DeepCyte

Cover Block

Attribute	Detail
Company Name	DeepCyte
Tagline	AI toxicology platform combining single-cell metabolomics to predict and explain drug toxicity in human cells.
Headquarters	Delaware, US; Copenhagen, Denmark
Founded	2025
Stage	Seed
Business Model	B2B
Industry	Deeptech
Technology	AI / Machine Learning
Geography	North America
Growth Profile	Venture Scale
Founding Team	Solo Founder
Funding Label	Seed (total disclosed ~$1,500,000)

Links

• Website: https://www.deepcyte.bio
• LinkedIn: https://www.linkedin.com/company/deepcyte

The Short Version

DeepCyte is a newly launched techbio startup applying single-cell metabolomics and AI to predict drug toxicity, a proposition that merits investor attention for its potential to address a costly and persistent bottleneck in biopharma development [PR Newswire, April 2026]. The company was founded in 2025 by Theodore Alexandrov, a metabolomics researcher whose academic work has focused on spatial and single-cell analysis, and Gina Wallbank, who serves as CTO [Deep Tech Week, 2026] [LinkedIn, 2026]. Its core offering integrates two proprietary components: MetaCore, a high-throughput single-cell metabolomics platform, and DeeImmuno, an AI model trained to detect metabolic changes in individual immune cells, predict toxicity class, and infer biological mechanisms [The SaaS News, 2026] [PR Newswire, 2026]. This approach differentiates from traditional animal models and bulk assays by providing human-centric, cell-specific readouts earlier in the drug discovery pipeline, with an initial focus on oncology and immunology therapeutics [DeepCyte, 2026]. The company has secured $1.5 million in seed funding, with medtech executive and investor Carl J. G. Evertsz serving as the lead backer and Chairman of the Board [PR Newswire, April 2026] [The SaaS News, 2026]. Over the next 12-18 months, key milestones to watch will be the validation of DeeImmuno with pharmaceutical partners, the publication of peer-reviewed performance data, and the expansion of the commercial team to convert scientific promise into contracted revenue. Data Accuracy: GREEN -- Confirmed by PR Newswire, The SaaS News, Crunchbase, and LinkedIn.

The Company in Brief

DeepCyte launched publicly in April 2026 with a $1.5 million seed round, positioning itself as a techbio startup at the intersection of single-cell biology and AI [PR Newswire, April 2026]. The company is legally incorporated in Delaware, US, and maintains a research and operational presence in Copenhagen, Denmark [Crunchbase, 2026]. Its founding story is centered on translating foundational research in spatial and single-cell metabolomics into a commercial platform for predictive toxicology.

The founding team is led by CEO Theodore Alexandrov, Ph.D., an academic researcher with a documented focus on metabolomics and single-cell analysis [LinkedIn, 2026]. His scientific contributions include the development of METASPACE, an open-source platform for spatial metabolomics, and SpaceM, a method for spatial single-cell metabolomics, work that has led to over 100 publications and several patents [LiverSeminars, 2026]. Co-founder Gina Wallbank is identified as the company's Chief Technology Officer [Deep Tech Week, 2026]. The company's initial capital and strategic guidance come from Carl J. G. Evertsz, a medtech executive and investor who led the seed round and serves as Chairman of the Board [The SaaS News, 2026].

Key milestones are concentrated in 2026, beginning with the company's formal launch and funding announcement in April. The concurrent introduction of its two core product components, the MetaCore metabolomics platform and the DeeImmuno AI model, established its initial commercial proposition [PR Newswire, April 2026]. Prior to this launch, the underlying technology was developed within Alexandrov's academic research group, with public scientific contributions dating back several years [ResearchGate, 2026]. Data Accuracy: GREEN -- Confirmed by multiple public press releases and corporate profiles.

What They Have Built

DeepCyte’s product architecture is a two-part system designed to move toxicology testing earlier and deeper into the drug development pipeline. The company’s core offering integrates a proprietary hardware-enabled data generation platform with a purpose-built AI analytics layer [DeepCyte, retrieved 2026].

MetaCore: Single-cell metabolomics data

The foundational layer is MetaCore, described as a “high-throughput single-cell metabolomics platform” that uses MALDI mass spectrometry to map cellular metabolism at scale [PR Newswire, April 2026]. This platform generates the unique dataset of metabolic profiles of individual human cells that feeds the company’s AI models. The emphasis on single-cell resolution and metabolic readouts is a direct challenge to traditional bulk assays and animal models, which the company argues mask cell-to-cell heterogeneity and are physiologically distant from human biology [DeepCyte, retrieved 2026].

DeeImmuno: AI toxicology analysis

The analytical engine is DeeImmuno, an AI model trained on proprietary single-cell metabolomics atlases derived from MetaCore [PR Newswire, retrieved 2026]. It is designed to detect metabolic changes in individual immune cells to evaluate drug toxicity, predict its class, identify relevant biomarkers, and infer biological mechanisms [Preqin, retrieved 2026] [PR Newswire, retrieved 2026]. The initial focus is on immunology and oncology, therapeutic areas where precise, mechanistic understanding of off-target effects is particularly valuable [LinkedIn, retrieved 2026]. Data Accuracy: YELLOW -- Product claims are consistent across company and press materials, but technical performance benchmarks and customer validation cases are not publicly available.

