Development of new medicines is the ultimate knowledge work. A new medicine is often the culmination of decades of work, hundreds of scientists, dozens of disciplines, and ultimately one hypothesis to improve the lives of patients. It is hard to tell if it is in spite of, or because of, this complexity that data and knowledge management is a significant challenge for the industry.

We’ve previously written about our excitement for the future of this industry, a data-driven revolution, and much of our excitement stems from new technologies to interrogate biological systems and an emergence of powerful new therapeutic modalities. We are not alone in our belief that advances in high-throughput chemistry and biology are driving a reimagining of the discovery process through the lens of computation and modern technology stacks. Early research and discovery represents an important yet limited subset of the complex activities that are required to bring a drug to market. The further a drug program moves through the drug development process–from early discovery to clinical trials and beyond–the more the program is de-risked and value is created. However, a majority of activities and investments into technology innovation in the pharmaceutical industry have focused on the earlier, discovery-oriented phases of drug discovery programs.

All of this work, all of these experiments, all of the hypotheses tested result in a single drug embodiment that hopefully enters clinical trials. The first time a new drug is taken in a first-in-human study is a massive achievement. It’s the culmination of too many hours and dollars to count. And it’s passed the first major regulatory hurdle — the FDA has deemed the drug safe enough to progress into a human study. This first regulatory filing is called the Investigational New Drug (IND) application that the FDA reviews prior to a sponsor having the opportunity to progress the drug into clinical trials, and it is the first of many submissions to the FDA through the lifecycle of a drug. The IND is a thousands-of-pages long document that meticulously summarizes all the information known about that drug candidate that includes detailed scientific data, manufacturing information, and the clinical study plan for the first trials.

It’s an interesting dynamic for companies at this stage. By this point in a drug’s journey, the sponsor has likely filed key IP, and the patent clock is ticking loudly. Yet, given how manual and labor-intensive the effort is, necessitating the collaborative efforts of large, multidisciplinary teams, most companies wait until the very last experimental data comes in before sprinting for months to summarize years of work in a single document. This is inefficient and can create costly errors that result in clinical holds that slows the drug from impacting patient care. Additionally, this critical data and knowledge is often ossified in static regulatory documents, limiting a company’s ability to learn from and leverage this critical information for the rest of the drug’s life as it progresses into clinical trials and eventually (hopefully) as a commercial product.

Enter Weave Bio

Weave Bio wants to enable a different future.

One where scientists weave together a living record of their therapeutic candidates enabled by modern digital technologies and AI. Their first product, AutoIND, is an IND authoring and preparation platform that augments the teams responsible for putting together the IND data package. The product includes a number of helpful features that enable teams to move quickly, collaborate seamlessly, and review and refine robustly. We are not yet in a world where AI can run without intervention and review, but with AI as a robust navigation tool or GPS that facilitates an intuitive workflow, scientists can significantly increase their throughput and spend more of their time on activities that drive meaningful value.

To get this right, Weave built a team that bridges life science, regulatory, AI, and software expertise. They forge new technology paradigms to solve hallucination challenges, to develop methods that link together biomedical concepts, and that faithfully reference the source documents. The leadership team at Weave Bio brings together a wealth of expertise across the life sciences. Ari Caroline (CEO), Umut Eser (CTO), Brandon Rice (CPO), and Lindsay Mateo (CCO) lead the team.

This is just the beginning of the journey for Weave. In essence, we view Weave as building a drug intelligence platform. Instead of these regulatory interactions being point-in-time submissions, each drug should have a living, digital embodiment. By seamlessly integrating all relevant information, that digital record becomes a mechanism for all future regulatory filings, strategic discussions about lifecycle management, and a more seamless mechanism for engaging with regulatory authorities.

This is why we are thrilled to announce our lead investment in Weave Bio, a groundbreaking company that is poised to transform the regulatory reporting landscape in drug development. We are proud to partner with Magnetic Ventures and the entire Weave Bio team on this exciting journey. The road ahead is long, but the potential impact on patient care and the drug development process is immense. If you are involved in drug development and are interested in learning more about Weave Bio’s platform, please reach out to us or the team at Weave.

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Innovation Endeavors was founded on the thesis of the Super Evolution: that a proliferation of data, computational capacity, and advanced engineering would converge and translate into significant, fast changes for the world. We’ve seen this firsthand.

