GNQ Insilico's ('GNQ') proprietary genomics-driven platform is leveraging Artificial Intelligence (AI) and Quantum Computing technologies to create 'intelligent digital twins' of human patients that can mimic how a drug will interact with an individual patient's unique biology, down to the cellular level..

GNQ Insilico的（“GNQ”）专有基因组学驱动平台正在利用人工智能（AI）和量子计算技术创建人类患者的“智能数字双胞胎”，可以模拟药物如何与个体患者的独特生物学相互作用，直至细胞水平。。

GNQ's platform has demonstrated success in synthesizing digital twins of human patients.

GNQ的平台在合成人类患者的数字双胞胎方面取得了成功。

Additionally, GNQ was able to simulate the effects of a drug on these digital twins.

此外，GNQ能够模拟药物对这些数字双胞胎的影响。

The results highlight how genomics and AI can be used by the pharmaceuticals and life sciences industries to improve the efficiency of clinical trial designs for new drug development.

结果突出了制药和生命科学行业如何使用基因组学和人工智能来提高新药开发临床试验设计的效率。

Vancouver, British Columbia--(Newsfile Corp. - June 18, 2024) - Trenchant Technologies Capital (CSE: AITT) (OTC: AITTF) (FSE: 5730) 'Trenchant' or 'the Company'), is pleased to announce that its portfolio company GNQ Insilico ('GNQ') has demonstrated promising results in synthesizing digital twins of human patients, and simulating the effects of an infertility drug on these digital replicas using its proprietary AI-driven platform..

不列颠哥伦比亚省温哥华--（新闻文件公司-2024年6月18日）-Trenchant Technologies Capital（CSE:AITT）（OTC:AITTF）（FSE:5730）“Trenchant”或“the Company”）很高兴地宣布，其投资组合公司GNQ Insilico（“GNQ”）在合成人类患者的数字双胞胎以及使用其专有的人工智能驱动平台模拟不孕症药物对这些数字副本的影响方面取得了令人鼓舞的成果。。

Applications of Digital Twins in Drug Discovery and Development

数字双胞胎在药物发现和开发中的应用

In the healthcare industry, digital twins are an emerging technology that has the potential to advance patient care and personalized medicine. Medical digital twins are computer-based virtual models of living and non-living entities which can range from an individual human patient to organs, tissue cells, neural networks, micro-environments, or entire populations.

在医疗保健行业，数字双胞胎是一种新兴技术，有可能推进患者护理和个性化医疗。医学数字双胞胎是基于计算机的活体和非活体实体的虚拟模型，其范围从单个人类患者到器官，组织细胞，神经网络，微环境或整个人群。

Rather than 3D models, medical digital twins are dynamic virtual replicas of real-life entities and processes, continually interacting with and adapting to real-time data and predicting corresponding future scenarios within a complex system, using AI and quantum computer technologies..

。。

Medical digital twins have the potential to significantly improve the drug discovery and drug development process by improving the efficiency, efficacy and outcome of clinical trials. Currently, the average new drug experiences a 90% failure rate1 during clinical trials, while the average cost to bring a new drug to market is estimated at between $161 million - $1.8 billion (fully capitalized costs inclusive of failures)2.

医学数字双胞胎有可能通过提高临床试验的效率，疗效和结果来显着改善药物发现和药物开发过程。目前，在临床试验期间，平均新药的失败率为90%1，而将新药推向市场的平均成本估计在1.61亿美元至18亿美元之间（包括失败在内的全部资本化成本）2。

The average timeframe for bringing a typical new drug to market, from discovery to FDA approval, is between 10 - 15 years3..

从发现到FDA批准，典型新药上市的平均时间为10-15年3。。

Significant improvements in drug discovery and development can be made possible through 'in silico' drug simulations using digital twins, by mimicking how a drug will interact with an individual patient's unique biology, down to the cellular level. This could assist pharmaceutical companies in better designing and optimizing clinical trial protocols by enabling them to more accurately predict how these drug compounds will behave prior to human trials, thereby reducing costs and failure rates..

