The Application Of Machine Learning To Evidence Based Medicine

 

What if, bear with me now, what if the phase 3 clinical trials for mRNA therapeutics conducted on billions of unsuspecting, hoodwinked and bamboozled humans, was a new kind of research done to yield a new depth and breadth of clinical data exceptionally useful toward breaking up logjams in clinical terminology as well as experimental sample size? Vaxxed vs. Unvaxxed the subject of long term gubmint surveillance now. To what end?

Nature  | Recently, advances in wearable technologies, data science and machine learning have begun to transform evidence-based medicine, offering a tantalizing glimpse into a future of next-generation ‘deep’ medicine. Despite stunning advances in basic science and technology, clinical translations in major areas of medicine are lagging. While the COVID-19 pandemic exposed inherent systemic limitations of the clinical trial landscape, it also spurred some positive changes, including new trial designs and a shift toward a more patient-centric and intuitive evidence-generation system. In this Perspective, I share my heuristic vision of the future of clinical trials and evidence-based medicine.

Main

The last 30 years have witnessed breathtaking, unparalleled advancements in scientific research—from a better understanding of the pathophysiology of basic disease processes and unraveling the cellular machinery at atomic resolution to developing therapies that alter the course and outcome of diseases in all areas of medicine. Moreover, exponential gains in genomics, immunology, proteomics, metabolomics, gut microbiomes, epigenetics and virology in parallel with big data science, computational biology and artificial intelligence (AI) have propelled these advances. In addition, the dawn of CRISPR–Cas9 technologies has opened a tantalizing array of opportunities in personalized medicine.

Despite these advances, their rapid translation from bench to bedside is lagging in most areas of medicine and clinical research remains outpaced. The drug development and clinical trial landscape continues to be expensive for all stakeholders, with a very high failure rate. In particular, the attrition rate for early-stage developmental therapeutics is quite high, as more than two-thirds of compounds succumb in the ‘valley of death’ between bench and bedside^1,2. To bring a drug successfully through all phases of drug development into the clinic costs more than 1.5–2.5 billion dollars (refs. 3, 4). This, combined with the inherent inefficiencies and deficiencies that plague the healthcare system, is leading to a crisis in clinical research. Therefore, innovative strategies are needed to engage patients and generate the necessary evidence to propel new advances into the clinic, so that they may improve public health. To achieve this, traditional clinical research models should make way for avant-garde ideas and trial designs.

Before the COVID-19 pandemic, the conduct of clinical research had remained almost unchanged for 30 years and some of the trial conduct norms and rules, although archaic, were unquestioned. The pandemic exposed many of the inherent systemic limitations in the conduct of trials⁵ and forced the clinical trial research enterprise to reevaluate all processes—it has therefore disrupted, catalyzed and accelerated innovation in this domain^6,7. The lessons learned should help researchers to design and implement next-generation ‘patient-centric’ clinical trials.

Chronic diseases continue to impact millions of lives and cause major financial strain to society⁸, but research is hampered by the fact that most of the data reside in data silos. The subspecialization of the clinical profession has led to silos within and among specialties; every major disease area seems to work completely independently. However, the best clinical care is provided in a multidisciplinary manner with all relevant information available and accessible. Better clinical research should harness the knowledge gained from each of the specialties to achieve a collaborative model enabling multidisciplinary, high-quality care and continued innovation in medicine. Because many disciplines in medicine view the same diseases differently—for example, infectious disease specialists view COVID-19 as a viral disease while cardiology experts view it as an inflammatory one—cross-discipline approaches will need to respect the approaches of other disciplines. Although a single model may not be appropriate for all diseases, cross-disciplinary collaboration will make the system more efficient to generate the best evidence.

Over the next decade, the application of machine learning, deep neural networks and multimodal biomedical AI is poised to reinvigorate clinical research from all angles, including drug discovery, image interpretation, streamlining electronic health records, improving workflow and, over time, advancing public health (Fig. 1). In addition, innovations in wearables, sensor technology and Internet of Medical Things (IoMT) architectures offer many opportunities (and challenges) to acquire data⁹. In this Perspective, I share my heuristic vision of the future of clinical trials and evidence generation and deliberate on the main areas that need improvement in the domains of clinical trial design, clinical trial conduct and evidence generation.

Fig. 1: Timeline of drug development from the present to the future.

The figure represents the timeline from drug discovery to first-in-human phase 1 trials and ultimately FDA approval. Phase 4 studies occur after FDA approval and can go on for several years. There is an urgent need to reinvigorate clinical trials through drug discovery, interpreting imaging, streamlining electronic health records, and improving workflow, over time advancing public health. AI can aid in many of these aspects in all stages of drug development. DNN, deep neural network; EHR, electronic health records; IoMT, internet of medical things; ML, machine learning.

Full size image

Clinical trial design

Trial design is one of the most important steps in clinical research—better protocol designs lead to better clinical trial conduct and faster ‘go/no-go’ decisions. Moreover, losses from poorly designed, failed trials are not only financial but also societal.

Challenges with randomized controlled trials

Randomized controlled trials (RCTs) have been the gold standard for evidence generation across all areas of medicine, as they allow unbiased estimates of treatment effect without confounders. Ideally, every medical treatment or intervention should be tested via a well-powered and well-controlled RCT. However, conducting RCTs is not always feasible owing to challenges in generating evidence in a timely manner, cost, design on narrow populations precluding generalizability, ethical barriers and the time taken to conduct these trials. By the time they are completed and published, RCTs become quickly outdated and, in some cases, irrelevant to the current context. In the field of cardiology alone, 30,000 RCTs have not been completed owing to recruitment challenges¹⁰. Moreover, trials are being designed in isolation and within silos, with many clinical questions remaining unanswered. Thus, traditional trial design paradigms must adapt to contemporary rapid advances in genomics, immunology and precision medicine¹¹.

