by Patrick Cox
February 13, 2018
The Right to Try (RTT) movement may be our best shot at saving the healthcare system. It may also be your best personal chance at living long enough to benefit from next-generation biotechnologies that will extend healthspans far beyond current limitations.
RTT legislation gives dying people the freedom to use unapproved drugs that have passed safety trials. The logic is simple: terminal patients shouldn’t be denied unproven therapies, since the worst-case scenario is already playing out. Worrying that a drug may cause side effects or won’t work when a patient is doomed anyway is sort of silly.
The truth is, this basic argument still vastly understates the importance of RTT.
Our outdated regulatory system, designed for 20th-century medicine, is holding back innovation and is rapidly failing. This failure is multifaceted, but let’s focus for now on the 800-pound gorilla in the room—the inability of government institutions to keep pace with technological innovation.
It was inevitable that medical regulators would fall behind when the first human genome was sequenced. With explosive progress in many areas, especially genomics and artificial intelligence, the regulators were destined to lag the technological speed train.
Don’t Blame the Bureaucrats
This isn’t the fault of the individuals who make up those organizations, by the way. The anger consumers on all sides of the political spectrum direct at the FDA is misplaced… mostly. The problem lies in the regulatory and organizational structure itself.
This problem extends beyond the FDA. It applies to Australia’s Therapeutic Goods Administration (TGA), Health Canada, Germany’s Commission E, the UK’s Medicines and Healthcare products Regulatory Agency (MHRA), the China Food and Drug Administration (CFDA), and other major regulatory agencies.
Some are better than others—notably the Japanese Ministry of Health, Labour and Welfare—but all suffer from political inertia and an outdated medical worldview.
Specifically, that worldview is based on the traditional drug approval process, which in turn is based on the statistically average patient. In the old days, this made sense. We had no way to easily predict how individual patients would respond to a drug, so all drugs were designed and approved for everybody.
The problem, of course, is that everybody’s biology is different. Some are subtly different from the hypothetical average human; some are very different.
Some drugs can provide nearly miraculous benefits to part of the population but would kill others. Historically, those drugs weren’t approved.
However, it is impossible to predict 100% safety across a patient population that runs in the millions and billions. Occasionally, a patient whose genotype wasn’t represented in clinical trials would die from an approved drug—and furious activists and politicians, abetted by malpractice lawyers, would blame the regulators.
As a result, regulators grew increasingly cautious to protect themselves. Over time, that caution extended the FDA’s reach beyond safety to efficacy (whether a drug works well).
A regulator’s career and reputation can be ruined by one patient with a previously unknown genetic profile. So no bureaucrat wants to approve drugs that don’t clearly help most people. Better safe than sorry (unless you’re the unusual individual whose life could be saved by that same drug).
As a result, the FDA exercises far more control over our medical choices than was granted in its initial charter. Originally, its mission was to root out dangerous scams, but it didn’t practice medicine by dictating to doctors and patients what therapies they could use.
Prior to advances in computers and genomics, this was less of a problem. Now, due to advances in scientific tools and biological knowledge, our ability to predict how patients will respond to specific drugs increases daily. The outdated one-size-fits-all approach to medicine is changing, but not nearly fast enough.
There are, for example, many differences between races and sexes. Prediabetic and diabetic Asians may respond better to acarbose than to diabetes medications developed for European populations. This may contribute to terrible diabetes-related mortality rates among American Indians, whose genomes include a major Asian component.
That raises an even more difficult question, though. What about those of us who have mixed genomes? My family has enough Algonquin and Cherokee blood to make most of us lactose intolerant and the men incapable of growing decent beards. Does that mean we should be taking acarbose rather than metformin?
I don’t have a clue. No one does. However, there is a solution: artificial intelligence (AI).
The cost of fully sequencing a genome is less than the cost of a comprehensive blood test, and still falling. The amount of genomic data generated today is overwhelming and growing constantly. We long ago reached the point where it is impossible for human scientists to analyze that data manually.
