How AI-powered innovation can democratize breakthrough science

It’s been four years since Google’s DeepMind effectively solved the biggest problem known to biology with AlphaFold, a prediction model for protein folding. For those of us surfing the edge of artificial intelligence (AI) and proteins, these years since have felt like the floodgates burst open. I now can't open my email without a rush of new approaches, discoveries and companies built on AlphaFold's open-source code.

This breakthrough – the ability to predict how nature’s most complex molecules fold – is a critical step towards predicting their function. The road to unlocking biology as a plug-and-play module for everything from therapeutics to bioindustrial enzymes, ingredients and materials science has never been this clear.

With AI-powered approaches now being used to transform the development of new materials across multiple industries, the real revolution occurs through democratized access to these technologies – biotech’s coming 'ChatGPT moment'.

AI compressed the full process – discovery, validation, commercialization – from years to months, upending an ingredients industry that hasn’t changed in generations, if not centuries.

At Shiru, we’re using these tools to identify natural compounds that can replace sugar with unprecedented precision, scale proteins that turn liquid oils solid without chemical modification, discover natural biopesticides with highly specific modes of action so the agriculture industry can stop using harmful chemical pesticides, and have paths to discovering enzymes that could revolutionize everything from textiles to rare earth extraction.

Having disrupted discovery – filing intellectual property (IP) on an exponentially increasing number of natural, high-value protein sequences each year since our founding – we’re now putting the same intensity towards disrupting go-to-market.

Here’s what concerns me: AI generates breakthrough predictions at dizzying speed, but validation and commercialization are stuck in the slow lane. These challenges can be addressed by creating business models that can extract exponential value from these scientific breakthroughs.

Implementation requires something AI can't provide: diverse perspectives, market knowledge and the collective intelligence of an entire industry. With democratized AI tools that even non-computer scientists can use, the barrier to entry for innovation has never been lower.

Society cannot afford to innovate at yesterday's pace or have breakthrough science trapped in proprietary silos: global health systems are straining under the burden of metabolic disease, climate change demands rapid decarbonization of our food systems and fragile supply chains are failing. In an era where global challenges demand urgent solutions, the original model isn't just inefficient. It's irresponsible.

So, how can we create strong, lasting corporate partnerships based on speed and flexibility that can harness this powerful pace of innovation, when traditional R&D partnerships in food and pharma have always operated more like exclusive clubs?

In most cases, the corporate partner funds research, negotiates strong ownership of the developed IP and controls market access. Smaller players, despite their agility and market insights, are frequently locked out of this innovation ecosystem due to the high cost of entry associated with accessing breakthrough technologies.

This might have made sense when discovery was expensive and slow, but with the rapid pace of discoveries in the materials sector, this needs to be completely re-envisioned.

At Shiru, we’re actively disrupting the go-to-market path for our intellectual property by doing things differently: lowering the price tag to engage, building consortia of partners rather than restricting ourselves to exclusive relationships, and reducing the friction that’s created by veils of confidentiality when it’s not even necessary. This means everyone gets access to the same AI platform, the same discoveries and the same opportunity to shape the future.

Here's the thing: how you commercialize matters as much as (if not more than) the discoveries themselves.

Without a sincere focus on how to disrupt the go-to-market path, the ability for AI to drive massive change in these applications will be limited. Traditional IP models create scarcity when we need abundance.

This approach mirrors what's happening across AI-driven industries. Just as language models become more powerful through diverse training data, ingredient discovery accelerates through diverse application insights. The future belongs to platforms that harness collective intelligence, not those that hoard it.

To my fellow innovators, investors, and industry leaders, the question isn't whether AI will transform your sector. It's whether your open thinking and proactivity will help increase access to transformative innovations, or your organization will watch from the sidelines.

The most successful companies of the next decade won't necessarily be those with the best technology, but those who build the best innovation ecosystems.

For startups: Don't assume you need millions in funding to access cutting-edge discovery platforms. Look for open innovation models that value your market insights as much as your capital.

For established companies: Your competitive advantage isn't in hoarding innovation. It's in being the partner of choice in open ecosystems. Share your expertise and watch it multiply.

For investors: Fund platforms, be patient as the industries you’re betting on are transformed, and your bets will pay dividends. The highest returns will come from technologies that enable entire industries to innovate faster.

At Shiru, we've highlighted how you can compress what has traditionally taken decades of research into months of high-paced, intentional discovery. But the real acceleration comes from opening these capabilities to solutions-based thinkers in leading organizations.

When a startup in Singapore can access the same protein discovery platform as a multinational in Switzerland, innovation becomes truly exponential.

The technology exists. The challenges are urgent. The only question is whether those building will have the courage to share the tools that can solve them. In this new age where AI drives the pace of innovation, democratizing discovery isn't just an ethical choice; it's the only choice that makes economic sense.

Join us in building an innovation ecosystem that matches the scale of our challenges. Because the future of food, materials and human health is too important to leave to the few when it could be shaped by the many.