But it’s people who make this era of innovation possible: changemakers working to revolutionize computing infrastructure, engineering biology, climate, intelligent software, and the physical economy. This interview series highlights the stories of the standout founders and entrepreneurs bringing the Super Evolution to life and gives you a firsthand look at what lessons they’ve learned along the way and how they hope to change our world.

We hope their candid insights are helpful for anyone tackling meaningful problems.
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What initially attracted you to entrepreneurship?

As a third culture kid, I’ve always lived at the intersection of different worlds — a sometimes challenging but always exhilarating experience. Looking back, I realize I’ve always chased this feeling that led me to the entrepreneurial journey today.

I chose to major in bioengineering and was often described as a “jack of all trades” because I enjoyed all subjects of science. On top of that, I always knew I wanted to build a career that combines science and business — despite not knowing exactly what this meant. After finishing college, I was fortunate to start my career in a rotational program at Genentech and saw how all the different fields of science come together to make a drug. But I also saw that science alone wasn’t enough to create a drug and run an organization to support it. Eager to learn about the industry's business side, I became a management consultant, where I had to learn a new way of thinking from my training as an engineer. I then pursued an MBA at Harvard Business School, where I was exposed to venture capital, startups, and the entrepreneurial spirit of Kendall Square. After HBS, to the surprise of my peers, I created a role at biotech startup in China because I was obsessed with learning about the biotech ecosystem there. There was plenty of culture shock, to say the least.

With each of these experiences, I got to see a new facet of building a company and inched closer to putting it all together. Whether cultural or technical, I’ve also enjoyed bridging very different ways of thinking. I realized entrepreneurship was the perfect way to operate at the nexus of many different fields.

What inspired you to co-found Think Bioscience?

To be honest, serendipity. During COVID, I was introduced to Jerome Fox, a professor at CU Boulder. Remarkably, it was through six degrees of separation. At the time, I was part of the Harvard Business School Blavatnik Fellowship, a program that supported alumni in life science entrepreneurship. In his academic lab, Jerome was working on an idea he had conceived dating back to his post-doc, an elegant process of letting nature solve our toughest drug design challenges. After all, nature has evolved powerful machinery to access diverse and bioactive molecules to solve its own ecological challenges. The science was innovative, to say the least.

From my internships in VC, I saw how important it was to have the right team to give innovative science the best shot as a life science business. Our backgrounds complemented, and our workstyles matched well — it was the perfect opportunity.

What’s the big problem you’re hoping to solve at Think Bioscience?

We’re working to develop small molecule drugs for challenging targets such as protein tyrosine phosphatases, which have no FDA approved drugs. In short, we solve two major small molecule discovery challenges.

Accessing novel chemical matter. Historical libraries are biased toward historical drug targets and associated active sites. Furthermore, they only cover a small fraction of the bioactive chemical space. And while natural products constitute many FDA-approved small molecules, they were first designed by nature for ecological solutions and can experience synthesis challenges.

Discovering functional binding sites. Proteins are complex. They operate in signaling networks and exhibit dynamic motion. Despite significant advances in computational approaches, identifying novel functional binding sites is incredibly challenging.

Think Bioscience’s platform addresses both challenges by leveraging Nature’s machinery. We encode a therapeutic objective into a microbe and instruct it to “find a way to inhibit this target or die.” The target is expressed in a cellular environment where more complex binding behaviors can be captured (not just simulated). Instead of telling the platform how to solve the problem, we simply define the functional activity desired. In parallel, we endow the population of microbes with unique biosynthetic pathways that encode for natural product scaffolds and let natural selection run its course. Those that survive reveal both a bioactive starting point and a functional pocket to begin new drug discovery campaigns.

What excites you the most about biotechnology?

The combination of intellectual stimulation and greater purpose. It’s a complex and captivating industry that blends cutting-edge science, multi-disciplinary teams, and careful capital allocation. There’s always so much to learn. It’s exciting to work in an industry where the ultimate goal is to help patients, and scientific advancements become the foundation for future work to be built upon. Working daily with people who share these values is icing on the cake.

The biotech space is rapidly accelerating. What breakthroughs do you think will be developed in the next ten years?

