BULLFROG AI HLDGS Stock Price, News & Analysis

BullFrog AI Holdings, Inc. (NASDAQ: BFRG) is a technology-enabled drug development company that applies artificial intelligence (AI) and machine learning (ML) to complex biomedical and clinical data. According to the company’s public disclosures, BullFrog AI focuses on using advanced AI/ML analytics to support the successful development of pharmaceuticals and biologics, with an emphasis on precision medicine and data-driven decision-making across the drug discovery and development lifecycle.

The company is incorporated in Nevada and conducts its operations through BullFrog AI Holdings, Inc. and affiliated entities. Its common stock and tradeable warrants are listed on The Nasdaq Capital Market under the symbols BFRG and BFRGW, respectively, as noted in multiple SEC filings. BullFrog AI describes itself as an emerging growth and smaller reporting company, reflecting its status as a growth-oriented participant in the professional, scientific, and technical services sector.

Core Technology and Platforms

At the center of BullFrog AI’s business is its proprietary AI/ML platform known as bfLEAP®. Company filings state that bfLEAP originated from technology developed at The Johns Hopkins University Applied Physics Laboratory (JHU-APL) and is designed for advanced analysis of complex biomedical data. BullFrog AI has secured an exclusive, worldwide, royalty-bearing license from JHU-APL covering issued patents, proprietary algorithm libraries, and related know-how, and later expanded this license to include additional improvements and intellectual property.

Public materials describe bfLEAP as an analytical platform that uses causal AI and an ensemble of machine learning models to interpret multimodal biological and clinical datasets. The platform is intended to uncover patterns, identify meaningful patient subgroups, and support target identification, biomarker discovery, and patient stratification. BullFrog AI reports that bfLEAP has been applied to translational research and clinical trial data, including oncology use cases, to help refine trial design and guide therapeutic development strategies.

In addition to bfLEAP, BullFrog AI has developed bfPREP™, a dedicated data preparation and standardization module. Company news releases explain that bfPREP was originally created to ingest and standardize large volumes of legacy and siloed clinical trial documents, transforming unstructured records such as clinical PDFs into analysis-ready datasets. bfPREP automates data cleansing, normalization, and structuring, and is described as purpose-built for clinical, omics, and real-world data. BullFrog AI positions bfPREP as a foundational component that feeds high-quality, standardized data into bfLEAP and related analytics workflows.

BullFrog AI also highlights BullFrog Data Networks™, a platform and solutions library that organizes and delivers AI-driven analytics for drug discovery and development. According to company communications, BullFrog Data Networks is designed as a modular, enterprise-grade stack that can be deployed within biopharmaceutical organizations’ existing infrastructure. It supports disease-centric, visual exploration of complex datasets and is intended to enable use cases such as early target identification, mechanism-of-action exploration, drug repurposing, and clinical trial optimization.

Business Focus and Collaborations

In its SEC registration statement and subsequent shareholder communications, BullFrog AI states that its objective is to apply bfLEAP and related tools to advance precision medicine in collaboration with biopharmaceutical partners, as well as in internal development programs. The company emphasizes the use of AI/ML to analyze preclinical and clinical trial data with the goal of making drug development more efficient and reducing failure rates in clinical trials.

BullFrog AI has disclosed collaborations with research and industry partners. Public news releases describe work with Eleison Pharmaceuticals, a Phase 3 oncology company, where BullFrog AI used bfPREP and bfLEAP to convert extensive historical clinical trial documentation into standardized datasets and then identify data-driven patient subgroups in oncology trials. The company reports that this collaboration produced insights relevant to patient stratification and trial optimization and led to a jointly authored abstract accepted for presentation at the American Society of Clinical Oncology Gastrointestinal Cancers Symposium (ASCO GI).

The company has also announced a commercial collaboration with Sygnature Discovery, a contract research organization specializing in drug discovery. Under this relationship, Sygnature’s business development team introduces BullFrog Data Networks target selection solutions to a global biopharma client base. BullFrog AI characterizes this collaboration as a way to extend the reach of its AI platforms into early-stage discovery programs across multiple therapeutic areas.

Applications in Drug Discovery and Development

Across its public communications, BullFrog AI describes a focus on several key application areas within drug discovery and development. These include data readiness and preparation, target discovery, biomarker identification, patient stratification, and clinical trial optimization. By applying causal AI and explainable machine learning methods, the company aims to help drug developers interpret large, heterogeneous datasets spanning genomics, transcriptomics, proteomics, clinical records, and real-world evidence.

In oncology, BullFrog AI has reported work in precision oncology analytics, including analyses of pancreatic cancer trial data. Using bfLEAP and bfPREP on historical trial datasets, the company states that it has identified biologically meaningful patient clusters and subgroups that may show enhanced response to investigational chemotherapeutic agents. These efforts are presented as examples of how AI-driven clustering and causal inference can reveal treatment effect heterogeneity and potential early predictors of clinical outcomes.

Company materials also describe broader use of its platforms to support disease categorization, medication normalization, and feature engineering within standardized data models. By combining automated data processing with human-in-the-loop validation, BullFrog AI emphasizes an approach that seeks to balance the speed of AI agents with the oversight required for high-stakes clinical decision support.