"Behavioral Genetics" "Social Science Genomics" - By Any Name - Race "Science" Still Turd-Frosting

newyorker |  Last summer, an anonymous intermediary proposed to Harris and Harden that they address their unresolved issues. Harden appeared on Harris’s podcast, and patiently explained why Murray’s speculation was dangerously out in front of the science. At the moment, technical and methodological challenges, as well as the persistent effects of an unequal environment, would make it impossible to conduct an experiment to test Murray’s idly incendiary hypotheses. She refused to grant that his provocations were innocent: “I don’t disagree with you about insisting on intellectual honesty, but I think of it as ‘both/and’—I think that that value is very important, but I also find it very important to listen to people when they say, ‘I’m worried about how this idea might be used to harm me or my family or my neighborhood or my group.’ ” (Harris declined to comment on the record for this piece.) As she once put it in an essay, “There is a middle ground between ‘let’s never talk about genes and pretend cognitive ability doesn’t exist’ and ‘let’s just ask some questions that pander to a virulent on-line community populated by racists with swastikas in their Twitter bios.’ ”

Harden is not alone in her drive to fulfill Turkheimer’s dream of a “psychometric left.” Dalton Conley and Jason Fletcher’s book, “The Genome Factor,” from 2017, outlines similar arguments, as does the sociologist Jeremy Freese. Last year, Fredrik deBoer published “The Cult of Smart,” which argues that the education-reform movement has been trammelled by its willful ignorance of genetic variation. Views associated with the “hereditarian left” have also been articulated by the psychiatrist and essayist Scott Alexander and the philosopher Peter Singer. Singer told me, of Harden, “Her ethical arguments are ones that I have held for quite a long time. If you ignore these things that contribute to inequality, or pretend they don’t exist, you make it more difficult to achieve the kind of society that you value.” He added, “There’s a politically correct left that’s still not open to these things.” Stuart Ritchie, an intelligence researcher, told me he thinks that Harden’s book might create its own audience: “There’s so much toxicity in this debate that it’ll take a long time to change people’s minds on it, if at all, but I think Paige’s book is just so clear in its explanation of the science.”

The nomenclature has given Harden pause, depending on the definition of “hereditarian,” which can connote more biodeterminist views, and the definition of “left”—deBoer is a communist, Alexander leans libertarian, and Harden described herself to me as a “Matthew 25:40 empiricist” (“The King will reply, ‘Truly I tell you, whatever you did for one of the least of these brothers and sisters of mine, you did for me’ ”). The political sensitivity of the subject has convinced many sympathetic economists, psychologists, and geneticists to keep their heads below the parapets of academia. As the population geneticist I spoke to put it to me, “Geneticists know how to talk about this stuff to each other, in part because we understand terms like ‘heritability,’ which we use in technical ways that don’t always fully overlap with their colloquial meanings, and in part because we’re charitable with each other, assume each other’s good faith—we know that our colleagues aren’t eugenicists. But we have no idea how to talk about it in public, and, while I don’t agree with everything she said, sometimes it feels like we’ve all been sitting around waiting for a book like Paige’s.”

Harden’s outspokenness has generated significant blowback from the left. On Twitter, she has been caricatured as a kind of ditzy bourgeois dilettante who gives succor to the viciousness of the alt-right. This March, after she expressed support for standardized testing—which she argues predicts student success above and beyond G.P.A. and can help increase low-income and minority representation—a parody account appeared under the handle @EugenicInc, with the name “Dr. Harden, Social Justice Through Eugenics!” and the bio “Not a determinist, but yes, genes cause everything. I just want to breed more Hilary Clinton’s for higher quality future people.” One tweet read, “In This House We Believe, Science is Real, Womens Rights are Human Rights, Black Lives Matter, News Isnt Fake, Some Kids Have Dumb-Dumb Genes!!!”

In 2018, she wrote an Op-Ed in the Times, arguing that progressives should embrace the potential of genetics to inform education policy. Dorothy Roberts, a professor of law, sociology, and Africana studies at the University of Pennsylvania, strongly disagreed: “There’s just no way that genetic testing is going to lead to a restructuring of society in a just way in the future—we have a hundred years of evidence for what happens when social outcomes are attributed to genetic differences, and it is always to stigmatize, control, and punish the people predicted to have socially devalued traits.” Darity, the economist, told me that he doesn’t see how Harden can insist that differences within groups are genetic but that differences between them are not: “It’s a feint and a dodge for her to say, ‘Well, I’m only looking at variations across individuals.’ ”

There is a good precedent for this kind of concern. In “Blueprint,” Robert Plomin wrote that polygenic scores should be understood as “fortune tellers” that can “foretell our futures from birth.” Jared Taylor, a white-supremacist leader, argued that Plomin’s book should “destroy the basis for the entire egalitarian enterprise of the last 60 or so years.” He seized on Plomin’s claim that, for many outcomes, “environmental levers for change are not within our grasp.” Taylor wrote, “This is a devastating finding for the armies of academics and uplift artists who think every difference in outcome is society’s fault.” He continued, “And, although Blueprint includes nothing about race, the implications for ‘racial justice’ are just as colossal.” Harden has been merciless in her response to behavior geneticists whose disciplinary salesmanship—and perhaps worse—inadvertently indulges the extreme right. In her own review of Plomin’s book, she wrote, “Insisting that DNA matters is scientifically accurate; insisting that it is the only thing that matters is scientifically outlandish.” ​(Plomin told me that Harden misrepresented his intent. He added, “Good luck to Paige in convincing people who are engaged in the culture wars about this middle path she’s suggesting. . . . My view is it isn’t worth confronting people and arguing with them.”)

With the first review of Harden’s book, these dynamics played out on cue. Razib Khan, a conservative science blogger identified with the “human biodiversity” movement, wrote that he admired her presentation of the science but was put off by the book’s politics; though he notes that a colleague of his once heard Harden described as “Charles Murray in a skirt,” he clearly thinks the honorific was misplaced. “Alas, if you do not come to this work with Harden’s commitment to social justice, much of the non-scientific content will strike you as misguided, gratuitous and at times even unfair.” This did not prevent some on the Twitter left from expressing immediate disgust. Kevin Bird, who describes himself in his Twitter bio as a “radical scientist,” tweeted, “Personally, I wouldn’t be very happy if a race science guy thought my book was good.” Harden sighed when she recounted the exchange: “It’s always from both flanks. It felt like another miniature version of Harris on one side and Darity on the other.”

The Delta Variant Narrative Eloquently Makes The Case For A Malfeasant Elite Agenda

Data show that:
Experimental mRNA Therapeutic Jabs REDUCE: symptoms, hospital admissions, and fatalities.

Data also show that:
The mRNA jabbed STILL become: infected; symptomatic; infectious; even super spreaders.

So what exactly does the planned vaccination passport aim to achieve other than a backdoor around lockdown protections and to create a two tiered political economy with no genuine biosecurity utility - only seething interpersonal resentment?

Polio vaccine gives a rough approximation of “sterilizing immunity.” You can fight off any infections by the polio virus for pretty much the rest of your life.

