Innovate Following Nature’s Lead: How Would Nature Solve This Problem?

A Dive Into Principle 11 of “Modernising the 12 Principles of Green Chemistry: It’s Time”

In the recent RSC Perspective, ‘Modernizing the 12 Principles of Green Chemistry: It’s Time’, Lipshutz and Handa propose a thoughtful update to the principles first published by Anastas and Warner in 1998. Their newly added Principle 11 – Innovate Following Nature’s Lead – is both a provocation and a challenge to the trajectory of modern medicine, and an important step towards nature-inspired green chemistry.

It asks a deceptively simple question: not only “Can we make it?” but rather “How would Nature make it?”. Yet embedded within that question lies a deeper critique of how chemical knowledge is generated, curated, and accessed by the scientists responsible for turning ideas into practical processes.

Nature as a Benchmark

At its core, Principle 11 reframes Nature not merely as a source of inspiration, but as the benchmark. Biological systems have conducted chemistry for millions of years, typically in water, at ambient conditions, and with exquisite selectivity.

In contrast, synthetic chemistry, remarkably successful though it is, has largely evolved over only a few centuries.  However, it remains heavily reliant on organic solvents, energy-intensive conditions, and often linear, waste-generating processes. Lipshutz and Handa propose that closing this gap is essential if green chemistry is to become the default rather than the exception.

The principle asks chemists to consider biological strategies earlier and more systematically. Could a transformation be achieved through biocatalysis? Could several steps be combined into a cascade? Could selectivity be controlled through molecular recognition, compartmentalisation or self-assembly? Could a biological or biomimetic route reveal a fundamentally different way of approaching the target? Nature-inspired methods should still be tested against appropriate process and sustainability metrics, but they should form part of the initial design space, rather than being introduced only after conventional approaches have fallen short.

Progress Without Normalisation 

Landmark examples of nature-inspired bio-transformations superseding a first-generation chemical synthesis have emerged over recent decades and demonstrate what this shift can achieve. Notably, in Merck and Codexis’ revised route to Sitagliptin,  an asymmetric hydrogenation step was replaced with an enzymatic reduction amination. The process demonstrated that enzyme engineering could deliver the selectivity, productivity, and robustness required for large-scale pharmaceutical manufacture.

In conjunction with high-profile academic research in the enzyme-engineering field, such breakthroughs ignited a sector-wide awareness of biocatalysis and helped move it into mainstream process development conversations. Although still commonly treated as a specialist discipline, 60% of small molecule drugs now incorporate biocatalytic steps in their synthetic pathway, injecting hope that paradigm shifts in pharmaceutical process design strategies are achievable.

Despite how monumental this progress feels, the uptake of nature-led initiatives has been incremental to date. Adoption of biocataylsis is only a small step in the journey, and the industry is yet to see the big leap required for nature-inspired manufacturing processes to be designed as routine. Achieving this shift across all areas of process design is not simply a matter of scientific ingenuity; it requires confronting structural biases embedded in how chemists’ access and interpret knowledge.

The Database Problem: Chemistry Searches Chemistry

Modern literature databases—whether discipline-specific repositories or general indexing platforms—are powerful, but they are not neutral. Their architectures reinforce disciplinary silos. A chemist searching for a synthetic transformation is overwhelmingly directed toward prior chemical literature: named reactions, catalytic systems, or incremental optimisations of existing methodologies. Biological literature, even when highly relevant, is often underrepresented in search results unless explicitly targeted.

This creates a feedback loop. Because chemists cite chemists, databases and AI prioritise chemical precedent; because databases prioritise chemical precedent, chemists continue to search within that domain. The result is a form of intellectual path dependence, in which solutions are repeatedly sought within the same conceptual space that created the original problem, even when an alternative biological strategy may exist.

This is particularly limiting when considering Nature-inspired solutions. Enzymatic cascades, metabolic pathways, and compartmentalised reaction environments—hallmarks of biological chemistry—are often described in biochemical journals, using terminology that differs from synthetic chemistry conventions. Without deliberate cross-disciplinary querying, potentially valuable insights can remain effectively invisible.