Intellectual Property and Licensing

According to the company’s S-1 registration statement, BullFrog AI’s core technology is underpinned by licensing agreements with JHU-APL. The original license granted exclusive, worldwide rights to technology underlying bfLEAP, including multiple issued patents and proprietary algorithm libraries. A subsequent license agreement in July 2022 expanded the intellectual property base and established royalty and minimum payment structures tied to net sales for services and internally developed drug projects that use the licensed technology.

The company has disclosed that JHU-APL is entitled to a percentage of net sales from services and internally developed projects that utilize the licensed technology, as well as tiered sublicensing fees. BullFrog AI notes that it has made equity and cash payments in connection with these agreements and that minimum annual royalty obligations are creditable against royalties paid. These arrangements form a key part of the company’s technology and IP foundation.

Capital Markets and Corporate Structure

BullFrog AI Holdings, Inc. completed an initial public offering and has since pursued additional financings, as reflected in its SEC filings. The company has entered into a purchase agreement with Lincoln Park Capital Fund, LLC, under which Lincoln Park has committed to purchase shares of BullFrog AI common stock up to a specified aggregate amount, subject to conditions and limitations. A related registration statement on Form S-1 covers the resale of shares issued or issuable under this agreement.

The company has also sought stockholder approval for matters such as reverse stock split authority, amendments to its equity incentive plan, and share issuance under the Lincoln Park agreement, as detailed in its proxy materials and Form 8-K filings. These actions are presented as part of BullFrog AI’s efforts to manage its capital structure, maintain Nasdaq listing compliance, and support ongoing operations and commercialization activities.

In an 8-K filing, BullFrog AI reported receiving a notice from Nasdaq regarding non-compliance with a stockholders’ equity requirement and later disclosed that Nasdaq granted an extension period to regain compliance. The company has indicated that it intends to take measures consistent with its submitted plan to address the listing requirement, while acknowledging that there is no assurance of success.

Position Within the Life Sciences and AI Ecosystem

Across its shareholder communications, whitepapers, and news releases, BullFrog AI presents itself as a participant at the intersection of AI, bioinformatics, and life sciences R&D. The company emphasizes the challenge of interpreting large, complex datasets in drug development and positions its platforms—bfPREP, bfLEAP, and BullFrog Data Networks—as tools intended to convert data abundance into actionable insights.

Rather than focusing solely on fully automated decision-making, BullFrog AI highlights a “human-in-the-loop” approach, where AI agents handle repeatable, large-scale data tasks and domain experts provide oversight and validation. This framework is described as central to building trustworthy, auditable analytics pipelines for pharmaceutical and biotechnology partners.

FAQs About BullFrog AI Holdings, Inc.

• What does BullFrog AI Holdings, Inc. do?
  BullFrog AI Holdings, Inc. applies artificial intelligence and machine learning to complex biomedical and clinical data to support drug discovery and development. Its platforms are designed to help biopharmaceutical organizations analyze preclinical and clinical datasets, identify patient subgroups, and inform trial and development strategies.
• What are bfLEAP® and bfPREP™?
  According to company disclosures, bfLEAP is BullFrog AI’s core AI/ML analytics engine, originally derived from technology developed at The Johns Hopkins University Applied Physics Laboratory. bfPREP is a data preparation and standardization module that ingests, cleans, and structures clinical and related data into analysis-ready formats that can be used by bfLEAP and other tools.
• What is BullFrog Data Networks™?
  BullFrog Data Networks is described by the company as a modular platform and solutions library that enables biopharma clients to deploy BullFrog AI’s technology within their own infrastructure. It supports applications such as target selection, biomarker discovery, patient stratification, and clinical trial optimization through a disease-centric interface.
• How does BullFrog AI work with biopharmaceutical partners?
  Public announcements indicate that BullFrog AI engages in collaborations and commercial relationships with organizations such as Eleison Pharmaceuticals and Sygnature Discovery. In these relationships, BullFrog AI applies its platforms to partner data to support activities like patient stratification, target discovery, and trial optimization, and may offer its technology through partner sales channels.
• What role does The Johns Hopkins University Applied Physics Laboratory play?
  BullFrog AI’s S-1 filing explains that its founding AI/ML platform, bfLEAP, originated from technology developed at JHU-APL. The company holds exclusive, worldwide licenses to this technology, including patents and proprietary algorithms, and has expanded these rights through subsequent agreements and amendments.
• On which exchange does BullFrog AI trade?
  According to multiple SEC filings, BullFrog AI’s common stock trades on The Nasdaq Capital Market under the symbol BFRG, and its tradeable warrants trade under the symbol BFRGW.
• What is BullFrog AI’s approach to AI in drug development?
  In its public communications, BullFrog AI emphasizes causal and explainable AI, combined with human oversight. The company describes its goal as enabling scientists and clinicians to make better and faster decisions by turning complex, multimodal data into interpretable insights, rather than replacing human expertise.
• How does BullFrog AI address clinical trial data challenges?
  BullFrog AI reports that bfPREP and bfLEAP can transform large volumes of legacy and unstructured clinical trial documentation into standardized datasets, then use AI/ML analytics to identify patient subgroups and patterns. This process is presented as a way to support trial design, patient stratification, and evaluation of treatment effects.