Exin Therapeutics

What do they actually do

Exin Therapeutics is an early-stage YC W25 company building an AI-driven discovery workflow for neurotherapeutics. Today, they run computational models to nominate neural circuit targets and potential interventions across multiple disorders, and are standing up an in‑house wet lab to generate in‑vivo validation data; their platform is described as in development rather than sold to external users (company site; YC profile).

Operationally, they are hiring and setting up a lab in the Philippines to run physiology, histology, and behavioral assays, with plans to begin commercial lab operations around Oct 2025 and later scale throughput (BOI press release; Glassdoor job listing). There are no public indications of paying customers or partnered clinical programs yet; the current “users” appear to be the internal R&D team, with a future path of advancing validated hits toward preclinical candidates and partnering/licensing to larger biopharma (company site; Fondo launch post).

Who are their target customer(s)

• Heads of neuroscience R&D at mid-to-large pharma: Need de-risked candidates tied to specific neural circuits with early in‑vivo evidence to inform quick in‑license decisions; internal teams are resource-constrained and risk-averse (company site; BOI).
• Founders/CSOs of small neuro biotechs: Often lack cash and in‑house capacity for high‑throughput animal studies; need credible targets and early data to raise capital or secure partners (YC profile; Glassdoor job listing).
• Pharma BD/licensing scouts: Under pressure to find programs with clear mechanism and behavioral/physiology readouts that justify deals and timelines (Fondo launch post; Business Inquirer).
• Academic translational labs and clinician‑scientists: Struggle to turn circuit-level insights into reproducible therapeutic candidates due to limited, scalable validation capacity (company site; BOI).
• CROs and preclinical service buyers: Need predictable, higher‑throughput neuro assays and validated readouts to serve multiple clients and meet deadlines; capacity and cost are constraints (Business Inquirer; BOI).

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

• First 10: Run high‑touch paid pilots with academics and small biotechs that deliver AI‑nominated targets plus in‑vivo readouts and raw data, using YC/founder intros; execute compute in SF and early wet work in Manila to control cost and quality (company site; YC profile; BOI).
• First 50: Package successful pilots into standardized proof‑of‑concept dossiers and sell fee‑for‑service studies with short option‑to‑license terms via targeted BD and conference outreach, supported by published case studies (Fondo launch post; Business Inquirer).
• First 100: Scale through CRO channel partnerships, volume contracts, and a pharma licensing funnel; offer white‑label assay bundles and SLAs while leveraging Manila capacity expansion to fulfill higher study volumes (Business Inquirer; BOI).

What is the rough total addressable market

Top-down context:

TAM combines (a) pharma’s annual spend to acquire or license de‑risked CNS programs and (b) outsourced preclinical neuroscience validation services; Exin targets both by generating candidates plus in‑vivo data (company site).

Bottom-up calculation:

At planned scale the Manila lab targets ~100 candidates/month (~1,200/year) per press, so SOM depends on utilization and price per validated candidate/package; converting to dollars requires real CRO-style price quotes for the chosen study batteries (Business Inquirer; BOI).

Assumptions:

• Utilization of 60–80% of stated capacity in early years.
• Average price per candidate reflects a defined behavioral+physiology+histology package; modality mix (small molecule vs. genetic) changes price and timelines.
• Non‑GLP discovery studies dominate early revenue; safety/tox packages remain out of scope initially.

Who are some of their notable competitors

• Recursion: AI-driven discovery company with large automated wet labs for high‑throughput phenotypic screening and internal programs; overlaps with Exin’s compute+in‑house biology model.
• Exscientia: AI-first drug discovery firm that designs molecules and partners/licenses with pharma; overlaps on ML‑nominated programs and partnering strategy, less on owning a neuro animal facility.
• BenevolentAI: Builds AI models to generate targets and candidates (including CNS) and progresses programs toward partners; overlaps on automated target discovery for neurological disease.
• Charles River Laboratories: Large CRO offering preclinical neuroscience services (behavioral, physiology, toxicology); competes on wet‑lab validation services for pharma and biotech.
• Cerevance: Neuro-focused biotech mapping human brain cell types to nominate CNS targets; competes on target discovery for neurotherapeutics.