WeTheMarket
1月前
BFRG Stock Surge Explained: Bullfrog AI’s Pharma Deal and Cash Crunch
The Byte-Size Brief
107 subscribers
Posted Apr 5, 2026
Bullfrog AI just shocked the market, but does the business justify the move?
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In this deep dive, we break down Bullfrog AI Holdings Inc. (BFRG) after its massive 138% single-day surge on March 30, 2026. The headline catalyst was a commercial agreement with an undisclosed top 5 global pharmaceutical company focused on finding novel drug targets for major depressive disorder using Bullfrog AI’s proprietary platform.
We unpack what Bullfrog’s causal AI and graph analytics actually aim to do, why that matters in modern drug discovery, and why a binding agreement with a major pharma player is such a meaningful validation point for a microcap company.
But this story is not just about technology. We also walk through the company’s 2025 financial picture, its limited cash reserves, Nasdaq listing risks, reverse split pressure, and the brutal race to convert scientific momentum into real commercial returns.
If Bullfrog AI can turn validation into milestone payments and long-term royalties, the upside could be dramatic. If not, the financial clock may run out first.
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Timestamps
00:00 The core problem in drug discovery
00:38 Why BFRG shocked the market
01:47 The top 5 pharma agreement and MDD focus
03:05 What causal AI and graph analytics actually mean
05:42 Why this deal matters for a tiny company
06:11 What the 2025 10-K reveals
06:51 Q1 2026 commercial progress and partnerships
07:50 Patient stratification in phase 3 trials
08:56 Cash burn, cash reserves, and runway pressure
09:36 Nasdaq deficiency notices and delisting risk
10:29 Reverse stock split risk explained
11:45 No Wall Street analyst coverage
12:55 BFPRP and the data bottleneck opportunity
14:11 Bullfrog’s drug rescue model and internal pipeline
15:24 BF114, Cell Reports, and liver disease opportunity
16:21 What AI can and cannot do in biotech
16:55 Strong technology vs. weak financial position
17:31 The upside case if the pharma option is exercised
17:53 The survival challenge through August 2026
18:29 Final takeaway and viewer question
WeTheMarket
2月前
BullFrog AI (BFRG) | Biotech Resurgence Conference Replay
RedChip Companies
79.9K subscribers
8,277 views Apr 20, 2026 #BFRG #BullFrogAI #AIStocks
AI is creating a new layer of value across drug discovery and development, especially for companies that can help pharma reduce timelines, improve decision-making, and increase the odds of clinical success. In this replay of BullFrog AI’s (Nasdaq: BFRG) presentation at RedChip’s Biotech Resurgence conference, CEO Vin Singh explains how the company is using proprietary, explainable AI to tackle one of healthcare’s biggest inefficiencies: the cost, complexity, and low success rates of drug development.
Watch this presentation and Q&A to hear BullFrog AI discuss:
• Its first commercial agreement with a top-five global pharma
• How its proprietary AI platform differs from wrapper-based AI tools
• The role of bfPREP™, bfLEAP®, and bfARENA™ in data preparation, analytics, and decision support
• Real-world validation from work with Eleison Pharmaceuticals and the Lieber Institute
• Why management believes the company is positioned for additional pharma contracts and larger strategic partnerships
• Cash runway into late 2027 and the company’s lean operating model
Link to Presentation Slides https://d1io3yog0oux5.cloudfront.net/_ca01eff9e96c949656d995091356c11a/bullfrogai/db/2639/25084/pdf/BFRG+Corporate+Presentation_April+2026.pdf
WeTheMarket
2月前
Turning Clinical Complexity into Predictive Intelligence: How BullFrog AI Is Redefining Drug Development
04 May 2026 | Monday | Interview
https://www.biopharmaboardroom.com/interview/12/4662/turning-clinical-complexity-into-predictive-intelligence-how-bullfrog-ai-is-redefining-drug-development.html
SUMMARY
Vin Singh, Chairman and CEO of BullFrog AI, discusses how causal AI, multimodal data analysis and precision patient targeting could help reduce clinical trial failure rates and accelerate smarter drug development
As pharmaceutical companies continue to face high attrition rates, rising development costs and increasingly complex clinical datasets, the industry is searching for more predictive approaches to drug discovery and development. In this exclusive Q&A with Biopharma Boardroom, Vin Singh, Chairman and CEO of BullFrog AI, explains how the company’s causal AI platform is helping biopharma organizations transform fragmented clinical and real-world data into actionable insights that support target identification, patient stratification and more efficient clinical development strategies. From optimizing drug–patient compatibility to uncovering new opportunities for shelved assets, Singh outlines how BullFrog AI is positioning itself at the forefront of a more data-driven and predictive drug development ecosystem.
