Week 1 HW: Final Project Ideas

HTBAA Homework #1

1. What you would like to biomanufacture and why?

Target product: a single-domain antibody fragment (nanobody, VHH) directed against PD-L1, intended for use as an immunohistochemistry (IHC) diagnostic reagent, designed to integrate with an automated digital quantification workflow.

Why: In triple-negative breast cancer (TNBC), eligibility for atezolizumab depends on a specific assay, SP142, which evaluates PD-L1 expression in tumor-infiltrating immune cells using a threshold of just 1%. This type of scoring presents challenges related to the pathologist’s visual assessment and inter-pathologist agreement when evaluating low thresholds in tissue. Without prior training, visual interpretation tends to be more subjective, and while training improves outcomes, it does not eliminate reliance on individual visual interpretation (Kim et al., 2021). This substantial variability among pathologists when evaluating immunological biomarkers has direct implications for therapeutic decisions (Van Bockstal et al., 2023). I have encountered this type of problem firsthand in my current position at a pathology laboratory in Peru. The accuracy of a reagent is not merely a technical issue; rather, it determines whether a patient has access to treatment. A nanobody produced through a standardized cell-free process, combined with an automated digital quantification system rather than a pathologist’s visual reading, could offer a more objective alternative to the current manual scoring. As far as I can tell from the literature, this combination has not been specifically explored for this problem.

Who it is for and why it matters: this reagent would be intended for patients with advanced or metastatic TNBC being evaluated for atezolizumab eligibility, and for pathology laboratories that currently rely on manual immune-cell scoring to make that determination. By combining a standardized biomanufactured reagent with an automated reading workflow, this approach could offer a more objective and reproducible alternative to current visual interpretation, particularly relevant in metastatic sites, where documented variability is greatest.

2. What living system would you use?

Proposed chassis: a cell-free system based on E. coli lysate, following the commercial NEBExpress-type approach, well documented for producing single-chain antibody fragments quickly, including nanobodies (Haueis & Kubick, 2022).

How it would work: The system needs a DNA template (linear or plasmid-based) encoding each candidate anti-PD-L1 nanobody sequence, fused to a histidine tag for later purification. It also needs E. coli lysate, which supplies the transcription and translation machinery, plus an energy mix of amino acids, NTPs, and an energy-regeneration system. The reaction runs through coupled in vitro transcription-translation (IVTT). A nanobody is a single domain with no light chain and no strict glycosylation requirement for binding activity, so a simple bacterial chassis works fine here. A full IgG antibody would need a mammalian system instead. The reaction finishes within a few hours. What comes out is a soluble nanobody, purified by affinity chromatography using Ni-NTA magnetic beads that capture the histidine tag.

Assumptions I’m making:

  • Preliminary research, such as a phage display library derived from immunized camelids, has already yielded a small set of candidate VHH sequences against PD-L1. Not a single final sequence, and not an unfiltered full library. This project focuses on manufacturing and selecting the best option from that small pool, not on the full initial discovery of the binder.
  • The E. coli lysate, whether produced in-house or purchased commercially, maintains consistent activity across batches.

3. How would you use automation?

Proposed technology: a desktop liquid-handling robot, Opentrons OT-2 type, organized around the biofoundry Design-Build-Test-Learn (DBTL) cycle.

What I would automate, step by step:

  • Build: automated assembly of the small pool of nanobody candidates from Question 2, using a standard method like Golden Gate, dispensed in parallel across 96-well plates.
  • Cell-free reaction: automated dispensing of the IVTT reaction mix into each well, then controlled incubation.
  • Purification: automated magnetic separation of Ni-NTA beads to isolate the nanobody from each candidate.
  • Test: each purified nanobody gets coupled to a staining assay on tissue samples (or a simulated model). Then comes image capture and automated digital quantification of the staining pattern on immune cells, replacing the pathologist’s visual reading identified as a source of subjectivity in Question 1.

Why automate these specific steps: it lets me compare candidates from the small pool in parallel to find the best one for affinity and specificity, instead of testing them one at a time. That matters, but what matters more for this proposal is that it builds a quantitative, reproducible reading step into the process from the start. No falling back on a pathologist’s visual read again.

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

(a) How much?

Peru records roughly 20,759 new breast cancer cases every year (Johnston, 2008). A cross-sectional study of 1,176 patients at the Regional Institute of Neoplastic Diseases in northern Peru found that 18.2% of immunohistochemical profiles were triple-negative (Gómez-Rázuri et al., 2024). That works out to about 3,777 patients per year in Peru who would need PD-L1 evaluation via SP142 to determine eligibility for atezolizumab.

