J.P. Morgan (JPM) Healthcare Conference Insights from Massive Bio Co-founder and CEO, Selin Kurnaz
Hello everyone! Another J.P. Morgan Healthcare Conference has come and gone. Overall, it was chaotic but productive for Massive Bio. There were no game changing learning experiences for our core which is precision oncology informatics services, maybe because we live and breathe this space every day. However, the necessity of Massive Bio increases everyday to streamline disparate clinical and genomic information and disparate stakeholders. Precision oncology needs a translator and accelerator more than ever to be mainstream. Massive Bio put precision oncology to “work” — organizes and harmonizes disparate knowledge into clinical utility. In any case, I have summarized our key take-aways from the conference in regards to our space, digital health and AI and overall healthcare. Hope you will find it as an enjoyable read and I am always happy to have a dialogue and attack healthcare issues with like minded people together.
In terms of precision oncology informatics services:
• Still same old…
o Molecular diagnostics labs are working on demonstrating clinical utility of their tests to FDA and CMS. The new CMS memo for “Next Generation Sequencing (NGS) for Medicare Beneficiaries with Advanced Cancer” made this more difficult because CMS is now looking FDA approval and/or strict NIH Genetic Testing Registry (GTR) for reimbursement.
o Commercial payers are trying to figure out which molecular diagnostics test to select and why. They were hoping to act based on CMS’ decision but now CMS seems to throw the ball to FDA.
o Providers are struggling to integrate precision oncology into their workflows and getting reimbursement.
o Clinical Research Organizations (CROs) are struggling to find the right patients for their clinical trials and in addition the complexity of clinical trials and the number of clinical trials are increasing.
o Pharma companies are trying to figure out what to do with the massive information provided by the technology platform companies. They paid handsomely but there is still no biomarker or drug has been invented based on these large data sets.
o Precision oncology technology platform companies ended up cleaning up the legacy EHRs instead of making sense of genomic data.
o Most importantly, patients are getting the same old treatments and same old bills with limited survival.
• Because of disparate information and disparate stakeholders, company like Massive Bio is a “must-have” in this eco-system to put precision oncology to “work”. Massive Bio organizes and harmonizes disparate knowledge into clinical utility.
In terms of digital health and AI:
• 95% of the applications are still “nice-to-have” although all of them have been developed with good intentions.
• Mental health is the fashion of this year, but the value is fairly uncertain.
• Premier VCs are hugging their portfolio company CEOs and trying to make other people believe that they invested in a rocket ship. Ironically, Practice Fusion, a start-up in the crowded electronic medical records market, was acquired on Jan 8 2018 for $100 million, two years after bankers were expecting to take the company public at a $1.5 billion valuation. Fueled by funding from powerful venture capital firms like Peter Thiel’s Founders Fund and Kleiner Perkins Caufield & Byers, Practice Fusion raised more than $157 million on the promise of developing medical records software that smaller practices could use for free. Don’t get me wrong, I love Practice Fusion and I continue to believe that they are an important part of the cloud-based EHR eco-system, but premier VCs, coupled with “distinguished” investment bankers, made up the $1.5 billion until Allscripts woke them up.
• Andy Slavitt, who served as the acting administrator of the CMS under the Obama Administration, says “When it comes to AI, it is the best of times, worst of times story”. Slavitt noted using AI to uncover fraud, waste, and abuse in healthcare would be a “slam dunk” but the complex issue of drilling down and addressing what drives healthcare costs is where the core need is. AI needs to lower its ambitions and focus on what is doable with greatest value.
In terms of the big picture of healthcare coupled with macroeconomy:
• New drug approvals hit a 21-year high in 2017 with a couple of firsts, such as Novartis’ Kymriah and Kite’s Yescarta made history as the first CAR-T therapies to gain approval.
• There is a lot of money flowing into oncology, specifically in gene therapy and immunotherapy, however, the same excitement is not there for most of the other diseases. On January 8, 2018, Pfizer has announced plans to end its research efforts to discover new drugs for Alzheimer’s and Parkinson’s diseases.
• There is a lot of optimism, due to a record level stock market, surrounding a 17-year high consumer confidence index and 10-year low unemployment bundled with new tax reform. Tax reform with a permanent 21% corporate rate, including the one-time 15.5% cash repatriation, is a massive boost to large caps and will fuel $1.2T firepower.
• There were not many M&A announcements because companies still need time to figure out what to do with the new tax reform and its overall impaction on the economy.
• Interestingly enough, no one is talking about the increase in financial performance of the companies as a result of tax reform. It is a pure “financial engineering” exercise and has nothing to do with the commercial and operational performance of the company. If companies do not strategically re-invest the money then it will lead to lazy companies and structural problems in the economy in the long term.
Overall, people are trying to be optimistic, but we are still very far away from focusing on value and understanding that technology and data are enablers to solve the problem — instead being a stand-alone solution.
Selin Kurnaz, PhD
Co-founder and CEO