Not a scientific breakthrough per se… I’m excited about new company formation models, particularly in new geographic hubs. Using NSF funding as a proxy for scientific innovation, the substrate of innovative science is relatively democratic across the country. Yet, funding is vastly disproportionately allocated to the coasts — for both understandable historical reasons and habitual pattern following. To me, there is an immense opportunity to catalyze these regions with the right teams and capital. I’ve seen this first-hand in the Colorado biotech community. Array Biopharma (acquired by Pfizer in 2019) has created fertile ground for the next generation of startups. Think Bioscience wouldn’t be where we are today without the expertise from ex-Array veterans and the tight-knit biotech community here. From my vantage point, an important rate-limiting step in biotech is coordinating the complex orchestra of science, people, processes, and capital. In the next ten years, I believe more innovation can be industrialized by continued advancements in enabling technologies, flexible work models, founder training, and more evenly distributed investment regions.

Do you have any takeaways from the fundraising process?

If you had asked me prior to Think Bioscience, I would have described fundraising along the lines of a discrete evaluation of a polished deck after a long period of being heads-down. Now, I see it as a more collaborative and continuous process. Conversations with investors have helped us refine our company strategy based on their own portfolio companies’ experiences and network with other investors/pharma. Perhaps even more surprising is how human the process is. There are a lot of calls/messages sharing ideas, questions, and feedback — which works best on a foundation of trust.

Lastly, what piece of advice do you have for entrepreneurs looking to break into engineering biology?

Build a support system for other founders going through the same journey. While there is a lot of written material online, there are still countless details about getting off the ground and operating. I’m incredibly grateful to all the folks who’ve been a great sounding board (and sometimes therapeutic session).

At Innovation Endeavors, we invest in what we call the Super Evolution, which is the idea that breakthroughs in underlying experimental and computational technologies enable rapidly increasing scale, speed, and fidelity of experimentation. We believe this is especially salient in the life sciences where biological systems are non-linear, dynamic, dense, stochastic, and operate on multiple spatial and temporal scales. As we outlined in our prior thinking, we firmly believe that breakthroughs in the life sciences emerge at the intersection of technologies that drive more data, captured in a relevant context, that can be used to build new solutions. Cutting-edge computational methods serve as a foundational enabler to all parts of this flywheel.

Over the past two decades, we’ve witnessed a cambrian explosion of drug modalities. As target discovery tools have improved, it’s become clear that new therapeutic methods to effect function will be required to treat disease. For example, we need new therapeutic methods to 1) enact more durable efficacy in diseases that rapidly find ways to mutate and escape that evolutionary pressure, 2) allow us to more selectively target hyper-specific molecules to enable safer medicines, 3) drive different pharmacodynamics through rational polypharmacology or logic-gated target engagement. While we’re probably still scratching the surface of novel mechanisms for targeting disease, it is clear that creative scientists will continue to find new ways of driving biological effects.

In the more recent past, we’ve seen significant interest in modalities that can drive molecular interactions and selectively traffic molecules to particular locations in the cell. As biology is inherently context-dependent, this is a really interesting premise and demonstrates an emerging drug mechanism. Foundationally, this is the premise of molecular glues, heterobifunctional small molecules like degraders, activators, and the many other targeting chimeras (TACs), as well as constructs like antibody-drug conjugates and a host of additional tools. If we have the ability to selectively traffic molecules together or to specific intracellular compartments, we can drive drug effects in really novel ways.

We get excited when we see new therapeutic modalities being explored that are paired with novel approaches for iteratively testing those constructs in relevant contextual environments at high throughput with high-dimensional readouts. The challenge is that this requires a team capable of thinking through and developing the entire technology stack paired with deeply creative scientists chasing novel biology. When we met founder and CEO, Doug Chapnick, we knew he and the BioLoomics team were working on something unique.

BioLoomics was born out of experiences on a rapid threat assessment project funded by DARPA. The core thinking that emerged from this work led to the development of a platform that could rapidly cycle through hypotheses to find rare biological events of interest. BioLoomics’ platform combines technical advancements across hardware, wetware, and software to create a high-throughput, rapid-iteration approach that allows for a sophisticated traversal of protein design space. In other words, BioLoomics built a powerful design-build-test platform with mammalian biology in the loop for rapidly iterating toward optimal biological solutions. The platform enables BioLoomics to work on novel and differentiated therapeutic candidates that are uniquely accessible and that solve real clinical unmet needs.

In particular, the team is setting its sights on mechanisms that drive specific cellular trafficking. As a first application, this begins with extracellular and cell surface protein degradation. As compared to other approaches that have emerged in the last few years, BioLoomics has developed a truly unique way to drive a mechanism that is not limited to a single receptor. This greatly expands the contexts in which degradation and lysosomal-targeting are amenable.

We’re incredibly excited to partner with the BioLoomics team.