The state of the art Coronavirus ‘mRNA Therapeutics’ are showing a steep drop off in effectiveness after six to eight months. Even with that, vaccinated individuals can and do catch Covid and spread Covid.

Have you ever heard or read of someone who has had a polio vaccination giving it to anyone else afterward?

Even when people are willing to get the coronavirus ‘mRNA jab,’ most of the working class in this country cannot afford the opportunity costs of getting the ‘jab.’ No health ‘care,’ no paid, or even unpaid time off to recover from the after effects many experience from having had the shots, etc.

For some as yet unspecified reasons, the American Health Establishment has massively bungled its handling of the Coronavirus Pandemic. Even now, the ‘vaccinated’ are told that they do not need to mask in public, even when the evidence says otherwise; even when they can be the disease vectors that ignite new ‘hot spots’ of infection - simply by not staying masked in public.

I am highly suspicious of the nature of the “bungling” in evidence in Britain and America.

I suspect now that a decision was made to let the disease run wild so as to “cull the herd.” Having survived an infection last year, I've become emotionally detached from the demographic sub-populations targetted for Covid 'culling,’

Some years ago, I would more openly profess my Malthusian predilections. However, now that I can plainly see a cull being effected by Elites via nullification of the Social Contract - I'm much less sanguine about the prospects for population control and much clearer about the utility of plague for human livestock management. 

NYTimes |  Those who have been inoculated against the coronavirus have little to worry about. Reports of infections with the Delta variant among fully immunized people in Israel may have alarmed people, but virtually all of the available data indicate that the vaccines are powerfully protective against severe illness, hospitalization and death from all existing variants of the coronavirus.

Even a single dose of vaccines that require two shots seems to prevent the most severe symptoms, although it is a flimsier barrier against symptomatic illness — making it an urgent priority to give people second doses in places like Britain that opted to prioritize first doses.

“When you have populations of unvaccinated individuals, then the vaccines really can’t do their jobs,” said Stacia Wyman, an expert in computational genomics at the University of California, Berkeley. “And that’s where Delta is really a concern.”

Britain’s experience with the Delta variant has highlighted the importance not just of vaccination, but the strategy underlying it. The country ordered inoculations strictly by age, starting with the oldest and carving out few exceptions for younger essential workers, outside of the medical profession.

 

 

The SMART Healthcards Framework

unlimitedhangout |  The SMART Health Cards framework was developed by a team led by the chief architect of Microsoft Healthcare, Josh Mandel, who was previously the Health IT Ecosystem lead for Verily, formerly Google Life Sciences. Verily is currently heavily involved in COVID-19 testing throughout the United States, particularly in California, and links test recipients’ results to their Google accounts. Their other COVID-19 initiatives have been criticized due to still-unresolved privacy concerns, something that has also plagued several of Verily’s other efforts pre-COVID-19, including those involving Mandel.

Of particular concern is that Verily, and by extension Google, created Project Baseline, which has been collecting “actionable genetic information” with a focus on “population health” from participants since 2017. Yet, during the COVID-19 process, Project Baseline has become an important component of Verily’s COVID-19 testing efforts, raising the unsettling possibility that Verily has been obtaining Americans’ DNA data through its COVID-19 testing activities. While Verily has not addressed this possibility directly, it is worth noting that Google has been heavily involved in amassing genomic data for several years. For instance, in 2013, Google Genomics was founded with the goal of storing and analyzing DNA data on Google Cloud servers. Now known as Cloud Life Sciences, the Google subsidiary has since developed AI algorithms that can “build your genome sequence” and “identify all the mutations that an individual inherits from their parents.”

Google also has close ties with the best-known DNA testing companies in the United States, such as Ancestry.com. Ancestry, recently purchased by private-equity behemoth Blackstone, shares data with a secretive Google subsidiary that uses genomic data to develop lifespan-extending therapies. In addition, the wife of Google cofounder Sergey Brin, Anne Wojcicki, is the cofounder and CEO of DNA testing company 23andMe. Wojcicki is also the sister of the CEO of Google-owned YouTube, Susan Wojcicki.

Google and the majority of VCI’s backers—Microsoft, Salesforce, Cerner, Epic, the Mayo Clinic, and MITRE Corporation, Change Healthcare—are also prominent members of the MITRE-run COVID-19 Healthcare Coalition. Other members of that coalition include the CIA’s In-Q-Tel and the CIA-linked data-mining firm Palantir, as well as a myriad of health-care and health-record companies. The coalition fits well with the ambitions of Google and like-minded companies that have sought to gain access to troves of American health data under the guise of combatting COVID-19.

The COVID-19 Healthcare Coalition describes itself as a public-private partnership that has enabled “the critical infrastructure to enable collaboration and shared analytics” on COVID-19 through the sharing of health-care and COVID-19 data among members. That this coalition and VCI are intimately involved with MITRE Corporation is significant, given that MITRE is a well-known, yet secretive, contractor for the US government, specifically the CIA and other intelligence agencies, which has developed Orwellian surveillance and biometric technologies, including several now focused on COVID-19.

Just three days before the public announcement of VCI’s establishment, Microsoft Healthcare and Google’s Verily announced a partnership along with MIT and Harvard’s Broad Institute to share the companies’ cloud data and AI technologies with a “global network of more than 168,000 health and life sciences partners” to accelerate the Terra platform. Terra, originally developed by the Broad Institute and Verily, is an “open data ecosystem” focused on biomedical research, specifically the fields of cancer genomics, population genetics, and viral genomics. The biomedical data Terra amasses includes not only genetic data but also medical-imaging, biometric signals, and electronic health records. Google, through its partnership with the Pentagon, which was announced last September, has moved to utilize the analysis of such data in order to “predictively diagnose” diseases such as cancer and COVID-19. US military contractors, such as Advanced Technology International, have been developing wearables that would apply that AI-driven predictive diagnosis technology to COVID-19 diagnoses.

(B x C x D = AHH) Biological Knowledge X Computing Power X Data = Ability To Hack Humans

Reuters |  BGI Group, the world’s largest genomics company, has worked with China’s military on research that ranges from mass testing for respiratory pathogens to brain science, a Reuters review of research, patent filings and other documents has found.

The review, of more than 40 publicly available documents and research papers in Chinese and English, shows BGI’s links to the People’s Liberation Army (PLA) include research with China’s top military supercomputing experts. The extent of those links has not previously been reported.

