Ethical Technology

"Patents save lives": what open-source biology proves otherwise

AlphaFold made 200 million protein structures freely accessible within months. 100,000 researchers work in the open on the diseases that kill the poorest. Here is how open-source biology is reinventing who benefits from science.

Published on 9 min de lecture

“Patents save lives”: what open-source biology proves otherwise

TL;DR: The classic argument is well rehearsed: without patents, laboratories would have no reason to invest in research. The result: the diseases that kill millions of people in the world’s poorest countries go untreated, because there is no solvent market. Open-source biology offers a different answer — publish the data, share the tools, decouple research costs from drug prices. AlphaFold has released 200 million protein structures for universal access. Teams from 400 universities are building solutions with no intellectual-property protection. And India’s OSDD identified therapeutic targets against tuberculosis at low cost, in a field where industry saw no market. This is not utopia — it is already in production.

There is a paradox at the heart of modern pharmacology: the diseases that kill the most people in the world are precisely those for which the fewest medicines are developed.

Tuberculosis still kills more than one million people per year. Leishmaniasis affects millions of people in low-income countries. So does Chagas disease. These conditions have not disappeared from biochemistry textbooks — they have simply disappeared from the development pipelines of major firms, because their victims do not constitute a profitable market.

This is not a critique of researchers’ ill will. It is the logical result of a research-funding model built on patents: investing heavily in R&D only makes sense if you can recoup that investment through sales. No market, no research.

The question then is: does a different model exist?

India tried it — and it worked

In 2008, India’s Council of Scientific and Industrial Research (CSIR) launched Open Source Drug Discovery (OSDD) — a programme of collaborative, open research against tuberculosis. The idea was simple and radical: apply to drug discovery the two founding principles of free software — collaboration and open access.

In a 2012 article in PLOS Neglected Tropical Diseases, researchers Christine Årdal and John-Arne Røttingen documented what this approach produces: high-quality research at low cost. The success factors identified? Clearly defined entry points, full data transparency, and funding that covers essential material costs — nothing more.

More importantly, this model decouples the cost of research from the price of the final drug. In the proprietary model, companies embed their R&D expenditure in the selling price — which explains treatments that can cost tens of thousands of dollars. In an open-source model, research is funded separately (by governments, foundations, academic institutions), and the results belong to everyone. The OSDD team identified more than 60 potential therapeutic targets against tuberculosis — data that any laboratory in the world can use.

The honest caveat: OSDD has not yet produced a commercialised drug. Identifying targets is the first step — clinical trials remain costly and slow regardless of the model. What OSDD proved is that the upstream discovery phase can work in open-source, at lower cost, on neglected diseases.

AlphaFold: when AI becomes public infrastructure

Understanding how a protein folds in three-dimensional space is one of the fundamental keys of molecular biology — and one of the hardest problems in science. For decades, determining the structure of a single protein could take months or years of laboratory work.

In 2022, Google DeepMind and the European Bioinformatics Institute (EMBL-EBI) published something unprecedented: a database of 200 million protein structures predicted by AlphaFold, covering virtually every catalogued protein known to science. Universal access. Free. For everyone.

The impact was immediate: within less than a year, more than 500,000 researchers in 190 countries had accessed the database. As the DeepMind blog notes, this openness accelerated research on problems as varied as antibiotic resistance and plastic pollution. Eric Topol, founder and director of the Scripps Research Translational Institute, described the tool as “a singular and momentous advance in life sciences.”

But the passage that interests Bloomii most is this: DeepMind explicitly partnered with the Drugs for Neglected Diseases initiative (DNDi) to advance research on leishmaniasis and Chagas disease — precisely the diseases for which industry saw no market. Open infrastructure is here a direct lever for neglected diseases.

This is not a coincidence. When data are open, the direction of research is no longer entirely dictated by patients’ ability to pay.

iGEM: training the generation that thinks open-source by default

Every year since 2003, student teams from around the world have gathered in Boston for the International Genetically Engineered Machine (iGEM) — a synthetic biology competition whose founding principle is openness: projects are public, results shared, standardised “biological parts” deposited in a common registry.

