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Stef van Grieken, co-founder and CEO of genAI biotech startup Cradle.
Until now, the field of biological research has largely been limited to those with science degrees or PhDs. However, the rise of AI has the potential of making protein engineering more akin to an engineering discipline, than a science. This is a huge opportunity, not just for the existing scientists, but also for other tech professionals such as software engineers, to contribute to anything from drug discovery to vastly more efficient and more sustainable methods of production for many of the physical goods we produce.
Stef van Grieken
When it’s a toss-up between using AI to improve advertisements, or to develop new therapeutics for thus far untreated conditions and to help battle climate change, there’s an obvious winner for those looking for more purpose from their work life.
I’m part of the early wave of professionals who moved from tech to science, having left Google in 2021 to co-found the biotech startup Cradle that helps scientists design and engineer the proteins that can be used to produce almost anything, from medicines to food and fuel. In fact, there’s already been a surge in talent from companies such as Google, Uber and Facebook moving into human health because they find the work a lot more rewarding, and the trend is only going to accelerate in 2024.
AI is Coming to Pharma
Already, pharma companies are embracing AI - take Sanofi, which recently announced it’s going to be an ‘AI first’ pharmaceutical company, implementing AI across the research, development, clinical trial and delivery of care disciplines in the company. What’s more, there are a range of AI-first full-stack therapeutics companies such as BenevolentAI, LabGenius and Exscientia that are making strong traction in AI for drug development.
As the uptake of AI in healthcare continues to rise, from building data sets to training ML models, pharma companies will soon be competing in the war for top AI talent. Traditionally, there are two ways for business to acquire these capabilities: build it or buy it.
To build these capabilities, it requires companies to complete three tasks. Firstly, to create comprehensive datasets from their existing proprietary data IP gathered over years, perhaps decades of research. This is a considerable logistical challenge spearheaded by data analysts and engineers that might require improvements across the tech stack.These challenges are substantial and we at Cradle have spent a great deal of effort to build a usable platform for designing proteins. Through design partnerships we’re helping customers to adopt AI tools, but I wouldn’t be surprised to see significant M&A activity in this space as companies look to buy in AI capabilities.
Can We Upskill?
Before tackling the challenge of expanding your team, consider upskilling existing employees, arguably a strategic imperative as AI has the potential to profoundly change the labour market.
Last year, we ran a survey with biotech scientists in partnership with Bits in Bio, a global community focused on building software for science, which revealed that coding is now an essential skill for those working in biotech - more than 8 out of 10 wet lab scientist respondents (87%) now write code, with three quarters of all respondents (74%) having taught themselves how to code. What’s more, our research found that 82% of those who don’t already use machine learning in their work report they are interested in doing so in the future.
Pharma companies can take advantage of the current gap in tech training available to not only boost employer branding through career development opportunities, but to build an organisational structure that can support long-term growth. Formally upskilling talent with data analytics and AI skills allows you to augment and enhance existing teams who already have a clear understanding of the ins and outs of your business.
An easy first step is to establish an internal AI ethics board, composed of leadership from across IT, legal, HR and research teams. Their role is to identify the opportunities to implement AI and lead the efforts to address the concerns and challenges that come with it.
Attracting New Blood
A motivation for many making the shift from tech to biology is purpose - I know because I was one of them. After spending over 7 years at Google, I met with my now co-founder Eli Bixby who introduced me to the world of DNA - we talked about how we can learn the underpinnings of DNA and turn it around to make more organic chemistry engineered by humans. Not only did I find it fascinating, but I thought of how I didn’t want to leave a broken planet to my two small daughters, and so Cradle was born, with the mission to help design drugs and therapeutics that improve human health and make human consumption far more sustainable by helping to replace many of today’s industrial farming and petrochemical production processes that damage the planet.
When hiring, use tangible examples to highlight the potential impact tech employees can deliver with their software and ML skills. By communicating the company history and ambitions for future innovation it can go a long way to showcasing the impact and purpose a career in pharma can bring.
Pharma’s AI Opportunity
The pharmaceutical industry has a rich history of attracting innovative minds to cure disease and solve global health challenges. AI will be one of the transformational technologies that will help advance human understanding of research and there is a huge opportunity for the pharmaceutical industry to tell this story to attract new AI talent to help find solutions to the global health challenges of the future.