BGI has sold millions of COVID-19 test kits outside China since the outbreak of the new coronavirus pandemic, including to Europe, Australia and the United States. Shares of BGI Genomics Co, the company’s subsidiary listed on the Shenzhen stock exchange, have doubled in price over the past 12 months, giving it a market value of about $9 billion.

But top U.S. security officials have warned American labs against using Chinese tests because of concern China was seeking to gather foreign genetic data for its own research. BGI has denied that.

The documents reviewed by Reuters neither contradict nor support that U.S. suspicion. Still, the material shows that the links between the Chinese military and BGI run deeper than previously understood, illustrating how China has moved to integrate private technology companies into military-related research under President Xi Jinping.

The U.S. government has recently been warned by an expert panel that adversary countries and non-state actors might find and target genetic weaknesses in the U.S. population and a competitor such as China could use genetics to augment the strength of its own military personnel.

BGI has worked on PLA projects seeking to make members of the ethnic Han Chinese majority less susceptible to altitude sickness, Reuters found, genetic research that would benefit soldiers in some border areas.

Elsa Kania, an adjunct senior fellow at the Center for a New American Security think tank, who has provided testimony to U.S. Congressional committees, told Reuters that China’s military has pushed research on brain science, gene editing and the creation of artificial genomes that could have an application in future bioweapons. She added that such weapons are not currently technically feasible.

BGI’s pattern of collaboration with the Chinese military was a “reasonable concern to raise” for U.S. officials, said Kania.

 

I'm NOT The Only Cat Seriously Fixated On The Low-Hanging Cornucopia Of SARS-CoV2 Fruit

harvardtothebighouse |  Some of the dystopian carnage creeping across China may be due to the fact that much of China’s population may have already been exposed to coronavirus infection via SARS or other less notorious strains, which would allow the Wuhan Stain COVID-19 to use antibody-dependent enhancement to much more efficiently enter into cells, and then become much more virulent since this enhancement hijacks the body’s preexisting immune response to coronavirus infections and allows easier entry. However whether or not people have been exposed to a coronavirus infection before, once it’s been circulating in a population for long enough the Wuhan Strain may be able to reinfect its own past hosts and use this molecular hijacking on antibodies left from its own previous infection to become far more virulent, regardless of whether or not someone has been exposed to other coronaviruses before COVID-19. And early reporting from Chinese doctors indicates that re-infections of the Wuhan Strain are far more lethal than the first.

– Additionally, although another since-retracted pre-print noted several very short genomic sequences in COVID-19’s spike-protein gene that look far more similar to sequences found in HIV than to other coronaviruses – critics quickly pointed out that the shared homology didn’t reach statistical significance. However a closer look at the data reveals that there were a few small shared genomic segments that, despite being physically separated from each other along each strand of DNA, all worked together to code for the Wuhan Strain’s protein-spike’s crucial receptor binding site. Something that is highly unlikely to have happened by chance. And despite most of its protein-spike being shared with SARS, these substituted segments weren’t shared at all – nor were they found in any other coronavirus. One possible but likely reason for these HIV-like segments is that they were meant to be epitopes, or molecular flags meant to mark intruders for a vaccine to target. It is mathematically possible for this to happen in nature – but only in a ten-thousand bats chained to ten-thousand Petri dishes and given until infinity sense. Alternatively, it could also be produced by infecting a room full of ferrets with a bespoke coronavirus vaccine and sifting through the wreckage for your genomic needle.

– Critics have brushed off the Wuhan Strain’s shared homology with HIV as statistically insignificant, however clinical reporting indicates that the Wuhan Strain may be using this shared HIV homology to attack CD4 immune cells just like HIV does, as an unusually high percentage of patients are showing low white blood cell counts, especially the sickest ones. This pathogenicity may well be due to the unique HIV-live genomics of the Wuhan Strain, as one white-paper by LSU’s professor emeritus of Microbiology, Immunology, and Parasitology who’s also a Harvard-educated virologist with a PhD in Microbiology and Molecular Genetics notes: “This is the first description of a possible immunosuppressive domain in coronaviruses… The three key [mutations] common to the known immunosuppressive domains are also in common with the sequence from [the spike-protein]. While coronaviruses are not known for general immunosuppression of the style shown by HIV-1, this does not rule out immunosuppression at the site of active infection in the lung, which would prolong and potentially worsen infection at that site.” And early research has indicated that this unique region may make COVID-19 up to 1,000 times more likely to bind to human cells than SARS.

– Even more troubling, a peer-reviewed study noted that one particular part of the Wuhan Strain’s spike-protein genome also wasn’t found in any of its relatives, “and may provide a gain-of-function to [COVID-19] for efficient spreading in the human population.”  And according to that paper, this particular type of furin cleavage site makes similar viruses both more pathogenic and more neurotoxic.

– Evidence for the Wuhan Strain’s neurotoxicity arrived in late February, in a published paper which notes that “the most characteristic symptom of COVID‐19 patients is respiratory distress, and most of the patients admitted to the intensive care could not breathe spontaneously.” Combined with the observation that “some COVID‐19 patients also showed neurologic signs such as headache, nausea and vomiting,” this paper asserts that since SARS was found heavily concentrated in the brainstems of its autopsied victims, COVID-19 is also probably crossing the blood-brain barrier and killing its victims not just via pneumonia, but also by causing neurological respiratory failure.

– And it should be noted that SARS – much ballyhooed as a close relative to the Wuhan Strain – didn’t notable effect white blood cell counts.  Additionally, clinical treatment guides published online in late January by established Chinese medical sources note the progressive reduction of white blood cells, as well as the importance of monitoring this decline. And reporting from Thailand indicates that adding a cocktail of two different anti-HIV drugs to the typical flu treatment regime seemed to effectively knock back the Wuhan Strain. Additionally, one of the only autopsies performed outside of China to date found that the deceased had a severely depleted white blood cell count. These lowered counts may come from this shared similarity with HIV, or it could also be the result of antibody-dependent enhancement as well, since this phenomenon primarily targets white blood cells for its hijackings and may help explain why consecutive infections are so lethal.

– In a highly concerning turn, scientists have noted that the Wuhan Strain can have a “striking” short term rate of mutation which doesn’t indicate an artificial origin but captures the unique threat posed by this coronavirus regardless of its providence, since a faster mutation rates makes it more likely this virus can dodge testing and neutralize vaccines. Something there is already early evidence for. Further concerning are reports out of China that even patients who appear cured still harbor COVID-19 in their system, and although the full implications of this are not yet known – none of them are good.

