Eh, usually less than you would expect. We’re really good at math and are quite capable of making synthetic experiments where we find people who either require the procedure, or where it’s been done incidentally and then inferring the results as though deliberate.
We can also develop a framework for showing benefit from the intervention, perform the intervention ethically, and then compare that to people who didn’t get the intervention after the fact. With proper math you can construct the same confidence as a proper study without denying treatment or intentionally inflicting harm.
It’s how we have evidence that tooth brushing is good for you. It would be unethical to do a study where we believe we’re intentionally inflicting permeant dental damage to people by telling them not to brush for an extended period, but we can find people who don’t and look at them.
He inserted a naturally occuring genetic variation.
Off the top of my head and not an expert: screen a very large number of people for having that variation, and monitor those that do for HIV infection. That phase will take a while.
Identify a collection of people interested in in vitro fertilization, ideally with some coming from your previous sample group. Since the process produces more embryos than can be used, perform your procedure on a random selection of discards. Inspection and sequencing of the modified segment should be indistinguishable from unmodified embryos bearing then variation naturally.
Now that you have confidence that the variation provides protection, and that you can make the change, identify people where the intervention offers a better chance than not having it, even though it’s experimental. This would likely be HIV positive women desiring IVF who would not be able to tolerate standard HIV treatment during the pregnancy. Engineering the embryo to be resistant therefore becomes the best available way to prevent infection.
You can then look back and compare infection rates with children born to untreated parents and parents who underwent treatment.
You also do a better job ensuring the parents know about the risks and what they entail. Informed consent and all that.
If this is really hard to do because you can’t find people that fit the criteria, maybe your research isn’t actually that critical. If HIV medication is essentially universally tolerated in pregnancy and is nearly 100% effective at preventing transmission to the infant without long-term side effects, then it might just be the case that while gene editing would work, it doesn’t provide enough of an advantage to be worth exploring for that disease.
Medical research is still medicine. You’re still obligated to do what’s best for the patient, even if it’s difficult or you’re curious about what would happen.
Eh, usually less than you would expect. We’re really good at math and are quite capable of making synthetic experiments where we find people who either require the procedure, or where it’s been done incidentally and then inferring the results as though deliberate.
We can also develop a framework for showing benefit from the intervention, perform the intervention ethically, and then compare that to people who didn’t get the intervention after the fact. With proper math you can construct the same confidence as a proper study without denying treatment or intentionally inflicting harm.
It’s how we have evidence that tooth brushing is good for you. It would be unethical to do a study where we believe we’re intentionally inflicting permeant dental damage to people by telling them not to brush for an extended period, but we can find people who don’t and look at them.
The current context is modifying babies to make them HIV resistant. How would you model something similar without performing the experiment?
He inserted a naturally occuring genetic variation.
Off the top of my head and not an expert: screen a very large number of people for having that variation, and monitor those that do for HIV infection. That phase will take a while.
Identify a collection of people interested in in vitro fertilization, ideally with some coming from your previous sample group. Since the process produces more embryos than can be used, perform your procedure on a random selection of discards. Inspection and sequencing of the modified segment should be indistinguishable from unmodified embryos bearing then variation naturally.
Now that you have confidence that the variation provides protection, and that you can make the change, identify people where the intervention offers a better chance than not having it, even though it’s experimental. This would likely be HIV positive women desiring IVF who would not be able to tolerate standard HIV treatment during the pregnancy. Engineering the embryo to be resistant therefore becomes the best available way to prevent infection.
You can then look back and compare infection rates with children born to untreated parents and parents who underwent treatment.
You also do a better job ensuring the parents know about the risks and what they entail. Informed consent and all that.
If this is really hard to do because you can’t find people that fit the criteria, maybe your research isn’t actually that critical. If HIV medication is essentially universally tolerated in pregnancy and is nearly 100% effective at preventing transmission to the infant without long-term side effects, then it might just be the case that while gene editing would work, it doesn’t provide enough of an advantage to be worth exploring for that disease.
Medical research is still medicine. You’re still obligated to do what’s best for the patient, even if it’s difficult or you’re curious about what would happen.