In 2025, the iGEM community brings together more than 100,000 members, with 400+ teams competing. But the most important thing is not the numbers — it is the culture iGEM forges. Thousands of young biologists learn that science can function like free software, where every contribution enriches a common good rather than feeding a patent portfolio.

iGEM teams’ projects often cover topics that would have no appeal to classical pharmaceutical industry: biosensors to detect contaminants in rural water supplies, bacteria engineered to decontaminate soils, theoretical vaccines against orphan diseases. No obvious market — plenty of social potential.

The model also trains a way of working: radical transparency, public iteration, exhaustive documentation. Principles that, if exported into academic and industrial research, fundamentally change who controls scientific results.

Precision fermentation: open biology comes to the table

Some developments in open biology touch on still more tangible questions: how to feed ten billion people with a smaller planetary footprint?

Precision fermentation is one answer currently being developed. American company Perfect Day produces whey proteins identical to those in milk — but without cows, through fermentation using genetically modified fungi. A life-cycle assessment certified to ISO 14067 standard and verified by independent experts established that this process generates 91 to 97% fewer greenhouse gas emissions than conventional dairy whey, with 96 to 99% less water.

An essential caveat: the calculation is based on the US electricity mix, which is predominantly fossil-fuelled. With decarbonised energy, the balance would be even more favourable — and conversely, the real benefits depend on the local energy context.

What precision fermentation illustrates is the power of combining scientific openness (the genomic databases on which this work draws are largely public) with advanced biological tools. The critical question for what comes next: that these technologies remain accessible to the countries that need them most, and do not reproduce the access inequalities of the classical pharmaceutical model.

What open-source cannot do alone

It is necessary to name this model’s limits — they are real.

Open-source does not make costs disappear. Identifying a therapeutic target is one step among a dozen before a drug reaches a pharmacy. Phase 3 clinical trials cost hundreds of millions of dollars regardless of the model. OSDD proved that the discovery phase can be pooled — not that the entire development pipeline can be run at zero budget.

Open-source does not solve the manufacturing problem. Even if AlphaFold makes protein structures accessible, the equipment, reagents, and sequencing technologies remain concentrated in wealthy-country laboratories. The gap between production and access is not bridged by data-sharing alone.

Open-source does not pay salaries. Researchers working on these projects need funding — often public (governments, universities, philanthropic foundations). This model depends on a political will to fund research as a common good, not as an investment with private returns.

What these limits point to is not a failure of the open model — it is an invitation to complete the picture: strong public funding of upstream phases, mandatory result-sharing mechanisms, compulsory licensing policies for essential medicines.

Biology as a commons

What connects iGEM, OSDD, AlphaFold, and precision fermentation is not a particular technology. It is a posture: biological knowledge as a common good, not as a proprietary asset.

This paradigm already exists in other sciences: mathematics, theoretical physics, and astronomy have always operated on open sharing of results. Biology, contaminated by the pharmaceutical model of the 1980s, drifted toward privatisation. Open-source biology is an attempt to correct that trajectory.

It does not propose eliminating private research — it proposes that research on neglected diseases, fundamental biological tools, and sustainable food solutions should not be confiscated by the sole criterion of short-term profitability.

The 500,000 researchers who use AlphaFold for free, the 100,000 members of the iGEM community, the Indian teams mapping tuberculosis with no patent on the horizon — they are already drawing this other biology. It is not complete. It is not without friction. But it exists, and it produces results.

What you can do

Open-source biology is not reserved for researchers in white coats.

  • Follow and support iGEM if you are a teacher, student, or simply curious: igem.org. Teams’ projects are public — reading their work is itself an act of support for this model.
  • Use iNaturalist if you are interested in biodiversity: with nearly 300 million observations contributed by 4.3 million users, it is one of the world’s largest open-source naturalist databases, feeding more than 4,000 research papers. Your observation of an insect in your garden contributes to science.
  • Engage your elected representatives on compulsory licensing for essential medicines and public funding of research on neglected diseases. This is not a technical question — it is a question of collective priorities.

The next breakthrough against a disease killing millions of people could come from an Indian university laboratory, from a freely accessible database, or from a student team that had no patent to protect.

That would be something.

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