– One of the worst possible scenarios for COVID-19’s mutation rate would be if it falls into the Goldilocks range that would allow it to form mutant viral swarms: too many mutations will cause a virus to eventually implode, not enough allows host immune systems to catch-up, but if things are just right mutant swarms can form and spread across host populations, burrowing into host nervous systems and causing permanent neurological damage. Mutant swarms form when a virus produces mutationally-damaged copies of itself inside a host, some of which aren’t infectious but find their way into the nervous system where they burrow in causing damage, and others that combine with complimentary broken copies inside host cells to produce working infectious copies of the virus. So a host can not only become crippled with neurological issues, but also still be producing infectious copies of the virus. And it seems as if COVID-19 has many characteristics that indicate the potential to form mutant swarms: the “striking” mutation rate mentioned above and the fact a second widespread mutated strain seems to have already emerged in Washington State with many other isolated strains reported elsewhere, crossing between species is another factor and a dog in Hong Kong appears to have tested positive, the fact that the Wuhan Strain can infect not only the respiratory tract but feces as well – multi-organ involvement is an important contributor to viral swarms, and finally the markedly viral load rate of COVID-19 compared to SARS – SARS produced a viral load several times lower which decreased over time, while COVID-19 produces a “very high” viral load that appears to increase over time and can peak several orders of magnitude higher than SARS was measured to reach. And alarming evidence that this phenomenon is occurring emerged from a Chinese pre-print which noted that over one-third of the roughly 200 patients studied has some neurological symptoms, with nearly half of the most severe patients exhibiting neurological issues.

– Another exceptional trait of the Wuhan Strain COVID-19 is that not only does it form its own clade, it’s calculated to have diverged from SARS and its other sister coronaviruses some 260 years ago. And yet in all that time, while it every other branch of the coronavirus tree was busy branching-off into countless variants, if it emerged naturally, COVID-19 somehow spent a quarter of a millennium as the lone known example of its clade, somehow not mutating into related lineages in all that time. Another simpler explanation is that this apparent hereditary distance and genetic uniqueness is the just the result of being altered in a lab. And although two distinct strains of COVID-19 have been identified, there’s no reason to believe this mutational differentiation happened before contact with humans in December of 2019. Additionally, when neutral sites, the specific points in the genome which most reliably show evolutionary change, were examined: COVID-19 looks even more evolutionarily distant from any of its possible relatives.

– Also giving credence to the idea that the Wuhan Strain was bio-engineered is the existence of a patent application registered to a scientist from Wuhan that looks to modulate a coronavirus’ spike-protein genes – the precise region altered by Zhengli Shi at UNC to make a hyper-virulent strain of coronavirus, and whose alteration and adaptation would explain the Wuhan Strain’s unusual behavior as discussed above.

Father Of Synthetic Genomics Better Be Careful Tampering With Whydte Folks Money....,

Genomeweb |  Human Longevity (HLI) is suing the J. Craig Venter Institute (JCVI) and a number of unknown defendants over the misappropriation and use of trade secrets passed along by Craig Venter, the founder of both the company and the institute that bears his name.

In a complaint filed last Friday with the US District Court for the Southern District of California, Human Longevity alleges that upon his termination from HLI on May 24, Venter took a company-owned laptop with trade secrets and passed on protected information to the Venter Institute, of which he is chairman and CEO. HLI also claims that the institute is working on a product that will compete with its own business.

According to the complaint, Venter was CEO of Human Longevity from 2014 until January 2017, when he became the firm's executive chairman and signed a "proprietary information and inventions" agreement. He assumed the role of interim CEO in November of 2017 until his employment was terminated in May of this year. During his time at HLI, Venter used a company-owned laptop computer, the contents of which were backed up in the cloud, and consistently used his JCVI email address rather than his HLI email to conduct company business, the complaint states.

In the spring of this year, Venter "withheld critical information from the board and the HLI investors regarding the conduct of an HLI key executive which would likely result in termination," the complaint says. Further, in May, Venter had an HLI-paid counsel "draft a Venter-favorable employment contract" and appointed a new interim president without conferring with the HLI board first.

On May 24, the HLI board "considered a rushed investor deal which Venter presented to them only less than two weeks earlier," the terms of which the board considered one-sided. The deal would have provided financial incentives to Venter and offered the new investor rights that had already been granted to another party, according to the complaint. "At that point, the HLI board voted to terminate Venter from HLI," it states.

Following his termination, Venter left the HLI offices with the company-owned laptop and "immediately began using the HLI computer and server to communicate to the public, solicit HLI investors and employees," the complaint says. In a Twitter message on May 24, Venter said that he was retiring from HLI and returning to JCVI.

His access to the HLI server and HLI emails was disabled the next day, but the company alleges that "even after his HLI termination, Venter used the HLI computer, accessed and sent HLI proprietary information and trade secrets," including communications involving Series C and Asia JV Series A documents.

Genetics in the Madhouse: The Unknown History of Human Heredity

nature  |  Who founded genetics? The line-up usually numbers four. William Bateson and Wilhelm Johannsen coined the terms genetics and gene, respectively, at the turn of the twentieth century. In 1910, Thomas Hunt Morgan began showing genetics at work in fruit flies (see E. Callaway Nature 516, 169; 2014). The runaway favourite is generally Gregor Mendel, who, in the mid-nineteenth century, crossbred pea plants to discover the basic rules of heredity.

Bosh, says historian Theodore Porter. These works are not the fount of genetics, but a rill distracting us from a much darker source: the statistical study of heredity in asylums for people with mental illnesses in late-eighteenth- and early-nineteenth-century Britain, wider Europe and the United States. There, “amid the moans, stench, and unruly despair of mostly hidden places where data were recorded, combined, and grouped into tables and graphs”, the first systematic theory of mental illness as hereditary emerged.

For more than 200 years, Porter argues in Genetics in the Madhouse, we have failed to recognize this wellspring of genetics — and thus to fully understand this discipline, which still dominates many individual and societal responses to mental illness and diversity.

The study of heredity emerged, Porter argues, not as a science drawn to statistics, but as an international endeavour to mine data for associations to explain mental illness. Few recall most of the discipline’s early leaders, such as French psychiatrist, or ‘alienist’, Étienne Esquirol; and physician John Thurnam, who made the York Retreat in England a “model of statistical recording”. Better-known figures, such as statistician Karl Pearson and zoologist Charles Davenport — both ardent eugenicists — come later.

