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  • Mark Zanders

MedTech overview

The views in this MedTech Overview are subject to change at any time based upon market or other conditions and are current as of January 12th, 2020. While all material is deemed to be reliable, accuracy and completeness cannot be guaranteed.


As an industry that has been around for thousands of years and seen very promising technological advances, yet which also has high inefficiencies, life sciences, and more specifically MedTech are an industry ripe for innovation. This is made even more important given that this is literally a life and death industry where innovation has the potential to directly save lives and improve the quality of life for millions if not billions of people. Like our other articles, books could and have been written about this industry, but a few points we would like to focus on based on recent innovations include:


  • Precision medicine, for example allowing oncologists to laser-target the appropriate cancer cells.

  • Genetic testing and Big Data/AI: While companies like 23&me have reached the mass market for social recognition, we believe there could be immense potential for the medical applications, such as genetic/hereditary propensity for a given disease, as well as other applications such as more efficient drug discovery and testing.

  • Telemedicine, which has the potential to drastically increase access to quality care.


Precision Medicine

As a non-physician/scientist  (albeit someone who has spent substantial time in the medical space both with my own startup and working with many startup/growth stage companies), one of the best articles I have ever read was a recent Wired article on Dr. Jim Allison, who won the 2018 Nobel Prize for Medicine with what could truly be game changing research and one of the most important discoveries of our time. I highly encourage readers to read the full article, but as a quick summary (emphasis ours), Allison was able to revolutionize an area that had historically evolved slowly and had major drawbacks:


Allison’s breakthrough was the discovery of a sort of secret handshake that cancer uses to evade the immune system, and a means to block that handshake—what the Nobel committee hailed as “a landmark in our fight against cancer,” which has “revolutionized cancer treatment, fundamentally changing the way we view how cancer can be managed.” (Allison’s co-recipient was Tasuku Honjo of Kyoto University.) Advances in cancer typically come in 50-year increments; the science that Allison and Honjo helped advance, cancer immunotherapy, has made a generational leap seemingly overnight.

Until very recently we’ve had three main methods for treating cancer. We’ve had surgery for at least 3,000 years. We added radiation therapy in 1896. Then in 1946, chemical warfare research led to the use of a mustard gas derivative to kill cancer cells. Those poisons were the foundation for chemotherapy.


These “cut, burn, and poison” techniques are currently estimated to be able to cure cancer in about half of the people who develop the disease. And that’s remarkable, a true medical accomplishment. But that leaves the other half of cancer patients. Last year, in the United States alone, that translated to nearly 600,000 people who died of the disease.


The fight was never fair. We’ve been pitting simple drugs against creative, mutating versions of our own cells, trying to kill the bad ones while sparing the good ones, and making ourselves sick in the process. And we’ve been doing that for a very long time.


But now we have added a new and very different approach—one that doesn’t act directly on cancer, but rather acts on the immune system. And that’s the breakthrough.

A second fascinating aspect & very relevant to our focus here is that this research was accomplished entirely with grant money, and the major private money has yet to come in on the investment side nor be made on the commercialization side. I cannot help but draw an analogy to the internet, more specifically with the government providing substantial assistance & funding with programs’ such as the Department of Defense's ARPANET to help develop the initial infrastructure, and with private companies then emerging in the internet and technology sectors as a major driver of the massive global economic growth, with many of the largest companies in the world - Amazon, Microsoft, Google, and Apple among others - being direct beneficiaries. On the medical side, I do not think we are anywhere near scratching the surface of what can be done with breakthrough discoveries such as Dr. Allison's, but this will be an area of high interest to watch as entrepreneurs, industry, and academia build on this powerful foundation.


Genetic Testing and Big Data/AI

Companies such as 23andMe have become well-known for their advertising campaigns helping people explore their ancestry; however, we believe the real value-add may be from the underlying science. More specifically, the company aims to leverage its deep database of user records.


Wojcicki wants to leverage the exponentially plunging costs of genetic sequencing (down 99 percent in a decade) and 23andMe’s massive DNA library (the world’s largest genetic research database) to fuel a “biotech machine” that will not just indicate genetic predispositions to certain diseases but also help create the drugs that will treat those diseases. Customers pay to find out about their heritage and then the company uses that genetic data to one day profit from potential new medicines. Eighty percent of 23andMe’s customers consent to allow their DNA to be used for biomedical research.


