Week 1 HW: Final Project Ideas

Emmanuel Cárdenas Barceló Barranquilla, Colombia Emmanel2003cardenas@gmail.com

September 22, 2026

What do you want to biomanufacture and why?

One of the things that concerns me most within the scientific field is experimentation involving animals. For this reason, I would like to develop an alternative that maintains the precision of experimental results without compromising animal welfare. To achieve this, the best option would be to develop organ-on-a-chip platforms capable of replicating and evaluating the same types of tests that are commonly performed in animals (Huh et al., 2010).

The problem with this technology is that no engineered tissue intended to replicate the three-dimensional architecture, cellular density, or metabolic function of a real organ can survive beyond a few hundred micrometers from a nutrient source without vessels capable of perfusing it.

Without active vascular flow, waste removal and the continuous supply of oxygen are severely limited, since diffusion alone can sustain only a viable region of approximately 100–300 μm around the point of oxygen entry (Ekengwu et al., 2026). Vascularizing these constructs is extremely complex because of the major challenge of biofabricating continuous, branched, and perfusable microvascular networks at the submillimeter scale while simultaneously ensuring a stable endothelial barrier capable of supporting dynamic flow without compromising tissue integrity (Chen et al., 2021; Kim et al., 2025).

Therefore, throughout this course I will focus on the development of vascularized liver tissue modules incorporating a perfusable synthetic vascular network capable of sustaining thick parenchymal tissue for weeks of culture, with the goal of enabling, in the not-too-distant future, the replacement of animal experimentation by using this type of tissue in an efficient manner.

What living system would you use?

I propose a hybrid system that combines structured 3D bioprinting with the biological self-assembly of cells, representing the most efficient strategy for achieving a hierarchical vascular network within the tissue (Son et al., 2025; Zhang et al., 2025). For this approach, three fundamental components or inputs are defined.

First, a collagen- or gelatin-based bioink loaded with hepatocytes and stromal cells forms the tissue matrix. Second, a sacrificial material defines the network of hollow channels extending from the main vessels to secondary branches (Shiwarski et al., 2025; Malkani et al., 2024). Third, a suspension of endothelial cells (HUVECs or iPSC-derived endothelial cells), together with pericytes, ensures vessel lining and mural stabilization (Krajewska et al., 2025; Son et al., 2025).

The biological process within the system focuses on tissue maturation and vascularization. Once the channels have been formed, endothelial cells are introduced into the lumen. When fluid circulation is initiated, the flow-induced shear stress stimulates these cells to adhere, align, and form an impermeable monolayer lining of the vascular compartment while simultaneously recruiting pericytes to stabilize the vessel wall (Shiwarski et al., 2025; Cai et al., 2025).

As the perfusable vascular network becomes functional, oxygen and nutrients begin to be distributed efficiently to hepatocytes within the parenchymal compartment by diffusion from the formed capillaries. Taking as a reference the parameters reported by Moon et al. (2025) for 1 cm³ liver constructs, I assume that this system will maintain cell viability above 85% and active hepatic metabolic function for at least 30 days of continuous perfusion.

As a final output, the system delivers a vascularized and mechanically stable block of liver tissue that is fully functional and ready to be connected to perfusion circuits for pharmacological evaluation assays.

How would you use automation?

Among the areas of opportunity mentioned in several articles, the step that most limits the transition from prototype to production is not printing itself, but rather post-printing handling. Manual assembly of each chip, sealing, and storage are slow processes that are prone to inter-batch variability (Fritschen et al., 2024; Liu et al., 2026; Nwokoye and Abilez, 2024). Therefore, I propose automating precisely this stage with a robotic handling system such as those described by Fritschen et al. (2024) and Lindner et al. (2024), capable of preparing, hermetically sealing, and storing vascularized tissue units without manual intervention, at a reported rate of three units per minute.

I choose this stage for two reasons. First, hermetic sealing under continuous perfusion is precisely the point at which reproducibility is most compromised, because inadequate sealing destroys constructs that have otherwise achieved a correct vascular architecture (Fritschen et al., 2024; Olaizola-Rodrigo et al., 2025). Second, automating physical handling frees human time for the stages that do require expert judgment, such as model-guided computational design of the vascular network (Sexton et al., 2025) and adjustment of bioink parameters.

How much would you need to make and how long would it take?

To define a physiologically and industrially relevant scale, a hepatotoxicity screening program equivalent to a high-throughput pharmaceutical campaign is proposed. Considering the evaluation of 50,000 candidate compounds per year, with three replicates per compound to ensure statistical robustness, the required production target is 150,000 vascularized liver tissue modules per year, corresponding to an average of approximately 411 units per day. In this model, the limiting factor is not the speed of bioprinting or robotic assembly, but rather the biological maturation time of the tissue. The literature reports that functional endothelialization under perfusion requires between 3 and 14 days, depending on the system employed (Ryma et al., 2022; Maggiotto et al., 2025; You et al., 2023). Adopting the most conservative value of 14 days of culture to ensure the formation of a mature endothelial barrier, and assuming a design capacity of 6,000 simultaneous incubation positions within the automated platform, the system can process 26 cycles per year. This results in an annual output of 156,000 units, comfortably meeting the demand of the proposed screening program. At an assembly rate of three units per minute, the robotic platform requires only 2.3 hours of effective daily operation (approximately 137 minutes) to accommodate this production volume, demonstrating that automation does not constitute a bottleneck.

