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How We Can Judge the Safety and Efficacy of New Vaccines Prior to Phase III Data and Why We Must – Article by Dan Elton

How We Can Judge the Safety and Efficacy of New Vaccines Prior to Phase III Data and Why We Must – Article by Dan Elton

Daniel C. Elton, Ph.D.


A common refrain we hear from public intellectuals about vaccines prior to Phase III data is “we don’t know anything about the safety or efficacy of vaccine X”. This attitude is both false and misleading to the public, instilling uncertainty and fear about vaccines. To see why it is false, consider if a normal vaccine safety study was done, but by coincidence all of the vaccines were given in hospital rooms that were painted blue. Could we conclude on the basis of such a study whether the vaccine would be safe if administered in rooms painted red? Yes, we can, and we should. We can utilize two forms of reasoning to conclude that the vaccine is safe if given in red rooms, even though we have no data on the matter.

The first form of reasoning roughly approximates the way an ideal Bayesian statistical reasoner would function to compute what is called a “prior probability distribution”. Under this form of reasoning, we consider the millions of doses of similar vaccines (called the “reference class”) that have been administered. For instance, we might consider the vaccines developed for very similar coronaviruses like SARS and MERS.  We note that if the color of paint did affect the safety of those vaccines, this would have likely been detected over the course of prior studies and over the course of millions of doses given previously. Of course, there is a chance the correlation might have been missed. To figure out how big that is, we can go a level deeper and consider a reference class of “things people might notice or fail to notice in medical studies”. We can conclude that for prior vaccines, if such correlations existed they would generally be picked up. On the basis of this and the fact that no such correlation was ever discovered in the reference class of prior vaccines we can conclude that the probability of vaccines like the COVID-19 vaccine being dependent on the color of paint is very small. 

The second type of reasoning, which happens to be much more straightforward in this situation, is what the physicist David Deutsch calls “reasoning from our best explanation of the world”. According to the philosopher of science Karl Popper, we should reason using our explanatory theories of the world which have survived the most rounds of attempted falsification, and which have the highest degree of falsifiability (this rules out non-testable explanations like “vaccines work via invisible ghosts”). In more prosaic terms, this simply means reasoning using the best scientific theories which make predictions in the domain under consideration. We note that our best theories of vaccine function do not anywhere depend on the color of paint in the room. Instead they depend on things like T-cells, binding affinities of molecules, the concentrations of certain molecules in the body, etc. So, we decide that the vaccine is safe regardless of the color of paint in the room where it is administered. 

Both of these forms of reasoning are valid and both are foundational to science, rationality, and human progress. Both of these types of reasoning can be used to say that vaccines under development are likely to be safe and effective before any data comes in. It’s why a reporter who interviewed numerous top scientists reported that they all told him that “they expected the vaccines were safe and effective all along.” Yet instead of proudly sharing this important knowledge with the public, we rarely hear scientists say publicly that they expect the vaccines are safe and efficacious. Instead, they hedge, saying “we have to wait until the data comes in”. This is unethical both on Kantian grounds (they are lying) and on consequentialist grounds, because it leads to undue caution and the public being afraid of vaccines. 

Unfortunately, there is little incentive for scientists to tell the truth about what the likely risks and benefits are with new vaccines before full Phase III data is published. If, for instance, one or two people suffer severe side effects in a Phase III trial (which is rare, but has happened) a scientist who said they suspected it was “very safe” might receive harsh criticism for making a premature assessment. On the other hand, the same scientist will get no pushback for saying “we need to wait for data to make a judgement”. Indeed, they are likely to even be praised for exhibiting the virtues of “caution, prudence, and scientific skepticism”. Moreover, under no scenario should someone be allowed to get a vaccine until the full data comes in, even though it’s fine to allow people to sign up for studies where they have a 50-50 chance of getting the vaccine. Not very consistent, eh?

