Evolvere BioSciences

What do they actually do

Evolvere BioSciences is developing new protein-based antibiotics using an internal computational design platform combined with lab testing. Today, the team runs a cloud pipeline that lets their scientists specify bacterial targets, generate large sets of candidate protein designs with open-source generative models, and triage those designs with folding and biophysical predictors before moving top hits into wet‑lab validation AWS blog co‑authored by Evolvere Y Combinator.

They are not selling software or a commercial drug yet. Current outputs are internally generated, early‑stage antibiotic candidates and engineering notes about their cloud pipeline. Early lab work was supported from BioEscalator facilities, and the near‑term plan is to iterate the design stack, expand wet‑lab validation, and advance validated leads toward preclinical development BioEscalator Y Combinator.

Who are their target customer(s)

• Hospitals and infectious‑disease clinicians: They treat patients with infections that fail existing antibiotics and have limited alternatives; they need new options that remain effective as bacteria evolve and can be deployed within stewardship constraints.
• Hospital pharmacy and antimicrobial stewardship committees: They must select therapies that work while minimizing harm to the microbiome and slowing resistance; current choices often force tradeoffs between short‑term efficacy and long‑term effectiveness.
• Pharma and biotech R&D teams (antibiotics/discovery): Discovery programs are slow and costly; teams need higher‑quality leads and reproducible pipelines to move from computational hits to validated preclinical candidates faster.
• Public health agencies and AMR funders: They need durable therapeutics to reduce resistance spread and protect population health, but few commercially sustainable programs are delivering next‑generation antibiotics today.
• Academic infectious‑disease labs and incubators: They lack scalable, reproducible protein‑design workflows and infrastructure to move designs quickly into wet‑lab validation.

How would they acquire their first 10, 50, and 100 customers

• First 10: Run low‑cost, short collaborative pilots with academic ID labs and incubator contacts (e.g., BioEscalator tenants), using real targets in exchange for data access; leverage the AWS case study and YC intros to secure warm leads into ID groups and small biotech R&D teams BioEscalator AWS blog Y Combinator.
• First 50: Convert successful pilots into fixed‑scope paid discovery contracts; publish engineering notes, early validation data, and open‑source tools to attract university labs and mid‑size pharma; use targeted conferences and grants to subsidize pilots where budgets are limited AWS blog Y Combinator.
• First 100: Scale via multi‑project partnerships and non‑exclusive licensing with larger pharma/CROs; hire a small BD team to productize “design + validation” offerings with clear pricing and follow‑on paths; use preclinical readouts to engage hospital stewardship groups and public‑health funders Y Combinator Sifted.

What is the rough total addressable market

Top-down context:

Two relevant markets: (1) AMR‑focused therapeutics ≈ USD 8–9B globally today, growing toward low double digits by 2030; (2) drug‑discovery informatics/AI platforms ≈ USD 3–4B today and growing Grand View Research — AMR Grand View Research — informatics. The broader antibiotics market is larger at ≈ USD 40–55B but is dominated by generics and stewardship‑limited use of novel drugs Fortune Business Insights Grand View Research.

Bottom-up calculation:

Therapeutics path: niche AMR indications often support only hundreds of millions per year (e.g., carbapenem‑resistant Enterobacterales ≈ USD 289M/year), so 2–3 targeted indications could yield ≈ USD 0.5–1.0B combined SAM at peak if priced and adopted appropriately Nature npj. Platform path: if commercialized, 50 customers (pharma, CROs, and labs) paying USD 0.25–1.0M/year for software/managed design would imply ≈ USD 12.5–50M annual revenue potential within today’s informatics TAM.

Assumptions:

• AMR drug sales are constrained by stewardship and narrow patient populations; pricing and uptake vary by geography and payer.
• Each targeted indication can sustain peak annual sales in the low hundreds of millions absent special reimbursement; multiple indications are required to reach ≈ USD 1B.
• Platform pricing assumes a mix of pilots, seats, and managed‑service contracts across academic and industry customers.

Who are some of their notable competitors

• Bugworks Research: AI‑enabled antibiotic discovery with small‑molecule assets targeting AMR; relevant as a discovery competitor pursuing similar clinical markets Bugworks.
• ArrePath: Applies machine learning and phenotypic profiling to discover novel anti‑infectives; competes for partnerships and AMR indications ArrePath.
• Locus Biosciences: Engineering CRISPR‑enhanced bacteriophages as precision antibacterials, an alternative modality aimed at drug‑resistant infections Locus.
• Adaptive Phage Therapeutics (APT): Clinical‑stage personalized phage therapy company addressing multi‑drug‑resistant infections; a competing approach to treating AMR UCSD IPATH ref.
• ContraFect: Develops lysins and other protein antimicrobials; notable as a direct protein‑based antibacterial modality competitor Yahoo profile.