Future of Biotech: Machines controlling biology

Hi there!

It’s release day! Tune in here 🎧.

Today, we dive into biotech’s increasingly successful quest to read and write natures code.

Was this forwarded to you? Subscribe to get the next one in your inbox!

Prolific Machines is the first biotech company to harness light to manipulate cells. Developing a breakthrough approach to efficiently produce lab grown food, life saving drugs, and novel biosolutions. It has opened the door to machine and AI controlled cell interface and a new chapter of accelerating biotech progress.

Prolific Machines CEO Dr Deniz Kent envisions a biotech renaissance fueled by merging advances in biology and AI. Through rapid cycles of software-driven innovation and light-based bioreactors, Prolific is setting the stage for a more efficient, scalable, and accessible approach to harnessing the fundamental elements of life.

My 5 Year Outlook:

• A Programming Language To Read/Write Biology

  Machines and software will be able to control cells.

• Virtual Cells Becomes The Next Human Genome Project

  Simulating a cell in software will be biology’s next moonshot.

• Pharmaceutical Industry Produces Everyday Commodities

  From high value high cost to mass produced goods.

Curious? Read on as I unpack each below 👇🏼

A Programming Language To Read/Write Biology

Today, scientists design experiments and manipulate cells using chemicals—a lengthy, imperfect process, reflected by the 90% failure rate for drugs in clinical trials. AI has accelerated drug discovery, but a missing link has been the ability for software to directly interface with cells. A language between machines and cells can shift research from being scientist-led to machine-driven, enabling rapid, iterative testing and a higher success rate of new drugs to market.

Prolific Machines’ breakthrough is using light, rather than chemicals, as an input to guide cellular behavior. Light is easily manipulated by machines, making it ideal for efficient, cost-effective experimentation. In a bioreactor, sensors monitor cellular changes, providing real-time feedback to the software. This creates a powerful feedback loop that iterates until the desired outcome in the cell is achieved.

This innovation transforms scientists from hands-on experimenters to architects, directing changes they want to see while machines handle the tests.

The implications of a machine-to-cell language are transformative. With machines driving experimentation, biotech development could become exponentially faster, more precise, and less costly. Drugs, treatments, and even lab-grown foods could reach consumers far more quickly, responding to demand with the agility of software updates. This shift could democratize biotech, making advanced treatments and products accessible to more people while reducing reliance on human labor for high-stakes testing. Ultimately, this innovation sets the foundation for a future where biological research adapts in real time to new insights, needs, and discoveries.

🎧 Listen to our discussion

Virtual Cells Becomes The Next Human Genome Project

Although scientists now have tools to control cells, they don’t fully understand how cells work on a fundamental level—they’re still largely a “black box.” Deniz points out that knowing every detail isn’t always necessary however. If we can make a cell behave as needed, we can create useful products without fully understanding every mechanism.

Yet, if we could digitally map the cell and understand its workings then it would revolutionize science. The Human Genome Project mapped DNA and unlocked CRISPR and genetic therapies, showing us that decoding biological blueprints leads to scientific leaps.

A digital representation of a cell would allow scientists to run experiments entirely in software, skipping expensive lab procedures and dramatically advance the research process. Imagine testing cancer treatments or anti-aging solutions on virtual cells, running countless high-speed experiments 24/7 instead of lab researchers painstaking lab work over months or years. Overcoming the current intractable questions in biology would just be a matter of time and compute power. This approach would make complex biology scalable and fast, allowing biotech breakthroughs to happen at the speed of software development.

A global effort to create this virtual cell map could transform biotech, putting life-altering discoveries within reach faster than ever imagined.

Pharmaceutical Industry Produces Everyday Commodities

Advances in cell science and production efficiency are reshaping the possibilities for biologically-produced products beyond today’s complex, high-cost pharmaceuticals. According to Deniz, the industry is moving toward a future where biotech and pharmaceutical companies produce a broader array of low-cost, everyday items. This shift is happening because designing and manufacturing these products is becoming faster, cheaper, and more efficient.

A prominent example is lab-grown food. Alternative proteins, meat, eggs, and milk have already been produced, yet current versions remain costly and prone to variability, which limits their viability for large-scale, reliable production. Precision-guided light bioreactors and machine learning could steadily improve consistency, transforming these products into accessible options for consumers. This could eventually allow pharmaceutical companies to venture further into the food industry, producing an increasingly large share of food products.

Similarly, this approach extends to other areas, such as livestock feed, agricultural inputs, biofuels, and biological plastics. We discussed this trend in greater depth on episode 5YF#24 with Synonym and the arrival of the $4T bioeconomy (listen to the episode).

The biotech and pharmaceutical sectors are experiencing rapid change, expanding from high-cost, illness-focused drugs to wellness-enhancing products for everyone—Ozempic and GLP-1 drugs are prime examples of this shift. Could expanding markets and product lines position biotech and pharma companies at the center of economic production? With the rapid trajectory of scientific innovation, this outcome seems more possible than ever.

Keep exploring!