As US Transhumanist Party Chairman Gennady Stolyarov II has described in detail in an an earlier publication on this site, all of this is the result of a deeply flawed and deadly ethical principle called the precautionary principle, which unfortunately many people have fallen under the sway of. The principle originates in the environmentalist movement but is widely applied in medicine, and was instrumental in decisions such as the Bush administration’s ban on stem-cell research and decisions to ban life-saving GMO technologies such as golden rice. It has been formulated to varying degrees in several different ways. The United Nations World Charter for Nature (1982) issued one version of the principle, stating: 

Activities which are likely to pose a significant risk to nature shall be preceded by an exhaustive examination; their proponents shall demonstrate that expected benefits outweigh potential damage to nature, and where potential adverse effects are not fully understood, the activities should not proceed. 

The principle starts off OK but dives into serious error in the last line. The issue is that the precautionary principle only focuses on the potential adverse effects of proceeding and ignores the potential adverse effects of not proceeding, i.e., the effects of delay. As should now be clear in the case of the COVID-19 vaccines, not proceeding can sometimes be much more deadly than proceeding! There is often a high but unclear risk to not proceeding, and a low but unclear risk to not proceeding. (Picture two probability distributions, both wide (unclear) but one with a mean that is distinctly higher than the other). That’s where the precautionary principle throws expected utility theory (cost-benefit analysis) out and says we cannot proceed. The Nobel Prize-winning physicist Freeman Dyson stated the issue as follows: 

The Precautionary Principle says that if some course of action carries even a remote chance of irreparable damage to the ecology, then you shouldn’t do it, no matter how great the possible advantages of the action may be. You are not allowed to balance costs against benefits when deciding what to do.” — Freeman Dyson, Report from the 2001 World Economic Forum

Imagine an alternative world in which our society and government was not under the sway of the precautionary principle. In this alternative world, scientists would give their truthful assessment of new vaccines to the public, stating that they are likely safe and effective, using one or both of the reasoning methods mentioned above. In such a world, given the clear potential harms of inaction, the public would be allowed to purchase new vaccines if they wanted, if the companies manufacturing them were comfortable doing so, and if they were fully informed prior to their decision that they were taking an unapproved product that carries potential risks but also potential benefits. Initially, only a few people would purchase the vaccines, perhaps on the basis of Phase I results. These would be folks like those who injected themselves with a DIY vaccine over the summer, and the tens of thousands who were willing to participate in clinical trials as early as last spring. Companies would be incentivized to survey those who took the vaccine and collect self-reported data on their outcomes, which is very cheap and easy to do. After a few months going by without any of those people keeling over and dying, and with very few (likely none) of those people getting hospitalized for COVID-19, more people would feel comfortable getting the vaccine. Things would quickly snowball, with more and more people becoming willing to get the vaccine. During this time the distribution system would have been stood up and become operational, with on-site stockpiles building up ahead of the FDA’s Emergency Use Authorization (currently, the FDA does not allow hospitals to stockpile unapproved vaccines ahead of their EUA). To present this case in its strongest form, in a future post I plan to estimate how many lives would have been saved, assuming many vaccines had become available to those who wanted them last March or August. However, I hope it’s easy to see that thousands of lives would have been saved in this alternative world.  

For more on the transhumanist alternative to the precautionary principle, the proactionary principle, see Max More’s excellent book chapter as well as the Wikipedia article and references therein.

Dan Elton, Ph. D., is Director of Scholarship for the U.S. Transhumanist Party.  You can find him on Twitter at @moreisdifferent, where he accepts direct messages. 

Review of Jamie Metzl’s “Hacking Darwin” by Dan Elton

Review of Jamie Metzl’s “Hacking Darwin” by Dan Elton

 

Dan Elton


Our inaugural  book review of 2020 covers Hacking Darwin by Jamie Metzl. As a  happy coincidence, David Wood of the London Futurists recently had Metzl speak to his group, and you can watch a recording of the event here.  This book is an exploration of how we might genetically engineer our children, why we might want to do so, and what the consequences might be.