通过使用数字双胞胎进行“计算机模拟”药物模拟，通过模仿药物如何与个体患者独特的生物学相互作用，直至细胞水平，可以实现药物发现和开发的重大改进。。。

GNQ's Virtually Simulated Clinical Trial

GNQ Insilico simulated the pharmacokinetics and pharmacodynamics of an existing infertility treatment on thousands of digital twins, spanning diverse genetic backgrounds and health profiles, that were synthesized using its platform. GNQ's AI optimizer then analyzed the simulated outcomes to identify optimal dosing strategies tailored to each digital twin's characteristics, accounting for factors like genetics, epigenetics, and environmental exposures..

GNQ Insilico模拟了使用其平台合成的数千对数字双胞胎的现有不孕症治疗的药代动力学和药效学，这些双胞胎跨越了不同的遗传背景和健康状况。然后，GNQ的AI optimizer分析了模拟结果，以确定适合每个数字双胞胎特征的最佳剂量策略，并考虑了遗传学，表观遗传学和环境暴露等因素。。

Sudhir Saxena, CTO of GNQ Insilico commented: 'Human clinical trials are often hindered by variability in how patients respond to drugs. Our AI-driven digital twins platform will enable us to better optimize the trial design for precise patient subpopulations, before ever running an expensive clinical trial.'.

GNQ Insilico的首席技术官Sudhir Saxena评论道：“人类临床试验经常受到患者对药物反应差异的阻碍。我们的人工智能驱动的数字双胞胎平台将使我们能够在进行昂贵的临床试验之前，更好地优化精确患者亚群的试验设计。”。

Two of GNQ's team members, in collaboration with other technologists from leading organizations, also co-authored a recently published paper on a related subject, which illustrates how quantum computing may be leveraged to optimize clinical trial design. To learn more, read the paper: 'Towards Quantum Computing for Clinical Trial Design and Optimization: A Perspective on New Opportunities and Challenges'..

GNQ的两名团队成员与领先组织的其他技术专家合作，也共同撰写了一篇最近发表的有关相关主题的论文，该论文说明了如何利用量子计算来优化临床试验设计。要了解更多信息，请阅读论文：“走向量子计算用于临床试验设计和优化：新机遇和挑战的视角”。。

About GNQ Insilico

关于GNQ Insilico

GNQ Insilico is an AI-biotechnology company pioneering the development and application of next-generation artificial intelligence capabilities to accelerate therapeutic research, clinical development, and individualized patient care. For more information, visit www.gnqinsilico.com.

GNQ Insilico是一家人工智能生物技术公司，致力于开发和应用下一代人工智能功能，以加速治疗研究、临床开发和个性化患者护理。有关更多信息，请访问www.gnqinsilico.com。

About Trenchant Technologies Capital

关于Trenchant Technologies Capital

Trenchant Technologies Capital (CSE: AITT) is an investment issuer focused primarily on seeking investment in companies introducing novel technologies, including Artificial Intelligence and Quantum Computing, to traditional business models that are due for disruption. Trenchant's team undergoes a rigorous due diligence process to identify companies led by seasoned management teams that are strong candidates for acquisition or an initial public offering (IPO)..

Trenchant Technologies Capital（CSE:AITT）是一家投资发行商，主要致力于寻求对将人工智能和量子计算等新技术引入传统商业模式的公司的投资。Trenchant的团队经过严格的尽职调查，以确定由经验丰富的管理团队领导的公司，这些公司是收购或首次公开募股（IPO）的有力候选人。。

In May 2024, Trenchant Technologies Capital acquired a 20% ownership interest in GNQ Insilico from parent company My Next Health Inc. Further, Trenchant holds an option to acquire up to 40% of GNQ Insilico. Learn more here.

2024年5月，Trenchant Technologies Capital从母公司My Next Health Inc.收购了GNQ Insilico 20%的所有权。此外，Trenchant拥有收购GNQ Insilico高达40%的期权。在此处了解更多信息。

ON BEHALF OF THE BOARD TRENCHANT CAPITAL CORP.

代表董事会TRENCHANT CAPITAL CORP。

Per: 'Eric Boehnke'

致：Eric Boehnke

Eric Boehnke, CEO

Eric Boehnke，首席执行官

For further information, please contact:

欲了解更多信息，请联系：

Trenchant Technologies Capital Corp.

