MMC Ventures’ focus on Digital Health
I joined MMC in the late summer of 2021 to lead and build upon our already strong, track record in Digital Health. As a research-led VC, we strive to provide deeper expertise and insight to the founders and teams we partner with. For those who don’t know us, MMC backs transformative technology companies and is focused on finding innovative technologies to disrupt existing markets or create entirely new ones. We focus our contribution on both our understanding of emerging technologies and the trends impacting specific verticals that we understand deeply. For me, that area of focus is Digital Health.
The opportunity now
MMC has been investing in the digitalisation of healthcare for many years, but we believe that we are on the cusp of a technological revolution within healthcare now. The Covid-19 pandemic has acted as an inflection point to accelerate the adoption of virtual care. This, in turn, has triggered an explosion of downstream innovation falling under the “consumerisation of healthcare”, allowing people to access healthcare services, such as self-diagnosis and genetic testing from their homes. And so, a core part of our digital health thesis stems from the belief that many, if not all, elements of primary, acute, and chronic care will be delivered digitally to patients in their own homes over time.
Whilst this addresses a significant problem where technology promotes more accessible healthcare, particularly against a backdrop of scarce medical resources and increasing healthcare costs, this also reinforces the data problem within healthcare. The benefits of more convenient, virtual healthcare services mean that much richer patient data (“real-world evidence”) can be collected over a long period (“longitudinal data”). This paves the way to bring the long-awaited, personalised medicine closer to reality. However, medical data is fragmented and becoming increasingly so due to limited interoperability between healthcare providers, which impacts the patient experience. This is not acceptable in an era where people expect an “Amazon-like” consumer experience.
Here is a primer where we talk about some of the technologies we are excited by, in the context of this data problem, which we think will result in better clinical and cost outcomes. Stay tuned for our deeper dives to come!
What we are excited by!
1. Machine learning, including natural language processing and computer vision, enables personalised care models and diagnostics.
Virtual care, such as telemedicine, is now widely adopted. This change is driving vast volumes of new types of patient data that couldn’t be captured by healthcare systems previously. There is also considerable latent, unstructured medical data within healthcare systems that are under-utilised. There is a massive opportunity for technologies to generate and curate data and use machine learning to extract insights to give a 360 view of a patient’s health. We believe all will be used to detect, research, and track potential markers of disease (“biomarkers”) by capturing and analysing facial expressions, tone of voice and speech analytics, and analysing text and language sentiment.
Deep dive: Mental health and disorders.
Mental Health was brought into the spotlight during COVID-19, and rightly so, given the scale of the problem and its widespread impact on society. Many companies have innovated in the virtual services space to make therapy more accessible. The next wave of companies will be looking at using sophisticated machine learning technologies to enhance our understanding of mental diseases by identifying novel markers of disease, tracking progression, and delivering better treatments and therapies. For example, Woebot Health, based in the US, and Limbic.ai, based in the UK, have developed empathetic, AI-driven chatbots to provide therapy using natural language processing (“NLP”). Whilst producing a therapeutic effect on patients, they collect data on mental disease presentation, which can help advance our scientific understanding of these diseases. This is important given many different mental diseases present with similar symptoms (e.g., social withdrawal or cognitive impairment) with no apparent physiological change, making diagnosis difficult and often subjective. In another use case, Novoic, based in the UK, uses NLP to detect changes in speech indicating mild cognitive impairment, a precursor of Alzheimer’s’ disease. Alzheimer’s has long been a focus on clinical trials with limited success, partly due to a lack of understanding of the disease’s biology. Novoic is building a dataset to detect early disease markers, which could provide disease insights and potential targets for drugs.
We also believe the next generation of diagnostics will be used at home. Regulation and reimbursement are changing, allowing healthcare providers to collect vital signs data from apps, wearables, and sensors in mobile phones. This enables the creation of high-quality, continuous datasets to monitor, analyse, and track chronic conditions’ progression, which caregivers can then analyse. This is a trend seen in the US, where providers are increasingly adopting “hospital at home” technologies to reduce costs for payers as well as provide a better patient experience.
