In the high-stakes, often homogenous world of biotech venture creation, Dr. Molly Gibson’s origin story defies the typical Silicon Valley archetype.
For the co-founder of Generate:Biomedicines, the journey to tech unicorn was a one defined not by a predetermined plan, but by a relentless pursuit of the most interesting problem in the room.
From building flight simulators in the Midwest to pioneering generative AI for medicine, her story is a masterclass in intellectual agility, resilience, and the transformative power of an outsider’s perspective.
From Rural Iowa to Academia
Dr. Gibson grew up in a remote area in central Iowa – far from any entrepreneurial influences. Even when she left for college, it wasn’t a place that pushed a founder culture. But the startup world was still far from her mind.
“It is a theme throughout my career: doing the most interesting thing at any moment in time,” she told LDV Capital, adding she had no strict direction she was headed. “I was exploring and trying to figure out what I wanted to do.”
But one subject eventually stood out to her while taking biology: computer science. She loved “the idea that you could teach a computer to think.”
With a new goal, she began pursuing the subject, even working with Boeing as a software engineer – building flight simulators for the F-15. She thought it would be the ideal setting for her, offering challenging and engaging puzzles of physics and code. But a deeper dissatisfaction simmered.
“I realized that it wasn't fulfilling some of the things that I wanted the most in my career,” she went on to explain to LDV. “One, applying my expertise to solving the most important problems that humans face today. And two, the creativity around how computers solve challenges that aren't straightforward.”
She began to reflect back on what else had caught her attention, and reminisced about discovering the inner-working of biology. It was there she saw a challenge that was worth pursuing.
She pivoted as she entered her Ph.D. program in computational and systems biology at Washington University in St. Louis, where she focused on the human microbiome – and a future that would catch up to her ideas.
“During my postdoctoral studies, I noticed many scientists could look at a protein structure and accurately reason about what it would and wouldn’t do, and whether a design would work or not,” she told Decoding Bio. “I posed a thought exercise: if a new structure walks in the door, and you have seen nothing similar to it before, how would you design a sequence for it using data-driven methods?”
But she soon realized these questions were too ahead of their time and it would come down to waiting a few decades or finding a unique approach. “This led me to explore whether we could use data-driven and statistical methods to develop such mastery much faster,” she went on to say.
She also found that her ideas went over the heads of those leading the very labs she wanted to experiment in. But she was determined to find a way to bring these theories to fruition.
This when she knew she needed to get into the ecosystem where building was the mission. So she ended up doing something she never thought she’d do: she left academia.
Finding the Right Prolem
Despite no experience in the business sector, it would end up being an advantage, running on pure curiosity without the established restrictions slowing her creativity.
Dr. Gibson’s entry into biotech was strategic and network-driven. She joined Kaleido Biosciences, a microbiome-focused startup, to lead computational biology. More importantly, it connected her to the venture creation engine that would become her home: Flagship Pioneering.
In 2017, she joined Flagship as a principal, part of an internal team tasked with originating and growing companies at the bleeding edge of science. Unlike a traditional venture capital firm, Flagship’s model operates as a studio, using its pooled scientific and entrepreneurial talent to conceive and launch companies from scratch.
Here, Gibson learned the discipline of entrepreneurial science. She contributed to the launch of Tessera Therapeutics and Cobalt Biomedicals (later part of Sana Biotechnology), honing her sense of what makes a transformative company.
Throughout her life, she was always in a fast-paced mindset, looking to solve problems now. But now she was forced to learn a critical founder skill: strategic patience.
Waiting for the right problem to present itself, she found her through a colleague’s frustration over the taxing process of engineering a specific protein. The traditional method, directed evolution, was painfully slow, but it offered her new insights.
She learned that if you could computationally understand the relationship between a DNA sequence and a protein’s function, you could bypass evolution altogether. You could generate the perfect protein from first principles.
Pioneering the Unnamed Frontier
In 2018, this insight became Generate:Biomedicines, which was conceived before its time. At this point, the term ‘generative AI' didn't even exist.
The premise was to use machine learning not to analyze biological data, but to learn the fundamental language of proteins from millions of examples, and then to write entirely new, therapeutic proteins that nature had never seen. The skepticism was profound.
“Most of the industry did not believe this was going to happen when we started,” Dr. Gibson recalled to LDV. One potential partner even “laughed me out of the room.”
It was when she found Flagship, that the startup found a partner willing to take a leap of faith.
Gibson and her co-founders pressed on, defining a new field they called “Generative Biology.” The early proof-of-concept focused on green fluorescent protein (GFP), their models generated novel sequences that produced proteins 50 times brighter than any known in nature.
The COVID-19 pandemic provided real-world validation at break-neck speed. Targeting the SARS-CoV-2 spike protein in early 2020, the Generate platform designed hundreds of antibody candidates computationally in minutes. The entire discovery process, from target selection to identifying potent binders, took just 17 days.
But for Gibson, the platform’s true success is its potential to democratize medicine. AI is making drug development faster and cheaper, could that also mean it will address a broader reach of patients. She believes this success demonstrates how we start to chip away at the failure rate for new drugs.
“I’m really excited about the opportunity for AI to change the economic equation for drug development,” Dr. Gibson told Mckinsey. “We should see a complete change in priorities. We’ll be able to pursue different types of patient populations: those in developing countries or places where clinical trials are higher risk or cost more.”
“You have more shots on goal, and you can do new and novel things that just haven’t been possible with models in the past.”
Even as Generate advances, Gibson’s builder’s mind is exploring adjacent frontiers. At Flagship, she is now applying the lessons of generative AI to the monumental challenge of climate change, asking if similar platforms can design novel materials for carbon capture or energy storage.
From the flight simulators of Boeing to the genesis of a new scientific paradigm, Molly Gibson’s journey underscores a powerful truth: groundbreaking innovation often comes from those who are not bound by the established paths of a field. It is fueled by the curiosity to ask “what if,” the resilience to endure the laughter of skeptics, and the builder’s conviction to make the answer real. She didn’t just join the AI biotech revolution; with a generative mind, she helped write its first rules.
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