Trenchant Technologies Capital Corp。

Eric Boehnke, CEO

Eric Boehnke，首席执行官

Phone: (604) 307-4274

电话：（604）307-4274

Forward-Looking Statements

前瞻性声明

This news release contains certain 'forward-looking statements' within the meaning of such statements under applicable securities law. Forward-looking statements are frequently characterized by words such as 'anticipates', 'plan', 'continue', 'expect', 'project', 'intend', 'believe', 'anticipate', 'estimate', 'may', 'will', 'potential', 'proposed', 'positioned' and other similar words, or statements that certain events or conditions 'may' or 'will' occur.

本新闻稿包含适用证券法所指的某些“前瞻性声明”。前瞻性陈述通常以“预期”、“计划”、“继续”、“预期”、“项目”、“打算”、“相信”、“预期”、“估计”、“可能”、“将会”、“潜在”、“提议”、“定位”等类似词语为特征，或者陈述某些事件或条件“可能”或“将”发生。

These statements, including but not limited to GNQ's ability to successful complete all necessary trials and regulatory approval processes necessary to be in a position to commercialize any of its technologies, including but not limited to its proprietary genomics-driven platform are only predictions.

这些声明，包括但不限于GNQ成功完成所有必要的试验和监管审批流程的能力，以使其任何技术商业化，包括但不限于其专有的基因组学驱动平台，只是预测。

Various assumptions were used in drawing the conclusions or making the predictions contained in the forward-looking statements throughout this news release. Forward-looking statements are based on the opinions and estimates of management of GNQ at the date the statements are made and are subject to a variety of risks and uncertainties and other factors that could cause actual events or results to differ materially from those projected in the forward-looking statements.

在本新闻稿的前瞻性声明中，得出结论或做出预测时使用了各种假设。前瞻性陈述是基于在陈述之日GNQ管理层的意见和估计，并受到各种风险和不确定性以及其他因素的影响，这些因素可能导致实际事件或结果与前瞻性陈述中预测的结果存在重大差异。

Trenchant Capital and GNQ are under no obligation, and expressly disclaims any intention or obligation, to update or revise any forward-looking statements, whether as a result of new information, future events or otherwise, except as expressly required by applicable law..

Trenchant Capital和GNQ没有义务更新或修订任何前瞻性声明，无论是由于新信息、未来事件还是其他原因，除非适用法律明确要求，否则明确否认任何意图或义务。。

Neither the Canadian Securities Exchange nor its Market Regulator (as that term is defined in the policies of the Canadian Securities Exchange) accepts responsibility for the adequacy or accuracy of this news release.

加拿大证券交易所及其市场监管机构（该术语在加拿大证券交易所的政策中定义）均不对本新闻稿的充分性或准确性承担责任。

1 Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharmaceutica Sinica B, 12(7), 3049-3062. https://doi.org/10.1016/j.apsb.2022.02.002

1 Sun，D.，Gao，W.，Hu，H.，＆Zhou，S.（2022）。为什么90%的临床药物开发失败，如何改进？药学学报B，12（7），3049-3062。https://doi.org/10.1016/j.apsb.2022.02.002

2 Morgan, S., Grootendorst, P., Lexchin, J., Cunningham, C., & Greyson, D. (2011). The cost of drug development: A systematic review. Health Policy, 100(1), 4-17. https://doi.org/10.1016/j.healthpol.2010.12.002

2 Morgan，S.，Grootendorst，P.，Lexchin，J.，Cunningham，C.，和Greyson，D。（2011）。药物开发的成本：系统评价。卫生政策，100（1），4-17https://doi.org/10.1016/j.healthpol.2010.12.002

3 Sertkaya, A., Birkenbach, A., Berlind, A., & Eyraud, J., Eastern Research Group, Inc. (2014). Examination of Clinical Trial Costs and Barriers for Drug Development. Assistant Secretary of Planning and Evaluation (ASPE). https://aspe.hhs.gov/reports/examination-clinical-trial-costs-barriers-drug-development-0.

3 Sertkaya，A.，Birkenbach，A.，Berlind，A.，＆Eyraud，J.，Eastern Research Group，Inc.（2014）。检查临床试验成本和药物开发障碍。规划与评估助理秘书（ASPE）。https://aspe.hhs.gov/reports/examination-clinical-trial-costs-barriers-drug-development-0.

To view the source version of this press release, please visit https://www.newsfilecorp.com/release/213409

要查看此新闻稿的源版本，请访问https://www.newsfilecorp.com/release/213409