What’s Next in MedTech: A Conversation with BioTech Investor, Robin Farmanfarmaian

What’s Next in MedTech: A Conversation with BioTech Investor, Robin Farmanfarmaian

- February 8, 2019

Robin Farmanfarmaian is a professional speaker, entrepreneur and angel investor actively involved in investing and advancing digital health companies poised to impact large populations. MedTech sat down with Ms. Farmanfarmaian to discuss the future of digital health.


Recent shifts in digital health (such as the implementation and broadening of Apple’s Personal Records program) are encouraging users to gain more control of their personal health records. How do you think the growing democratization of health data will influence healthcare?

It is really going to reset expectations. Now that patients are increasingly able to aggregate more of their data onto mobile devices, they will begin looking to other health players to streamline these processes. I really think that we are going to start seeing patient expectations shift in response to things like Apple Personal Records–there will be an increased demand for the ability to integrate the back-end of various EHR systems together.

We’ve seen companies like Oracle, Salesforce, IBM, Amazon, and others begin to enter the healthcare IT space to assess and eventually address these interoperability issues.


In the past few quarters alone, the digital health industry has experienced record numbers in venture capital funding. As an active angel investor yourself, what role do you anticipate venture capital to play in the digital health startup ecosystem this year?

Venture capital will continue to fund and grow this industry. While digital health is still in its infancy, tech is an incredibly fast-paced industry. The first iPhone was only released about 12 years ago. We are going to see some truly incredible developments in the very near future. Up until now, a lot of new medical technology has been consumer-facing–not a whole lot of clinical grade or FDA-approved consumer technology. But in the past year, we have seen that begin to shift. Recently we saw the first FDA-approved digital health opioid treatment from Pear Therapeutics. They are really beginning to lead the way in digital therapeutics.

Of course, investment is largely dependent upon the economy and politics. There may be an uptake or slowdown in response to these external factors, however in general investments will continue to move upwards.


As an Angel investor, what are your thoughts surrounding consumer marketing versus provider/payer marketing? How big of a difference does that make when reviewing potential investments?

I will only invest in FDA-approved, clinical grade technology. I think consumer-based products serve a very important purpose, but I only invest in clinical grade tech that will go to hospitals and physicians, and which insurers will take seriously. In fact, most of my investments are in early-stage pharmaceuticals and medical devices.

The FDA is continually reassessing regulatory processes for medical technology. Most recently, the FDA released a new Pre-Cert program in an effort to streamline the process for software companies. How do you foresee regulation influencing the digital health industry?

Scott Gottlieb is really forward-thinking and has been coming up with very productive changes. The new medical device Pre-Cert program is a really big deal. Allowing companies that are using novel approaches to care –such as VR for stroke and brain injury rehabilitation — to reach the market with FDA approval. I am really excited that he is doing things like this. Regulation can really hinder or accelerate innovation. I think things are getting better under Gottlieb.


Artificial intelligence is arguably the single most transformative factor in healthcare right now. What opportunities and challenges do you anticipate for AI in healthcare in the coming years?

The biggest barrier for AI in healthcare is ‘garbage in, garbage out.’ It’s that simple. If we are feeding artificial intelligence inaccurate or biased data that is the kind of information we will receive. So many clinical trials are based on the average Caucasian male. Over 16 million genomes have been digitally sequenced, and the vast majority of them are from Caucasians. That is a big problem. We need to get accurate, reliable, and unbiased data that is representative of the solutions we are looking for. If the AI we are hoping to use to treat an African American female is largely based off of data comprised mostly from white males, then we are missing the mark. I think this is the biggest issue we are facing with AI.


Machine learning is being used for a variety of healthcare functions including PET scans, EHR processes, and numerous administrative services. How do you expect machine learning to disrupt existing healthcare processes?

The company I am currently working with is working to repair the p53 gene for oncology and the AHR protein to treat autoimmune disease. Our approach to preparing p53, which could potentially cure or treat more than 50% of all cancer, was found using machine learning at UC Irvine.

Machine learning is, to say the least, transformative. It allows healthcare professional to do what they do best: spend time and treat patients as opposed to using valuable time trying to analyze patterns.


What particular aspect of digital health are you most looking forward to seeing develop this year?

I am most looking forward to seeing more accessible clinical grade wearables. That is what is most exciting to me: the prospect of average people wearing clinical grade technology. Omron just got FDA approval –finally– for their blood pressure monitoring watching. This is huge. We are seeing these clinical grade wearables hit the market and reach consumers. Generally, this sort of data is only gathered when a patient goes to a physicians office once or twice a year. Capturing data at those inopportune times is less than ideal because of things like white-coat syndrome– where a patient’s blood pressure is higher in medical settings because of stress. I think having clinical grade reliable data from the patient’s daily life is huge.





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