Week 1 HW: Principles and Practices
1) Describe a biological engineering application or tool you want to develop and why
At my lab, we came across the problem that, after doing the analysis of the best peptides of interest, we're unable to correctly asses the complete presentation of such peptides in the trained T cells, and we don't know if it is because of the lack of translation (peptide is not being produced), or if it's a lack of presentation (peptide is not going through the ER to an MHC, or not going through the Golgi apparatus to the outside of the cell). Thus, it would be very usefull to be able to use a circuit to express fluorescence when peptide is presented, and also, inside the cell, to know with fluorescence microscopy, the specific location of the peptide if it's inside the cell, or just not at all translated. This is also a general problem we're finding in T Cell Therapy, and could also target the problem where we don't usually have standards for Mass Spec analysis. In views of this problem and, after a little bit of research, I found a good inspiration paper.
I would like to develop a circuit similar to the one described by Ayano, Mohammad et al. (2025), in their paper "High-throughput discovery of MHC class I- and II-restricted T cell epitopes using synthetic cellular circuits". My ideal circuit would use the peptides of interest that have gone through the first filters of utility before being implemented into a cancer vaccine for clinical trials. I could USE APCs as well as we're also interested in understanding MHCII expression and would help to understand better the self regulation and long memory of the immune system.
2) 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.
1 non-malfeasance
- Standarization and validation of the circuit - Confirmation with ortogonal methods - Trazability and quality control of the circuit2 Responsible use of personalized medicine
- Protecction of the genetic and immunological data of each patient. - Specific Informed Conscent3 Access equity
- Promote technology transfer - Look for models of licencing and collaboration between labs4 Prevention of dual use of the technology
- Define limits of what types of antigens can be evaluated - Ethic filtering through outside institutionsGovernance of this technology should prioritize patient safety, responsible handling of biological data, equitable access, and prevention of misuse.
3) Describe at least three different potential governance “actions” by considering the four aspects below (Purpose, Design, Assumptions, Risks of Failure & “Success”)
Action: Regulation requisit for a validation prior to clinical impact
Purpose:
Currently, there's not always a required and standard validation method before results of epitope research gets to clinical decisions. The proposal or getting a multicentric of validation of the peptide prior to clinical impact witll help prioritize will help tackle this problem.
Design:
Main actors would be the FDA, Health Canada or EMA, as well as ethics committees, hospitals and private sector.
- We should define benchmarks that are used as minimal performance indicators (sensibility, specificity, reproducibility, robustness, etc.) - Reference datasets should be used. - Translation lab-clinic evidence should be necessary - Should be added in guides as "companion tools for diagnostics/treatments"Assumptions:
- Regulators have the availability of rapid analysis
- Standars are not stopping innovation
- There’s a consensys about which is “enough evidence” of success for translaiton of epitopes to vaccines.
Risk of failure and success:
- Failure: Too much burocracy.
- Success: Can create barriers of entry that will make it difficult for small research groups to join.
Action: Incentives for open source data and reproducibility proof
Purpose:
Promote data sharing, generate open standards and promote transparent reporting.
Design:
Main actors would be financing agencies (NIH, CIHR), NGOs, Fundations, journals and universities.
- Require to have a open source data center with data and genetic constructs. - Financing groups that generate open data. - Bring benefits during grant evaluation.Assumptions:
- Researchers have the willing to share
- Openess enhances quality and trust
- Intellectual Property won’t be affected
Risk of failure and success:
- Failure: Some companies might step back or patent aggressively before sharing.
- Success: There could be some actors with bad intentions that could use information to optimize harmful peptides.
Action: Ethics-by-design
Purpose:
Incorporate ethical limits from the design of the project, instead of after the technology has been developed.
Design:
Main actors would be bioengineers, companies, institutional committees, providers.
- Restricted libraries of approved antigens. - Require registration to have access to more information. - Auditable use log.Assumptions:
- Technical filters really limit misuse of information.
- Users won’t look for alternative access.
Risk of failure and success:
- Failure: Systems might be easy to jump / false security.
- Success: Could limit research.
4) Score governance actions
| Does the option: | Action 1 | Action 2 | Action 3 |
|---|---|---|---|
| Enhance Biosecurity | |||
| • By preventing incidents | 1 | 2 | 2 |
| • By helping respond | 1 | 2 | 2 |
| Foster Lab Safety | |||
| • By preventing incident | 1 | 2 | 2 |
| • By helping respond | 1 | 2 | 2 |
| Protect the environment | |||
| • By preventing incidents | 3 | 3 | 1 |
| • By helping respond | 3 | 3 | 1 |
| Other considerations | |||
| • Minimizing costs and burdens to stakeholders | 2 | 2 | 3 |
| • Feasibility? | 2 | 2 | 3 |
| • Not impede research | 1 | 2 | 3 |
| • Promote constructive applications | 2 | 2 | 3 |
5) Describe which governance option, or combination of options, you would prioritize, and why.
For the proposed actions mentioned above, I would combine the first and the third, and then implement the second option: 1) require peptide validation prior to the clinical stage and promote experimental design alongside the development of ethical guidelines to be met, and 2) encourage transparency.
To design experiments in the best possible way and ensure compliance with all necessary regulations, it is imperative to develop the research in parallel with ethical requirements. Within these ethical requirements, the importance of peptide validation prior to clinical trials should also be emphasized. If ethical standards and validation are met, moving on to clinical and industry stages should be faster and more appropriate, while also facilitating the bureaucratic steps for acceptance.
Finally, implementing transparency incentives would reduce time in peptide/antigen development, as it would prevent redundancy in research (i.e., repeating tests on antigens already shown to be ineffective) and would also save significant resources. Moreover, making this information publicly available could improve accessibility for laboratories with limited capacity for antigen discovery, enabling the application of already known antigens.