Fifty million new startup companies emerge every year, yet only one in ten businesses will make a profit in their first two to three years, according to data reporting firm DemandSage. This is where Microsoft for Startups can help. Sally Ann Frank, worldwide lead for health and life sciences (HLS) at Microsoft for Startups, explains how the team is accelerating the development and growth of new businesses by offering support and advice.
What was your professional background before joining Microsoft and how does your experience contribute to your understanding of the challenges startups face?
While I have had roles in both the defence and social services industries, I have also worked as vice president of marketing for a Microsoft partner. Starting out as a part-time marketing coordinator while my daughter was a toddler, I eventually took a full-time role, adding to my duties in marketing and sales. The company was essentially a startup when I joined, so that, along with my experience owning two companies, helps me understand the startup journey and the unique challenges of developing a business within the confines of a larger ecosystem.
Please tell us about the Microsoft for Startups team and your specific area of expertise.
Microsoft for Startups has been around for decades, known under various names like Bizspark. However, our team established in 2020 is specifically industry focused. Our team helps accelerate growth for startups in key industries like retail, cybersecurity, artificial intelligence and HLS. From an HLS perspective, we are engaged with big data plays, generative AI and machine learning. We focus on the delivery of healthcare – whether that is helping healthcare professionals to collaborate, improve patient engagement, or accelerate drug discovery.
My expertise is concentrated on business development strategies, marketing and sales with a bit of technical expertise thrown in. I’ve been in the technology industry for far longer than I’d like to admit, but my experience has always been on the business development side. This has prepared me to guide startup founders and their teams on how to go to market effectively. I share best practices with the startups, not just those from my own experience, but also from what I see in the industry. I spend about an hour every day catching up on the HLS startup news so I can monitor trends and understand what makes some startups successful and why others fail.
How has the combination of a global pandemic and economic downturn across many parts of the world affected the work that you’re doing? Where has the Microsoft for Startups strategy for healthcare played a useful role in driving innovation?
We are all aware that the Covid-19 pandemic accelerated the concept of care outside the traditional healthcare models. Telehealth has been around for a long time, but only in pockets. Now it is ubiquitous in areas that can easily support the technology. The pandemic also highlighted the healthcare deserts, not just in local areas of the industrialised world but also all over the globe where vaccines, anti-viral medications and other measures were beyond the grasp of developing countries.
In terms of economic downturn, we have seen the venture capital community become more cautious about how and when they invest in digital health startups. One area that remains popular is generative AI but, even in this area, we aren’t seeing the unabashed enthusiasm that we saw from investors just a few years ago.
The benefits of AI products like Copilot is the subject of great debate. Where does generative AI play a part in HLS startups?
Generative AI remains well established in administrative use cases, driven by the amount of risk (or lack thereof) that can be tolerated in HLS. However, as the industry improves with content moderation and effectively ringfencing the sources used in generative AI, we will be able to move towards more clinical applications. Additionally, Microsoft remains committed to responsible AI practices of fairness, reliability and safety, privacy and security, inclusiveness, transparency and accountability, such as through its AI Assurance Program.
How are partners adding value to the HLS space and how is Microsoft helping to nurture new entrants to the field?
Microsoft depends on our partner ecosystem to bridge the last mile from our tools and platforms to solutions that our customers can use to achieve their organisational goals. For our startup partners in HLS, this includes everything from helping providers to improve patient outcomes with clinical support tools to optimising clinical trials and everything in between. Through our Founders Hub startup programme, we are supporting new entrants in the market with tools and resources, including free access to GitHub for software development and the Microsoft Cloud, $2,500 of OpenAI cred and up to $150,000 in Azure credits. Startups also benefit from a range of product benefits, personalized advice from our experts and go-to-market support.
What recent successes have startup partners achieved in the HLS sector?
There are so many to choose from, most of which I have shared in previous issues of this magazine. But we recently published a case study with AI tools company BeekeeperAI that makes it possible to develop an AI algorithm for healthcare predictions in a zero-trust framework. The EscrowAI solution allows the de-identification of sensitive data to be used to be part of the AI training and testing process. It does this by creating a trusted execution environment where the content is invisible to data managers or AI developers but delivers verifiable results. BeeKeeperAI was able to improve its solution by adding Azure Secret Ledger to record the algorithm and dataset relationships. The company, originally born out of the University of California at San Francisco, works directly with leading pharmaceutical companies around the world to accelerate the safe and responsible use of AI in healthcare.
Another recent partner success involved Pangea Data’s product platform helping the UK’s National Health Service (NHS) identify patients with cachexia. Pangea Data combines artificial intelligence and medical guidelines to characterize patients with 7,000 difficult-to-diagnose conditions. The platform mimics the manual review process used by employees without manipulating patient data, enabling a larger population of undiagnosed, misdiagnosed, and miscoded patients under hard-to-diagnose conditions to be connected for monitoring, screening, treatments, and trials.
The NHS has teamed up with two pharmaceutical companies from the US and Japan to identify cachexia patients at an earlier stage. The NHS consulted a dataset from the Pangea Data platform of 8,484 patients who had previously been assessed using traditional sources such as ICD (International Classification of Diseases) or symptom-based searches. The platform correctly identified 41 known cachexia patients and 253 previously unidentified patients. The earlier discovery of these patients helped halve the cost of treatment from £10,000 ($12,600) to £5,000 ($6,280) per patient, generating £1 billion ($1.26 billion) annually for the NHS due to the identification of 200,000 such patients. savings were achieved. Patients are missed every year in the UK. Additionally, it has improved patient outcomes and justified the allocation of healthcare resources with empirical evidence. This has enabled healthcare providers to more efficiently and cost-effectively deliver quality care to a broader patient population.
What awaits you, your team and your partners? What innovations can we expect to be introduced as we enter 2024?
We will continue to see more AI solutions enter the clinical arena, which will be used in everything from diagnostics to imaging to digital therapy. There will also be greater adoption of personalized medical treatments such as personalized implants, chronic condition management or medications. While we don’t talk much about the metaverse anymore, we are seeing increasing adoption and application of virtual and augmented reality, especially in the field of mental health.
Finally, we will see changes in care delivery systems, with more routine visits shifting to telehealth, with in-person appointments freed up for more urgent and complex illnesses.