Note 1 – Organization and Liquidity

Organization and Line of Business

Shuttle Pharmaceuticals Holdings, Inc. (“we,” “us,” “our,” or the “Company”) was originally formed as Shuttle Pharmaceuticals, LLC in the State of Maryland on December 18, 2012. On August 12, 2016, the Company filed articles of conversion with the State of Maryland to convert from an LLC to a C corporation, at which time the Company changed its name to Shuttle Pharmaceuticals, Inc. (“Shuttle”). In connection with the conversion, the Company issued 22,500 shares of common stock in exchange for 100% of the outstanding membership interests in Shuttle prior to conversion. On June 4, 2018, Shuttle completed a reverse merger with Shuttle Pharmaceuticals Holdings, Inc. (then known as Shuttle Pharma Acquisition Corp, Inc.), a Delaware corporation, pursuant to which Shuttle, our operating entity, became a wholly-owned subsidiary of the Company. Shuttle Diagnostics, Inc, a subsidiary of the Company, was formed in the State of Maryland on November 14, 2023.

On November 21, 2025, substantially all of the assets of Molecule.ai, a pharmaceutical software company building an artificial intelligence (“AI”) driven platform for molecular discovery and early-stage drug development, were acquired by a wholly owned subsidiary of the Company. By combining modern AI techniques with structured scientific workflows, the Molecule.ai platform (hereafter, “Molecule.ai” or the “platform”) is designed to help researchers explore the chemical space more efficiently, evaluate molecular ideas with greater clarity and make more informed decisions during the earliest stages of drug development. The platform is engineered to accelerate the iteration cycles that characterize modern drug discovery while preserving scientific reproducibility, traceability and operational reliability. The Molecule.ai technology adapts state-of-the-art AI algorithms to create a practical, domain-specific AI infrastructure layer for molecular research and development. The Company will seek to leverage Molecule.ai’s molecular modeling and predictive analytics platform to significantly augment our drug discovery and development business purpose. In tandem with the Molecule.ai asset acquisition, on November 20, 2025, the Company committed to a plan to wind-down the Clinical Trials of Ropidoxuridine.

Molecule.ai is built on three core architectural components: a unified inference engine, an API-first integration layer and a modular model framework. The unified inference engine orchestrates model execution and multi-step reasoning through a deterministic and traceable sequence of operations. Molecule.ai uses an API-first design, which means that all platform capabilities can be accessed programmatically. All predictive and reasoning functions are modular, which allows the platform to expand over time without changing the underlying infrastructure. Molecule.ai currently supports three scientific and computational functions that reflect both its pharmaceutical focus and the structured inference techniques seen in modern agentic LLM systems: (1) molecular property prediction, (2) cross-molecule and cross-property evaluation and (3) prediction reasoning and structured molecular insights. The platform predicts a wide range of molecular properties that are relevant to early-stage discovery and medicinal chemistry and provides inference pipelines for predicting molecular properties. By using transformer-based models, the platform computes predictive outputs on a wide range of therapeutic tasks. The platform evaluates multiple molecules across multiple properties in a unified workflow, helping researchers quickly identify the most-promising candidates, understand trade-offs, and make structured, evidence-based decisions. Molecule.ai also includes a reasoning module that uses LLM-based structured inference to contextualize predictions, explain differences between compounds, perform rule-guided reasoning and produce narrative or structured scientific interpretations with the goal to make complex scientific outputs understandable and actionable for broader research and development audiences.

The broader competitive landscape in the AI ecosystem, especially AI-driven drug discovery, is rapidly advancing toward agentic AI systems and more integrated, end-to-end platforms. To stay at the front of this shift, Molecule.ai is seeking to expand its molecule predictive capabilities, and automated multi-tool workflows. These expansions are designed in accordance with the agentic framework and multi-tool reasoning to further strengthen the platform. A new module will evaluate chemical–protein interaction likelihoods, which will help researchers estimate how molecules may interact with specific biological targets. Molecule.ai is adding biological context reasoning supported by curated genomic and disease-association evidence, which helps tie together chemical ideas with the biological systems they may ultimately affect. The Company intends for the platform to increasingly support insights that connect chemical properties with biological implications, to create a more complete, end-to-end picture for early research teams. Molecule.ai is also developing an autonomous AI agent designed to reduce manual workload and accelerate early research cycles, which would be designed to interpret a discovery objective, plan a series of actions, route each step to the appropriate tools, evaluate preliminary outputs and iterate until a stable result is achieved.

