# Lunai Bioworks Inc.: Form 10-Q for the period ended Dec 31, 2024

- Company: [Lunai Bioworks Inc.](/companies/lnai.md) (CIK 1527728)
- Form: 10-Q
- Filed: 2025-02-19
- Accepted by EDGAR: Feb 19, 2025, 16:02 ET
- Period: 2024-12-31
- Accession: 0001731122-25-000258
- Inline XBRL: yes
- Main document: https://www.sec.gov/Archives/edgar/data/1527728/000173112225000258/e6372_10q.htm
- All documents and exhibits: https://www.sec.gov/Archives/edgar/data/1527728/000173112225000258/

## Figures reported in this filing

Standardized XBRL line items for the period ended 2024-12-31.

| Line item | Period | Value | XBRL concept |
| --- | --- | ---: | --- |
| Research and development | 3 months, 2024-10-01 to 2024-12-31 | $161.1k | us-gaap:ResearchAndDevelopmentExpense |
| Research and development | 6 months, 2024-07-01 to 2024-12-31 | $551.3k | us-gaap:ResearchAndDevelopmentExpense |
| Operating income | 3 months, 2024-10-01 to 2024-12-31 | −$4.5m | us-gaap:OperatingIncomeLoss |
| Operating income | 6 months, 2024-07-01 to 2024-12-31 | −$57.9m | us-gaap:OperatingIncomeLoss |
| Interest expense | 3 months, 2024-10-01 to 2024-12-31 | $98.9k | us-gaap:InterestExpenseNonoperating |
| Interest expense | 6 months, 2024-07-01 to 2024-12-31 | $349.0k | us-gaap:InterestExpenseNonoperating |
| Net income | 3 months, 2024-10-01 to 2024-12-31 | −$7.3m | us-gaap:NetIncomeLoss |
| Net income | 6 months, 2024-07-01 to 2024-12-31 | −$51.5m | us-gaap:NetIncomeLoss |
| Diluted EPS | 3 months, 2024-10-01 to 2024-12-31 | −$0.04 | us-gaap:EarningsPerShareDiluted |
| Diluted EPS | 6 months, 2024-07-01 to 2024-12-31 | −$0.32 | us-gaap:EarningsPerShareDiluted |
| Basic EPS | 3 months, 2024-10-01 to 2024-12-31 | −$0.04 | us-gaap:EarningsPerShareBasic |
| Basic EPS | 6 months, 2024-07-01 to 2024-12-31 | −$0.32 | us-gaap:EarningsPerShareBasic |
| Diluted shares (weighted) | 3 months, 2024-10-01 to 2024-12-31 | 161,825,205 shares | us-gaap:WeightedAverageNumberOfDilutedSharesOutstanding |
| Diluted shares (weighted) | 6 months, 2024-07-01 to 2024-12-31 | 160,909,289 shares | us-gaap:WeightedAverageNumberOfDilutedSharesOutstanding |
| Operating cash flow | 6 months, 2024-07-01 to 2024-12-31 | −$4.6m | us-gaap:NetCashProvidedByUsedInOperatingActivities |
| Cash and equivalents | at 2024-12-31 | $311.8k | us-gaap:CashAndCashEquivalentsAtCarryingValue |
| Current assets | at 2024-12-31 | $1.7m | us-gaap:AssetsCurrent |
| Total assets | at 2024-12-31 | $111.3m | us-gaap:Assets |
| Current liabilities | at 2024-12-31 | $28.6m | us-gaap:LiabilitiesCurrent |
| Total liabilities | at 2024-12-31 | $29.3m | us-gaap:Liabilities |
| Shareholders' equity | at 2024-12-31 | $82.1m | us-gaap:StockholdersEquity |

## Management's discussion and analysis

As filed, 46,979 characters.

### Forward-Looking Statement Notice

Certain statements made in this Quarterly Report on Form 10-Q are “forward-looking statements” (within the meaning of the Private Securities Litigation Reform Act of 1995) regarding the plans and objectives of management for future operations. Such statements involve known and unknown risks, uncertainties and other factors that may cause actual results, performance, or achievements of Renovaro Inc. (“Renovaro,” and together with its subsidiaries, the “Company”, “we” or “us”) to be materially different from any future results, performance or achievements expressed or implied by such forward-looking statements. The forward-looking statements included herein are based on current expectations that involve numerous risks and uncertainties. Our actual future results and trends may differ materially depending on a variety of factors, including, but not limited to, the risks and uncertainties discussed in Part I, Item 1A, “Risk Factors” in our Annual Report on Form 10-K as filed with the SEC on October 10, 2024. The Company’s plans and objectives are based, in part, on assumptions involving the continued expansion of the business. Assumptions relating to the foregoing involve judgments with respect to, among other things, future economic, competitive and market conditions and future business decisions, all of which are difficult or impossible to predict accurately and many of which are beyond the control of the Company. Although the Company believes its assumptions underlying the forward-looking statements are reasonable, any of the assumptions could prove inaccurate and, therefore, there can be no assurance the forward-looking statements included in this Quarterly Report will prove to be accurate. In light of the significant uncertainties inherent in the forward-looking statements included herein, the inclusion of such information should not be regarded as a representation by the Company or any other person that the objectives and plans of the Company will be achieved.

### Our Business

Renovaro Inc. operates through two subsidiaries, Renovaro Biosciences and Renovaro Cube. Renovaro Cube refers to Renovaro Cube Intl. Ltd. (formerly known as GediCube Intl. Ltd.) and its wholly owned subsidiaries GediCube, B.V. and Grace Systems B.V., which were acquired on February 13, 2024.

