What changed, and when

Turbine $25m Series B for virtual biology led by Interactive Venture Partners, with Beiersdorf Venture Capital participating, and with existing investors including MSD Global Health Innovation, Accel, and Mercia also named. (turbine.ai)
In the same announcement, Turbine said it is expanding beyond oncology into immunology via a new partnership with an unnamed “top 10 pharma” partner. (turbine.ai)

60-second thesis frame

This round matters less for the headline dollars, more for whether Turbine can turn a decade-long “virtual cell” effort into a repeatable platform workflow that sits inside pharma R&D, and now also adjacent verticals like skin biology (via Beiersdorf). (turbine.ai)
The confidence builder is the lab-in-the-loop positioning, Turbine claims it generates proprietary perturbation datasets to “virtualize” new assays and deliver them through a no-code Virtual Lab that plugs into pharma workflows. (turbine.ai)
The confidence reducer is the field-level reality that “virtual cell” performance can look good in narrow settings yet fail on generalization, and even simple baselines can outperform headline foundation models on perturbation tasks, so diligence needs hard, prospective validation and clear ROI claims, not just partner logos. (PMC)

The seven diligence questions

Clinical

• What is Turbine’s prospective validation standard for a “virtual assay” (endpoints, error bars, decision thresholds), and how often does it change the next wet-lab experiment in a way that improves hit-rate or shortens cycles? (turbine.ai)
• For immunology specifically, what evidence exists that the approach can generalize beyond oncology, and what “ground truth” is being used (primary immune cells, co-cultures, cytokine panels, transcriptomics), with what holdout strategy? (turbine.ai)

Payer or Access

• Where does Turbine land in pharma budgeting, discovery, translational, biomarker, clinical positioning, and what is the measurable economic unit (cost avoided per screen, fewer PDX studies, fewer failed combos entering animal or early clinical)? (turbine.ai)
• If Turbine is also targeting skin biology and “active ingredient” questions, what is the buyer and adoption pathway, and what is the regulatory or claims environment for using in silico evidence in product development decisions? (turbine.ai)

Ops or Adoption

• What is the minimum partner data package needed to stand up a new virtual assay, and how long is time-to-first-decision (weeks vs quarters), including wet-lab capacity constraints on the “loop”? (turbine.ai)
• How does Virtual Lab integrate with LIMS, ELN, and partner security requirements, and who owns what IP when models are trained on partner-provided proprietary datasets? (turbine.ai)

Competitive

• What is Turbine’s defensible wedge versus (a) high-throughput perturbation biology platforms, (b) single-cell foundation models and benchmarks, and (c) bespoke mechanistic modeling, and how is that moat expressed, data, workflow, interpretability, or outcomes? (PMC)

Team or Cap table

• The public record describes founding dates as 2015 and 2016 in different places, what is the correct origin story, and how has the cap table evolved through the 2022–2023 Series A and the new 2026 Series B (option pool refresh, investor protections, runway)? (Business Wire)

Red flags

• If the unnamed top 10 pharma immunology partnership does not progress to a renewal, expansion, or publishable case study within 12–18 months, it suggests the platform is not yet “workflow sticky.” (turbine.ai)
• If Turbine cannot show performance that clears meaningful baselines on out-of-domain generalization (a known failure mode in the broader virtual-cell ecosystem), the “platform” risks reverting to bespoke services. (PMC)
• If Virtual Lab adoption requires heavy Turbine operator time per program, unit economics may not support multi-partner scaling, even with fresh capital. (turbine.ai)

Next catalyst

Watch for external, benchmarkable proof in 2026 that Turbine’s approach generalizes, for example participation/results tied to Virtual Cell Challenge 2026 (mid-year) and/or a named immunology partner case study. (Virtual Cell Challenge)

Publisher / Disclosure

Publisher: LucidQuest Ventures Ltd. Produced: 25 Feb 2026, 20:21 London. Purpose: general and impersonal information. Not investment research or advice, no offer or solicitation, no suitability assessment. UK: directed at investment professionals under Article 19(5) and certain high-net-worth entities under Article 49(2)(a)–(d) of the Financial Promotion Order 2005. Others should not act on this. Sources and accuracy: public sources believed reliable, provided “as is,” may change without notice. No duty to update. Past performance is not reliable. Forward-looking statements carry risks. Methodology: questions-first framework using public sources. No conflicts. Authors do not hold positions unless stated. © 2026 LucidQuest Ventures Ltd.

FAQ

• What exactly changed by Turbine’s “$25M Series B” news on 24 Feb 2026, and why does it matter for the biopharma market?
  Turbine secured $25 million in funding to expand its AI-driven virtual cell platform into immunology and other industries (PR Newswire). This transition marks its first major move beyond oncology, offering the potential to simulate complex immune cell behaviors and drug combinations at scale (Just AI News).
• What is the regulatory path after Turbine’s latest expansion, and what are the next formal steps in the US?
  While Turbine is a platform provider rather than a drug sponsor, its simulations are increasingly used to support IND (Investigational New Drug) filings and clinical trial designs (MedPath). The next step involves validating its immunology models through wet-lab experiments conducted by its pharmaceutical partners (Global Cosmetics News).
•  Which technology drove the results cited in Turbine’s recent partnership news, and how meaningful is it?
  The news centers on Turbine’s “Simulated Cell” technology and its “lab-in-the-loop” approach, which creates interpretable digital twins of cellular systems (Pharmaceutical Technology). The platform has already supported over 30 programs, demonstrating a 2–3x increase in the likelihood of success for validated hypotheses versus traditional methods (Tech.eu).
• What safety issues matter post-expansion, and do they change real-world use?
  A key focus of the new funding and the Beiersdorf partnership is assessing how active ingredients interact with skin biology and safety (Just AI News). This virtualization aims to identify toxicities earlier in the discovery process, potentially reducing the risk of late-stage clinical failures (PR Newswire).
• How will major pharmaceutical partners treat access to Turbine’s platform following the Series B?
  Existing partners like AstraZeneca and MSD (Merck & Co.) have already extended or expanded their collaborations to include complex areas like ADCs and hard-to-treat tumor populations (Fierce Biotech, Turbine News). The Series B funding enables Turbine to provide multi-year access to its “Virtual Lab” through no-code interfaces, democratizing simulation tools for internal pharma scientists (Nasdaq).

Entities / Keywords

Turbine; Virtual Lab; Simulated Cell; virtual assays; virtual biology; lab-in-the-loop; perturbation datasets; immunology; oncology; ADC discovery; antibody-drug conjugates; combination therapy; AstraZeneca; MSD Global Health Innovation; Merck & Co.; Accel; Mercia; Interactive Venture Partners; Thomas Peterffy; Interactive Brokers; Beiersdorf Venture Capital; NIVEA; skin biology; Champions Oncology; PDX; translational medicine; biomarkers; DNA damage repair; DDR; in silico experiments; Virtual Cell Challenge; Arc Institute; single-cell perturbation modeling; generalization benchmarks.

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