Failure rate of drugs in clinical development remains one of the most persistent challenges in drug development. From your perspective, what are the key limitations of traditional data analysis approaches that BullFrog AI is aiming to overcome?
Traditional models often fail in clinical development due to inadequate data or inadequate tools for preparing and analyzing the data that many companies in this industry already have. The fact of the matter is that all AI is not created equal and there are incredibly complex datasets that are just not prepared for ingestion into AI models. Well structured, AI-ready multimodal data is needed to uncover the kind of game changing insights that will grant clinical researchers access to the type of detailed nuance that enables them to make the right decisions. Ultimately leading to clinical success. Unfortunately, that critical data can be complicated to collect or cost prohibitive to many of the small or microcap companies that are searching for that kind of insight. As technology continues to evolve, and platforms like BullFrog’s AI data preparedness tool bfPREP™ become widely used in the industry, these types of barriers will become less of a hurdle.
BullFrog AI emphasizes working with “messy” clinical and real-world data. Could you elaborate on how your platform structures and extracts actionable insights from such complex datasets, and what differentiates your approach from conventional AI models?
When BullFrog AI started, the focus was on validating the core causal AI approach and proving it could deliver insights that traditional methods could not. Over time, we’ve significantly expanded the platform’s capabilities, improved performance, and refined how insights are delivered to end users. We’ve also deepened the platform’s biological focus, ensuring it is purpose-built for life sciences rather than adapted from general analytics tools by customizing and focusing our AI models and associated tools.
A lot of traditional models use what is called correlation-based machine learning. Correlations show relationships and patterns whereas causal AI provides the magnitude and direction of those relationships. The main difference between the two, especially in complex biological systems, is causal AI can provide an understanding of the drivers of disease, as well as the associated pathways, which can be crucial to making discoveries that will lead to successful drugs developed in less time and for less investment. We want to provide more insight beyond just identifying correlations, relationships, or patterns, and that’s what BullFrog’s end-to-end workflow is designed to provide.
In terms of messy data, we recognized that a lot of companies just don’t have their data in a good enough place to make AI analysis successful. Based on some of our initial partnerships, we recognized that companies sometimes had data all over the place, on multiple servers, in different formats, sometimes even with clinical notes scribbled on a notepad and scanned in as a PDF. This problem led to the design of our solution, bfPREP™, which is designed to clean, harmonize, and structure biological and clinical data so it can be analyzed using AI tools.
Many AI-driven drug discovery companies focus on molecule generation. How does BullFrog AI’s focus on drug–patient compatibility shift the paradigm, and what impact can this have on late-stage trial success rates?
You are correct that many AI-driven companies are focused on drug design. That’s not our space. By using advanced ML-driven causal modeling to identify high-potential drug targets, reduce false positives, and generate actionable insights from complex omics and clinical datasets, we can identify the best targets, decrease their traditional discovery/development timelines, and cut back on the number of candidates that will fail before reaching approval. Our partners can then proceed with their drug screening activities knowing that they are working with targets that have a high potential of association with a disease.
In addition, our technology can identify optimal patient populations based on molecular signatures, predicted response, and real-world data, helping partners design precision trials and assist in patient stratification. Using these predictive analytics to flag high-risk trial variables, reveal confounding factors, and suggest adaptive trial designs, our clinical partners can lower trial failure risk and enhance their clinical ROI. This is especially important for smaller biotech companies where you can only really afford to fund one lead clinical target.
You recently announced a commercial agreement with a top 5 global pharmaceutical company in major depressive disorder. Can you share more about how BullFrog AI’s platform is being applied in this collaboration and what outcomes you aim to achieve?