### Renovaro Biosciences Overview

Renovaro Biosciences is a biotechnology company intending, if the necessary funding is obtained, to develop advanced allogeneic cell and gene therapies to promote stronger immune system responses potentially for long-term or life-long cancer remission in some of the deadliest cancers, and potentially to treat or cure serious infectious diseases such as Human Immunodeficiency Virus (HIV) infections. As a result of our acquisition of GEDi Cube Intl Ltd. on February 13, 2024, we have shifted the Company’s primary focus and resources to the development of the Renovaro Cube technologies.

### Therapeutic Technologies

Renovaro Biosciences aims to train the immune system to allow a person to better fight diseases through allogeneic cell and/or gene therapy. Our vision is for a world with healthy longevity, and free from toxic chemotherapy, for those with cancer and other serious diseases. Renovaro Biosciences will seek to leverage general principles and advances in the knowledge of the immune response to engineer cells with enhanced attributes to promote the recognition and elimination of disease cells.

#### Allogeneic Cell Therapy

The strategic benefit of the allogeneic cell therapy technologies is to potentially allow for the manufacture of large, “off-the-shelf” banks of therapeutic cells that are readily available on demand by healthcare professionals, to potentially decrease the time between diagnosis and treatment.

In certain treatments (e.g., HIV and cancer), cells taken from healthy donors are engineered to introduce signaling molecules that are designed to enhance the ability of specific immune cells to recognize diseased cells, and to help recruit other cells that will destroy cancer or virus infected cells.

#### Gene Therapy

Renovaro Biosciences may also seek to explore various approaches for gene therapy design elements to potentially eliminate virus-infected or cancer cells by the modulation of the patient’s immune system. Upon injecting into the patients, these genetically engineered allogeneic cells have little to no risk of passing those modifications to the patient since they are terminally differentiated with locked functionality to activate the host immune system. Gene modified allogeneic cells are expected to be rejected naturally once they activate the patient’s immune system therefore will have a very short survival time.

### Renovaro Biosciences Focus Areas:

### Oncology:

**RENB-DC11: Genetically modified Allogeneic Dendritic Cell Therapeutic Vaccine as Potential Product for Long-term Remission of Solid Tumors; specifically Pancreatic tumors**

#### Allogeneic Cell Therapy Platform – Completed pre-IND, IND-enabling phase.

Based on learnings from our internal research, literature reviews of ongoing clinical development for solid tumors, and recent advances in immune modulation, we have designed an innovative therapeutic vaccination platform that could potentially be used to induce life-long remission from some of the deadliest solid tumors such as pancreatic, liver, triple negative breast and head & neck cancers.

The platform may one day enable broad immune enhancements that are combined with cancer specific antigens that could be applicable to a wide range of solid tumors. This approach allows us to quickly adapt our approach to any patient solid tumor using the same banked allogenic drug substance.

**RENB-DC20: Genetically modified Allogeneic Dendritic Cell Therapeutic Vaccine as Potential Treatment Product for Long-term Remission of Triple Negative Breast Cancer**

Triple Negative Breast Cancer (TNBC) is a subtype of breast cancer that is negative for estrogens receptor (ER) negative, progesterone receptor (PR) negative and human epidermal growth factor receptor 2 (HER2). TNBC is characterized by its unique molecular profile, aggressive nature, and distinct metastatic patterns that lack targeted therapies. TNBC is well known for its aggressive behavior and is characterized by onset at a younger age, high mean tumor size, and higher-grade tumors.

Based upon our internal research, literature reviews of ongoing clinical development for solid tumors, and recent advances in immune modulation, we believe we may have the ability to design an innovative therapeutic vaccination platform that could potentially be used to treat some of the deadliest and hard-to-treat solid tumors that include triple negative breast cancer.

### Infectious Diseases:

**RENB-HV12: Genetically Modified Allogeneic Dendritic Cell Therapeutic Vaccine as Potential Treatment Product for Long-term Remission of HIV; A Chronic Infectious Disease**

The oncology therapeutic vaccine technology could potentially be adapted to target infectious disease antigens and be a viable therapeutic approach in difficult to treat chronic infectious diseases. As described above, the engineered allogenic dendritic cell drug substance is thought to be able to be loaded with various cancer antigens for specific solid tumors but could or may be loaded with infectious disease antigens to elicit a more robust immune response to viruses and other difficult to treat infections.

### Renovaro Cube Overview

Renovaro Cube is an AI-driven healthcare technology company focusing on the earliest possible detection of cancer and its recurrence. Renovaro Cube has developed a proprietary AI platform that analyzes genetics using Explainable AI (as defined below) to provide earlier and more accurate cancer diagnosis. This platform uses a multi-omics approach to search for individual biomarkers that are present even in asymptomatic patients. This approach is combined with differential molecular capabilities that are designed to identify, differentiate and pinpoint the exact source. Renovaro Cube’s process also involves the mining of biomarker panels, which are integrated into a machine learning library referred to as “RenovaroCube” to further enhance diagnosis.

Renovaro Cube also aims to utilize its proprietary AI platform in the development of commercial products to support clinical, research and pharmaceutical organizations that are trying to improve patient care through precision diagnosis, prediction of success of therapy, new drug discovery, treatment protocols or clinical trials. Specifically, Renovaro Cube is focused on developing products and services aimed at (i) early cancer characterization, (ii) personalized treatment selection, (iii) prediction and tracking response to therapies, (iv) recurrence detection and efficacy monitoring, and (v) ultimately, drug discovery.

