Automating stochastic antibody–drug conjugation: a self-driving lab approach for enhanced therapeutic development†

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY
Liam Roberts, Matthew E. Reish, Jerrica Yang, Wenyu Zhang, Joshua S. Derasp and Jason E. Hein
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引用次数: 0

Abstract

Antibody–drug conjugates (ADCs) have become a promising cancer treatment over the past two decades due to their on-target drug-release capabilities. However, labor-intensive manual conjugations currently limit the throughput of ADC synthesis. Herein, we introduce a Self-Driving Lab (SDL) for automated stochastic antibody–drug conjugation and characterization. The robotic platform performs conjugations and determines drug to antibody ratios from chromatography data, enabling the production of target ADCs iteratively in a closed loop. Our SDL establishes a robust foundation for increasing ADC production throughput and accelerating the development of cancer therapeutics.

Abstract Image

自动化随机抗体-药物偶联:一种增强治疗发展的自驾车实验室方法
在过去的二十年中,抗体-药物偶联物(adc)由于其靶向药物释放能力而成为一种有前景的癌症治疗方法。然而,劳动密集型的人工共轭目前限制了ADC合成的吞吐量。在这里,我们介绍了一个自动驾驶实验室(SDL),用于自动随机抗体-药物偶联和表征。机器人平台执行偶联,并根据色谱数据确定药物与抗体的比例,从而在闭环中迭代地生产目标adc。我们的SDL为提高ADC产量和加速癌症治疗药物的发展奠定了坚实的基础。
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CiteScore
2.80
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