Week 1 HW: Principles and Practices

1. First, describe a biological engineering application or tool you want to develop and why. The engineering of extracted hematopoietic stem cells so their B-cell progeny produces bnAbs (broadly neutralizing antibodies), so after exposure to an immunogen (a highly mutable virus like HIV, Influenza, and so on) they can provide protection for a long time after autologous engraftment.

The reason why I want to develop this is because it is near within our reach to be able to create a method of viral protection against a lot of viruses which we thought we’d never be able to get rid of.

2. Next, describe one or more governance/policy goals related to ensuring that this application or tool contributes to an “ethical” future, like ensuring non-malfeasance (preventing harm). Break big goals down into two or more specific sub-goals.

Governance/policy goal: Trials for healthiness.

First and foremost: the evaluation if this should be something to be researched, weighing the benefits and the possible risks of bringing such tools into the world, the same way that chiral lifeforms was evaluated.

Secondly: biological safety for the patient. Rigorous and extensive research, as it goes for any kind of treatment! Specifically, see if this treatment leads to the development of an autoimmunity, or causes any harm in trials using an in-vivo model, then murine model, then human model.

3. Next, describe at least three different potential governance “actions” by considering the four aspects below (Purpose, Design, Assumptions, Risks of Failure & “Success”).

–First governance action: Authorization by prescription/indication

Purpose: To ensure this therapy doesn't drift abroad, it is required to make sure that only people go through the same approval process as gene therapies or CAR-T cell therapy.
Design: To make it work, we'd need FDA approval for risk groups in which conventional vaccines (if any were to be approved) or drugs like lenacapavir do not work. Once that's done, this immunotherapy could be standarized in capable hospitals. Hopefully can be funded by government, alternatively, donations, or both.
Assumptions: Assuming that non-authorized use is detectable/enforceable.
Risks of Failure & “Success”: Failure would be slowing down their the translational part of immunotherapy, success would be the exact opposite, but could lead to 'medical tourism'.

–Second governance action: Long term surveillance

Purpose: To ensure no harm happens off-target and there are no adverse effects, there is the need for long term surveillance.
Design: Hospitals collect periodic data, which incude checkups for any symptoms of autoimmunity. Funded by the patient's health insurance.
Assumptions: Data is secured and used ethically. 
Risks of Failure & “Success”: Underfunded registries may lead to loss of the follow ups, which would lead to (if present) any effect going undetected. Success would lead to privacy concerns.

–Third governance action: Contain by design

Purpose: Standarize the protocol (as much as it can be, considering this is a personalized immunotherapy) to ensure it doesn't go off-target, 
Design: by establishing the gene(s) to be inserted, promoter(s), and the locus/loci to target. Lastly, a kill switch in case the immunotherapy goes wrong, such as an over-expressed protein to target with antibodies.
Assumptions: Assumes that the protocol and go wrong can also be 'reversed' by the addition of a kill switch.
Risks of Failure & “Success”: By design there's the assumption that the safeguards will generate confidence (that could be false confidence if the design does not work). Success can bring costs higher by adding complexity (particularly the kill switch). 

4. Next, score (from 1-3 with, 1 as the best, or n/a) each of your governance actions against your rubric of policy goals. The following is one framework but feel free to make your own:

5. Last, drawing upon this scoring, describe which governance option, or combination of options, you would prioritize, and why. Outline any trade-offs you considered as well as assumptions and uncertainties. For this, you can choose one or more relevant audiences for your recommendation, which could range from the very local (e.g. to MIT leadership or Cambridge Mayoral Office) to the national (e.g. to President Biden or the head of a Federal Agency) to the international (e.g. to the United Nations Office of the Secretary-General, or the leadership of a multinational firm or industry consortia). These could also be one of the “actor” groups in your matrix.

Definitely the third option, contain by design. Not only because of the scoring, but because I believe the first 2 options already are a must, given how common the those logistics are in medical proceedures alike. I believe the trade-offs mostly come from the risks (of failure and the ones that come from success in every option) rather than from the operation itself. I believe this would be the most relevant to academic medical centers.

–Reflecting on what you learned and did in class this week, outline any ethical concerns that arose, especially any that were new to you. Then propose any governance actions you think might be appropriate to address those issues. This should be included on your class page for this week.

The possibility of the immunotherapy causing autoimmunity, after a long time. I wasn’t accounting on the duration of the immune cells in the body. The governance actions appropriate for those issues would be option 3 and/or 2.

Assignment (Week 2 Lecture Prep) — DUE BY START OF FEB 10 LECTURE

Homework Questions from Professor Jacobson

1. Nature’s machinery for copying DNA is called polymerase. What is the error rate of polymerase? How does this compare to the length of the human genome. How does biology deal with that discrepancy?

The error rate is 1:10 to the power of 6! This doesn’t compare much to the length of the human genome, which is 3:10 to the power of 9. Biology deals with this through proofreading activity; through 3’ to 5’ exonuclease activity.

2. How many different ways are there to code (DNA nucleotide code) for an average human protein? In practice what are some of the reasons that all of these different codes don’t work to code for the protein of interest?

So the average human protein has 1036 base pairs, and the average aminoacid has 4 ways of synthesis, and because this is permutations (how many combinations there are), it would be 4 to the power of 1036. There can be many reasons such as, unoptimal within cellular context (such as, pH is not optimal for the final product when using a certain combination of aminoacids, and so the protein’s faulty, but it would be for a different combination of aminoacids in which the pH is actually suitable for the protein, so the second one would be conserved), another one reason could be rare tRNA’s that would slow down the synthesis, paradoxically, it could also be a combination of only optimal codons, which would make ribosome speed go beyond its capability, as in, make it go too fast to the point where the folding does not occur correctly (this last one I read in a paper that I’d like to be able to find again, it was something about mechanistic properties of synthesis from the ribosome).

Homework Questions from Dr. LeProust

1. What’s the most commonly used method for oligo synthesis currently? Phosphodiester method, I believe that’s what the majority has access to.

2. Why is it difficult to make oligos longer than 200nt via direct synthesis? Because each nucleotide addition requires all steps such as coupling, capping, oxidation, deblocking, at around 200 cycles is where it begins to truncate

3. Why can’t you make a 2000bp gene via direct oligo synthesis? Because truncation seems to happen after 200 cycles. There are methods that can go up to 500nt, but that’s pushing it!

Homework Question from George Church

1. Choose ONE of the following three questions to answer; and please cite AI prompts or paper citations used, if any.

[Using Google & Prof. Church’s slide #4] What are the 10 essential amino acids in all animals and how does this affect your view of the “Lysine Contingency”? No AI. (Kansas State University, n. d). The 10 aminoacids are lysine, methionine, tryptophan, threonine, valine, isoleucine, leucine, arginine, histidine and phenylalanine. Peculiar, that does nothing… and even if they were to do that, couldn’t the dinosaurs just get their lysine from regular animals or plants? I think this contingency plan would work if it was instead a deletion or anything that were to stop the translation of the enzyme(s) that synthesize an aminoacid or metabolite that is produced by dinosaurs (and is rarely ever found in diet).

Bibliography:

Kansas State University. (n. d.). Essential and non-essential amino acids. Animal Sciences And Industry. https://www.asi.k-state.edu/extension/swine/swinenutritionguide/general_nutrition_principles/essentialandnonessentialaminoacids.html