Renovaro Cube was initially incorporated as Grace Systems B.V. (“Grace Systems”) in 2013 under the laws of the Netherlands to develop unique data mining algorithms to enable banking, finance and government entities to extract business insights from data. Grace Systems began applying its algorithms to biological data in 2018 to uncover cancer-associated patterns. Beginning in 2018, Grace Systems pivoted its platform to focus only on healthcare. Renovaro Cube has focused on developing its AI technology for early cancer detection.

Renovaro Cube has now focused on commercialization of its AI technology. Renovaro Cube believes that it has developed a unique approach to the early detection and diagnosis of cancer and its recurrence and, in time, other rare diseases through the systematic analysis of data using AI technologies, data mining procedures and algorithms for health technology.

Renovaro Cube’s technology has been trained on complex heterogeneous cancer data and appears to find patterns associated with cancer in public and private data resources. With the help of Renovaro Cube’s algorithms, discovered patterns may be translated into biomarkers that can be used in a clinical setting to target various aspects of cancer diagnosis and treatment.

### Renovaro Cube’s Strategy

Renovaro Cube’s product development focuses on four core areas:

- **Early Detection.** Multi-cancer early detection (“MCED”) blood tests are advanced diagnostic tools that analyze cell-derived molecules present in the bloodstream. These tests specifically look for abnormal genetic, epigenetic or proteomic patterns of these cell-derived molecules, which can indicate the presence of cancer cells. By examining the molecules shed from various cells, including cancer cells, MCED tests aim to detect cancer at an early stage. This approach holds promise for improving cancer detection and potentially saving lives.
- **Recurrence of cancer**. A recurrence refers to the return of cancer after a period of remission. A cancer recurrence happens because, in spite of the efforts to kill the cancer, some cells may remain, which grow and eventually cause symptoms. In rare instances, a patient may develop a new cancer that’s completely unrelated to the originally diagnosed cancer, which is referred to as a second primary cancer. An early warning system could help to identify a recurrence as early as possible, thereby helping to accelerate any treatment and diagnosis. The different types of recurrence include:
- **Local recurrence,** meaning that the cancer has returned in the same place it first started;
- **Regional recurrence**, meaning that the cancer has returned to the lymph nodes near the place it first started; and
- **Distant recurrence**, meaning the cancer has returned in another part of the body.
- **Response to treatment.** At Renovaro Cube we aim to develop a new array of diagnostic products that can accurately identify patients that are going to respond or fail to a certain drug. In highly toxic therapies it will not only increase survival but will also reduce unnecessary exposure to chemotherapy. Furthermore, the costs for cancer drugs are usually very high. Providing the right therapy to the right patient will therefore significantly reduce the costs of medicine in cancer.
- **Clinical trials**. Clinical trials involve a type of research that studies new tests and treatments and evaluates their effects on human health outcomes. People volunteer to take part in clinical trials to test medical interventions including drugs, cells and other biological products, surgical procedures, radiological procedures, devices, behavioral treatments and preventive care. Clinical trials are carefully designed, reviewed and completed, and need to be approved before they can start.

In response to these four core areas, the key components of Renovaro Cube’s product development are to build a software and hardware platform that:

- Uses data science to develop novel insights into the characterization of diseases such as cancer. Renovaro Cube intends to apply its proprietary technology to biological data from multiple sources to enable the typification (or classification) of disease entities and sub-entities to provide insights about the nature and behavior of diseases to payers, providers, pharmaceutical companies and patients.
- Enables more accurate diagnosis and earlier detection of cancer and other diseases with the goal of maximizing outcomes and minimizing the costs of treatment. Renovaro Cube intends to develop a system to understand the smallest fragments of cancer in the blood of the patient. Presently, Renovaro Cube is developing a product to analyze results from liquid biopsy run through an Oxford Nanopore Sequencer. We expect the Renovaro Cube product will subsequently identify, train and validate explainable biomarkers, panels and models on different molecular layers. Multiple models will be individually trained for optimal stratification through the entire health journey, ensuring the right accuracy for a therapeutic decision in every stage. Renovaro Cube will integrate different modalities and molecular data sources into a differential diagnostic report. Diagnostics and prognosis will be explainable with quality control reports and biomarker insights for different disciplines ensuring maximum trust and insight in medical decision making.
- Assists in clinical trials with patient cohort selection and response tracking, to be used by companies like Renovaro Biosciences in their patient cohort selection for their clinical trials, by looking at which patients are reacting positively, negatively and have no reaction. This data becomes more important through the progression of the different phases of drug development, as more and more patients are added. Renovaro Cube will provide multi-omic data analysis, looking for specific changes in the patients that might indicate a change in their molecular make-up. This can then be used for the next phase of a clinical trial to look for the specific molecular data that has showed a positive reaction in the previous phase. It also provides insights for more effective response tracking, which Renovaro Cube believes is important to the providers of care as well as the development and evaluation of new pharmaceuticals and immune therapies in clinical trials. Patient response to treatment can be used to focus the target audience for drugs in development and in subsequent clinical practice. As Renovaro Cube collects more data, longitudinal about treatment and response, it will have the ability to train prognostic models to give an insight in disease progression and treatment response, both critical for enrolling in clinical trials and eventually every treatment. Because Renovaro Cube consists of many independently trained and validated models, it will have the ability to assist in virtually every therapeutic decision, for different subtypes and groups (stratifications). The multi-omics and multi-modal pipelines could allow the use of multiple combinations of tissue samples and diagnostic platforms. The detailed diagnostic reports will allow and support insights for multiple disciplines such as cancer biology, genomics and pathology to look at underpinning biomarkers, pathways and clinical annotations.
- Provides insight into patients who have had cancer previously. These insights will provide for more effective recurrence monitoring, which Renovaro Cube believes is important to the providers of care and patients during follow-up monitoring of remissions. Renovaro Cube anticipates that payers want to detect and re-treat recurrences at the earliest possible stage to maximize patients’ outcomes in terms of time and cost and that, similarly, patients with a recurrence are keen to re-engage with effective treatment at the earliest opportunity. A key aspect of this will be taking blood from the patients, sequencing this blood and running it through the Renovaro Cube platform which will identify if the patient has any indication of the recurrence of the same or a new cancer. For recurrence monitoring, Renovaro Cube will focus on a highly sensitive combination of lab and information technology. Lab protocols, sequence post processing and machine learning will all be designed, trained and validated to get the best signal with the highest sensitivity to catch early signals of recurrence. This will be done on a regular basis allowing surveillance analysis over time.
- Includes biomarker panels that will be extended to include as many layers of genetic information (multi-omics) as possible including mutation, gene expression, methylation status, fragmentomics, nucleosome mapping, collectively named multi-omics, with the goal to reach the highest accuracy possible, both in terms of sensitivity and specificity of each individual biomarker panel. This provides a non-invasive alternative for the current complex, expensive and cumbersome procedures.
- Create value through advancing more sophisticated typification of diseases in an effort to address some of the pressing problems faced by modern healthcare, including healthcare costs, an aging population and developments in medical technology that produce a stream of increasingly sophisticated treatments requiring more precise targeting.

