That solution will remain proprietary; "that doesn't really change anything". In the open-source world, instead, the solution, too, is out in the open.

Drug discovery

The next step is to try to discover new molecules that can be used to attack diseases. The usual process starts with some molecule that is effective against a disease (it kills the malaria parasite, for example), but which cannot be used because it is toxic to humans or has some other problem. By researching variations of that molecule, one hopes to move from a "hit" to a "lead" that is potentially usable as a medication. This process tends to happen in secret, but Todd and colleagues hoped to find a way to do it in the open instead.

It turns out that GlaxoSmithKline had published a paper identifying thousands of molecules that killed the malaria parasite; this information had been put into the public domain for anybody to work from. From this starting point began the Open Source Malaria (OSM) project. This project is based on six "laws" of open science:

• All data is open and all ideas are shared
• Anybody can participate at any level of the project
• There are no patents
• Suggestions are the best form of criticism
• Public discussion is more valuable than private email
• The project is bigger than, and not owned by, any given lab

The first three, he said, are the most important.

Open access is seen as increasingly important in the biochemical sciences. The Bill and Melinda Gates Foundation and the Wellcome Trust have been particularly aggressive in pushing open research, where the results and the data must both be available. The Open Source Malaria project agrees with all of that, but goes another step by making the laboratory notebooks available as well.

OSM has run four campaigns to date. Each campaign is essentially looking at a molecule until something useful is found or it becomes clear that nothing is forthcoming. Importantly, when the project gives up and moves on, it doesn't hide any of its data on the failing molecule; anybody can resume that effort in the future if they want. The first three campaigns at OSM have stalled out; the fourth is ongoing.

The bedrock of OSM is the open lab notebook. This is a bit challenging in this field, Todd said, because most of his colleagues still use a paper and pen. So the first step is to make everything electronic so that it can be shared. The project initially used LabTrove for this work, but development has been slow on that project. OSM has now transitioned over to LabArchives (seemingly not an open-source project) owned by the University of Sydney.

Then, the project needed a to-do list. There were a number of "extremely unfortunate" experiments with systems that didn't work out at all, until somebody came up with the idea of using GitHub's issue lists. The project has no idea what it's doing with GitHub, Todd said, but issue lists have been "sensational"; they have brought people in who are actually using them. The data for the molecules themselves is stored in a Google Docs spreadsheet.

The molecule that OSM is working on now is "very promising"; the work is at the point where somebody would normally be filing for patents. It works in mice, and it is getting close to being ready to try in humans. But the investigators still don't know how the molecule actually works, which "will eventually matter". They decided to run a competition to figure that out, and got six models submitted in return which they then tried against a separate, secret dataset. There were some winners in the competition, but none of the models worked particularly well; it seems necessary to retry the experiment with more data. The submitters all want to keep trying with more data, and they want to work together to figure out how to model what this molecule is doing. Todd believes that a predictive model will eventually result from this work.

Contributions to OSM don't just come from individuals, though; there has also been some good input from big pharmaceutical companies. The companies themselves cannot participate in something like OSM, but they can allow their people to do so. A scientist from Pfizer found and contributed an especially potent molecule; interestingly, when the OSM scientists synthesized it, it didn't work at all. So something is different somewhere; there is an open issue on GitHub dedicated to figuring that out. It is, Todd noted, especially important to be open about things that do not go right.

Work is happening in university classrooms as well. Some students have come up with molecules and have shown them to be effective, which is exciting for everybody involved. There was also an interesting episode where OSM worked with students to cheaply synthesize Daraprim; that is the drug that "pharma bro" Martin Shkreli increased the price of by a factor of 50. Working in a university lab, the students were able to create $150,000 worth of "primo-quality" Daraprim cheaply.

To summarize: OSM is a platform and a growing body of machine-readable knowledge. But it's also a community demonstrating ideas about how things can be done differently in the area of drug discovery. There have been issues about how discoveries from OSM can be published in the academic literature. Five years ago, that was a problem, but the journals have become much more receptive to publishing the results of open research. The openness of projects like OSM engenders trust in the results they get. Beyond that, people like to see how results are achieved. Just like people will watch the cooks in a restaurant with an open kitchen, they will watch how this kind of science is performed when it's open. That, in turn, helps people to quickly learn how the scientific community works.