Fortunately, new AI technologies, both hardware and software, are developing in parallel. They automate thinking to perform immense, and immensely boring, analyses. As they reveal the rules of our genetic machinery, they enable solutions to the medical challenges every one of us faces. They can also solve the crushing debt problem imposed by a rapidly aging population. Traditional medical and regulatory tools are simply not up to the task.
Juvenescence AI Announced First Drug Candidate
I’ve written before about Insilico Medicine, one of the top AI companies focused on unraveling the mysteries of the genome. A few other firms with comparable skills are also working in biotech, though Insilico is unique. Alex Zhavoronkov PhD, a driven AI pioneer who dropped everything to solve the long game, aging itself, leads the team consisting of the best AI experts from around the world.
Perhaps the most important thing he’s working on is Generative Adversarial Networks (GANs). These are neural networks that scan massive amounts of data to create new solutions. You may have seen programs that will create images of any subject matter you define, done in the style of your favorite classical painter. Zhavoronkov is using GANs to analyze information about molecular genetic mechanisms to create new synthetic drugs.
Zhavoronkov has teamed up with the equally impressive Jim Mellon, a legendary British investor and self-made billionaire. Mellon, known for identifying the trends that create fortunes long before the market does, is now focused on aging. To that end, he co-founded Juvenescence AI, a company utilizing advances in artificial intelligence to solve the medical aging problem.
Last week, the company announced its first drug candidate, JAI-001. Juvenescence AI hasn’t announced what disease the drug will target when it enters the regulatory labyrinth, but we know that there are many options. The press release states, “JAI-001 and its analogues have demonstrated in-vitro activity in assays directly relevant to ageing and age-related diseases.”
This is the 21st-century approach to drugs and medicine. Instead of ameliorating the symptoms of disease, we address aging itself. If we fix the systems that cause aging, we can prevent or reverse age-related disease.
Right to Try: We Might See It Sooner Than You Think
This brings us back to RTT. The promise of Juvenescence AI and GANs is true personalized medicine. The company is capable today of recreating your genome in an AI-controlled virtual reality. Based on the sum of all knowledge about genetic actions, entirely new drugs could be synthesized specifically for you.
How does a regulatory system designed to serve the statistical average deal with this technology? The answer is, “It doesn’t.”
How do you perform a clinical trial, even a safety trial, for such a drug outside of VR? The answer is, “You can’t.”
The most radical reformers Trump named as candidates to head the FDA were not nominated. However, the most innovative that could have been confirmed, Dr. Scott Gottlieb, may be running the FDA now.
Gottlieb supports RTT, and President Trump reconfirmed his support in his State of the Union address. It may not be obvious, but this could be his administration’s most important policy effort.
Despite serious opposition from many within the regulatory community, the public overwhelming supports RTT. Versions have already become law in 38 states, with other efforts likely to succeed soon.
On the federal level, the House unanimously passed a Right to Try bill last year. Approval by the Senate would force the FDA to further streamline the process of getting permission to take unapproved drugs that have passed phase 1 safety trials. It would also provide critical legal protections for companies and doctors who sell unapproved drugs.
Critics of the movement warn that terminal patients may be exploited by companies selling ineffective therapies. That may, in fact, sometimes happen, but other patients will benefit immensely from access to unapproved therapies. A body of scholarly research supports the idea that increased access saves more lives than restricted access.
If RTT becomes federal law, people will once again get used to the idea that doctors and patients, not Washington DC, are responsible for medical decisions. It will normalize the use of drugs unapproved by a regulatory bureaucracy. It will accelerate drug development by providing scientists with important information about their discoveries. The FDA could be transitioned, as Milton Friedman suggested, into the ultimate peer review agency.
However, most importantly, it will help visionary companies like Juvenescence AI prove that aging is treatable, even when patients are close to death.
This is more important than you may think because I’ll let you in on a secret (maybe you should sit down): you’re dying. You just don’t know the details of your demise.
If people with life expectancies measured in months have the right to try to save their own lives, shouldn’t those of us with only years or decades left in the hourglass have the same right?
For more information on RTT, check out righttotry.org.
— Right to Try: Our Best Shot at Saving Healthcare originally appeared at Mauldin Economics.