One additional key focus of Renovaro Cube is its multi-modal, data analysis. Multi-modal data encompasses the whole aspect of data from a patient perspective, whether genomics, imaging, phenotypic or even wearable data, which can be cross analyzed to produce data that could not be previously produced. Renovaro Cube intends to use multi-modal data to bring new insights to the clinical and research teams trying to understand what to do next with the patient.

### Renovaro Cube’s Technology and Techniques

Renovaro Cube is dedicated to the development of early cancer detection blood tests and expects to develop partnerships with third-party laboratories across the United Kingdom, the Netherlands and the rest of Europe and will also expand to the United States. Renovaro Cube is focused on developing diagnostic tests and test kits that would analyze samples derived from non-invasive liquid biopsy samples and intends to perform these tests from Renovaro’s dedicated fully certified service laboratory and engage third-party laboratories to perform these tests for end-users.

For this purpose, Renovaro Cube has developed an AI platform that aims to leverage expertise in both biological and computational sciences and to go beyond traditional tumor signals by detecting the body’s early warning signs of cancer. Renovaro Cube’s goal is to provide accurate and reliable tests that can aid in the early diagnosis and treatment of cancer. Renovaro Cube’s AI technology is created to detect a wide range of biological signs to enhance the accuracy and sensitivity of early cancer detection and, thereby, enable earlier intervention and potentially improved patient outcomes.

Renovaro Cube’s AI technology aims to address three critical facets of medical needs within the domain of cancer diagnosis (as illustrated below):

- type-specific cancer detection;
- pan-cancer detection; and
- patient stratification.

Moreover, the versatility of Renovaro Cube’s AI technology extends to encompass the realm of rare cancers, including cases such as cancer of unknown primary.

Leveraging DNA methylation data, Renovaro Cube has identified and validated biomarker panels tailored for the detection of a wide range of cancers, including bladder, breast, colon, prostate, thyroid, head and neck, liver, kidney and lung cancer.

The foundational architecture of Renovaro Cube’s AI technology is engineered to facilitate comprehensive pan-cancer analysis through its extensive record of informative biomarkers discovered across a diverse array of cancer types. This comprehensive repository empowers Renovaro Cube’s AI technology to swiftly cross-reference biomarkers and explore molecular commonalities and distinctions that span multiple tumor categories.

For example, the capabilities of Renovaro Cube’s AI technology have unearthed biomarkers capable of pinpointing a specific subgroup of thyroid cancer patients characterized by a distinct genomic alteration, the neurotrophic tyrosine receptor kinase (“NTRK”) gene fusion. Identification of these NTRK-positive patients provides an actionable therapeutic target.

#### Uses of Renovaro Cube’s AI Technology

Renovaro Cube has developed its AI platform to support:

- AI-assisted patient diagnostics;
- multi-omic data analysis;
- genome-wide or targeted analysis;
- pan-cancer analysis;
- different technology platforms (sequence or array);
- tracking of each sample;
- AI-guided biomarker discovery for single or multiple cancer types; and
- logs of analysis steps and outcomes (data preparation, discovery, validation).

Renovaro Cube’s AI platform is an enterprise software platform that is distinguished from its competitors’ technology by its core attributes encompassing AI-guided analysis and meticulous record-keeping of data handling procedures within audit trails, logs, and data discoveries. Renovaro Cube designed this technology to support and validate every phase of the process, from the initial handling of raw data to the creation of essential biomarker panels. Renovaro Cube’s AI platform also facilitates the integration of data originating from diverse sources, including public databases and collaborative partnership data.

Illustrated below is the three-phase workflow behind Renovaro Cube’s AI platform for biomarker discovery using DNA methylation data. This workflow commences with the identification of pertinent single- and multi-omic data best suited to address the specific inquiries of Renovaro Cube’s clients, and the subsequent stages involve the meticulous pre-processing and loading of this data into the platform. This process culminates in the availability of a dashboard offering the client insights into the data’s characteristics, such as data quality, the technology employed, and associated metadata.

