In an industry dominated by patents, proprietary data, and the race to get a first-in-class drug, the concept of open source drug development once seemed like an impossible dream. Yet as traditional pharma continues to leave many global health needs unaddressed—particularly for diseases affecting low and middle income countries^1,2—the open source model has evolved from idealistic theory to pragmatic reality. In this post, I’ll lead us through how open source drug development has overcome key obstacles of funding and intellectual property (IP) management to deliver real-world solutions.

Open source versus proprietary drug development

Open source drug development takes the term from software development and the Open Source Initiative^®, with the major components listed below^3–5.

1. Access to the source code.
2. Free redistribution.
3. Creation of derived works.

There are many publications^6–9 on how this open source software model looks applied to drug development and how it differs from the traditional/proprietary approach, but I’ll just outline the high-level differences below.

Seen from that list there are many differences but one thing that others and I get stuck on is, how do you pay for it all and convince manufacturers to produce your final product? We know that drug discovery and development (a term I’m using to describe all steps from preclinical testing to regulatory approval) is a highly complex process with significant attrition and monetary investment. The question is: how do you acquire enough money and manage the IP across the whole process of drug development?

The traditional/proprietary approach is to convince investors to give you money early on to cover costs, then once the drug has shown to work (after many steps I’m skipping over), you can patent it and then lease or sell that patent to generate a return. Usually a “composition of matter” patent is used which covers the novel chemical structure of the therapeutic agent itself¹. In exchange for fully disclosing the chemical structure and method of making it, the patent owner is granted a time-limited, exclusive right to prevent others from exploiting the compound without the maker’s consent. When taking this approach, usually patents are filed as broad as possible, with the goal of excluding competitors from making similar or second-generation compounds, even if they might be better, cheaper, or have fewer side effects. Therefore, usually this approach is done as secretive as possible (not releasing any data) since another competitor could release their “composition of matter” patent with a different compound but targeting the same disease. If your compound and the population you’re trying to target is too similar, well no luck, since you’d be violating their patent and you’d get no monetary return.

With open source, the many ideations of business models to secure enough funding look different, and I’ll outline a few.

Early pioneers

In 2004, Maurer et al. proposed that open source drug discovery could be financially viable through three main mechanisms⁶:

1. Government and charitable grants to support the direct costs of R&D.
2. In-kind contributions from scientists who would participate for non-monetary rewards like academic recognition and professional advancement.
3. Contract research organizations developing discoveries into commercial products through guaranteed purchase contracts (where buyers commit in advance to purchasing a specified quantity of a drug at a predetermined price if it meets criteria). This is similar to how the March of Dimes developed polio vaccines in the 1950s without patents¹⁰.

Importantly, Maurer et al. argued that patents weren’t essential to incentivize drug development if appropriate alternative funding structures were in place such as guaranteed purchase contracts. The use of guaranteed purchase contracts differs from the traditional model where companies rely on patent protection to charge high prices after development. Instead, the guaranteed purchase contract provides upfront certainty about the market size and price.

These theoretical models were soon tested by several pioneering projects. The Synaptic Leap’s Schistosomiasis Project (2006) relied on the first mechanism, securing 450,000 USD in government funding from Australia and the WHO⁷. The project focused on improving an existing off-patent drug for schistosomiasis by synthesizing it as a single enantiomer to help reduce the bitter taste and size of the pill. Using a website and a closed LinkedIn process chemistry group of 2,500 members as platforms for collaboration, this resulted in identifying tartaric acid as the resolving agent to isolate the active single enantiomer. In 2011, they published⁷, ending with the following quote.

Whether completely open-science efforts can provide a complementary — yet disruptive alternative to the traditional process of drug discovery is the next interesting question. That the answer is unclear makes it worth trying.

Woelfle, M et al. Nature Chem 2011

Another early project was The Council for Scientific and Industrial Research Team India Consortium’s Open Source Drug Discovery (2008), starting with an initial grant from the Government of India of ~35 million USD⁸. They targeted tuberculosis as their primary research area, released a website, and started a small molecule repository. This project was one of the first open source initiatives to work across the entire drug discovery process, and while it had 54 molecules in its pipeline (including candidates in lead optimization phases), there’s no clear evidence it progressed any compounds to clinical trials despite plans to do so, and its current operational status is unclear.

Open Source Malaria (2016) worked on antimalarial compound development and started after GSK released data on >13,000 antimalarial compounds into the public domain¹¹. Using direct public/philanthropic funding for core activities and benefiting from in-kind contributions from academic labs and industry partners such as crowd sourcing synthesis experiments in university classes, this project pursued two synthesis avenues but yielded no biologically active compounds with many activity cliffs. An all too familiar ending!

Current initiatives

Current open source drug discovery projects have evolved to incorporate more sophisticated approaches to funding and IP protection, learning from earlier initiatives.