Market Size and Demand

The push to de-risk drug development is accelerating, and the market for tools that can predict failure earlier is expanding beyond traditional preclinical models. DeepCyte operates at the intersection of two high-growth sectors: AI-powered drug discovery and advanced in vitro toxicology.

Demand is driven by the pharmaceutical industry's need to reduce both financial losses and development timelines. The high cost of bringing a drug to market, often cited at over $2 billion, is heavily weighted by failures in Phase II and III trials, where toxicity is a leading cause of attrition [Nature Reviews Drug Discovery]. This creates a clear economic incentive for more predictive human-relevant models earlier in the pipeline. Concurrent tailwinds include regulatory shifts, such as the FDA Modernization Act 2.0, which explicitly allows for the use of alternative non-animal testing methods [FDA].

Market Segment	Reported Size	Source
AI in Drug Discovery	$4.9B (by 2028)	[Grand View Research, 2024]
Preclinical Toxicology Testing	Multi-billion dollar	Industry standard

Data Accuracy: YELLOW -- Market sizing is drawn from analogous, third-party industry reports; specific TAM for single-cell AI toxicology is not publicly defined.

Who Else Is Fighting for This

DeepCyte enters a crowded field of drug safety testing by claiming a unique position at the intersection of single-cell metabolomics and AI-driven toxicology. Its primary competition is not a single entity but a fragmented set of incumbents and challengers across different layers of the value chain.

• Incumbent service providers. The most direct substitutes are large contract research organizations (CROs) like Charles River Laboratories and Labcorp, which offer traditional in vivo toxicology studies and in vitro assays.
• Specialized challengers. A newer wave of companies applies computational biology to de-risk drug development. Firms like Recursion Pharmaceuticals and Insitro use high-content cellular imaging and machine learning for phenotypic drug discovery.
• Adjacent technology vendors. DeepCyte's MetaCore platform competes with instrumentation and software from vendors like Bruker (for MALDI mass spectrometry) and 10x Genomics (for single-cell genomics).

DeepCyte's defensible edge today rests almost entirely on its proprietary data and scientific founder's expertise. The company's AI model, DeeImmuno, is trained on "proprietary single-cell metabolomics atlases" generated by its MetaCore platform [PR Newswire, April 2026]. This creates a data moat; replicating such a specialized dataset would require significant capital and time. Data Accuracy: YELLOW -- Competitive analysis is inferred from the company's stated positioning against animal models and bulk assays; no direct competitors are named in captured sources.

Opportunity

If DeepCyte can successfully translate its single-cell metabolomics and AI platform into a new standard for predictive toxicology, the company could capture a significant portion of the multi-billion dollar drug safety testing market by offering a more precise, human-centric alternative to legacy methods.

Scenario	What happens	Catalyst
Platform Adoption	Biopharma partners integrate MetaCore and DeeImmuno as a standard in-vitro toxicology screen for early-stage assets.	A landmark publication or a partnership with a top-20 pharma company validating the platform's predictive power against clinical outcomes.
Regulatory Pathway	The company's single-cell metabolic signatures become accepted biomarkers for specific toxicity endpoints by regulatory bodies.	Successful completion of a regulatory-grade study submitted to the FDA or EMA as part of a partner's Investigational New Drug (IND) application.

Data Accuracy: YELLOW -- The opportunity analysis is based on the company's stated positioning and the founder's publicly documented scientific background. Market size and valuation comparables are inferred from the broader industry context rather than specific, cited projections for DeepCyte.

Sources

1. [PR Newswire, April 2026] DeepCyte raises $1.5M to bring single-cell AI toxicology to drug development | https://www.prnewswire.com/news-releases/deepcyte-raises-1-5m-to-bring-single-cell-ai-toxicology-to-drug-development-302737632.html
2. [The SaaS News, 2026] DeepCyte Raises $1.5M Seed Round | https://www.thesaasnews.com/news/deepcyte-raises-1-5m-seed-round
3. [Crunchbase, 2026] DeepCyte - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/deepcyte
4. [LinkedIn, 2026] DeepCyte | https://www.linkedin.com/company/deepcyte
5. [DeepCyte, 2026] DeepCyte | https://www.deepcyte.bio
6. [Preqin, 2026] DeepCyte Inc. | Preqin | https://www.preqin.com/data/profile/asset/deepcyte-inc-/796976
7. [Deep Tech Week, 2026] Deep Tech Week | https://www.deeptechweek.com
8. [LiverSeminars, 2026] LiverSeminars | https://www.liverseminars.com
9. [ResearchGate, 2026] ResearchGate | https://www.researchgate.net
10. [ContractResearchMap, 2026] DeepCyte | ContractResearchMap | https://www.contractresearchmap.com/providers/deepcyte
11. [Nature Reviews Drug Discovery] Nature Reviews Drug Discovery | https://www.nature.com/articles/nrd.2016.230
12. [FDA] FDA Modernization Act 2.0 | https://www.fda.gov
13. [Grand View Research, 2024] AI in Drug Discovery Market Size Report, 2021-2028 | https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-in-drug-discovery-market