- Phase I of the workflow behind Renovaro Cube’s AI platform primarily centers on the pivotal process of biomarker discovery. This intricate procedure unfolds through the application of data mining algorithms and statistical methodologies integrated into the AI platform. The paramount objective of Phase I is to reduce the plethora of genomic features displaying variations across samples, which is accomplished by systematically eliminating extraneous or inconsequential features while preserving those features that exhibit the greatest potential for accurately detecting cancer.
- Phase II of the workflow builds upon the foundation of selected biomarkers by focusing on understanding the dynamic interplay among these chosen biomarkers, culminating in the creation of composite panels. The goal of Phase II is to pinpoint biomarker combinations that not only demonstrate robustness in detecting cancer but also maintain their efficacy across diverse contexts. Renovaro Cube believes that its AI algorithms are adept at uncovering multiple combinations across a spectrum of panels, which is supported by Renovaro Cube’s AI-guided panel mining, a proprietary combinatorial optimization technique used by Renovaro Cube’s AI technology. This approach, coupled with the capacity to explore numerous panels, significantly enhances the likelihood of discovering panels that align with specific metric criteria, such as sensitivity, specificity, precision, and recall and allows for tailoring criteria to align with clients’ unique needs, such as the number of biomarkers included per panel, or the inclusion of biomarkers associated with the expression of specific genes. The performance of the top-tier panels is further fine-tuned through the application of machine learning models. Subsequently, the efficacy of these biomarker panels in detecting cancer is validated through independent data sets.
- Phase III of the workflow involves Renovaro Cube’s collaboration with its clinical partners to validate the performance of the biomarker panels. Through this collaboration, Renovaro Cube can confirm the utility and accuracy of its biomarker panels in real-world clinical contexts.

#### AI-Assisted Diagnostics

The process of biomarker discovery facilitated by Renovaro Cube’s AI technology has yielded a set of data that enables scrutiny of the genomic distinctions and commonalities inherent in diverse cancer types. This data set can support the diagnosis of cancers when their type or origin remains unidentified.

In addition to this role in biomarker discovery and the development of diagnostic tests, Renovaro Cube’s AI technology also integrates AI-guided molecular profiling of patient samples and furnishes diagnostic patient reports. These diagnostic reports reflect the outcomes of molecular profiling, coupled with interpretations provided by Renovaro Cube’s team, to facilitate the process of cancer diagnostics by a qualified healthcare provider, who can consider these reports in the context of a patient’s medical history, clinical signs, and symptoms, among other factors.

### Quality Control Process

Renovaro Cube undertakes post-processing of data generated from sequence and arrays to ensure accurate and meaningful results. These post-processing steps for omic data include:

1\. Quality Control: Quality control is performed to assess the overall data quality and to identify any technical issues or anomalies.

2\. Normalization: arrays can introduce various sources of technical variation, such as batch effects, intensity variations, and probe-specific biases.

3\. Quality Filtering: After genotype calling, additional quality filtering may be performed to remove low-quality SNPs based on criteria like call rates, minor allele frequency, Hardy-Weinberg equilibrium p-values, and linkage disequilibrium.

Other post-processing steps may include genotype calling, population stratification and association analysis. Specific post-processing steps may vary depending on the type of array used, the study design, and the analytical goals.

### Planning for Commercialization

#### Partnerships in Development

To enhance multi-omic and multi-modal capacity, and to work to validate those capabilities with human samples including liquid-biopsy-based tests/test kits, Renovaro Cube is actively pursuing relationships with leading academic cancer centers, pathology and imagery centers in Europe, the USA and the Middle East. In certain cases, scopes of work are in process. This is a very attractive model for partners to be involved with Renovaro Cube to perform multi-omics genetic analysis using liquid biopsies.

#### Resources

Renovaro Cube intends to hire additional staff to increase the speed and velocity of its organization, including the development of the AI platform and the opportunities to deploy the AI platform for research perspective and ultimately for clinical practice and into clinical trials.

In addition, Renovaro Cube intends to build out its infrastructure by leasing space for storage, networking and hosting facilities.

#### Target Market

Renovaro Cube’s intended customers will be hospitals, clinics, insurance companies, pharmaceutical companies, biotech companies, research centers, physicians and individual patients.

Renovaro Cube aims to utilize its AI technology to commercialize products and test kits for healthcare providers, hospitals, clinics and doctors that will expedite diagnosis and the selection of appropriate treatment for various types of cancer. Renovaro Cube intends to differentiate its products based on the following factors:

- Proprietary and unique panel mining algorithms to create multiple biomarker stratifications per cancer;
- Explainable AI, offering traceability between the prediction and the exact biomarkers, panels and genes;
- Differential diagnosis, inclusion and exclusion of cancer types based on facts; and
- Precision diagnosis, with a high accuracy percentage with machine-learning tuning.

The multi-omic design of Renovaro Cube’s AI platform enables the use of different molecular layers, such as epigenomics, transcriptomics, and metabolomics, together with genomics and clinical data.

#### Panel Mining

The unique panel mining technique in Renovaro Cube’s technology repeatedly investigates genes to identify relevant biomarkers. The proprietary technique in Renovaro Cube’s technology not only searches for individual biomarkers, but also integrates validated panels for different cancer types into the “RenovaroCube” machine learning library. This process enables precision diagnosis, by including one cancer and excluding others based on statistically, scientifically and clinically validated machine-learning panels.