M4K Pharma (Meds for Kids) is an initiative (started in 2018 and still active) designed to develop drugs for rare pediatric brain cancers, relying on regulatory exclusivity as its primary IP and commercial asset¹². Regulatory exclusivity is a mechanism that prevents regulatory agencies from approving generic versions of a drug for a set period, effectively creating a market monopoly. For their focus on pediatric brain cancer, they would likely qualify for orphan drug exclusivity, providing additional market protection. Their funding structure is unique: all equity is held by an independent charity (the Agora Open Science Trust), eliminating private profit motives. This has helped them secure funding from public and philanthropic sources, as well as in-kind contributions from industry partners.

While M4K shares research results in the public domain through OpenLab Notebooks, they strategically restrict the use of their data for regulatory approval of competing products, protecting their pathway to regulatory approval while maintaining open science principles. While I couldn’t easily access their OpenLab Notebooks, they do regularly host and post scientific update meetings for anyone to view (https://m4kpharma.com/online-meetings).

The COVID Moonshot project^13–15 started in 2020, which later evolved into ASAP Discovery (https://asapdiscovery.org/) in 2022. This initiative represents what I consider the most prolific and accessible open source drug development initiative to date. Initially launched as a crowdsourced effort between computational, structural, and medicinal chemistry teams across the world to develop a SARS-CoV-2 antiviral^13–15, the project attracted significant attention and resources during the pandemic. Then receiving a 65 million USD grant from the NIH, ASAP Discovery has now just released a pancoronavirus antiviral that is currently at the preclinical stage¹⁶.

Their approach to handling the IP associated with the pancoronavirus antiviral is described in an article by Griffen and Boulet¹, which I highly recommend reading. First the idea was to initially carry out a direct to generic approach (no IP restrictions allowing immediate generic production), but one problem was how to convince manufacturers to produce their compound when anyone could have taken their data and put a patent on it or inappropriately use their data.

They take what they call “minimally defensive patents: a precise, focused patent, that only specifies the exact molecules to be studied clinically”¹. This approach directly addresses this problem by ensuring that they have IP protection on only the exact compounds they want to develop further and hopefully manufacture. Also, any other data can be released to the public allowing others to build on their work, possibly discovering improved compounds.

Other than this minimally defensive patent approach to deliver on their primary goal of “generating new antivirals for pandemic use that will be available globally, affordably and equitably, while being as open as possible with the results of our research as quickly as possible”, they also prioritize adopting FAIR principles with data sharing¹. A public ML benchmarking challenge was even hosted for ligand pose, potency, and ADMET predictions (https://polarishub.io/competitions/asap-discovery/antiviral-drug-discovery-2025#competiton-results).

Recently, there was a completely open release of an Investigational New Drug (IND) (a package of data that a drug developer submits to the FDA to request to dose a human with a new drug for the first time) for a novel treatment for prion disease (https://www.cureffi.org/2025/04/14/open-ind-whats-next/). That is pretty cool considering there were only two public releases of INDs and they’re really complex to put together (the IND itself is 92 PDF documents of varying length and requires years of data to collect).

Lessons learned and the path forward

What began as a theoretical model postulated over 20 years ago⁶ has now been demonstrated through multiple successful initiatives: open source drug development is not only possible but increasingly practical. The evolution from purely open approaches to strategically “minimally defensive” IP strategies show how the field has matured to balance idealistic goals with pragmatic realities.

These projects reveal a consistent pattern. Successful open source drug development requires:

• Substantial funding from public or philanthropic sources.
• Strategic IP protection focused narrowly on enabling manufacturing and distribution.
• Robust platforms for collaboration and data sharing.

Perhaps most importantly, these initiatives are creating tangible solutions for neglected disease areas where traditional pharmaceutical development has fallen short. As funding models continue to evolve and more researchers embrace open science principles, open source approaches are becoming an increasingly important complement to traditional drug development.

References

(1)       Ed J. Griffen; Pascale Boulet. Enabling equitable and affordable access … | Wellcome Open Research. https://wellcomeopenresearch.org/articles/9-374/v1 (accessed 2025-04-16).

(2)       Council on the Economics of Health For All. Governing health innovation for the common good – The WHO Council on the Economics of Health for All – Council Brief No. 1. https://www.who.int/publications/m/item/governing-health-innovation-for-the-common-good (accessed 2025-05-21).

(3)       Årdal, C.; Alstadsæter, A.; Røttingen, J.-A. Common Characteristics of Open Source Software Development and Applicability for Drug Discovery: A Systematic Review. Health Research Policy and Systems 2011, 9 (1), 36. https://doi.org/10.1186/1478-4505-9-36.

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(6)       Maurer, S. M.; Rai, A.; Sali, A. Finding Cures for Tropical Diseases: Is Open Source an Answer? PLoS Med 2004, 1 (3), e56. https://doi.org/10.1371/journal.pmed.0010056.

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