Visual technologies empower and disrupt the scientific process in life sciences, biotech, advanced materials, and beyond. These transformations are poised to have a profound impact on both business and society at large.

We invest in people building businesses powered by visual technology and AI. This thesis has not changed since the founding of LDV Capital in 2012. On March 21, we will celebrate our 10th LDV Vision Summit Anniversary! It’s a premier global gathering for people in the visual tech sector. Every year we bring together an impressive array of brilliant speakers, ranging from tech giants to under-the-radar startups, esteemed research labs and leading venture capital firms.

**Dr. Molly Gibson, Co-Founder and Chief Strategy and Innovation Officer at Generate:Biomedicines**

We are thrilled to announce the fireside chat between LDV Capital’s Evan Nisselson and Dr. Molly Gibson, Co-Founder and Chief Strategy and Innovation Officer at Generate Biomedicines, a new kind of therapeutics company existing at the intersection of biology, machine learning, and biological engineering. The company is dedicated to revolutionizing drug discovery within the protein therapeutics space. Rather than relying on traditional approaches that involve discovering new molecules through natural processes and evolution, they employ algorithms to understand the rules governing proteins and their functionality. This allows the team to generate entirely novel molecules tailored to specific requirements, paving the way for the creation of more effective, cost-efficient, and safer drugs.

In the lead-up to the Summit, Evan had the privilege of asking Dr. Gibson a few questions.

Evan: You started your career as a software engineer at Boeing. What inspired you to transition to computational biology, biotech & life sciences?

Molly: I’ve always been passionate about engineering, math and learning how things work. I am formally trained as a computer scientist, and I love how logic and math underpin everything about how we interact with computational systems.

I began my career as a software engineer building flight simulators for the F-15 at Boeing. I was constantly tasked with new challenges on how to simulate the feeling of flying as close to reality as possible. In many ways, it was magical, in other ways, I felt like I was missing the chance to make an impact.

I was constantly thinking back to my biology classes in grad school and realizing how just like computers, math and statistics underly almost every biological process – and if that’s true, we could apply the same type of engineering principles I was trained to do not only to airplanes, but to living cells and biology too.

I pursued a Ph.D. in Computational & Systems Biology at Wash U in Saint Louis, where my passion for innovating at the intersection of biology and machine learning began. I soon joined the venture creation team at Flagship Pioneering in Cambridge - the firm that founded Moderna - to found and grow new biotechnology companies. While there, I co-founded Generate:Biomedicines in 2018 to bring the revolution of Generative AI (the technology that underpins things like ChatGPT and DALL-E) to bear on some of the most long-standing and pressing challenges in drug discovery and development.

Evan: What aspects of drug discovery within the protein therapeutics space drew your interest?

Molly: I believe AI has the power to change the world for good and I’m most passionate about building companies that have the potential to disrupt entire industries and ultimately solve some of humanity's most pressing problems, including climate change and affordable healthcare.

When we started exploring some of the challenges we faced in harnessing nature’s molecular machines - or proteins - to the benefit of humans, we realized that the function of a protein must be encoded directly in the one-dimensional amino acid sequence - and this relationship between sequence and function should be learnable with enough data. If you could do this, you could not only replace some of the brittle and time-consuming steps of protein drug development, but you could find therapeutics you potentially couldn’t find through empirical methods alone. It was this belief that both the challenge was ripe for disruption combined with the outsized potential for impact that drew me to this space.

Evan: At Flagship Pioneering, you operate as part of a venture-creation team to found and grow companies at the intersection of biology and machine learning including Generate:Biomedicines, Tessera Therapeutics, and Cobalt Biomedicines (merged into Sana Biotechnology). What visual tech opportunities that relate to your fields of interest are you most excited about right now?

Molly: As you can see, a theme throughout my career has been the influence of AI in the life sciences and to date there have been many applications where we are applying AI to visual image processing. One of the most prominent areas where this has happened is the ability to learn deep phenotypic data about cellular states, just by looking at the cells. We’ve seen that a visual approach can learn as much about the state of a cell as a deep molecular analysis - and much faster and cheaper. With the aid of AI, I believe we will start to see visual approaches extend beyond cellular phenotyping into other molecular settings as well as into the physical lab environment itself.

Molly is speaking with one of her fellow co-founders at Generate:Biomedicines, Gevorg Grigoryan.

Evan: You mentioned on our last call that you are excited about the opportunity for AI to transform the scientific method. We will speak more about this during our fireside chat at our Summit. How would you explain your excitement in one sentence?

Molly: We are at a one-in-a-lifetime opportunity to define how recent advancements in AI will not only augment science but re-think how we do science altogether and dramatically enhance every scientist and entrepreneur to unprecedented levels of creativity and efficiency.

Evan: Over the next 10 years - how do you see innovation within the biotech and material sciences landscape evolving, specifically related to visual tech? Where do you see opportunities that are leapfrog solutions?

Molly: The ability to process and analyze data at increasingly raw levels will be essential to getting the most out of advancements in AI - and much of raw data can be perceived in the form of images. As we take increasingly unbiased approaches to analyzing this data, we will begin to uncover patterns in scientific discoveries that we are unable to see today.

In addition, I see visual tech enhancing and transforming the way science is performed in the lab. The more we have the potential to see how science is done on a quantitative level, the more we will be able to optimize it in new ways.

Evan: What are you most looking forward to at our 10th Annual LDV Vision Summit?

Molly: Visual tech is essential to how we think about the intersection of science and machine learning, I’m excited to be a part of an event that is deeply at that intersection and to learn from others who are pushing the boundaries of what’s possible.

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