Connect Biopharma Holdings Ltd

Current report

Unregistered Sales of Equity Securities

Current report

Except as disclosed in a Current Report on Form 8-K filed with the SEC on March 30, 2026, there were no other sales of unregistered equity securities during the quarter ended March 31, 2026.

Current report

Issuer Purchases of Equity Securities

Current report

None.

Current report

None.

Current report

Not applicable.

Previous report

The increasing use of artificial intelligence (“AI”) and machine learning in drug discovery and development introduces new and evolving risks that could harm our business and competitive position.

Previous report

AI is increasingly playing a role in our industry, being used for target identification, drug discovery, preclinical modeling, clinical operations, and data analysis, among other things. While it is not a significant factor in our current operations, AI may play a future role in our operations based upon our evaluation of its usefulness to us. As with many new and emerging technologies, AI presents numerous risks and challenges that could adversely affect our business.

Previous report

AI technologies are inherently complex and evolving. They may not function as intended, produce accurate results, or provide actionable insights. The quality of AI outputs depends heavily on the quality and quantity of input data, which in the life sciences context may be limited, biased, incomplete, or subject to regulatory and privacy constraints. If we utilize AI in the future and our AI systems fail to achieve their intended purposes – such as identifying viable therapeutic candidates or targets, predicting biological outcomes, producing reproducible results, optimizing clinical trial designs or operations, and other similar or related purposes – our product development efforts may be delayed or unsuccessful. If we are unable to successfully integrate and manage AI within our business, or if AI fails to deliver the expected benefits, our ability to develop rademikibart or any other new therapies could be materially adversely affected.

Previous report

The industry in which we compete is characterized by rapid technological advancements, frequent introductions of new products and heavy competition. The development of rademikibart and any other future product candidates is vital to our success. The implementation of AI technologies and processes by us or by any third-party collaborators, including advanced predictive analytics, computational approaches and so-called “generative” AI, has the potential to provide significant benefits in these areas. Use of AI in our efforts may be difficult to deploy successfully due to operational issues inherent in such methods. In particular, AI algorithms utilize machine learning and predictive analytics which may lead to flawed, biased, or inaccurate results, or exposure to competitive and reputational harm.

Previous report

Even with the successful implementation of AI, we may fail to correctly identify indications and allocate resources efficiently, which could adversely impact our pipeline and ability to compete effectively. Developing, testing and deploying resource-intensive AI systems may also require additional investment and increase our costs, and there is no guarantee that our investment in such systems would lead to more effective or efficient development of rademikibart or other investigational products, or lead to eventual regulatory approval or commercialization of any new products.

Previous report

We also face increased competition from other companies that are using AI and related methods for drug discovery and development, some of which have more resources than we do and may have developed more effective methods than we and any third-party collaborators have, which may reduce our and any third-party collaborators’ effectiveness in identifying potential targets and attracting additional collaborators to work with us. If our competitors are able to utilize new technologies more effectively (including but not limited to those that may involve AI or be created using AI) to discover, develop and commercialize products that compete with any of our product candidates or potential commercial products, such technologies could adversely impact our ability to compete.

Previous report

Further, AI presents additional risks and challenges, especially as the use of these technologies becomes more important to our operations over time. Generative AI may be used improperly or inappropriately which could lead to the tainting of our proprietary information and render us unable to qualify for certain patent or trade secret protection. Its use by people, including our vendors, employees, suppliers and contractors, with access to our proprietary and confidential information, including trade secrets, may continue to increase and may lead to the release of such information, which may impact our ability to realize the benefit of our intellectual property. The increasing use of AI and machine learning in drug discovery and development introduces new and evolving risks related to ownership, inventorship, and protection of intellectual property generated by or with the assistance of AI technologies. Regulatory and legal frameworks governing AI-generated inventions are still developing and may create uncertainty regarding our ability to secure and enforce rights in such inventions. Our use of generative AI platforms may lead to novel and urgent cybersecurity and privacy risks, which may adversely affect our operations and reputation, as well as the operations of any third-party collaborators. Emerging ethical issues surround the use of AI, and we may be subject to reputational and legal risk if our deployment or use of AI becomes controversial. Regulators could limit our, or any third-party collaborator’s ability to develop or implement AI-based technologies as part of measures taken against us or any third-party collaborators in particular or as a consequence of broader legislation, which could have an adverse effect on our or any third-party collaborator’s business, results of operations and financial conditions. Several jurisdictions around the globe, including Europe and the U.S., have proposed, enacted, or are considering laws governing the development and use of AI/Machine Learning, such as the EU’s AI Act and the Colorado Artificial Intelligence Act. For example, the EU AI Act, which entered into force on August 1, 2024 and most provisions of which will become effective on August 2, 2026, sets out a risk-based framework, subjecting certain AI technologies to numerous compliance obligations, including transparency, conformity and risk assessment, monitoring and human oversight requirements. Under the EU AI Act, non-compliant companies may be subject to administrative fines of up to 35 million Euros or 7% of a company’s total worldwide annual turnover for the preceding financial year, whichever is the higher. Certain of our activities could subject us to the EU AI Act and depending on how the EU AI Act is implemented and interpreted, we may have to adapt our business practices, contractual arrangements, and services to comply with such obligations. Likewise, in the U.S., several states, including Colorado and California, passed laws to re…

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