Jenny Rooke drives innovation in the life sciences field through investing and business building around brilliant scientists and engineers with novel technologies. Prior, Jenny held multiple executive roles at U.S. Genomics.

As a zealous believer in the potential of synthetic biology, I've been looking to invest in synthetic biology tools and applications for years (not as long as some, longer than many). I've even put serious thought into raising a venture fund with a focus on synthetic biology investments, but, for now, conclude that there simply aren't enough investment-grade opportunities to justify a dedicated fund (yet!). Why is it challenging to invest in synthetic biology companies? What is the disconnect between that sense of enormous potential and actually betting on companies to achieve it (besides investors' reputations for being more risk averse than we'd like to admit)? Here are several barriers to investing in synthetic biology that I've observed, drawing on comparisons to biotech investing more generally.

Transition from labs to enterprise

We're still early in the process of transitioning synthetic biology technologies out of research labs and into applied, for-profit settings (i.e., companies). In the last decade, the field has seen a profusion of novel pathway design tools, gene editing techniques, DNA synthesis and sequencing technologies, and analytical tools -- all of which fuel that sense of synthetic biology's potential. We are closer than ever to being able to go from an idea for a novel genetic pathway to proof of concept, rapidly and inexpensively. But we're not yet at the point where the cost, performance, and scalability of the tools are suitable to broad commercial application. As an example, I see a number of startups whose business plan hinges on engineering a proprietary genetic pathway in a microbial host for production of a particular high value chemical. The tools are there to test their hypothesis -- which in itself is a remarkable advance over even five years ago. But it's still so expensive, slow, and unpredictable that they'll get only one or two shots at making it work on early-stage capital. That's a fairly high degree of technical risk for an investor to embrace.

Nascent business strategies and models

We're still early in demonstrating the business models, partnering models, and exit strategies that will work for synthetic biology companies. In biotech, entrepreneurs have decades of success (and failure) stories to draw upon when deciding what business model to pursue to commercialize a novel technology; likewise for investors, when assessing the likelihood and value of a company's options. In synthetic biology, those foundational success stories are still being written. We can't rely on established patterns of capital formation and value inflections to know how much to invest in a synthetic biology company, when, and at what valuation. We don't have robust data to compare to help us predict when a company will be a good acquisition or IPO candidate, and at what valuation. Remember, to succeed, investors need more than just opportunities to put capital into great companies -- for returns, they need to be able to get out.

Diverse applications present unique challenge

High-value applications of synthetic biology are inherently multi-disciplinary, making it especially challenging to build great synthetic biology companies. Very few teams (much less individuals) comprise the expertise to, say, refactor a biosynthetic pathway in a commercially relevant host and develop an effective customer segmentation and sales strategy to a relevant industry (e.g. specialty chemicals); similarly, very few investors have the expertise and comfort to assess both technical and business aspects of a synthetic biology company when considering whether to invest. Most synthetic biology startups I've seen tend to be long on technical expertise, and short on knowledge of and access to their intended markets -- a risky investment proposition. And most investors tend to have either deep life sciences expertise or familiarity with synthetic biology target markets, but not both -- leaving them unable or unwilling to seriously consider even best-in-class synthetic biology companies.

Lack of market transparency and actionable data

The target sectors for synthetic biology applications (e.g., chemicals, feed & food, agriculture and the like) lack transparency, making it difficult to identify and assess market opportunities. In biotech, it is possible to define a target product profile for a new drug, plan the clinical trials required to develop it, and estimate its market potential with a fairly high degree of confidence (leaving aside for the moment the challenges of actually doing so). Similarly, relevant information is widely discussed in biotech conferences, publicly available clinical trial documentation, analyst reports, online patient forums, and even in the popular media. By contrast, start-ups and investors often struggle to find good data about market opportunities for synthetic biology innovations; for example, large incumbent companies in these sectors often do not break out their revenues and margins by specific product lines (e.g., a particular specialty chemical). Further, these companies' needs and strategies around new product development and production are often tightly guarded secrets, and companies and investors can struggle to gain access to industry insiders whose perspectives could provide essential guidance.

It is clear that these challenges confront both the entrepreneurs who would build great synthetic biology companies and the investors who would fund them (although not equally -- as an investor, I'll be the first to admit that the entrepreneurs have the harder, riskier job). So what are we to do? How shall we forge ahead, undaunted, building great synthetic biology companies? What can be done to grow the quality and quantity of synthetic biology investment opportunities? In my next post, I'll discuss some options for surmounting these barriers, aimed at would-be synthetic biology investors.