Absolutely. We’re very excited about the agreement to identify and prioritize therapeutic targets for that pharma partner specifically in major depressive disorder (MDD). This will be our first partnership since the launch of our bfARENAS™ defensible decisions platform that completes our end-to-end analytical AI workflow. The potential to uncover key targets that could help future patients in a disease like MDD, which is ranked as the third leading cause of disease burden worldwide by the World Health Organization, is something we are intensely focused on. Under the agreement, we will be using our causal AI platform to identify and prioritize novel drug targets specifically for MDD, accelerating the partner’s drug discovery and clinical development program for this indication. The outcomes and deliverables from the partnership will be prioritized drug target candidates, associated causal gene networks, and target dossiers for advancement-ready drug candidates to accelerate their pipeline. Ultimately, we want to determine the best candidates to pursue for the indication so the best treatments can be streamlined to reach patients faster.
There is growing interest in repurposing or reviving shelved assets. How does your AI workflow help identify new opportunities for previously unsuccessful or deprioritized compounds?
As you mentioned earlier, the failure rate of drugs in clinical development remains one of the most persistent challenges in drug development. Expanding the life cycle of an existing pipeline often involves identifying new therapeutic uses. With bfLEAP®’s advanced analytical capabilities, the platform can unearth potential expansion opportunities for existing drugs. By analyzing mechanistic overlaps and patient subtypes most likely to benefit, our platform can uncover new indications for already approved or shelved compounds and open new revenue streams or release new promising candidates from within your pipeline that otherwise would remain shelved.
Looking ahead, how do you see AI evolving in the clinical development space over the next 3–5 years, and what role do you expect BullFrog AI to play in shaping a more predictive and efficient drug development ecosystem?
Looking ahead, our goal is to continue innovating and expanding the impact of the bfLEAP® platform across drug discovery and development. That includes deeper engagement in central nervous system (CNS) disorders, where unmet needs are high, and success rates are low, as well as expanding into additional therapeutic areas.
We see no shortage of opportunities to apply our platform and causal AI capabilities to the challenges facing the pharmaceutical industry. We are being recognized as an AI innovator with unique know-how and capabilities that should translate into AI partnerships across the entire drug discovery and development workflow, disease categories, and drug modalities. Ultimately, the long-term goal is to help improve drug development success rates, reduce costs, and bring better therapies to patients faster, saving and extending lives through better treatment. That mission continues to guide every strategic decision we make.
WeTheMarket
2月前
Filed yesterday after market close, SEC Filing Alert, DEF 14A: Definitive proxy statements.
Virtual Annual Meeting of Stockholders to be held on Thursday, June 11, 2026, at 10:00 a.m. Eastern Time (the “Annual Meeting”). To be admitted to the Annual Meeting at www.virtualshareholdermeeting.com/BFRG2026, you must enter the control number found on your proxy card, voting instruction form or notice you previously received. You may vote during the Annual Meeting by following the instructions available on the meeting website during the meeting. We hope you can join us.
As of April 20, 2026, the Company had 18,530,865 shares of common stock outstanding. Only shareholders of record as of the close of business on April 20, 2026 are
entitled to receive notice of, to attend, and to vote at, the Annual Meeting.
https://d1io3yog0oux5.cloudfront.net/bullfrogai/sec/0001493152-26-020511/0001493152-26-020511.pdf
WeTheMarket
3月前
BullFrog AI (BFRG) | Biotech Resurgence Conference Replay
Link to Presentation Slides https://d1io3yog0oux5.cloudfront.net/_e3cb576ca74b1b18f9b21dd2ade1eb28/bullfrogai/db/2639/25084/pdf/BFRG+Corporate+Presentation_April+2026.pdf
RedChip Companies
79K subscribers
Posted Apr 17, 2026
AI is creating a new layer of value across drug discovery and development, especially for companies that can help pharma reduce timelines, improve decision-making, and increase the odds of clinical success. In this replay of BullFrog AI’s (Nasdaq: BFRG) presentation at RedChip’s Biotech Resurgence conference, CEO Vin Singh explains how the company is using proprietary, explainable AI to tackle one of healthcare’s biggest inefficiencies: the cost, complexity, and low success rates of drug development.