Panel mining is designed to combine biomarkers into panels in such a way that the final panel meets:

- performance metric criteria;
- technical criteria, such as a minimum or maximum number of biomarkers for the selected assay;
- biological criteria, non-annotated genes inclusion; and
- stratification criteria.

#### Explainable AI

The term “Explainable AI” refers to the ability of an AI system or model to provide human-understandable explanations for its decision-making process or predictions. This feature aims to bridge the gap between the “black box” nature of many AI algorithms and the need for transparency, interpretability, and accountability in AI applications.

In traditional machine learning approaches, such as deep neural networks, the internal workings of the model can be complex and difficult to interpret. This lack of interpretability poses challenges in critical domains where decisions have significant implications, such as healthcare.

Renovaro Cube believes that Explainable AI is crucial for ensuring transparency, fairness, and accountability in AI systems. Renovaro Cube’s AI platform includes Explainable AI by design. All data points, calculations and results are traceable, and all calculations are verifiable and reproducible with the same result.

Disease prognosis is one of the diagnostic capabilities of the Explainable AI feature of Renovaro Cube’s technology. Disease prognosis gives more insight for a specific patient that empowers healthcare providers, patients, and their families to make well-informed decisions about treatment, care, and future planning, thereby enhancing patient-centered care, optimizing resource utilization, and contributing to improved patient outcomes and quality of life.

#### Differential Diagnosis

Renovaro Cube’s AI platform offers differential diagnosis by design due to its approach with a multitude of models for different diseases and the ability to include and exclude diseases.

Diseases like cancer are very homogenous, meaning that markers like TP53 or BRCA are expressed with multiple cancers. To address this homogeneity, differential diagnosis distinguishes between two or more conditions or diseases that share similar signs, symptoms or characteristics. The goal of differential diagnosis is to consider and evaluate all possible diagnoses for the patient’s symptoms to determine the most likely cause. Differential diagnosis therefore aims to identify the underlying condition accurately and guide appropriate treatment and management strategies.

### Corporate History

We were incorporated under the laws of the State of Delaware on January 18, 2011, under the name Putnam Hills Corp. and in 2014 we merged with and changed our name to DanDrit Biotech USA, Inc. In 2018, we acquired Enochian Biopharma and changed our name to Enochian BioSciences Inc. In August 2023, the Company changed its corporate name to Renovaro Biosciences Inc. On February 13, 2024, the Company changed its corporate name to Renovaro Inc. On February 13, 2024, Renovaro Inc. acquired Renovaro Cube Intl Ltd and its subsidiaries, in which Renovaro Cube became a wholly-owned subsidiary of Renovaro Inc.

### Going Concern and Management’s Plans

The Company’s consolidated financial statements are prepared using the generally accepted accounting principles applicable to a going concern, which contemplates the realization of assets and liquidation of liabilities in the normal course of business. However, the Company has incurred substantial recurring losses from continuing operations, has used cash in the Company’s continuing operations, and is dependent on additional financing to fund operations. The Company incurred a net loss of $7,252,394 and $51,464,429 for the three and six months ended December 31, 2024, respectively. As of December 31, 2024, the Company had cash and cash equivalents of $311,764 and an accumulated deficit of $383,919,510 and a working capital deficit of $26,898,493. These conditions raise substantial doubt about the Company’s ability to continue as a going concern for one year after the date the financial statements are issued. The consolidated financial statements do not include any adjustments relating to the recoverability and classification of recorded asset amounts and classification of liabilities that might be necessary should the Company be unable to continue in existence.

Management has reduced overhead and administrative costs by streamlining the organization to focus around the development and validation of its AI-driven cancer diagnostics platform. The Company has tailored its workforce to focus on these activities. In addition, the Company intends to secure additional required funding through equity or debt financing. However, there can be no assurance that the Company will be able to obtain any sources of funding. Such additional funding may not be available or may not be available on reasonable terms, and, in the case of equity financing transactions, could result in significant additional dilution to our stockholders. If we do not obtain required additional equity or debt funding, our cash resources will be depleted and we could be required to materially reduce or suspend operations, which would likely have a material adverse effect on our business, stock price and our relationships with third parties with whom we have business relationships, at least until additional funding is obtained. If we do not have sufficient funds to continue operations, we could be required to seek bankruptcy protection or other alternatives that could result in our stockholders losing some or all of their investment in us.

Funding that we may receive during the fiscal year 2025 is expected to be used to satisfy existing and future obligations and liabilities and working capital needs, to support commercialization of our products, to conduct the clinical and regulatory work to develop our product candidates, and to begin building working capital reserves.

### Results of Operations for the Three and Six Months ended December 31, 2024 and 2023

The following table sets forth our revenues, expenses and net loss for the six months ended December 31, 2024 and 2023. The financial information below is derived from our unaudited condensed consolidated financial statements.