The fact is, some people are already “hacking Darwin”. The first “test-tube baby” was born in 1978. This set the stage for preimplantation genetic testing, which became popular in the 1990s and widely used today. But “hacking Darwin” had already been occurring earlier due to genetic testing. A striking example Metzl discusses is the rapid decrease in Tay-Sachs disease in the  Ashkenazi jewish community.  Tay-Sachs is a genetic disorder which has devastating effects on the nervous system. By age 2, children with Tay-Sachs start to experience seizures and decline in mental functioning. Sadly, most die in agonizing pain by the age of five. About one in twenty seven Ashkenazi Jews carry the Tay-Sachs genes. Remarkably though, since the 1980s, the prevalence of the disease among Ashkenazi Jews has been very low, due to extensive genetic testing and family planning. Marriages between people who have tested positive for the disease were discouraged, and when they do occur, the couples tended to adopt rather than risk having a child born with the disease. The result was a great reduction in needless suffering, which is hard to argue against.

One of the major objections to genetic engineering is that it is “unnatural”. Metzl points out that a better term is “unfamiliar”. He points out that many things that seem natural are actually very “unnatural” – for instance, if you went back a few thousand years, you wouldn’t find anything resembling today’s corn or bananas – they are human concoctions from centuries of selective breeding. It seems that the queeziness people feel, which they label as due to “un-naturalness” is actually just due to unfamiliarity, which naturally invokes anxiety. History shows us that any radical technology or new idea naturally experiences widespread pushback. But history also shows that acceptance of a radical new idea or technology can be remarkably fast notwithstanding.

In-vitro fertilization provides an interesting case study of how public opinion can shift. Initially it was demonized, but public acceptance of it rapidly changed over the course of only a few years.

The next technology that will come down the pipeline, according to Metzl, is iterated embryo selection. Embryos are already inspected visually to select the one that is least likely to result in a miscarriage, and as noted in some cases preimplantation genetic testing is performed to check for a few genetic illnesses. This process can be scaled up and improved dramatically. Instead of having 10-15 eggs fertilized, a hundred might be, and instead of just doing visual checks, the genome of each embryo might be sequenced to screen out certain genetic disorders and select for certain traits. The process could also be “iterated”, using induced pluripotent stem cells (IPCs) from the embryos to create new gametes (eggs & sperm) which could be combined to create new embryos.

Fig. 1 – The Cost of Sequencing a Human Genome.

Source: National Human Genome Research Institute

 https://www.genome.gov/about-genomics/fact-sheets/Sequencing-Human-Genome-cost

The benefits of expanding IVF and embryo selection could not only eliminate unnecessary suffering but also result in large financial savings which will allow money to be redistributed elsewhere in our healthcare system. The current cost of taking care of the current number of people born with genetic diseases each year was roughly estimated by Metzl to be $48 billion, spread over 37 years into the future.

The cost of sequencing is dropping dramatically (see Fig. 1). This is allowing for larger genome-wide association studies (GWASs). Using big data, statistical methods, and machine learning, many outcomes can be predicted by analyzing the many genes which can influence most traits. Already, the height a child will grow to can be predicted to within an inch (assuming they get adequate nutrition) by analyzing thousands of genes.

Two major types of enhancements which will benefit our offspring are discussed in length by Metzl – increased intelligence and increased healthspan, and it’s worth discussing some of his main findings here. (Other possible enhancements he notes are increased empathy, supersensory capabilities, increased physical stamina and strength, increased beauty, increased ability to extract nutrition from foods, and better ability to tolerate mircrogravity and  radiation.)

Regarding intelligence, the Minnestota Family Twin study found that 70% of IQ is genetic. More recent works put the number somewhat lower (about 50%), but a surprising amount is hereditary, and the variance due to genetics is significant (about 15 points of IQ in each direction). The rest seems to be largely due to things like childhood nutrition and having a rich environment as a kid. Higher IQ provides many benefits. Among them is a better ability to adapt to change and work in a dynamic environment where you constantly have to learn new skills. Statistically, people with lower IQ tend to work jobs with a regular routine, such as service positions. Currently, those with low IQ can still have a great life (there’s no evidence IQ correlates with happiness), and low-IQ people can learn a trade where there is reliable demand, become very good at it, and be valued by society. With the advent of AI and robotics, this is rapidly changing, and the risk of large-scale technological unemployment is real. Metzl asks, in light of this, is it really fair that we are trusting the economic wellbeing of our children to the genetic lottery of sexual recombination? It’s already not easy to compensate for a bad draw in the genetic lottery. Additionally, if other parents are doing it, why would any parent want to risk their child being far behind their peers? According to Metzl, the choice will be clear for parents in the future.

