The Commercialisation of Science

THE COMMERCIALISATION OF SCIENCE… is something I first became acquainted with back in 2006. It’s a massive topic. One that has perplexed many and still does to this day. Even today, in 2019, I am reminded by how difficult it is to do effectively as we begin our planning for the 12th Malaysia Plan.

Once again I am asked “how do we do it effectively?” in a way where we can show success stories in the same way the digital space has been able to do over the last 5-10 years. Lets face it, digital tech startups are thriving while its close cousins, hard tech startups, have languished. How come? Faced with this daunting prospect, I find myself reflecting on my own experiences over the past 16 years and I am reminded of a deceptively simple concept.

By their nature, scientific innovations carry with it significant uncertainties and risks. What works in the lab doesn’t necessarily work in large scale, regulatory compliance is tough and expensive, the equipment, materials and expertise are expensive… but wait, that is assuming you have got the science right in the first place. But everyone knows, even when you start with awesome science with great promise it is still tough. Investors and industry know this and they don’t want any part of that. Even if they do, they will want a discount for the risk they are taking and the amount of money they will still need to spend to make the whole thing work.

So what is the key? A gradual process of de-risking. The more you do to establish and validate the technology and feasibility of the innovation the more likely you will be able to attract the necessary support you need to move the project forwards. By removing risks and uncertainties you make the innovation more attractive to different investors/funders/supporters. So, at every stage you need to concentrate on removing different risks and uncertainties. For example - It’s just an idea or concept now but can it be proven or validated? It works in the lab but will it scale (consistently)? Is it safe? Does it meet standards? Do you have a prototype or demonstrator (I need to see it work)?

You essentially need to match the level of risk/uncertainty with the right investor/funder/supporter. To illustrate - if the investor is someone who is a scientist himself who has already made money from selling his pharma company, he may be willing to invest very early, even when there are significant uncertainties and risk e.g if it’s a drug, say as early as target or lead identification stage. Why? Because that investor understands the risks and potential, what’s more, he probably has the networks and know-how, to make the whole thing work. Typically, you are more likely to secure an investor much later, say during the clinical trial stage, especially when clinical data looks positive (so the drug has a higher chance of being approved for use) because by then a significant amount of risk and uncertainty has been removed or is better understood.

But that’s not all.  Understanding other key elements such as product-market fit, a good business model and an understanding of how IP works (where relevant), all play a critical role, and you will begin to see that one thousand and one piece jigsaw puzzle slowly come together.

Allied with de-risking is the need to build an enabling ecosystem around this process. Key success factors include a (public/private) R&D ecosystem that is aligned in terms of direction, expertise, funding and resources. Next is a supportive policy framework that supports the commercialisation of R&D output effectively, and finally, robust engagement by the private sector to ensure product-market fit and overall development needs are addressed. The digital tech space already enjoys the benefit of such an ecosystem. The commercialisation of science will require similar elements. We need an angel investing community who have the right expertise and risk appetite for hard tech, we need accelerators/incubators that cater specifically to hard tech because their needs are different and just as importantly, we need to build awareness and capacity within the R&D and science community of critical concepts like product-market fit, effective business models, fund raising etc. Things the digital tech community already take for granted.

We at Cradle hope to be part of that de-risking process going forward and look forward to meeting awesome founder scientists.

Fun fact : >80% of Cradle’s grant recipients are from digital based tech sectors. Maybe if we get this right we may be able to see more homegrown science innovations make it to the market. What say you?

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