Watch this presentation and Q&A to hear BullFrog AI discuss:
• Its first commercial agreement with a top-five global pharma
• How its proprietary AI platform differs from wrapper-based AI tools
• The role of bfPREP™, bfLEAP®, and bfARENA™ in data preparation, analytics, and decision support
• Real-world validation from work with Eleison Pharmaceuticals and the Lieber Institute
• Why management believes the company is positioned for additional pharma contracts and larger strategic partnerships
• Cash runway into late 2027 and the company’s lean operating model
Why Investors Should Watch:
? Our replay gives investors direct access to management commentary on BullFrog AI’s commercial traction, platform differentiation, expansion strategy, and the milestones that could shape near- and long-term shareholder value.
Learn more about BFRG: https://ir.bullfrogai.com/
iHub News
3月前
BullFrog AI lands first pharma deal, expands AI drug discovery pushApril 13, 2026 11:10 AM
IH Market News
BullFrog AI Holdings Inc (NASDAQ:BFRG) said it has secured its first commercial agreement with a major global pharmaceutical company, marking a key milestone as it enters the second quarter of 2026 with a strengthened financial position.The deal, announced on March 30, will see BullFrog deploy its bfLEAP® platform to identify potential drug targets for major depressive disorder, an area of growing demand within the pharmaceutical sector. The company’s AI technology, originally developed from research at Johns Hopkins University, is gaining recognition as a tool to enhance drug discovery processes.BullFrog said it intends to deepen its engagement with strategic pharmaceutical partners while maintaining a disciplined financial strategy aimed at supporting operations through late 2027.The company also highlighted the rollout of its bfARENAS platform, designed as a comprehensive solution for pharmaceutical research and development. The platform integrates multiple capabilities to support drug discovery workflows, positioning BullFrog as a provider of end-to-end AI-driven solutions for the industry.
More about BullFrog AI
BullFrog AI focuses on applying artificial intelligence and machine learning to improve the efficiency of drug discovery and development. Through partnerships with leading research institutions, the company combines causal AI techniques with its proprietary bfLEAP® platform to analyze complex biological datasets, with the goal of accelerating therapeutic development and reducing failure rates in clinical trials.
Original: BullFrog AI lands first pharma deal, expands AI drug discovery push
WeTheMarket
3月前
SEC From 8-K filed February 17, 2026.
https://www.sec.gov/Archives/edgar/data/1829247/000149315226007142/form8-k.htm
Item 3.01 - Notice of Delisting or Failure to Satisfy a Continued Listing Rule or Standard; Transfer of Listing.
On February 10, 2026, BullFrog AI Holdings, Inc. (the “Company”) received a letter from The Nasdaq Stock Market LLC (“Nasdaq”) notifying the Company that, for the last 30 consecutive business days, the closing bid price for the Company’s common stock, par value $0.00001 per share (the “Common Stock”), was below $1.00 per share, which is the minimum closing bid price required for continued listing on the Nasdaq Global Market (the “Minimum Bid Price Requirement”) pursuant to Nasdaq Listing Rule 5550(a)(2) (the “Bid Price Notice”). The Bid Price Notice has no immediate effect on the listing of the Company’s Common Stock and tradable warrants. As such, the Company’s Common Stock will continue to trade on the Nasdaq Capital Market under the symbol “BFRG,” and its tradable warrants will continue to trade on the Nasdaq Capital Market under the symbol “BFRGW.”
In accordance with Nasdaq Listing Rule 5810(c)(3)(A), the Company is provided a compliance period of 180 calendar days from the date of the Bid Price Notice, or until August 10, 2026, to regain compliance with the Minimum Bid Price Requirement. If at any time during the 180-calendar day grace period, the closing bid price of the Company’s Common Stock is at least $1.00 per share for a minimum of ten consecutive business days (unless the Nasdaq staff exercises its discretion to extend this ten business day period pursuant to Nasdaq Listing Rule 5810(c)(3)(H)), Nasdaq will provide the Company written confirmation of compliance, and the matter will be closed.
If the Company does not regain compliance during the initial 180-calendar day compliance period, the Company may be provided a second 180-calendar day period to regain compliance. To qualify, the Company must meet the continued listing requirement for market value of publicly held shares and all other initial listing standards for the Nasdaq Capital Market (with the exception of the Minimum Bid Price Requirement) and notify Nasdaq of its intent to cure the minimum bid price deficiency by effecting a reverse stock split, if necessary. If the Company does not regain compliance within the allotted compliance periods, including any extensions that may be granted by Nasdaq, the Company’s listed securities will be subject to delisting. The Company would thereafter have the right to appeal a determination to delist the Company’s securities, and the Company’s securities would remain listed on the Nasdaq Capital Market until the completion of the appeal process.
