Fighting against techno-eugenics

A Chinese scientist who shocked the medical community last year when he said he had illegally created the world's first gene-edited babies has been sentenced to three years in prison by a court in southern China.
He Jiankui announced in November 2018 that he had used a powerful technique called CRISPR on a human embryo to edit the genes of twin girls. He said he modified a gene with the intention of protecting the girls against HIV, the virus that causes AIDS. Many scientists expressed concerns about possible unintended side effects of the genetic changes that could be passed down to future generations.
Last fall, He also indicated there might be another pregnancy involving a gene-edited embryo. The court indicated that three genetically edited babies have been born.
The closed court in Shenzhen found He and two colleagues guilty of illegal medical practice by knowingly violating the country's regulations and ethical principles with their experiments, Xinhua news agency reported. It also ordered He to pay a fine of about $430,000.

Such unethical medical behavior is the worst news of 2019. And this article explained last June the reasons:

The link between CCR5 and HIV is fairly well studied. Disabling CCR5 removes the doorway HIV uses to enter and infect cells, but it does so only for some strains of HIV; there are others that don’t need CCR5. Further, the genetic sequence He’s edits produced does not match this well-studied variant of CCR5; in fact, it has never been observed in humans or animals. In other words, no one has any idea whether the variant with which Lulu and Nana are now living will affect HIV immunity or anything else.
That’s a key issue: Genes don’t do just one thing. Most illnesses and traits are influenced by dozens, hundreds, even thousands of DNA variations. Each of our roughly 20,000 genes is linked to many different aspects of our physiology and health. So what else does CCR5 do? A variant that provides protection against HIV also seems to increase susceptibility to a number of more common diseases, like flu and West Nile virus.
CCR5 has also been linked to brain function, which led to some sensational headlines and media speculation that the gene-edited babies might have enhanced brains. There are likely myriad other processes to which CCR5 contributes that we don’t know about yet. To that point: before the recent study, no one had researched whether the CCR5 mutation resulted in better or worse health over a person’s lifetime.
The CCR5 story illustrates a flaw in the logic that underlies gene editing. Efforts to change one gene to affect one illness in a future person ignore the fact that health is the result of infinitely complex interactions within and outside a person’s body. In most cases, the presence or absence of a particular genetic variant is not the sole determinant of a disease or condition.

And this article reminds us that, despite the appearance of agreement, ethical questions that have surrounded human germline editing for years have yet to be properly addressed.

Unnatural Selection: Season 1 | Main Trailer | Netflix

Key issues for Population Health improvement

Aspectos clave para la mejora de la salud poblacional

Gestión Clínica y Sanitaria 72

You'll find inside my article on key issues for population health improvement.

How confirmation bias contributes to polarization

Confirmation bias in the utilization of others’ opinion strength

Humans tend to discount information that undermines past choices and judgments. This confirmation bias has significant impact on domains ranging from politics to science and education. Little is known about the mechanisms underlying this fundamental characteristic of belief formation. Here we report a mechanism underlying the confirmation bias. Specifically, we provide evidence for a failure to use the strength of others’ disconfirming opinions to alter confidence in judgments, but adequate use when opinions are confirmatory. This bias is related to reduced neural sensitivity to the strength of others’ opinions in the posterior medial prefrontal cortex when opinions are disconfirming. Our results demonstrate that existing judgments alter the neural representation of information strength, leaving the individual less likely to alter opinions in the face of disagreement.

The notion that the strength of disconfirming opinion is not necessarily proportionate to its impact on belief change is in accord with anecdotal and ‘real-world’ observations in domains ranging from science to politics. The underlying process is remarkably flexible, with the neural circuitry involved switching on a trial-bytrial basis from high sensitivity to relative neglect, contingent on whether the opinion is confirmatory or disconfirming. This process may leave the individual less likely to alter opinions in the face of disagreement.

Interesting article from Nature. So what? Is there any exercise to train the neural sensitivity of our posterior medial prefrontal cortex? If so, I would suggest these exercise to some guys.

Bloomberg The year in pictures. Police brutality. Barcelona Airport October 2019.

Ethical algorithms like hammers?

Main messages:

All decision-making—including that carried out by human beings—is ultimately algorithmic. The difference is that human decision-making is based on logic or behaviors that we struggle to precisely enunciate. If we humans had the ability to describe our own decision-making processes precisely enough, then we could in fact represent them as computer algorithms. So the choice is not whether to avoid using algorithms or not, but whether or not we should use precisely specified algorithms.

Machine learning is a powerful tool that has many extant and potential benefits.  Technology companies such as Google and Facebook of course rely on products powered by machine learning for much of their revenue—but as these techniques grow in applicability, their scope and societal benefits grow as well.

The result is that, at least for a while, the critics of the algorithmic approach may often be right. There are many consequential domains where algorithmic tools are still too naive and primitive to be fully trusted with decision-making. This is because to model the forest, we need to start with the trees. This book offers a snapshot of exciting strands of research aimed at developing ethical algorithms, many of which are still in their very earliest days.

Global pharmaceutical market vs. local regulators

Regulating Medicines in a Globalized World: The Need for Increased Reliance Among Regulators

As defined by the World Health Organization (WHO), recognition occurs when a regulatory authority accepts the regulatory decision of another authority “as its own decision;”— reliance takes place when a regulatory authority takes into account the work products of another authority (e.g., inspection reports, scientific assessment reports, joint assessment reports produced together with another authority) to help inform the receiving authority's own regulatory decision, which, in the end may differ from the made by the initial authority using the same products. 

Recognition and reliance are the first steps towards an improvement of real coordination between regulatory bodies. If the pharmaceutical market is global, the regulators should cooperate for a coherent global regulation.

Anchoring and adjusting heuristic

Effect of Teaching Bayesian Methods Using Learning by Concept vs Learning by Example on Medical Students’ Ability to Estimate Probability of a Diagnosis

Why do we need more bayesian reasoning?. Can we improve clinical decision making? The answer in this JAMA article.

Although bayesian reasoning has been widely promoted in the literature as a diagnostic strategy, there has been scant evidence that teaching bayesian reasoning actually improves diagnostic accuracy. Providing learners with relatively brief instruction on these abstract concepts appeared to significantly improve their diagnostic performance in comparison with simply providing a number of relevant examples or no relevant instruction.

 The previously reported discrepancy between human probability estimation and optimal bayesian probability estimation has become traditionally accepted in the psychology and medical literature as cognitive biases, including base-rate neglect, anchoring bias, confirmation bias, and representativeness, all of which suggest suboptimal revision and have been purported to be a primary cause of diagnostic error.13,14 However, on closer scrutiny, much of this evidence was derived from situations that were not representative of the typical diagnostic setting. One highly cited study9 used a screening situation in which the base rate was very low and any positive test result, even one with excellent operating characteristics, would have most likely been a false-positive result. Participants in that study also appeared to exhibit semantic confusion by confusing the posttest probability with the conditional probability that was presented in the problem-solving exercise.

Medicine as a data science (7)

Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril

The National Academy of Medicine’s Special Publication: Artificial Intelligence in Health Care: The Hope, The Hype, The Promise, The Peril synthesizes current knowledge to offer a reference document for relevant health care stakeholders such as: AI model developers, clinical implementers, clinicians and patients, regulators, and policy makers, to name a few. It outlines the current and near-term AI solutions; highlights the challenges, limitations, and best practices for AI development, adoption, and maintenance; offers an overview of the legal and regulatory landscape for AI tools designed for health care application; prioritizes the need for equity, inclusion, and a human rights lens for this work; and outlines key considerations for moving forward.

A must read