Next steps

The next step would be to get one of these molecules into a clinical trial with humans; that would be the first time such a thing has ever happened with an openly developed molecule. There are just a couple of problems that need to be solved before that can happen. At that point, there will be new funding issues; human clinical trials have a number of ethical and legal issues that need to be worked out.

Dropping back into technical details, Todd noted that there still isn't any easy way to convert a molecule into a string representation. The form in which molecules are stored in the computer looks like:

    O=C(/C(S/1)=C/C2=C(C)N(C(C)=C2)C3=CC=C(S(=O)(N)=O)C=C3)NC1=N\C4=CC=CC=C4

Needless to say, such things are rather painful to type. The real problem is that, at present, computers don't understand molecules; if they did, lab notebooks would be far more useful. It would be possible to search for people working on similar molecules, for example. There is a proposal out there for a system called SCINDR to introduce scientists to possible collaborators; building that requires better machine-readable lab notebooks. Projects like C6H6 are a step in the right direction, but there is work to be done in this area still.

There are various other details that need to be solved. A better web page would be a good start ("we don't know what we're doing there"). A tool to automatically move data between the Google document and public databases is on the list. With a reference to the discussion at the previous day's opening session (which was a celebration of LWN's 20th birthday) he noted that newsletters are important, and the project is about to put out its first issue. There are thoughts of becoming a non-profit organization. The project has T-shirts, but he observed at the conference that stickers are needed too.

The biggest thing that's missing, though, is automatic construction of narratives. When somebody is doing work, one of the most important things to do is to reflect that work in a wiki, but that rarely happens; people are too busy. It would be nice to have this happen easily, with a simple "publish" button to hit at the end. There is scope for research into AI systems that could help with this task.

There is a new project, the Drugs for Neglected Diseases Initiative (DNDi), which seeks to expand this approach to diseases that tend not to attract attention from pharmaceutical companies. The first topic is a nasty fungus called Mycetoma that, currently, has no treatment other than amputation. The DNDi is launching its first clinical trial for a new molecule in this area, and others are in the works. This is a good target: the need is immediate and there is nothing available for this disease now.

A question he is often asked is: who is going to pay for this kind of work? How can a drug be brought to market with no secrecy? There are a number of different initiatives in this area, many of which are discussed in this 2017 paper co-authored by Todd. There is a lot of money from foundations going into drug discovery. The real problem is a lack of precedent for an openly discovered molecule going into production; that hampers funding of the crucial clinical-trial phase. What is needed is the sort of corporate investment that is seen in the open-source industry; there's currently nothing like it in the pharmaceutical business. In the field of law, companies require that their legal staff do pro-bono work; that, too, doesn't happen in pharmaceuticals. He hopes that will change in the next few years.

Some people feel that drug development cannot be done without patents, but that is clearly not the case, he asserted. Penicillin and polio medicines were never patented. One of the most widely used antimalarial drugs (ASAQ/Coarsucam) is patent-free, as is Fexinidazole, a new drug for sleeping sickness. He thinks there is a workable model that enables investment from companies that allows them to get their money back when they need to. Under this "data exclusivity" model, any company that pays for the trials that show a molecule to be effective and safe would get exclusive rights to sell it for six years. That clock would only start when the drug hits the market, a feature that can make this approach more attractive than patents, for which the clock can start many years before the drug can be sold. After six years, the drug would go generic.

The one thing that worries him, he concluded, is that there is continual talk about how new approaches are needed in this field, but they are not happening. Alzheimer's and dementia are a looming catastrophe, for example, but we have no answers for these problems. The current approach isn't working to solve them, but nobody is doing anything differently. If we generally want to try radical approaches, we need to try the things that the pharmaceutical industry cannot do, and that requires working collaboratively in the open.

Interested viewers can watch the full video of this talk.

[Your editor thanks the Linux Foundation and linux.conf.au for assisting with his travel to the event.]