Inevitably, study methods changed over time. The early handwritten correlation tables and pedigrees of patients gave way to more elaborate statistical tools, genetic theory and today’s massive gene-association studies. Yet the imperatives and assumptions of that scattered early network of alienists remain intact in the big-data genomics of precision medicine, asserts Porter. And whether applied in 1820 or 2018, this approach too readily elevates biology over culture and statistics over context — and opens the door to eugenics.

American Nations As Revealed In Identity By Descent (IBD) Networks

medium  |  Earlier this summer, I presented the American Nations: the eleven regional cultures that comprise the United States and North America. Their existence explains much about our history, our constitutional arrangements, and, indeed, our political fissures — past and present. If you have any ancestors who were living in North America prior to the Civil War, the existence of these rival nations is likely reflected in parts of your family tree and, according to a recent study published in Nature Communications, may very well have left a mark on your DNA.

I couldn’t miss this study, because shortly after it came out, readers of my 2011 book, American Nations: A History of the Eleven Rival Regional Cultures of North America, were stuffing my inbox and flooding my social media feeds with it. A glance at the thumbnail illustration that accompanied the study made it clear why: Unbeknownst to the scientists who’d written the paper, the map depicting the key results of their research on the patterns of genetic variation in North America over time and space mirrored the American Nations map to an uncanny degree.

Here they are for comparison:

Clustering of 770,000 genomes reveals post-colonial population structure of North america. Nature Communications 8 (2017)

This is remarkable because the American Nations paradigm is resolutely not about genetics or genealogy. Rather, it’s built on the late cultural geographer Wilbur ZeFrolinsky’s Doctrine of First Effective Settlement, which argues that when a “new” society is settled, the cultural characteristics of the initial settlement group will have a lasting and outsized effect on the future trajectory of that society — even if their numbers were very small and those of later immigrants of different origins were very large. These lasting characteristics, which inform the dominant culture of entire regions of North America, are passed down culturally, not genetically, which explains why the Dutch-settled area around New York City still has obvious and distinct characteristics inherited from Golden Age Amsterdam, even though the portion of people there reporting Dutch ancestry to census takers is a vanishingly small 0.2 percent. Culture is learned, not inherited.

And yet the Nature study — powered by the enormous cross-referenced genomics and genealogy databases of Ancestry.com — reveals that the regional cultures have left a significant genetic imprint as well. That’s because members of a regional culture tended to mate with one another, rather than with people from rival areas, even when those rivals lived nearby, in the very same colony or state.

“Who we are today — the genetics of Americans all over the place — is the result of all kinds of cycles of reproductive isolation and the release of that isolation,” says Catherine A. Ball, a geneticist and the chief scientific officer at Ancestry who oversees the company’s DNA work. “Who your mates would be was linked to geography, politics, religion, war, and all of that is showing today in people walking on the streets and who they are related to.”

Ball wasn’t familiar with American Nations before I spoke with her, but the results show that the boundaries of the regional cultures were very real when it came to human reproduction, creating reproductive clusters centuries ago that geneticists have been able to recreate through the examination of nearly a million living Americans’ DNA.

Future Genomics: Don't Edit A Rough Copy When You Can Print A Fresh New One

technologyreview  |  It took Boeke and his team eight years before they were able to publish their first fully artificial yeast chromosome. The project has since accelerated. Last March, the next five synthetic yeast chromosomes were described in a suite of papers in Science, and Boeke says that all 16 chromosomes are now at least 80 percent done. These efforts represent the largest amount of genetic material ever synthesized and then joined together.

It helps that the yeast genome has proved remarkably resilient to the team’s visions and revisions. “Probably the biggest headline here is that you can torture the genome in a multitude of different ways, and the yeast just laughs,” says Boeke.

Boeke and his colleagues aren’t simply replacing the natural yeast genome with a synthetic one (“Just making a copy of it would be a stunt,” says Church). Throughout the organism’s DNA they have also placed molecular openings, like the invisible breaks in a magician’s steel rings. These let them reshuffle the yeast chromosomes “like a deck of cards,” as Cai puts it. The system is known as SCRaMbLE, for “synthetic chromosome recombination and modification by LoxP-mediated evolution.”

The result is high-speed, human-driven evolution: millions of new yeast strains with different properties can be tested in the lab for fitness and function in applications like, eventually, medicine and industry. Mitchell predicts that in time, Sc2.0 will displace all the ordinary yeast in scientific labs.

The ultimate legacy of Boeke’s project could be decided by what genome gets synthesized next. The GP-write group originally imagined that making a synthetic human genome would have the appeal of a “grand challenge.” Some bioethicists disagreed and sharply criticized the plan. Boeke emphasizes that the group will “not do a project aimed at making a human with a synthetic genome.” That means no designer people.

Ethical considerations aside, synthesizing a full human genome—which is over 250 times larger than the yeast genome—is impractical with current methods. The effort to advance the technology also lacks funding. Boeke’s yeast work has been funded by the National Science Foundation and by academic institutions, including partners in China, but the larger GP-write initiative has not attracted major support, other than a $250,000 initial donation from the computer design company Autodesk. Compare that with the Human Genome Project, which enjoyed more than $3 billion in US funding.

Like Genomics - Reality is Computational

edgarlowen |  A computational model is by far the most reasonable and fruitful approach to reality. The computational model of Universal Reality is both internally consistent and consistent with science and the scientific method. This may initially seem counter intuitive but there all sorts of convincing reasons supporting it.

There is overwhelming evidence that everything in the universe is its information or data only and that the observable universe is a computational system:

1. To be comprehensible, which it self-evidently is, reality must be a logically consistent structure. To be logical and to continually happen it must be computable. To be computable it must consist of data because only data is computable. Therefore the content of the observable universe must consist only of programs computing data.

2. The laws of science which best describe reality are themselves logico-mathematical information forms. Why would the equations of science be the best description of reality if reality itself didn’t also consist of similar information structures? This explains the so-called “unreasonable effectiveness of mathematics” in describing the universe (Wigner, 1960).

3. By recognizing that reality is a logico-mathematical structure the laws of nature immediately assume their natural place as an intrinsic part of reality. No longer do they somehow stand outside a physical world while mysteriously controlling it. A physical model of the universe is unable to explain where the laws of nature reside or what their status is (Penrose, 2005).

4. Physical mechanisms to produce effects become unnecessary in a purely computational world. It’s enough to have a consistent logico-mathematical program that computes them in accordance with experimental evidence.

5. When everything that mind adds to our perception of reality is recognized and subtracted all that remains of reality is a computational data structure. This is explained in detail below and can actually be confirmed by carefully analyzed direct experience.

