Week 1 HW: Principles and Practices

I am interested in the computational design of biomarker-integrated biomedical devices that combine localized therapeutic delivery with biological sensing to improve safety and precision in cancer treatment.

Specifically, I am working on the conceptual design of an antitumoral intrauterine device (IUD) for endometrial adenocarcinoma that leverages intrauterine molecular and transcriptomic biomarkers to support real-time monitoring and data-driven therapeutic decisions. By integrating localized drug delivery potentially through drug repurposing strategies with biomarker-informed feedback, such a system aims to reduce systemic toxicity while increasing treatment specificity.

While biomarker-driven therapeutic devices have the potential to significantly improve clinical outcomes, they also raise important ethical and governance concerns. These include risks related to patient safety, data governance, algorithmic bias, unequal access to precision technologies, and the challenge of managing systems where computational interpretation of biological data directly informs therapeutic action.

High-level goal:
Ensure that biomarker-driven biomedical devices and computational biological design tools are developed and deployed in ways that are safe, clinically responsible, and equitable.

Sub-goals:

• Patient Safety & Non-malfeasance
  Prevent harm arising from incorrect biomarker interpretation, device malfunction, or inappropriate therapeutic responses.
• Equity & Access
  Avoid reinforcing disparities in access to precision biomedical technologies across healthcare systems and regions.
• Responsible Innovation
  Enable translational progress in biomarker-integrated medical devices without imposing governance frameworks that unnecessarily slow legitimate research or clinical adoption.

Purpose
Require early-stage ethical and clinical risk assessment for biomarker-driven therapeutic devices prior to clinical testing or deployment.

Design

• Implemented by universities, hospitals, ethics committees, and funding agencies
• Short, standardized assessment focused on patient safety, data use, and system autonomy

Assumptions

• Designers can anticipate plausible failure modes and misuse risks
• Institutions are willing to meaningfully enforce early review

Risks

• Assessments may become procedural rather than substantive
• Overregulation could discourage early-stage innovation if applied rigidly

Purpose
Limit misuse or premature deployment of sensitive biomarker-driven design tools and therapeutic decision-support algorithms.

Design

• Tiered access based on clinical training, certification, or institutional affiliation
• Monitoring of high-risk functionalities, such as automated therapeutic adjustments

Assumptions

• Access control reduces patient risk
• Monitoring does not unduly hinder clinical research

Risks

• Centralization of control over design and deployment tools
• Exclusion of low-resource or underrepresented research groups

Purpose
Encourage safety-by-design and equity-focused development of biomarker-integrated biomedical devices.

Design

• Funding incentives for designs prioritizing patient safety, interpretability, and clinical robustness
• Recognition programs implemented by funders, hospitals, and research institutions

Assumptions

• Positive incentives influence research and design priorities

Risks

• Unequal distribution of incentives
• Difficulty in measuring long-term clinical and societal impact

(1 = best)

I would prioritize a combination of Option 1 and Option 3.

Early ethical and clinical risk assessment establishes a shared baseline of responsibility, while incentive-based mechanisms encourage designers to proactively integrate patient safety, interpretability, and equity into biomarker-driven biomedical devices.

Audience:
Academic institutions, funding agencies, hospital ethics boards, and translational research consortia.

This week highlighted that ethical responsibility in biotechnology increasingly emerges before physical deployment, particularly in systems where computational interpretation of biological data directly informs therapeutic action.

A key insight was the importance of anticipatory governance—especially for biomarker-driven medical devices—where risks arise from data interpretation, system autonomy, and unequal access rather than from biological materials alone.

Proposed Action:
Integrate ethics, governance, and clinical risk analysis into the early design phase of biomarker-informed biomedical devices as core engineering constraints rather than post hoc considerations.