We’re about to cripple the genomic medical era
Over the past two years, as the Chief Data Scientist for the U.S., I’ve had the opportunity to look over the horizon and see what’s coming in advancements to medicine. First off, I couldn’t be more bullish. The costs of genetic testing continues to drop and is increasingly used to address diseases like cancer. We also now have a wide array of new sensors to understand the impact of our environments both around us (e.g., air quality) and inside us (e.g., our microbiome). These combined with with advancements of data science, machine learning, and artificial intelligence (AI) have laid the foundation to revolutionize how we treat disease. But there’s a catch and it’s called preexisting conditions. And bringing back preexisting conditions, will derail us in three ways if the American Health Care Act (AHCA)—Trumpcare goes forward.
1. Missing out on the era of genomic + big data/AI Medicine
When we look at the next great horizon of medicine, it’s going to require the responsible collection of large amounts of data to be able to develop truly customized medical treatments for each patient. This idea is the foundation of the Precision Medicine Initiative, which I was fortunate to help lead at the White House. Being able to safely and responsibly bring together large volumes of data such as a patient’s DNA, environment, or health history offers an unparalleled view into how disease manifests. In fact, when we were working on the Cancer Moonshot, it became very clear that the primary route to winning the war on cancer is to bring together fragmented data sets with modern data science and artificial intelligence. With these elements, doctors can utilize a more complete picture of a patient’s health to provide better care.
Remember that time when you applied to for health insurance and you had to fill in all of your preexisting conditions? It was not only painful to be reminded of what we have undergone, but also the threat of having that data used against us. At the genetic level, everyone of us has a preexisting condition. Our genes are preexisting conditions waiting to be triggered. Some good. Some bad. This is what makes us unique. It’s what makes us human.
But we, as a country, can’t enter the genomic revolution if there is even a remote threat of our genetic or genomic information being used against us. It is true, there are some protections such as the Genetic Information Nondiscrimination Act (GINA), but that was written in 2008 and given the pace of technological change we need to see an aggressive update. And there are increasing legal questions regarding wearable data and your employer.
2. Slowing down the pace of science and the fight against cancer
It’s one thing to be able to have great advancements in data science, machine learning, and AI; but, if you don’t have the data, it really doesn’t matter. That’s why the Precision Medicine Initiative is so unique and, under which, the National Institutes of Medicine (NIH) has developed the All of Us Research Program. It’s designed to responsibly and securely collect data from at least 1 million Americans to build the greatest biological data set ever put together. However, programs like it all depend on people being willing to donate their data without fear of it being used against them.
When we were developing the Precision Medicine Initiative and meeting with Americans across the country, a key concern was ensuring that their data couldn’t be used against them or their family (this is genetic information so if you share a biological basis, you have overlap in the data). If there is any threat of this data being used in a way that it contrary to research, my deep fear is that people won’t be willing to donate their data. And there are too many people who have diseases that need us to donate our data to help.
It’s not just our country’s race to end disease, many other countries are racing to develop their own precision medicine programs. China is aiming to put in $9.2 BILLION (nearly 10x the U.S. investment) to recruit 100 MILLION individuals to their program (a 100x goal of the Precision Medicine Initiative). The prize isn’t only to massively identify disease, but to also secure the intellectual property for the next set medical breakthroughs that could exceed $1 TRILLION.
3. Got organs?
We often think of an organ donation as that check-box when we get our drivers licence. The idea being, in case we’re killed, we could help another person. The facts are stunning—today alone, 22 people will die waiting in line for a transplant. And just 1 organ donor can save 8 lives and change the lives of more than 50 people.
Here’s the thing that we don’t talk about, many donors are living donors. Maybe they donated a kidney, part of a liver, a lung, part of the pancreas, or even part of an intestine. Nearly 6,000 living donations take place every year. According to organdonor.gov that’s 4 out of every 10 donations. These people are heroes. They have literally saved a life and many times, they saved a life of someone they didn’t know.
Let’s just take kidneys for a moment. There are nearly 500,000 people in the U.S. undergoing dialysis treatment that would benefit from kidney donation. (Did you know that, by law, dialysis is covered by law for those that need it? And it takes about 1% of the Federal Budget!) What happens if you or a loved one needs a new kidney? First, you go on dialysis (here’s a good assessment of what that means) and look for a match with a potential donor (alive or deceased). If you don’t find a match in your network, you go on the waiting list and hope there is a match in time.
Another alternative that has been enabled through data and altruism is creating chains of donors. Let’s say my brother needs a kidney and I’m not a match, but I’m still willing to donate to another person to establish a trade of kidneys; we increase our the chances of finding a donor. Thanks to better data and algorithms we can make this a chain of donations where everyone gets the right kidney at the right time. This model is so powerful, that one of the longest chains was 68 people (34 donors and 34 recipients) using 26 hospitals.
Thanks to the Affordable Care Act, none of these courageous donors could ever be discriminated against. Unfortunately, if we let preexisting conditions become a vehicle to deny coverage via Trumpcare, everyone of these donors will now have to list that they have a preexisting condition. Even worse, the benefits from these fragile organ donation chains could collapse due to the fear of being discriminated against.
Winning the Long Game
As a country we need to look at both the short-game and that long-game. In the short-game, we know that the Affordable Care Act (ACA) needs iteration. Healthcare is complex and it takes a steady hand and determination. There is no fast fix. Only steady and regular iteration to improve the quality of care for all Americans.
The American Health Care Act (AHCA)—Trumpcare is a massive step backwards. It cuts coverage for 24 million people, raises premiums by 20%, limits the care under Medicaid, and effectively eliminate Medicaid expansion (services so many depend on no matter which way they voted). It also disproportionately targets health care services for women— it eliminates the requirement that plans cover maternity and newborn care or access to preventive and contraceptive care, and it defunds Planned Parenthood. Even sexual assault and rape could be considered as a preexisting conditions and used to deny coverage going forward.
Let’s also keep in mind the long-game—the things we need from medicine and science for our kids and our kid’s kids. Innovation is hard and we’re lucky that those before us laid down the foundations for us to enable the incredible medical advancements we see see today. Let’s also be clear, the AHCA will cripple our nation’s efforts to enter the era of genomic medicine and the second order effects to ending cancer and addressing problems such as organ donation.
Partner at Finbouquet LLP
7 年katyayani agarwal
Artificial Intelligence Resident @ Shell | Ph.D. Physics
7 年Ana Javed you should relate
Software Engineer
7 年Good article. But genetic diseases are still rare. Could you give one example of a disease which is common in which genetic testing could help? Are we going to catch too many false positives with genetic testing? What is going to be the gold standard to compare against?
Producer, NoMoreBoxes LLC
7 年Eloquently stated. Thank you.