| Operating Expenses | For the Three Months Ended December 31, 2024 | 2023 | Increase/(Decrease) $% |  | For the Six Months Ended December 31, 2024 | 2023 | Increase/(Decrease) $% |  |
| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
| General and administrative | $4,353,123 | $3,616,392 | $736,731 | 20% | $9,654,373 | $11,906,602 | $(2,252,229) | (19)% |
| Research and development | 161,084 | 620,521 | (459,437) | (74)% | 551,273 | 1,187,165 | (635,892) | (54)% |
| Goodwill impairment | — | — | — | 0% | 47,614,729 | — | 47,614,729 | 100% |
| Depreciation and amortization | 32,109 | 33,162 | (1,053) | (3)% | 64,494 | 60,422 | 4,072 | 7% |
| Total Operating Expenses | 4,546,316 | 4,270,075 | 276,241 | 6% | 57,884,869 | 13,154,189 | 44,730,680 | 340% |
| **LOSS FROM OPERATIONS** | (4,546,316) | (4,270,075) | 276,241 | 6% | (57,884,869) | (13,154,189) | (44,730,680) | 340% |
| **393)Other Income (Expenses)** |  |  |  |  |  |  |  |  |
| Change in fair value of contingent consideration | (2,590,000) | — | (2,590,000) | 100% | 6,660,000 | — | 6,660,000 | 100% |
| Loss on extinguishment of debt | — | — | — | 0% | — | (120,018) | 120,018 | (100)% |
| Interest expense | (98,891) | (274,984) | 176,093 | (64)% | (348,971) | (454,255) | 105,284 | (23)% |
| Interest and other income | (17,187) | 15,938 | (33,125) | (208)% | 109,411 | 24,313 | 85,098 | 350% |
| Total Other Income (Expense) | (2,706,078) | (259,046) | (2,447,032) | 945% | 6,420,440 | (549,960) | 6,970,400 | (1,267)% |
| **NET LOSS** | $(7,252,394) | $(4,529,121) | $(2,723,273) | 60% | $(51,464,429) | $(13,704,149) | $(37,760,280) | 276% |

32

### Revenues

We are a pre-revenue, pre-clinical biotechnology and artificial intelligence driven healthcare technology company. We have never generated revenues and have incurred losses since inception. We do not anticipate earning any revenue until our therapies or products are approved for marketing and sale.

### Expenses

Our operating expenses for the three months ended December 31, 2024 and 2023, were $4,546,316 and $4,270,075 respectively, representing an increase of $276,241 or approximately 6%. The increase in operating expenses primarily relates to the increase in general and administrative expenses of $736,731, partially offset by the decrease in research and development expenses of $459,437.

Our operating expenses for the six months ended December 31, 2024 and 2023, were $57,884,869 and $13,154,189 respectively, representing an increase of $44,730,680, or approximately 340%. The increase in operating expenses primarily relates to the increase in goodwill impairment of $47,614,729, partially offset by the decrease in general and administrative expenses of $2,252,229 and the decrease in research and development expenses of $635,892.

General and administrative expenses for the three months ended December 31, 2024, and 2023, were $4,353,123 and $3,616,392, respectively, representing an increase of $736,731 or approximately 20%. The variance is related to an increase in consulting fees expense of $667,815, compensation and related expenses of $354,968, and accounting fees of $134,620, partially offset by a decrease in non-cash stock-based compensation expense of $440,597.

General and administrative expenses for the six months ended December 31, 2024, and 2023, were $9,654,373 and $11,906,602, respectively, representing a decrease of $2,252,229 or approximately 19%. The variance is related to a decrease in consulting fees expense of $2,098,916, and non-cash stock-based compensation expense of $1,066,778, partially offset by an increase in compensation and related expenses of $637,587 and legal expenses of $192,571.

Research and development expenses for the three months ended December 31, 2024, and 2023, were $161,084 and $620,521, respectively, representing a decrease of $459,437 or approximately 74%. The variance is primarily driven by a decrease of $236,026 in collaborating partner expenses with CDMO and CROs and $205,057 in consumables related to pre-clinical testing.

Research and development expenses for the six months ended December 31, 2024, and 2023, were $551,273 and $1,187,165, respectively, representing a decrease of $635,892 or approximately 54%. The variance is primarily driven by a decrease of $498,092 in collaborating partner expenses with CDMO and CROs, and consulting expenses of $107,433.

The Company recorded other expense of $2,706,078 for the three months ended December 31, 2024, compared to other expense of $259,046 for the three months ended December 31, 2023, representing an increase in other expense of $2,447,032 or 945%. The variance is primarily due to an increase of $2,590,000 in the change in fair value of contingent consideration in the current period.

The Company recorded other income of $6,420,440 for the six months ended December 31, 2024, compared to other expense of $549,960 for the six months ended December 31, 2023, representing a decrease in other expense of $6,970,400 or 1,267%. The variance is primarily due to the change in fair value of contingent consideration liability of $6,660,000 in the current period.

### Net Loss

Net loss for the three months ended December 31, 2024, and 2023, was $7,252,394 and $4,529,121, respectively, representing an increase in net loss of $2,723,273 or approximately 60%. The increase in net loss was primarily due to an increase in the change in fair value of contingent consideration of $2,590,000, an increase in general and administrative expenses of $736,731, partially offset by a decrease in research and development expenses of $459,437.

Net loss for the six months ended December 31, 2024, and 2023, was $51,464,429 and $13,704,149, respectively, representing an increase in net loss of $37,760,280 or approximately 276%. The increase in net loss was primarily due to an increase in goodwill impairment of $47,614,729, partially offset by the decrease in general and administrative expenses of $2,252,229 and change in fair value of contingent consideration of $6,660,000.

### Liquidity and Capital Resources

We have historically satisfied our capital and liquidity requirements through funding from stockholders, the sale of our Common Stock and warrants, and debt financing. We have never generated any sales revenue to support our operations, and we expect this to continue until our therapies or products are approved for marketing in the United States and/or Europe. Even if we are successful in having our therapies or products approved for sale in the United States and/or Europe, we cannot guarantee that a market for the therapies or products will develop. We may never be profitable.