The Molecule.ai platform adheres to strict engineering standards, including reproducibility, traceability, extensibility, scalability and interoperability, which align with modern AI infrastructure expectations for regulated biomedical environments. Molecule.ai aims to become the foundational AI layer for molecular and biological reasoning in pharmaceutical research and development. By integrating property prediction, biological context, multi-step reasoning and agentic automation, the platform seeks to accelerate early discovery while maintaining scientific reliability and operational transparency.

On May 6, 2026, the Company completed its merger by and among the Company, Shuttle Merger Sub, Inc. (a wholly-owned subsidiary organized for the purpose of effecting the merger) and United Dogecoin, Inc. (“United Dogecoin” or “UD”), pursuant to the merger agreement entered into on April 30, 2026. Upon the closing of the merger, Shuttle Merger Sub, Inc. merged with and into United Dogecoin, with United Dogecoin surviving the Merger. As a result of the Merger, United Dogecoin became wholly-owned by the Company (however the Company does not have a controlling interest in United Dogecoin, as discussed further in Note 7).

United Dogecoin was founded as a Dogecoin mining company built on three foundational advantages: scale, preferential access to best-in-class equipment, and an industry leading management team. Its mission was to establish and maintain category leadership in the Dogecoin sector through high-efficiency, low-cost mining operations and strategic coin accumulation, combining operational excellence, consistency and expert execution to build a robust reserve. Since the acquisition, UD has sought to become a start-up digital infrastructure company focused on the development, ownership, and operation of large-scale computing infrastructure supporting blockchain networks, artificial intelligence (“AI”), and high-performance computing (“HPC”) workloads. UD is currently seeking to build an energy-first digital infrastructure platform designed to deploy computing capacity across multiple end markets as demand evolves. UD’s strategy is to identify, acquire, develop, and operate energy infrastructure capable of supporting large-scale computing operations. UD is seeking opportunities where long-term access to reliable, low-cost power can provide a sustainable competitive advantage.

Initially, UD intends to deploy infrastructure supporting Dogecoin mining while designing its facilities to accommodate AI, HPC, cloud computing, and other computational workloads over time. This flexible approach is expected to allow management to allocate computing capacity based on market demand and expected returns. To date, UD has purchased 500 rigs and has initiated a co-location agreement for these units. UD continues to evaluate strategic acquisitions, infrastructure development opportunities, commercial partnerships, and financing transactions intended to expand its digital infrastructure platform.

Liquidity and Going Concern

Our unaudited condensed consolidated financial statements are prepared on a going concern basis, which contemplates the realization of assets and the satisfaction of liabilities and commitments in the normal course of business. The Company has incurred losses since inception and has a net loss of approximately $5.3 million and no revenues for the six months ended June 30, 2026 and working capital deficit of approximately $3.1 million as of June 30, 2026. The Company does not expect to generate positive cash flows from operating activities in the near future.

In May 2026, the Company closed a private investment in public equity (“PIPE”) financing consisting of (i) 1,910 shares of Series B-2 Convertible Preferred Stock and (ii) Common Warrants to purchase up to 927,185 shares of the Company’s common stock at an exercise price of $10.30 per share (the “May 2026 PIPE Warrants”). In addition, subject to stockholder approval and the achievement of specified milestone events, investors may receive Pre-Funded Warrants exercisable for up to 3,148,619 shares of the Company’s common stock (the “2026 Pre-Funded Warrants”). The PIPE financing resulted in gross proceeds of $9.6 million and net proceeds of approximately $8.4 million after deducting placement agent fees, legal costs, and other transaction costs of approximately $1.2 million. The Company intends to use the proceeds for digital asset infrastructure initiatives related to the merger with United Dogecoin and the remainder for working capital and general corporate purposes.

However, the Company’s existing cash resources and the cash received from the equity offerings are not expected to provide sufficient funds to carry out the Company’s operations through the next twelve months.

The ability of the Company to continue as a going concern is dependent upon its ability to continue to successfully raise additional equity or debt financing to fund ongoing operations, commercialize and market the Molecule.ai platform, develop and expand its digital asset infrastructure operations through United Dogecoin, and generate sufficient revenues and cash flows from its business activities. The Company and UD are currently in the final stages of negotiating a data center land deal. Building on this anticipated transaction, management plans to undertake a significant capital raise in the near term, targeting between $120 million and $150 million. This financing will leverage the Company and UD’s existing sector network, investment bankers, and established industry relationships. The successful completion of this financing, however, cannot be guaranteed. These conditions raise substantial doubt about the Company’s ability to continue as a going concern within one year after the date that the consolidated financial statements are issued.

The accompanying unaudited condensed consolidated financial statements do not include any adjustments to reflect the future effects on the recoverability and classification of assets or the amounts and classification of liabilities if the Company is unable to continue as a going concern.