Tanja Dowe, CEO of Debiopharm Innovation Fund – Interview Series Leave a comment
Tanja Dowe is the CEO of Debiopharm Innovation Fund, the corporate venture capital arm of Debiopharm Group. The fund invests in digital health companies that have an impact on cancer, infectious diseases, and drug development.
Debiopharm Innovation Fund is known for investing in companies that are leveraging AI and big data. How important is AI to accelerating drug discovery?
A typical drug discovery process takes 4.5-6 years and requires iterative experiments in the lab with uncertain outcomes. Less than 12% of drug candidates resulting from the traditional drug discovery process make it all the way through the clinical trials and to the market.
As healthcare costs continue to increase, our society cannot afford more expensive drugs. In the past 10 years, the ROI from drug development has declined by 80% – making drug discovery (and development) as we know it unsustainable in the long term due to its high costs.
AI can cut the time spent on drug discovery to as little as a few months to a year. AI techniques have been improving fast – computing power has accelerated exponentially, and more and more high-quality data sets are available to train the AI models. Combined, this enables more precise understanding of the chemical and the biological spaces and the acceleration of drug discovery.
What do you look for in companies that are leveraging machine learning and AI?
We look for a combination of technical and scientific skills. The team needs to have biological or medical expertise, as well as state of the art data science capabilities. AI is a great tool, but the team also has to understand the problem they are trying to solve.
On the data science side, we look for the backgrounds of the engineers and developers: do they come with the newest knowledge and a track record of applying AI to complex problems?
As competition continues to grow in the space, we also look for a track record of existing customers before we invest to show that the company is able to engage with customers and solve relevant problems.
Generative AI is all of the rage, in your view what are the best use cases for Generative AI in the healthcare sector?
There are many areas where generative AI can be used in healthcare – starting from simple opportunities such as content development for patient education and patient support programs, providing clinical decision support systems with up-to-date information from scientific literature, and stretching all the way to drug discovery.
In drug discovery, generative AI learns the relationships between chemical structures and their activity on a given biological target to suggest de novo molecule designs that have the desired properties.
Some of Debiopharm’s previous investments focus on genomics, what are your views on how machine learning can be incorporated in genomics?
The human genome is composed of 20,000-25,000 genes, but only a little over 800 disease-related molecular targets are used today by the drugs available on the market. We know only a fraction of how genomics affects diseases. But the complexity and the increasing amount of genomic data combined with other omics and clinical data need better analysis methods. Machine learning has the potential to point to new connections between genomics and health conditions and enables us to develop better and more targeted treatments for diseases.
The Debiopharm Innovation Fund focuses on Series A investments, these are often successful at proof of concept, but proof of scalability may still be an issue. How do you identify companies that can scale?
There are two axes to scalability. The first is whether the market is ready to scale, and the second is whether the start-up’s technologies and business model is scalable.
On the market side, we see that more than 20 drug development programs from AI discovery companies have already reached clinical trials today. We also see a critical mass of pharma collaborations with AI companies. So, we believe the market is ready.
On the start-up side, we want to see that the tech platform is mostly together, being used at least internally for customer projects, even if UX/UI have not been fully optimized. We also want to see access to high quality data. There needs to be a clear development roadmap for the platform to show what needs to be built to ensure scalability and usability in the customer’s hands.
Most of the companies we see have started with a service model and have a plan to evolve towards a recurring revenue model. Our investment thesis is to invest in companies with software business models rather than biotech asset models, and we steer away from AI companies that solely believe in developing drug assets for licensing. So, we need to see a credible roadmap towards a recurring revenue model and a pricing strategy that makes sense.
You’ve spoken about the importance of the education that is needed on both sides of big pharma and start-ups for them to understand each other, how does Debiopharm assist with this?
When we invest in a start-up company, we organize a ‘Meet-the-Startup Day’ at Debiopharm. We invite the start-ups to give a company-wide presentation, and we open our doors for the start-up to access Debiopharm’s expertise. Whether it is for translational medicine, drug development or market access teams, we connect the start-up with experts that they need to test their hypothesis on customer needs or to understand which technical features are necessary for connecting with pharma’s internal tech stacks. Often, we also facilitate collaborative discussions between the start-up and Debiopharm. In this process, the start-up can refine their understanding of their customer groups. We also educate our internal teams to work with start-ups – to access the newest innovation, you cannot expect turn-key solutions, but you should adopt a mindset of co-creation.
What do you personally look for in entrepreneurs that you are considering investing in?
I get asked this a lot. I look for that entrepreneurial ingredient that is hard to explain – passion, energy, enthusiasm, strong conviction that you can overcome difficulties, curiosity and flexibility of mind. The entrepreneur also needs to be an optimist. You get beat down so many times that it is not possible to build a thriving company without being an optimist. And you have to understand that you are an optimist, so that you mitigate over-optimism by bringing the type of people around you that keep you grounded.
There is one concrete feature that I look for in entrepreneurs that I can share though. It is responsiveness. We live in a fast-paced world, and, as an entrepreneur, you have to keep up. Responsiveness builds relationships and trust, whether it is with a customer or an investor. No matter how great a technology you have, communication between people is what will make or break you.
What advice do you have for startups and founders that are considering approaching Debiopharm or other VC funds to raise capital?
Investors are always looking for new, interesting start-ups, so don’t hesitate to reach out to us at events, through networks or digitally. However, remember that we go through 400-500 investment opportunities per year so be crystal clear about what you do, how your customers work with you and how much money you are looking for. We are very efficient in screening and filtering opportunities and want to easily identify if your company could be a fit with our investment thesis.
What is your vision for the future of digital health?
It is simple: individualized, accessible, preventive.
Individualized means that your health data (whether it is your health history, genetic profile or continuous monitoring data from wearables) is digitally available and is efficiently used for treatment selection and treatment management.
Accessible means that you have access to all your data, as well as digital access to your healthcare providers, and that the quality of diagnosis or treatment decisions remain constant regardless of where you are located in the world – thanks to AI-assisted diagnosis methods and clinical decision support systems.
Preventive means that, based on your health data, digital diagnostics identify potential health issues early and personalized digital therapeutics help you modify your behavior in order to maintain a healthier lifestyle and prevent – or even reverse – a health risk.
Thank you for the great interview, readers who wish to learn more should visit Debiopharm Innovation Fund.