Principle 11 therefore implicitly challenges this infrastructure. If chemists are to ask, “how would Nature solve this problem”, then databases must enable that question to be answered. This could involve stronger cross-indexing between chemistry and biology, semantic search tools capable of recognising functional analogies rather than relying on disciplinary keywords, and curated interfaces that highlight bioinspired strategies alongside traditional synthetic routes.

Yet infrastructure alone will not suffice.

The Mindset Problem: Defaulting to Synthetic Orthodoxy

Even with perfect databases, chemists must be willing and equipped to look beyond their own familiar frameworks. The discipline has long been trained to approach synthesis through a specific lens: retrosynthetic analysis, reagent selection, and optimisation of yield and selectivity under controlled conditions. These are powerful tools, but they have also become culturally entrenched defaults.

When faced with a synthetic challenge, most chemists instinctively search for chemical solutions: new catalysts, alternative solvents, or modified reaction conditions. The possibility that the problem might be reframed in biological terms, for example, solved via an enzyme, a cascade, or a self-assembled system, is often considered only secondarily, if at all.

Part of the issue is perception by the bench-scientists. Nature-based approaches are still frequently regarded as specialist domains rather than mainstream tools, and despite significant advances they are often still seen as requiring niche expertise, bespoke infrastructure, or having limited substrate scope. Although the scope and accessibility of these technologies have advanced considerably, those perceptions can still exist. This creates both a practical and psychological barrier. If Nature-inspired methods are viewed as exceptional rather than routine, they are unlikely to be considered at the outset of problem-solving, precisely where Principle 11 demands they be placed.

Responsibility for changing this mindset does not sit solely with the scientists working at the bench. There is also opportunity for greater participation by the academic researching community, where proportionally very few synthetic chemists seek to explore biological systems from a chemistry perspective. In important fields, such as prebiotic chemistry, biomimetics and synthetic biology, synthetic chemists are underrepresented. If we are to truly mimic Nature and learn from its example, the chemistry community must more heavily prioritise the funding and execution of de novo research into some of Nature’s cornerstone chemical pathways. Why else would a routine method of making amide bonds with enzymes still illude the synthetic chemist when Nature does it so elegantly and effortlessly?

Toward Convergence: Infrastructure Meets Culture

The promise of “following Nature’s lead” depends on the convergence of two transformations: one technical, one cultural.

On the technical side, literature ecosystems must evolve. Databases should not merely catalogue knowledge but actively connect it across disciplinary boundaries. Imagine a search for a C–C bond formation that surfaces not only cross-coupling reactions but also enzymatic carbon–carbon ligases, metabolic pathways, and biomimetic strategies. Such integration would normalise the presence of biological solutions within chemical workflows.

On the cultural side, education and training must shift. Green chemistry is already described as both a methodology and a mindset, and Principle 11 extends this by demanding intellectual flexibility. Students and practitioners should be encouraged to think in terms of systems, environments, and function rather than solely reagents and conditions. Asking “how does Nature do this?” should become as habitual as drawing a retrosynthetic arrow.

Crucially, these changes are mutually reinforcing. Better databases make it easier to adopt a broader mindset; a broader mindset increases demand for better databases.

An Upbeat Outlook: Rediscovering Chemistry Through Nature

There is good reason for optimism. The tools needed to realise Principle 11 are already emerging, with advances in bioinformatics and machine learning–driven literature mining enabling proficient data extraction from multiple complex databases.

One example is BioNavi-NP, a bio-retrosynthesis prediction tool, published in Nature Communications. Trained using both general organic and biochemical reactions, the BioNavi-NP model was shown to predict the biosynthetic pathways of natural products. Using such computer-aided models to construct a conceptual bio-retrosynthesis for any target API, even non-natural structures, surely could be the big leap that the pharmaceutical industry needs to be truly nature-led.

What remains is alignment. The chemical industry must recognise that Nature is not an alternative approach; it is the original chemist. By integrating its lessons into both our information systems and our intellectual habits, we can move toward a form of chemistry that is not only more sustainable, but also more elegant and efficient.

Principle 11 is therefore more than a simple addition to the list. It is a call to reorient the discipline: to look beyond familiar precedent, to question inherited practices, and to rediscover innovation in the oldest laboratory of all.