Explore Options for a High Impact Health Tech Startup
The goal of this post is to explore building a organization in the B2B space with meaningful impact within 5–10 years. The evaluation criteria focused on what matters most for both planetary-scale impact and commercial viability: scalability potential, time-to-revenue, pilot feasibility with current resources, and the credibility needed to attract customers and partners.
Evaluating Our Options
I reviewed three high-leverage areas: pathogen monitoring (wastewater surveillance), global genomic equity (population datasets), and engineered microbiomes.
I prefer B2B and are skeptical of B2C. B2C is too hard.
Wastewater pathogen tracking was selected because it: (a) has the fastest path to revenue (govt / enterprise contracts), (b) is pilotable locally with modest resources, (c) gives actionable signals quickly (qPCR → alerts), and (d) scales geographically.
Global genomic equity remains attractive for long-term moat and defensibility but is slower, more research/PhD friendly, and requires longer timelines to monetize.
Engineered microbiomes was ruled out despite its high impact potential because it has medium time-to-revenue that varies significantly by product type, requires deeper expertise in synthetic biology and therapeutics, and faces higher regulatory burdens especially for human therapeutics. While consumer products could be faster to market, they conflict with the B2B preference.
I agreed a practical route: run a wastewater pilot (twice-weekly sampling + qPCR normalization + sequencing triggers), validate sensitivity and customer interest, then scale or pursue genomics in parallel/after.
Decision-making (tables)
Table 1 — Options compared (concise)
| Option | Time-to-revenue | B2B fit | Pilot feasibility (MSc) | PhD helpfulness | 5–10yr impact |
|---|---|---|---|---|---|
| Wastewater pathogen monitoring | Fast (shortest) | Very good (govt, hospitals, enterprise) | High — local pilot doable | Not required | High (early-warning, public health) |
| Global genomic equity (population datasets) | Slow (longer build) | Good (pharma, gov) | Medium — needs cohorts & partnerships | Useful / likely recommended | Very high (defensible dataset, long-term) |
| Engineered microbiomes | Medium (varies by product) | Good (agri, pharma) | Medium — some products faster (D2C) | Helpful for therapeutics/synbio | High (health, agriculture, climate) |
Table 2 — How I chose wastewater (criteria -> outcome)
| Decision criterion | Why it matters | Wastewater outcome |
|---|---|---|
| Time to commercial revenue | B2B contracts accelerate cashflow | Best — rapid govt/enterprise use cases |
| Pilot speed & cost | Need 6–12 month proof of traction | High — 3 site pilot workable |
| Technical risk / regulatory burden | Affects speed to market | Manageable — lab validation & partnerships |
| Strategic defensibility | Long-term moat vs quick wins | Moderate — dataset value grows with scale |
| Fit with your status (MSc + optional PhD) | Feasibility to lead as a student | Good — you can run pilot now; PhD optional |
Next Steps
Immediate
- Partnerships & approvals - Secure partner lab / local wastewater utility and any sample access approvals
- Procurement & protocol - Finalize sampling protocol (24-h composite preferred), preservatives, and process control spike-ins
- Skill-building - Practice the metagenomics/amplicon & qPCR workflows and set up a containerized pipeline (Nextflow/Snakemake or similar)
Pilot execution
Sites & sampling cadence
- 3 sentinel sites (university WWTP, small-town WWTP, one high-risk facility)
- Sampling: twice per week (e.g., Mon/Thu) 24-hour composite where possible
- Sample volume: 500 mL–2 L; concentrate from 50–250 mL depending on method
Assays - Rapid: RT-qPCR panel for key pathogens (SARS-CoV-2, influenza, RSV, norovirus) + normalization marker (PMMoV or crAssphage) and process controls - Discovery: monthly or trigger-based shotgun metagenomics; amplicon sequencing for targeted variant tracking when needed
Lab QC - Negative extraction/PCR controls every batch; spike-in recovery and inhibition controls; flag low-recovery samples
Bioinformatics & pipeline cadence - qPCR: process + normalize immediately; update dashboard within 24–48 h - Sequencing: preprocess → taxonomic classification → mapping for specific viruses/variants → AMR detection; expect 3–10 day turnaround depending on batching - Automate: per-sample pipeline on data arrival; daily cron to catch batches; weekly aggregation for baseline/trend
Analytics & alerting - Build EWMA/CUSUM anomaly detection - Use a 6–8 week baseline per site. Alert rules: - Yellow/watch: ~2× increase vs 2-week mean or >1 SD above baseline - Orange/investigate: ~4× increase or >2 SD - Red/action: sustained increase over 3 samples or clinical corroboration
Reporting - Automatic dashboard updates per run; weekly summary reports to partner public health contacts