The second major area where genetic engineering will have an effect is aging. The diseases of aging were not something evolution cared much about, so there are likely genetic hacks that are possible but were just never selected for – it’s an area ripe for optimization.  For a glimpse of what is possible, Metzl has us consider the naked mole rat, a species which is remarkable in many ways (click here for a  full list of ways this species is special). Most notably, naked mole rats don’t exhibit the normal signs of aging, and they don’t get cancer. Thus, as odd as it may seem, the naked mole rat is the subject of intense research, and this humble species even serves as a sort of touchstone increasing the confidence of venture capitalists investing in longevity biotech startups in Silicon Valley. According to Metzl, “Calico, Google’s San Francisco–based life-extension company, maintains one of the world’s largest captive colonies of naked mole rats to see if it can uncover biomarkers of aging and unlock the secrets of naked mole rat longevity.”

It seems that genetic engineering will eventually be accepted as the ethically superior way of creating children – no one will want to leave something as important as the health and economic wellbeing of their children to blind chance. Human beings naturally crave control and certainty where possible — that’s why we give our kids vaccines and parents spend thousands of dollars on prophylactic dental procedures such as orthodontics or the removal of wisdom teeth. Yes, there will always be some hold-outs who will want to stick with “traditional conception”, but after reading Metzl’s book I can’t help but think that eventually the numbers will be quite small. Consider, for instance, that even the Amish use modern medicine.

The scientific and technological path to a much more healthy world, with much less suffering and longer, healthier lives is clear. There are straightforward steps we can take to reduce congenital ailments, for instance. However, there’s a real chance we may delay even this for decades, causing much needless suffering. Part of the reason is that any discussions of the subject immediately bring up a lot of cultural baggage from the horrible legacy of eugenics. The horrors of eugenics form an unfortunate negative emotional halo around any discussion of genetic engineering. While the eugenics movement is largely dead, the subject is so important that Metzl rightly devotes a large part of the book to it. Concerns about a re-emergence of the horrors of eugenics are legitimate, but conflation of what is being proposed with those horrors is not. Eugenicists advocated forced sterilization, whereas nobody is proposing that today. Instead, all that is being proposed is that parents have a choice in how their children are conceived. However, there is a real concern that parents will voluntarily choose children with certain biases, such lighter skin and heterosexuality. There are also concerns that the creation of genetically engineered “super children” would lead to a caste system of some sort, leading to a highly in-equitable society where the non-genetically-engineered are constantly discriminated against and made to feel unworthy. Metzl acknowledges each of these risks as real, but he also points out that none of the scenarios are inevitable and asks the reader to consider the benefits of genetic engineering as well, some of which we previously discussed. He notes that our current world is already very unequal in terms of genetics. Might a bit more genetic inequality be acceptable, Metzl asks, if the children created make enormous contributions to the arts and sciences which benefit all of humanity? Regarding whether a caste system might form, Metzl suggests that we must work to ensure the technology is widely distributed (at one point I recall he suggests insurance companies might have an incentive to provide genetic engineering as it would reduce health costs later on). A bigger horror, Metzl suggests, is not genetic inequality, but perfect genetic equality – the creation of a uniform generation of cookie-cutter children, where misfits and non-neurotypicals (which have historically contributed so much) have been selected out.  Each of these concerns are real, and Metzl doesn’t try to argue otherwise.

While ethical concerns may stifle the development of genetic engineering, a different scenario is a genetic arms race. In other areas such as AI, China is making more aggressive investments in genetic technology – a “$9 billion, fifteen-year investment to improve national leadership in precision medicine”. Metzl points out that the Chinese seem to have far fewer hang-ups around the subject and are blazing full steam ahead.

While the author is sympathetic to genetic engineering, the book presents a balanced treatment and never waxes too polemical. The first part of the book is mostly about the science. The later sections, on the ethical concerns and the genetic arms race scenario, are the most thought-provoking and are parts I may re-listen to at some point. Overall, this book is a very timely and thought-provoking introduction to the subject.

Dan Elton, Ph. D., is Director of Scholarship for the U.S. Transhumanist Party.