The Company intends to monitor the closing bid price of its Common Stock and assess potential options to regain compliance with Nasdaq’s Listing Rules. While the Company plans to review all available options, there can be no assurance that the Company will regain compliance with the Minimum Bid Price Requirement during the compliance period, secure a second 180-day period to regain compliance with the Minimum Bid Price Requirement, or maintain compliance with the other Nasdaq listing requirements.
WeTheMarket
3月前
Webinar by Juan Felipe Beltrán Lacouture, PhD, Senior Director of AI, Machine Learning & Innovation, BullFrog AI, Turning AI Recommendations into Clear, Defensible Decisions
BullFrog AI
Posted Mar 31, 2026
Juan Felipe Beltrán is Senior Director of AI, Machine Learning & Innovation at BullFrog AI, where he leads development of AI systems that transform fragmented clinical trial data into actionable intelligence for pharmaceutical decision-makers. Previously, he developed protein sequencing algorithms at Quantum-Si, with work published in Science. Juan holds a PhD in Computational Biology from Cornell and specializes in making advanced analytics auditable, repeatable and operationally useful for cross-functional drug development teams.
WeTheMarket
3月前
Insights from Google Gemini:
The selection of Major Depressive Disorder (MDD) and the use of specialized data—including the "brain data" you mentioned—are highly significant for several strategic reasons. While the press release focuses on the $8 billion market size and the Top 5 pharma partner, the underlying technical "moat" involves exactly the kind of data and platform origins you are tracking.
1. The Significance of the MDD Choice
Starting with MDD is a "high-risk, high-reward" move that signals immense confidence in the AI.
The "CNS Wall": Central Nervous System (CNS) disorders like depression are the "graveyard" of drug development. They have much higher failure rates than oncology because the brain is complex and biological markers are harder to find.
Solving the "Heterogeneity" Problem: Depression isn't one disease; it’s a collection of symptoms. Pharma companies have struggled because a drug might work for 20% of patients but fail a clinical trial because it doesn't work for the other 80%.
Strategic Play: By picking MDD, BullFrog AI is attempting to prove that its bfLEAP® platform can find "precision" targets—sub-types of depression where a drug is almost guaranteed to work. If it works here, the industry will view the AI as capable of solving almost any complex disease.
2. The Role of "Proprietary Brain Data"
You are correct that BullFrog AI has a deep connection to specialized data, even if not highlighted in the headline.
The Johns Hopkins Connection: The bfLEAP® platform was originally developed at the Johns Hopkins University Applied Physics Laboratory (APL). This institution is world-renowned for its work in neuro-engineering and brain-machine interfaces.
Multimodal Data Integration: The press release mentions "multimodal biological complexity." This is code for the AI’s ability to "crunch" different types of data simultaneously:
- Genomic data (DNA/RNA).
- Proteomic data (Protein levels).
- Real-world data (Patient history).
Brain Imaging/Neuro-data: While not explicitly named in the March 30 release, BullFrog’s core technology is designed to ingest high-dimensional "graph" data—which is exactly how brain connectivity and neural networks are mapped.
The Factor in the Deal: The "Top 5" partner likely chose BullFrog specifically because their AI can "see" relationships in brain-related data that standard linear models miss. The partner is paying for BullFrog’s ability to find "causal" links—not just correlations—in that data.
3. Influence on Future Deals
This deal acts as a "Lead Magnet" for several reasons:
The "Validation" Effect: In drug discovery, the first deal is a "Technical Due Diligence" stamp. Other large firms (e.g., Pfizer, Eli Lilly, Takeda) now know that a Top 5 peer has audited BullFrog’s code and data and found it valuable.
Expanding Beyond MDD: CEO Vin Singh’s comment about this being the "most difficult one" refers to the fact that they had to prove the platform works on a "blank slate." Future deals in areas like Oncology (Cancer) or Neuroinflammation (Alzheimer's) will likely move much faster because the "plumbing" of the partnership (legal, data security, and platform proof) is already done.
