At Synthesis, in addition to the expertise of our in-house team, we regularly draw on our advisory network, both when assessing new opportunities and when working to support our portfolio.

When considering who to welcome as a formal advisor to Synthesis, we look for experts who can move fluently between technical detail and real-world commercial implementation; a combination which is often hard to find.

Recently, we were fortunate to welcome two such advisors to our network: Sharon Walbert, who brings over three decades of experience navigating global food and agriculture value chains, and Zubin Siganporia, a mathematician and data scientist with a background in advanced analytics, machine learning, and optimisation, and applying this expertise to industrial problems.

We sat down with both Sharon and Zubin to explore some of the big questions facing our sector today.

For a fuller introduction to Sharon and Zubin, visit "Our Team".

Sharon Walbert and Zubin Siganporia, Synthesis Capital Advisors

Sharon Walbert

Rosie: We see enormous opportunity ahead for our portfolio in driving scale through partnerships with incumbent corporates. From your experience inside global food and bioindustrial companies, what does a “smart partnership” look like today, one that accelerates scale without sacrificing long-term strategic advantage?

Sharon: The best partnerships are built on transparency, clear objectives from both partners, and a mutual understanding that both parties must be successful for either to win. I’ve seen too many “partnership" discussions derailed too early in the process because one or both parties aren’t clear on what they truly want and ask for too much for fear of missing out on something they don’t even want. Having the right decision makers from both parties (usually a P&L owner at a corporate) is critical. I counsel founders to be firm and transparent with potential corporate partners to achieve outcomes that enhance not limit the potential value of the company. Founders have more leverage than they think.

Rosie: We’ve taken the view that there won’t be one single winning production platform (e.g. cell cultivation, plant molecular farming, continuous fermentation); each will have its role to play in the system. From your perspective, where do you see the greatest opportunity for durable scale over the next decade? And what practical constraints (regulatory, supply chain, procurement behaviour) will most determine who captures that opportunity?

Sharon: I hate to sound cynical, but the last several years have shown that what drives adoption and change in the food system is:

1) Scarcity - Both the supply disruptions caused by the war in Ukraine and the recent cocoa crisis showed that CPGs are unwilling to change at any price until commodities became unavailable. Then, they look for ready alternatives, even if at a premium. What is most at risk? What can be scaled in a relatively short timeframe with readily accessible raw materials? Achieving durable scale requires adoption by the largest MNCs for whom reliability of supply is key. You can’t replace a scare commodity with another challenged or fragmented supply chain.

2) Cost optimization - Affordability will continue to be a struggle for consumers worldwide, and CPGs are more limited in their ability to pass increases onto consumers. So, cost parity is a must. Cost reduction should be the goal.

3) Asset utilization/technologies that fit core competencies - Technologies requiring complementary assets or unit operations similar or complementary to existing scaled technology (fermentation, extraction, separation) have an easier path to acceptance due to avoidance of capital and core competency fit.

Rosie: What made you want to work with Synthesis, and what has your experience of working with the team been like so far?

Sharon: I love working with good humans who are also smart business people trying to solve real problems. Synthesis believes not only that the challenges of our global food system must be solved, but that they can be solved profitably in the hands of the right founders. Their approach with founders is both collaborative and delivered with a healthy dose of reality.

Zubin Siganporia

Rosie: Besides LLMs, which are getting a lot of attention at the moment, which intersections of biology and mathematics are you most excited about?

Zubin: Beyond LLMs, I’m particularly excited by areas where mathematical thinking directly shapes experimental and operational decisions in biology. The design of experiments is a well-established area of mathematics, and is becoming increasingly powerful in biological settings, where the space of possible interventions is large and experiments are often costly. It provides a structured and efficient way to explore systems with many different inputs, enabling faster iteration and more informative results in areas such as strain engineering, formulation, and process optimisation. In other words, we can strive to extract maximal insight from minimal lab work.

More broadly, even relatively simple models, when carefully constructed, can yield actionable insight into complex biological processes and help answer specific, practical questions across the biomanufacturing pipeline. This is particularly useful in situations where experimentation alone would be too slow, expensive, or difficult to scale. The combination of mechanistic modelling with data-driven methods, including machine learning, is enabling a shift towards more predictive and quantitative biology. This allows for better anticipation of system behaviour and supports more informed decision-making.

Biological data is often highly sensitive, and since mathematics underpins modern encryption, secure data analysis is another important intersection of the two fields. There are modern forms of encryption that allow heavy processing of biological data by untrusted entities in ways that maintain security.

Overall, I’m most excited about mathematicians and biologists genuinely working together in a way that leads to meaningful progress on important real-world problems.

What advances in mathematics that have been successfully introduced in other data-rich industries (e.g. defence, motorsport, banking) could be applied in biomanufacturing to improve efficiency?

Zubin: Techniques using mathematical modelling and data science have proved extremely valuable in many other industries, and the underlying methods will often be directly applicable and transferable to biomanufacturing. Optimisation is a broad area within mathematics, and can address both discrete and continuous problems. It offers a powerful framework in biomanufacturing for improving key operational drivers such as resource allocation, scheduling, and process design.

Bayesian inference provides a principled way to update beliefs and make decisions under uncertainty, which is especially relevant in noisy biological systems. Meanwhile, more recent developments in machine learning, and particularly reinforcement learning, have the potential to automate and adapt complex process control in real time. As a final example, the study of cryptography forms the basis of data security. Although this remains relatively underexplored in biomanufacturing, it may become increasingly relevant, particularly as collaboration and data sharing become more important to the industry.

Rosie: What made you want to work with Synthesis, and what has your experience of working with the team been like so far?

Zubin: I had several initial conversations with David Welch at Synthesis, and really enjoyed speaking to him. As I met more members of the team, it became clear to me that they were all really friendly, thoughtful people who also had a huge amount of knowledge in their field. I was invited to the most recent LP meeting in London, and had a great time. Honestly, I think Synthesis team are brilliant, and feel lucky to be working alongside such a great group of people.