MMC portfolio spotlight: Current Health was founded by Chris McCann. Current health was the first mover in developing a medical-grade, AI-driven platform for remote patient monitoring allowing healthcare providers to monitor patients’ vital signs from their own homes. MMC first invested in 2018, later led the series A and participated in the Series B. During this time, Current Health partnered with world-leading healthcare institutions, including the NHS, Mayo Clinic, and Sinai, achieving rapid growth before being acquired by Best Buy in 2021 for $400m.
2. Decentralisation of healthcare data supported by scalable and flexible infrastructure technology with high data security and ownership of medical data being returned to the patient.
In a world where patient data volumes continue to grow, there is an opportunity to harness the full power of the data, but only if companies can reach across the various pools across an ecosystem of healthcare providers. We believe decentralised data models, supported by intelligent data infrastructure, are the answer. Technologies that can integrate, in a scalable way, with the highest quality medical and patient data pools and provide superior population-based insights will win in this space. For example, companies such as Owkin (France) are leading the way, having developed a federated learning platform which allows them to run and refine their AI algorithms on smaller, hyper-localised data sets within the customer’s cloud environment. This allows them to optimise their AI analytics without needing to pool large amounts of personalised, sensitive data.
Deep Dive: Genomics and personalised medicine
Personal data is now more profound and more personal than ever before. An exponential increase in genomic data has been possible through technical innovation and bringing down the sequencing costs. Technology has also enabled genetic fact-finding to be available to the mass public. This will continue to go deeper, profiling a higher percentage of the human genome, building our understanding of nature vs nurture and how this affects a disease state. Whilst this is exciting, pushing the frontiers of medicine, this makes medical data more personal than ever. We think people are alive to this and will reclaim ownership of their medical data, only partnering with companies with solid data governance, a market-leading approach to privacy, and a strong consumer experience.
MMC portfolio spotlight: Sano Genetics was founded by Patrick, Will and Charlotte, to better find and engage people with specific genetic profiles for precision medicine clinical trials. Sano is developing an end-to-end operating system with solutions for participants, Pharma and Biobanks which will fundamentally change the way pharma interacts and re-engages with participants where the participant is at the centre. In doing so, they are creating the largest decentralised genetic database globally as well as improving the efficacy of precision medicine trials. Read more about why we invested here.
3. Next-generation healthcare operating systems, including EHRs, and API software, re-inventing care pathways.
There is a growing acknowledgment that many care pathways are inefficient with a poor feedback loop, impacting the care journey. Healthcare decision-makers have realised that collaboration with digital health companies is required to deliver joined-up platforms with customisable care pathways, which is key to better engaging patients and providing superior patient care. From our investments in Ably and Tyk, we have a good understanding of developer tools and infrastructure technology. Healthcare is the next sector to benefit from re-vamped infrastructure following the wave of digital solution innovation to promote more joined-up care pathways and achieve better outcomes.
Deep Dive: Patient navigation within a broader healthcare ecosystem
Navigating the variety of growing health providers (virtual or physical) as an individual can be difficult and costly. This is felt by enterprises, such as insurers or employers, that procure healthcare services and need to help their employees navigate the solutions they offer. There is an opportunity for data-led infrastructure businesses to develop tools to promote interoperability, resulting in better data visibility and a better patient journey across the healthcare ecosystem. For example, ribbon health, based in the US, provides an API layer for accurate data on doctors, insurance plans, and quality of care to help people navigate their healthcare choices. Xund.ai, based in Austria, has developed a medical device in an API, which gives GP-equivalent recommendations based on symptoms or illnesses and integrates with downstream health services fuelled by a flexible medical engine.
MMC portfolio spotlight: C the Signs was founded by Bea and Miles, ex-GPs who experienced first-hand how many early-stage cancers are missed despite early symptoms being flagged to the GP. They have developed an AI-driven clinician decision support tool used by the NHS to detect early-stage cancer which has shown to reduce inappropriate referrals, reduce cost for the provider, and detect cancer early resulting in a better prognosis for the patient. Their software integrates into the electronic healthcare record and completes the feedback loop of cancer care allowing closer tracking of outcomes for healthcare decision-makers. MMC backed CTS to fuel its US expansion in 2022.