The transition from the development stage to industrial-scale production involves substantial operational differences. A technical validation prototype consisting of a batch of 20 units, fabricated through manual embedded bioprinting with benchtop robotic assistance for bioink preparation, requires approximately three to four weeks from computational vascular design to the production of mature and functional tissues. In contrast, continuous operation at a scale of 150,000 units per year requires integration of the complete robotic platform while continuously coordinating the rotation of incubation positions. This large-scale infrastructure requires substantial investment, which becomes economically justifiable only after the technical parameters of the prototype have been fully validated.

What do you not know yet?

Some of the aspects that create the greatest friction within this project are related to the development of the vascular channels in the final product. Computational design can generate vascular trees down to the capillary scale, but current robotic bioprinting cannot reliably structure channels below approximately 20 μm. Therefore, the computational design and the final capillary geometry become decoupled and depend on biological self-assembly to close this gap (Liu et al., 2026; Mandrycky et al., 2021; Guy et al., 2026). I am not yet clear about how much real control my proposed system retains over the final microvasculature.

Another critical area requiring further evaluation is product quality control at large scale. Most automated systems lack sensors capable of measuring endothelial barrier integrity or perfusion quality in real time (Vasconez Martinez et al., 2024; Zhao et al., 2023). Without this capability, I have no way of determining whether my assumption of 6,000 units in parallel would actually produce consistent batches or whether a significant fraction would fail without being detected until the final assay.

AI Tools Used

In completing this work, I used Consensus to determine which research directions were available and to identify the one that most closely aligned with my intentions and the requirements of the assignment. I then used its findings as a reference to focus the response to this assignment around current trends in the field, thereby enabling the tracking of academic references related to organ-scale synthetic vasculature.

The results from Consensus, together with additional articles analyzed independently, formed a research dossier in Markdown that was uploaded to ChatGPT (GPT-4o / Voice Mode, OpenAI) to use its conversational functionality and dynamically understand the assignment guidelines and its fundamental concepts.

On the other hand, I used Claude (3.5 Sonnet, Anthropic) as an assistant to structure and analyze my ideas and to identify weaknesses in the proposed arguments based on the previously prepared research dossier.

The exact prompts used were:

Consensus

1.

Role & Objective: Act as an academic research synthesizer. Search peer-reviewed literature for novel and emerging products fabricated using Biomanufacturing 4.0 technologies (e.g., synthetic biology, metabolic engineering, in vitro cell-free enzymatic systems, 3D/4D bioprinting, engineered living materials).
Scope: Provide a broad, representative overview of groundbreaking products across key sectors (such as advanced biomaterials, regenerative medicine, novel bio-based materials, smart functional coatings, renewable energy, agri-food, textile/industrial).
Please structure the synthesis as follows:
Product / Biomaterial Name: Name and describe the novel product and its biological/synthetic components.
Biomanufacturing 4.0 Technique: Specify the exact advanced fabrication technique used (e.g., iPSC tissue engineering, cell-free synthetic biosystems, metabolic pathway engineering, bioprinting).
Target Application & Sector: Describe the industry or domain where it is used (medical/biomaterials, environmental, energy, agri-food, textile/industrial).
Key Innovation & Development Stage: Explain why it represents a breakthrough over traditional manufacturing methods and state its current development status (lab stage, pilot production, or commercialized).
Citations: Provide peer-reviewed references with DOIs where available.

2.

I want to fully understand the current state of the art in synthetic organ-scale vasculature for tissue biofabrication, that is, the design and generation of artificial vascular networks that allow perfusion of large tissue constructs made through 3D bioprinting. Bring me the most relevant literature, not just a single study, and organize the answer into the following sections.
First, what biological problem this technology solves, why perfusion is the main bottleneck for manufacturing large tissues or organs, and what limitations earlier methods of vascular network generation had in tissue engineering.
Second, what living systems or cell types are typically used to form these vessels, how endothelial and supporting cells behave inside a printed channel or vascular scaffold, and what biological processes occur for that channel to become a functional vessel capable of carrying fluid.
Third, what fabrication approaches exist to generate this vasculature, including model-guided computational design, computational fluid dynamics (CFD) simulation, freeform 3D bioprinting, and any other relevant technique, and what role automation or software plays in optimizing vascular geometry before or during fabrication.
Fourth, what performance metrics the literature reports, such as vascular generation speed, cell viability, perfusion times, or the maximum size of constructs achieved, and how different approaches compare to each other.
Fifth, what would be needed to scale this technology from a lab prototype to relevant production, what scaling and manufacturing limitations exist today, and what technical gaps the literature identifies as still unresolved.
Give me several different studies per section when they exist, not just the most cited one, with full references.

3.

What is the typical number of vascularized organ-on-chip units required in a preclinical pharmaceutical drug screening campaign?

4.

What print time and resolution has been reported for FRESH embedded bioprinting of vascularized channel networks?

5.

What throughput, in units per hour, has robotic automation achieved for fabricating or assembling vascularized organ-on-chip devices?

6.

What volume of collagen bioink is typically required to print one vascularized organ-on-chip channel network?

7.

What are the main unresolved bottlenecks in combining computational vascular design with robotic automation for scaling organ-on-chip production?

ChatGPT

Analyze this document; after this message, I will activate the voice mode for this chat so you can explain everything about this assignment to me in a dynamic way. In theory, all the information needed to complete it is here, but I would like to understand it so I can write it myself.

Claude

Help me continue drafting this sentence, taking into account the context: "[different parts of the text]" [paragraph explaining what I am referring to and why I want to say it].

References

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