6. We know that our internal simulation of reality exists as neurochemical data in the circuits of our brain. Yet this world appears perfectly real to us. If our cognitive model of reality consists only of data and seems completely real then it’s reasonable to assume that the actual external world could also consist only of data. How else could it be so effectively modeled as data in our brains if it weren’t data itself?

7. This view of reality is tightly consistent with the other insights of Universal Reality, which are cross-consistent with modern science. Total consistency across maximum scope is the test of validity, truth and knowledge (Owen, 2016).

8. This view of reality leads to simple elegant solutions of many of the perennial problems of science and the nature of reality and leads directly to many new insights. Specifically it leads to a clear understanding of the nature of consciousness and also enables a new understanding of spacetime that conceptually unifies quantum theory and general relativity and resolves the paradoxical nature of the quantum world (Owen, 2016).

9. These insights complete the progress of science itself in reducing everything to data by revealing how both mass-energy and spacetime, the last remaining bastions of physicality, can be reduced to data as explained in Universal Reality (Owen, 2016).

10. Viewing the universe as running programs computing its data changes nothing about the universe which continues exactly as before. It merely completes the finer and finer analysis of all things including us into their most elemental units. It’s simply a new way of looking at what already exists in which even the elementary particles themselves consist entirely of data while everything around us remains the same. Reality remained exactly the same when everything was reduced to its elementary particles, and it continues to remain the same when those particles are further reduced to their data.

Computational Genomics F'Real...,

WSJ |  A QUICK RIDDLE: WHAT DO 100 works of classic literature, a seed database from the nonprofit Crop Trust and the Universal Declaration of Human Rights have in common? All of them were recently converted from bits of digital data to strands of synthetic DNA. In addition to these weighty files, researchers at Microsoft and the University of Washington converted a high-definition music video of “This Too Shall Pass” by the alternative rock band OK Go. The video is an homage to Rube Goldberg-like contraptions, which bear more than a passing resemblance to the labyrinthine process of transforming data into the genetic instructions that shape all living things.

This recent data-to-DNA conversion, completed in July, totaled 200 megabytes—which would barely register on a 16-gigabyte iPhone. It’s not a huge amount of information, but it bested the previous DNA storage record, set by scientists at Harvard University, by a factor of about 10. To achieve this, researchers concocted a convoluted process to encode the data, store it in synthetic DNA and then use DNA sequencing machines to retrieve and, finally, decode the data. The result? The exact same files they began with.

Which raises the question: Why bother?

“We are seeing this explosion in the amount of data that needs to be stored,” says Karin Strauss, the principal Microsoft researcher on the project. “To continue storing this information, we need radical new approaches.” In an age of gargantuan, power-sucking data centers, the space-saving potential of data stored in DNA is staggering. “You can archive all the data on the internet in a shoebox,” says Luis Ceze, an associate professor of computer science and engineering at the University of Washington.

Dystopian Now: the future is here - just not evenly distributed

CSMonitor | Dr. Church told The Washington Post that the meeting wasn’t open to the public or to media because its theme overlapped with a paper written by many scientists that’s pending publication in a major scientific journal. The organizers didn’t want to be accused of "science by press release," reported the Post, so decided not to share their project publicly until they had a peer-reviewed article validating their research.

"It wasn't secret. There was nothing secret or private about it," said Church, who told the Post that the video of the event will be released when the scientific paper is published, likely soon.

Church also said that the project is not aimed at creating people, only cells, and not just for human genomes, despite that an invitation to the meeting at Harvard said that the primary goal “would be to synthesize a complete human genome in a cell line within a period of 10 years,” as the Times reports.

There has been tremendous progress in genomics since scientists finished sequencing the entire human genome in 2003. As the Times reports:

Scientists and companies can now change the DNA in cells, for example, by adding foreign genes or changing the letters in the existing genes. This technique is routinely used to make drugs, such as insulin for diabetes, inside genetically modified cells, as well as to make genetically modified crops. And scientists are now debating the ethics of new technology that might allow genetic changes to be made in embryos. But synthesizing a gene, or an entire genome, would provide the opportunity to make even more extensive changes in DNA.

A team headed by genomics pioneer J. Craig Venter first synthesized the chromosome of one bacterium in 2010 and inserted it into another species, thereby replacing the host species's DNA. The result, named Syn 1.0, was a microbial cell that was able to replicate and make a new set of proteins, powered by its synthetic genome, as the Monitor has reported.

the minimal cell

theatlantic |  In 2010, a team of scientists announced that they had created a synthetic living cell. The team, led by Nobel laureate Ham Smith, microbiologist Clyde Hutchison III, and genomics pioneer Craig Venter, fashioned the full genome of a tiny bacterium called Mycoplasma mycoides in their lab, and implanted the DNA into the empty cell of another related microbe. They nicknamed it Synthia. Some news sources claimed that the team had, for the first time, created artificial life.Others noted that they had merely photocopied life, putting an existing genome into a new chassis, like a “hermit crab taking up residence in an abandoned shell.”

But amid the hyperbole and skepticism, the team continued working. “The 2010 paper was basically the control experiment,” says Venter. Their true mission was to create a cell with a minimal genome.

All living things evolved from a common ancestor, so despite our grand variety, we all share genes that are essential for our survival. They’re at the core of our operating systems: the fundamental software without which we would die. Smith, Hutchinson, Venter, and their colleagues wanted to create an organism with just these essential genes—only those it needed to survive, and nothing more. A minimalist microbe. Kondococcus, perhaps.

Why bother? Because they ultimately want to intelligently design new life-forms from scratch—say, bacteria that can manufacture medical drugs, or algae that churn out biofuels. And creation requires understanding. “We had to start with a system where we knew and understood all the components, so that when we added specific ones to it, we could do so in a logical design way,” Venter says. They needed a minimal genome—a vanilla model that they could later kit out with deluxe accessories.

And they’ve done it. Six years after Synthia, they’ve finally unveiled their bare-bones bacterium. And in piecing together its components, they realized that they’re nowhere close to understanding them all. Of the 473 genes in their pared-down cell, 149 are completely unknown. They seem to be essential (and more on what that means later). Many of them have counterparts that are at work in your body right now, probably keeping you alive.

And they’re a total mystery.