As noted above under the heading “Going Concern and Management’s Plans,” through December 31, 2024, we have incurred substantial losses. We will need additional funds both in the next twelve months and beyond for (a) research and development, (b) increases in personnel, (c) the purchase of equipment, and investment in the development and validation of our technology. The availability of any required additional funding cannot be assured. In addition, an adverse outcome in legal or regulatory proceedings in which we are currently involved or in the future may be involved could adversely affect our liquidity and financial position. We may raise such funds from time to time through public or private sales of our equity or debt securities. Such financing may not be available on acceptable terms, or at all, and our failure to raise capital when needed could materially adversely affect our growth plans and our financial condition and results of operations.

As of December 31, 2024, the Company had $311,764 in cash and working capital deficit of $26,898,493 as compared to $220,467 in cash and working capital deficit of $28,312,274 as of June 30, 2024, an increase of 41% and decrease of 5%, respectively.

### Assets

Total assets at December 31, 2024, were $111,340,272 compared to $163,129,450 as of June 30, 2024. The decrease in assets is primarily due to goodwill impairment of $47,614,729 in the current period.

### Liabilities

Total liabilities at December 31, 2024, were $29,280,954 compared to $31,152,306 as of June 30, 2024. The decrease in total liabilities was primarily related to the decrease of $6,660,000 in contingent consideration liability, partially offset by an increase of $2,679,004 in notes payable – related parties, net and an increase in accounts payable of $1,485,872.

The following is a summary of the Company’s cash flows (used in) or provided by operating, investing, and financing activities:

|  | Six Months Ended December 31, 2024 | Six Months Ended December 31, 2023 |
| --- | ---: | ---: |
| Net Cash Used in Operating Activities | $(4,576,052) | $(5,923,830) |
| Net Cash Used in Investing Activities | — | (1,115,209) |
| Net Cash Provided by Financing Activities | 4,620,162 | 5,409,682 |
| Effect of exchange rates on cash | 47,187 | (1,143) |
| Change in Cash and Cash Equivalents | $91,297 | $(1,630,500) |

34

### Cash Flows

The decrease in our cash used in operating activities is primarily related to the changes in our operating assets and liabilities. The change is primarily drive by our net loss offset by significant non-cash charges such as stock based compensation, impairments and change in fair value of contingent consideration. Additionally, our operating cash flow was positively impacted by changes in our operating assets and liabilities, primarily other receivables, prepaid expenses and accounts payable.

Cash used in investing activities during the prior period primarily related to the issuance of notes receivable prior to the acquisition of Renovaro Cube totaling $1,073,625.

Cash provided by financing activities during the period primarily related to net proceeds of $2,671,926 from issuance of notes payable and $2,376,181 from private placements that were partially offset by $427,945 in repayment of a finance agreement.

### Off-Balance Sheet Arrangements

The Company does not have any off-balance sheet arrangements that have or are reasonably likely to have a current or future effect on the Company’s financial condition, changes in financial condition, revenues or expenses, results of operations, liquidity, capital expenditures or capital resources that is material to investors.

### Significant Accounting Policies and Critical Accounting Estimates

The methods, estimates, and judgments that we use in applying our accounting policies have a significant impact on the results that we report in our financial statements. Some of our accounting policies require us to make difficult and subjective judgments, often as a result of the need to make estimates regarding matters that are inherently uncertain.

For a summary of our accounting policies, see Note 1 to the unaudited condensed consolidated financial statements.

## Market risk

As filed, 175 characters.

As a “smaller reporting company” as defined by Rule 12b-2 of the Securities Exchange Act of 1934, the Company is not required to provide the information required by this Item.

## Controls and procedures

As filed, 2,156 characters.

### Evaluation of Disclosure Controls and Procedures

Our Chief Executive Officer and Chief Financial Officer (the “Certifying Officers”) are responsible for establishing and maintaining disclosure controls and procedures for the Company. The Certifying Officers have designed such disclosure controls and procedures to ensure that material information is made known to them, particularly during the period in which this Report was prepared.

The Certifying Officers are responsible for establishing and maintaining adequate internal control over financial reporting for the Company and used the “Internal Control over Financial Reporting Integrated Framework” issued by the Committee of Sponsoring Organizations (“COSO”) to conduct an extensive review of the Company’s “disclosure controls and procedures” (as defined in the Exchange Act, Rules 13a-15(e) and 15-d-15(e)) as of the end of each of the periods covered by this Report (the “Evaluation Date”). Based upon that evaluation, the Certifying Officers concluded that, as of December 31, 2024, our disclosure controls and procedures were not effective in ensuring that the information we were required to disclose in reports that we file or submit under the Securities and Exchange Act of 1934, as amended, is recorded, processed, summarized and reported within the time periods specified in SEC rules and forms. The deficiency is attributed to the Company not having adequate resources to address complex accounting matters. This control deficiency will be monitored, and attention will be given to this matter as we grow.

The Certifying Officers based their conclusion on the fact that the Company has identified a material weakness in controls over financial reporting, detailed above. We expect to be deficient in our disclosure controls and procedures until sufficient capital is available to hire the appropriate internal accounting staff.

### Changes in Internal Controls

There have been no changes in our internal controls over financial reporting during the six months ended December 31, 2024, that have materially affected or are reasonably likely to materially affect our internal controls.

## Risk factors

As filed, 175 characters.

As a “smaller reporting company” as defined by Rule 12b-2 of the Securities Exchange Act of 1934, the Company is not required to provide the information required by this Item.

Filed Feb 19, 2025.
Source: SEC EDGAR, the filing index for accession 0001731122-25-000258. Last ingested by Listed: Nov 2, 2026, 15:40 ET. No prices; not investment advice.