Singapore-based Biofourmis, which claims to be the world’s first personalised physiological data analytics firm, has closed a US$ 1 million round, that was led by South African healthcare professional services provider SpesNet and Eden Strategy. The round also saw participation from other angel investors in the healthcare space.
Founded in 2015 by chief executive Kuldeep Singh Rajput and COO Mark Niu, the startup is attempting to use cognitive technology, machine learning and artificial intelligence (AI) to make sense of the immense amount of raw data generated by medical devices, managing this information ‘to make it understandable and actionable’. This comes amidst the proliferation of medical device companies – with wearables in particular – leading to the emergence of a new cluster of companies seeking to benefit from the massive volumes of big data.
“The vision of Biofourmis is to personalise healthcare, and to make healthcare data actionable and understandable to people, Singh said in an interaction with DEALSTREETASIA.
Following this investment, Biofourmis plans to start monetising its analytics engine by early 2017. Currently, it is reliant on a B2B2C (business to business to consumer) model, but will develop a direct B2C (business to consumer) platform some time in the future. Singh described this as, “The point of sale will be the point of care.”
With the intent to operate across all segments of the healthcare space, corporate wellness programmes represent amongst the most profitable opportunities for Biofourmis, given that its “one stop shop” functionalities and ability to transfer data from many devices.
The company’s solution is rooted in Singh’s work as a researcher at MIT Media Lab’ Camera Culture group, focusing on wearable technologies and biosignal analytics for cardiac health monitoring.
Having won the Healthcare Information & Management Systems (HIMSS) inagural innovation award in the Asia Pacific, Biofourmis ended up coming into contact with South African tech-solutions firm SpesNet. This led to it conducting its first pilot project in South Africa, in collaboration with SpesNet, and this laid the foundation for developing its analytics engine, Biovitals.
Singh explained:”This engine uses cognitive technology and advanced machine learning to provide actionable health insights. Biovitals intelligently interprets any form of data formulating personalized health models that are understandable and actionable displaying real-time patient information and physiological changes, thus, offering real-time suggestions for proactive and preventative healthcare actions especially in cardiovascular diseases.”
Put simply, Singh is of the view that the world is on the cusp of the next medical revolution, where even the slightest change in person’s health can be tracked and acted upon, leading to personalised and precision medicine for patients.
According to Singh, Biovitals is device-agnostic, with the capability to pull in data from over 250 devices that have been cleared by the US Food and Drug Administration (FDA), as well as structured and unstructured data from hospital records.
In his interview with DEALSTREETASIA, he shared: “We can pull in any kind of data, ranging from devices, apps, fitness devices, electronic health record data – this make is more powerful,” Singh said, even as he pointed out that the two wearables on him were generating 10 megabytes of data per minute.
“We want to leverage on that kind of data, and learn your physiology and bring outcomes,” he added, sharing that Biofourmis is intended to be more than a data aggregator.
Enabling engagement with users, it allows customers to set diet goals that can be monitored, as well as activity goals, and also has facilities to provide measurement and notifications for medication compliance, and while the app is targeted at users of all age groups, it may see increased adoption from the elderly, even as its family sharing feature permits family members to track compliance of loved ones.
Singh opines: “They key to success in developing a tech-startup must be 50% technology development and 50% getting in the market as quick as possible. A lot of startups spend too much time polishing their product and end up missing many crucial opportunities. Using our partners such as, for example, a big Australian insurance company, we are focused in getting in the right channels with businesses that understand the the real challenges in the healthcare industry.”
Could you provide us with a bit of context on the origins and motivations behind Biofourmis?
Enormous amounts of data on patient-physiology is constantly generated by multiple sources such as lab reports or wearable technologies. The question that came to me and co-founder Mark Wendou Niu during our time at NUS was “what to do with all this data?”.
I had previously established a precise algorithm to understand causes of cardiac arrhythmia on a personal level, not relying on big databases. We took the idea and decided to found Biofourmis. We then conducted a pilot in South Africa, and used the engine on 30 patients. The results were good, as we were able to diagnose 3 patients with tachycardia, which got them adequate treatment well before any complications occurred.
We the decided to widen our focus from the electrocardiogram and create Biovitals, the world’s first personalized physiological data analytics engine, that uses cognitive technologies.
Biofourmis emphasises on the fact that it provides personalised actionable data. Could you elaborate on this?
Biovitals is data-agnostic. It can acquire data from hundreds of medical devices, applications and wearables.This makes our engine much more powerful and useful, for the constraints on which type of hardware or format to use is no longer an issue. You can even pull unstructured data, the engine will make it analysable and actionable.
In addition to being easily transcribed, the data analysis and following healthcare prescriptions are personalized, for our engine intelligently and precisely understands the user’s physiology, habits and lifestyle. Indeed, we believe it is better to compare patients with themselves instead of using population data, allowing for far greater precision.
On average, Biovitals will know 4 days in advance before a patient equipped with the adequate wearables will be hospitalized. This allows for more time to find solutions that could very much often avoid hospital readmission, saving a lot of money for hospitals, patients and insurance companies alike.
What are your thoughts on possible competition from big groups, other healthcare data aggregators or wearable healthcare device companies?
Since we are data-agnostic and do not rely on one brand or product – following this model for device companies would require them to go through a very big strategic change. Regarding big groups such as IBM, they use population data, comparing your health with big databases.
Of course this doesn’t mean they cannot get into personalized data themselves as well, but we have got it right, we are clinically validating our platform with some of the leading hospitals, and we have good relationships across the globe so that we can start and deploy it. As for other healthcare data aggregators, we are already ahead of them and are moving quickly.
With so much data being collected, the regulations are different across countries. How do you address the privacy and data concerns?
Some markets aren’t as demanding on regulations, and are quicker to get into. Biofourmis will start there to build momentum before moving on to markets that are more heavily regulated such as the US.
Though sometimes regulations are heavy and represent a challenge, we are sure the engine Biovitals will be approved. Regarding one of our main market prospects, corporate wellness programs, we follow PDP (Personal Data Protection) compliances, being a data company.
Personalised data does not go to HR or employers, the aggregation of these do, allowing companies to see what departments are more stressed out, overworked or in less good health.
Regarding monetisation, how much will you be charging for your services?
We will propose several packages with monthly prices varying on the amount on individual data collected, and extent of data presentation. Lifestyle applications will cost less than the heavier physiological monitoring used for more serious patients.