This is an excellent example of the convergence of science and technology, as what would have been either impossible or impractical just 10 years ago has now become a mainstream idea. Additionally, this may be beneficial on several levels, both with helping patients preemptively understand their risk factors, identifying the best treatments for a given disease, and with the drug development process itself. As one example, having worked with a company in the cancer diagnostic space, having efficient, effective means of screening both pre-disease and after treatment can be extremely valuable in tilting the balance toward beneficial, life-saving outcomes and preventing recurrences by identifying potential issues early.


In addition to the diagnostic and treatment side, Big Data/AI could also play a very valuable role in drug testing and development.  The latter is currently a major source of inefficiency as for every successful drug discovery, there are are often dozens, hundreds, or even thousands that fall short due to not meeting clinical goals. In fact, just this month, I met with a practicing physician of 25+ years who mentioned that for roughly every 1 drug that successfully gains approval, there are hundreds that fall short due not meeting endpoints or being used for the wrong indication. Similar to many of our other discussion points, he was working on an early-stage company that leveraged AI to facilitate the drug discovery process that would not have been possible a few yeara ago, and while early, he felt this could be a gamechanger as even improving the success rate from 0.5% to 2% would be highly beneficial not just for the bottom line but also as a way to directly help patients.


Like the technological breakthroughs that made 23andme's business viable where it would not have been so, Big Data and AI have seen amazing recent breakthroughs, whether via cloud computing that can leverage the power of numerous computers to analyze data at a pace never done before, machine learning technologies that can adapt far faster than any human. while still retaining the deep knowledge, humans have accrued over thousands of years of medical practice. Diagnostic fields, such as radiology for example, may be a great example, as the software would not replace the radiologist but instead complement their diagnosis by leveraging a massive pool of data to provide potential diagnoses and serve as another means to improve diagnostic accuracy. Similarly, physicians may be able to leverage Big Data for high risk specialties like surgery, as a deep data analysis may help provide a good foundation for difficult decision making.


Telemedicine

Telemedicine is another area where technology can complement and improve the medical field. Even without considering physicians, patients are able to leverage websites like WedMD, and there have recently been companies like Roman that offer remote diagnosis and prescription services. At a high level, telemedicine may provide access to high level care that was not possible years ago - for example, a general physician in a small town lacking specialists may be able to leverage both Big Data databases to assist his/her diagnosis, as well as send their x-ray/MRI/CT Scan to a specialist in a larger hospital. The latter may have existed in theory earlier, but the newer high-speed technologies should allow for a faster, better quality process vs. having to send the documents by physical mail. Remote surgery is another related intriguing area of high promise, with companies like Intuitive Surgical (manufacturer of Da Vinci and Ion) already very active in the space. Like Big Data & AI, this technology does not replace the surgeon, but instead serves as a complementary resource that helps them do their job better. In fact, this technology has been used for remote surgeries with the physician in another region of the country but still able to successfully perform a wide range of technology leveraging the Da Vinci robot! Needless to say, this is also an area of high interest, as it has the potential to greatly expand access to high quality healthcare.


Potential Hurdles

While we are very excited and certainly bullish on the potential developments above, we must also be aware of potential hurdles.  Given the massive amount of data involved with technologies like Big Data and AI, companies must be very cautious to stay within HIPAA and other regulations protection privacy. 23andme has preemptively addressed this to some extent by having customers affirmatively consent to their data being used for scientific research, but the company and its peers must still maintain data privacy protection standards. There have also been some high-profile failures on the data side, with even blue-chip companies like Google and Microsoft falling short on health record-keeping technologies. Apple has had some success in medical information but has also had mixed results with the health applications from the iWatch. Finally, cost may be a factor too - while these could rightfully be seen as investments that improve both the quality of and access to healthcare, many of these innovations do not come cheap, and large companies will be looking to make a profit. With that said, we still believe the overwhelming risk/reward in MedTech is extremely positive, and we remain excited to see how the industry evolves in 2020 and beyond.

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