I’m assuming each test requires on the order of 1 µg of reagent, based on typical primary antibody volumes in IHC (roughly 100-200 µL applied at a working concentration of 1-5 µg/mL). Adding a ×3 factor for controls and possible repeat testing gives 3,777 × 3 µg, or about 11.3 mg of nanobody per year to cover this need in Peru.

(b) How long would it take?

New England Biolabs has published real yield data for their NEBExpress system showing nanobody (VHH) production in the range of 50-250 ng/µL, or 0.05-0.25 mg/mL, in E. coli cell-free reactions completed within 2-4 hours (NEB, 2026; Buss, n.d.). Taking a conservative 0.1 mg/mL and a 96-well plate at 200 µL per well, each well yields roughly 20 µg. A full plate run produces about 1.92 mg in a single 2-4 hour run. To cover Peru’s 11.3 mg annual need, that comes out to roughly 6 plate runs per year.

5. What don’t you know yet?

Real specificity and affinity: it’s unclear whether any candidate from the reduced pool of VHH sequences would reach sufficient affinity and specificity against the relevant PD-L1 epitope on TNBC immune cells. Class 7 (Measurement & Assays) should give me the conceptual grounding I’m missing here, general principles of quantitative measurement of biomolecular interactions, so I know what kind of affinity assay would actually make sense to design.

Compatibility with existing staining protocols: a nanobody, typically detected through its tag rather than a traditional secondary-antibody system, would likely require reworking the current visualization protocol. What I don’t understand yet, at a general level, is what alternative diagnostic detection formats exist beyond conventional IHC. Class 5 (Digital Microfluidics) seems like the right place to build that understanding, and Lab #2 should help me get a better feel for the proposed chassis hands-on. Neither would hand me a ready-made solution for this specific reagent, but together they’d give me a reference framework for thinking about different detection platforms.

Real yield and reproducibility of this specific VHH: the NEB data (0.05-0.25 mg/mL) comes from generic nanobodies, not the anti-PD-L1 VHH in this project. I still need the general principles behind what drives yield and reproducibility in cell-free systems, lysate quality, reaction conditions, scale-up, and Class 3 (Cell-Free Systems, Cloud Labs) plus Lab #1 are where I’d expect to build that conceptual base.

References

Buss, J. A. (n.d.). Cell-free production of antibody fragments for high-throughput analyses [Poster]. New England Biolabs. https://www.neb.com/en/-/media/posters/document/cell-free-production-of-antibody-fragments-for-high-throughput-analyses.pdf

Gómez-Rázuri, K., Abad-Licham, M., Astigueta, J., & Moreno, J. (2024). Cáncer de mama en el norte del Perú: subtipos moleculares y HER2 low. Revista Peruana de Medicina Experimental y Salud Pública, 41(1), 62–68. https://doi.org/10.17843/rpmesp.2024.411.13424

Haueis, S., & Kubick, S. (2022). A cell-free expression pipeline for the generation and functional characterization of nanobodies. Frontiers in Bioengineering and Biotechnology, 10, 896763. https://doi.org/10.3389/fbioe.2022.896763

Johnston, M. (2008). Raising breast cancer awareness in rural Peru. University of Washington Global Health Group. https://students.washington.edu/uwghg/images/IHOP08/Peru_Johnston.pdf

Kim, S. (2021). Programmed death ligand 1 immunohistochemistry in triple-negative breast cancer: Evaluation of inter-pathologist concordance and inter-assay variability. Journal of Breast Cancer, 24(3), 266–279. https://doi.org/10.4048/jbc.2021.24.e29

New England Biolabs. (2026). NEBExpress® Cell-free E. coli protein synthesis system [Product documentation]. https://www.neb.com/en/products/e5360-nebexpress-cell-free-ecoli-protein-synthesis-system

Van Bockstal, M. R., Cooks, M., Nederlof, I., Brinkhuis, M., Dutman, A., Koopmans, M., Kooreman, L., van der Vegt, B., Verhoog, L., Vreuls, C., Westenend, P., Kok, M., van Diest, P. J., Nauwelaers, I., Laudus, N., Denkert, C., Rimm, D., Siziopikou, K. P., Ely, S., Zardavas, D., … van Deurzen, C. H. M. (2021). Interobserver agreement of PD-L1/SP142 immunohistochemistry and tumor-infiltrating lymphocytes (TILs) in distant metastases of triple-negative breast cancer: A proof-of-concept study. Cancers, 15(6), 1690.

AI disclosure: Claude (Anthropic) was used throughout the development of this assignment to verify internal consistency across answers, refine technical wording, translate content between Spanish and English, and format this document in Markdown. All scientific claims were reviewed against cited primary sources.