‘Investing in start-ups in the healthcare sector in these extraordinary times’
Nicole Junkermann is an international entrepreneur and investor, and the founder of NJF Holdings, an international investment company with interests in venture capital, private equity, and real estate. Through NJF’s venture capital arm, NJF oversees a portfolio of over 30 start-ups across three continents, including in the healthcare sector. Here, Nicole Junkermann shares recommendations from within her portfolio:
The COVID-19 global pandemic is having a devastating impact on the world as we know it. In these unprecedented times, and with no clear signs of when things will return to normal, technology and innovation – particularly in the healthcare sector – will be absolutely vital not only in overcoming this pandemic, but more importantly, to help safeguard our globalised and interconnected world against a similar threat in the future.
By investing in healthcare-focus technology and innovation, we can develop new drugs and vaccines, reduce development times and manufacturing costs, and ultimately improve access to these innovations for the entire population. If there is one real positive to emerge from this crisis, it is that finally scientific research in healthcare, and importantly the work of healthcare professionals, are getting the recognition and visibility they deserve.
I was a very early investor in both the healthcare and biotech sectors, particularly focusing on early-stage companies looking to utilise the latest advancements in technology – such as Artificial Intelligence (AI) and machine learning – to make much-needed breakthroughs in their fields. I have always looked to support bright entrepreneurs with the potential to tackle some of the society’s greatest challenges, and for me, healthcare has always been a clear priority.
I am proud to be supporting three healthcare sector companies and look forward to helping wherever I can along their exciting journeys. These companies are:
Deep Genomics
Toronto-based Deep Genomics have developed an AI-driven platform which can enable a systematic, efficient, and reliable approach to drug development.
Deep Genomics’s research shows that, on average, it takes at least 10 years for new medicine to complete the journey from initial discovery to the marketplace at a cost of $2.6 billion. The platform they have built is designed to reduce this traditional timeline to years not decades and the costs from millions not billions and resulted in the company being the first AI-focused company to discover a drug candidate in less than 18 months – for the potentially life-threatening genetic condition Wilson’s disease.
I have invested in Deep Genomics alongside a number of leading VC investors from across the world, including Future Ventures and Khosla Ventures, as the company successfully raised US$40m in Series B funding. The proceeds from this new funding will be used in part to develop new treatments for other rare genetic diseases and to expand the company’s proprietary AI discovery platform to support the discovery and development of novel therapies for more common disorders.
Aether
Aether is a biotech company that employs next generation bioengineering to produce new and existing chemicals and materials faster, cheaper and more sustainably than ever before. The company is therefore not only able to repurpose enzymes in order to create entirely new compounds, but also to reinvent the production of compounds previously discovered.
What I like about this company is that they are innovating at the intersection of machine learning and Synthetic Biology, utilising technology to accelerate research at high speed and that you can really see the value of investor support to companies like Aether where this type of ground-breaking R&D and certain technological solutions require significant initial costs, but will hopefully be worth the investment.
OWKIN
Finally, I am proud to be director of Paris-based OWKIN, which harnesses the power of AI for medical research. OWKIN, has a singular but powerful mission; to use machine learning, integrated with system biology, to develop faster, safer, and more effective medicines and treatments for patients.