Precision Psychiatry Trend: There is a massive industry shift toward "Precision Psychiatry." Companies are looking for ways to prescribe the right antidepressant the first time. BullFrog’s access to specialized data and its ability to segment patients makes them a prime target for additional "Companion Diagnostic" deals.
Summary for Your Portfolio
The MDD deal is significant not just for the revenue, but because it positions BullFrog as a specialist in "Hard-to-Crack" diseases. If the internal brain data leads to a successful "target validation" within the next 12 months, the company's valuation would likely shift from that of a small "tech provider" to a "strategic asset" in the global CNS market.
Watch for: Announcements involving "biomarker discovery" or "patient stratification." These are the specific terms that will indicate they are successfully leveraging that proprietary brain data to make the MDD program more efficient than traditional methods.
INV4
3月前
$1.85+ 😃
==================
US Markets See Extreme Stock Swings as Elevai Labs, BullFrog AI Surge While Tech Heavyweights Slide
US equities witnessed another session of sharp divergence and speculative volatility, with several small-cap names posting triple-digit gains even as major technology and index-linked stocks traded lower.
Leading the most advanced list, Elevai Labs (ELAB) surged 113.17%, followed closely by BullFrog AI Holdings (BFRG), which jumped 106.57%. Astrotech Corporation (ASTC) also rallied 102.17%, while Iterum Therapeutics (ITRM) rebounded strongly with a 97.75% gain. Falcon’s Beyond Global warrants (FBYDW) added another 88.37%, underscoring strong speculative interest in micro-cap and event-driven counters.
On the losing side, the sell-off remained equally dramatic. Neuberger Berman High Yield (NHS) plunged 70.4%, while Skycorp Solar (PN) dropped 68.92%. Other steep decliners included BlackRock Utility Infrastructure (BUI), down 61.48%, Real Messenger Corp warrants (RMSGW), lower by 50.92%, and Sharps Technology (STSSW), which slipped 49.29%.
Trading activity was heavily concentrated in volatile small caps. ITRM led share volume with more than 775 million shares, followed by BullFrog AI, Ridgetech (RDGT), and Linkers Industries (LNKS), highlighting aggressive retail and short-term speculative positioning.
However, the broader tone in large-cap markets remained weak. In most active by dollar volume, major ETFs and megacaps were under pressure.
Link article
$BFRG 💹
iHub News
3月前
BullFrog AI signs commercial agreement with top global pharmaceutical company to identify drug targets for depressionMarch 30, 2026 10:22 AM
IH Market News
BullFrog AI Holdings, Inc. (NASDAQ:BFRG), a technology company focused on applying artificial intelligence and machine learning to biomedical data analysis, announced a commercial agreement with one of the world’s top five pharmaceutical companies by revenue in 2025. The partnership will use BullFrog AI’s proprietary bfLEAP® platform to identify and prioritize potential therapeutic targets for major depressive disorder (MDD), supporting the partner’s drug discovery and clinical development efforts in this area. The agreement also grants the pharmaceutical company exclusive access to a selected target candidate.According to data from Stellar Market Research, the global MDD treatment market was valued at more than $8 billion in 2025 and is projected to expand at an average annual growth rate of nearly 5%, potentially exceeding $11 billion by 2032.“This agreement represents strong, high-quality validation of our proprietary capabilities from a leading industry partner, and we are confident that this relationship will expand across other areas of the Customer’s research and development portfolio,” said BullFrog AI Founder and CEO Vin Singh. “Our platform provides drug developers with an end-to-end analytical tool engineered to resolve multimodal biological complexity at scale. Our bfLEAP®, bfPREP, and bfARENAS integrated platform leverages causal network inference to provide drug developers a clearer path forward in the discovery and characterization of drug targets for complex disease like MDD. We look forward to continuing to build on our successful record in identifying and prioritizing portfolios and expanding our commercial partnerships.”About BullFrog AIBullFrog AI applies artificial intelligence and machine learning technologies to improve the drug discovery and development process. Working with leading research institutions, the company combines causal AI methods with its proprietary bfLEAP® platform to analyze complex biological datasets. The goal is to enhance therapeutic development while helping reduce the likelihood of failure during clinical trials.BullFrog AI Holdings stock price
Original: BullFrog AI signs commercial agreement with top global pharmaceutical company to identify drug targets for depression
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