“We’ve discovered that we don’t know a third of the basic knowledge of life,” says Venter. “We expected that maybe 5 percent of the genes would be of unknown function. We weren’t ready for 30 percent. I would have lost a very big bet.”

geneticists/molecular biologists are indispensible knowledge-workers...,

harvarddesignmagazine |  GC  The synthetic biology revolution is not just about going from reading to writing. Genomics already went from reading single genes to reading multiple genes; now synthetic biology is going from writing single genes to writing whole genomes. Both reading and writing are tangled up in the design process. In many fields, there is a design-build-analyze loop: you build something, and then you look for its failure modes. After living in a building for a while, you notice that it leaks. Then you do another round of design; you radicalize your structures and hold them to stronger standards until they fail. Then you slowly eek your way back to something that works, but works better than before. The same thing is true in synthetic biology. We have design software, like BIOCAD, cadnano, Millstone, and others.

But I see two fundamental differences between synthetic biology and architecture. In architecture, you might start with walls and windows as your standard parts. In biology, our standard parts have been refined by three billion years of evolution, on 10²¹ liters of soil and water. That’s a lot of debugging. Also, in synthetic biology we have the ability to recreate that refinement process ourselves, on a smaller scale and in a more directed way. We can run our own evolutions. When you do the design-build-analyze loop for buildings, you might make one small prototype, build it, and, if it starts to go wrong, you debug it in real time. Like the John Hancock Tower, in downtown Boston—you know its history, right?

MA

Glass panels mysteriously falling off …

GC

It was being debugged as it was being used. With synthetic biology, we can make a billion or a trillion designs, build them all, test them all, take the winner from that testing, and then do it all again.

MA

What is the timescale for this type of experiment?

GC

It depends on your goal. If your goal is to make a chemical, say, or to build a little factory that makes chemicals, you can design, build, and test a billion things in one day. If your goal is to make a pig, you’re talking more in the order of years. And if you are creating a human pharmaceutical, you’re talking about 10 years just to get it through all the regulatory phases. You might find a clever way of doing billions of prototypes by working with human cells in the lab, but when you want to introduce it into the marketplace, you’re going to be testing one drug at a time, just like you test one building at a time.

MA

You’ve worked on some things that are pretty far removed from our daily concerns—like how to bring the wooly mammoth back to life—but a lot of your work stands to affect our everyday bodily experience. What are you working on that you might want to use to change your own genome?

GC

There is an APP (amyloid precursor protein) allele that I wouldn’t mind having—it gives an extra 10 years of resistance to Alzheimer’s. That’s something that’s preventative, and it’s something we more or less know how to do. But there are some things we don’t know how to do yet, such as having better memory or making more effective use of the brain. Those would be great. Reversing aging would be nice, too.

MA

Aren’t our inadequacies part of what makes us human? How would it affect the human experience if we could live much longer, for example?

GC

I think what makes us human is mainly our ability to plan and to care for others. Chimpanzees form little cliques, and they certainly care for their families, but I think our ability to imagine scenarios that have never happened—to think of ways to avoid having an asteroid eliminate all life on the planet—is uniquely human. We have an ability to be thoughtful about ourselves and oth- ers over long periods of time. I think that would remain true if we lived longer.

meticulously planned parenthood WILL NOT be taken slowly because tards are scared of it...,

SA |  The official policy of the American Society of Reproductive Medicine is as follows: “Whereas preimplantation sex selection is appropriate to avoid the birth of children with genetic disorders, it is not acceptable when used solely for nonmedical reasons.” Yet in a 2006 survey of 186 U.S. fertility clinics, 58 allowed parents to choose sex as a matter of preference. And that was seven years ago. More recent statistics are scarce, but fertility experts confirm that sex selection is more prevalent now than ever.

“A lot of U.S. clinics offer non-medical sex selection,” says Jeffrey Steinberg, director of The Fertility Institutes, which has branches in Los Angeles, New York and Guadalajara, Mexico. “We do it every single day. We did three this morning.”

In 2009 Steinberg announced that he would soon give parents the option to choose their child’s skin color, hair color and eye color in addition to sex. He based this claim on studies in which scientists at deCode Genetics in Iceland suggested they could identify the skin, hair and eye color of a Scandinavian by looking at his or her DNA. "It's time for everyone to pull their heads out of the sand,” Steinberg proclaimed to the BBC at the time. Many fertility specialists were outraged. Mark Hughes, a pioneer of pre-implantation genetic diagnosis, told the San Diego Union-Tribune that the whole idea was absurd and the Wall Street Journal quoted him as saying that “no legitimate lab would get into it and, if they did, they'd be ostracized." Likewise, Kari Stefansson, chief executive of deCode, did not mince words with the WSJ: “I vehemently oppose the use of these discoveries for tailor-making children,” he said. Fertility Institutes even received a call from the Vatican urging its staff to think more carefully. Seifert withdrew his proposal.

But that does not mean he and other likeminded clinicians and entrepreneurs have forgotten about the possibility of parents molding their children before birth. “I’m still very much in favor of using genetics for all it can offer us,” Steinberg says, “but I learned a lesson: you really have to take things very, very slowly, because science is scary to a lot of people.” Most recently, a minor furor erupted over a patent awarded to the personal genomics company 23andMe. The patent in question, issued on September 24th, describes a method of “gamete donor selection based on genetic calculations." 23andMe would first sequence the DNA of a man or woman who wants a baby as well as the DNA of several potential sperm or egg donors. Then, the company would calculate which pairing of hopeful parent and donor would most likely result in a child with various traits.

Illustrations in the patent depict drop down menus with choices like: “I prefer a child with Low Risk of Colorectal Cancer; “High Probability of Green Eyes;” "100% Likely Sprinter;" and “Longest Expected Life Span” or “Least Expected Life Cost of Health Care." All the choices are presented as probabilities because, in most cases, the technique 23andMe describes could not guarantee that a child will or will not have a certain trait. Their calculations would be based on an analysis of two adults’ genomes using DNA derived from blood or saliva, which does reflect the genes inside those adults’ sperm and eggs. Every adult cell in the human body has two copies of every gene in that person’s genome; in contrast, sperm and eggs have only one copy of each gene and which copy is assigned to which gamete is randomly determined. Consequently, every gamete ends up with a unique set of genes. Scientists have no way of sequencing the DNA inside an individual sperm or egg without destroying it.

“When we originally introduced the tool and filed the patent there was some thinking the feature could have applications for fertility clinics. But we’ve never pursued the idea, and have no plans to do so,” 23andMe spokeswoman Catherine Afarian said in a prepared statement. Nevertheless, doctors using PGD can already—or will soon be able to—accomplish at least some of what 23andMe proposes and give parents a few of the choices the Freemans made about their second son.