AI Proteins partners with University of Missouri to advance cancer theranostics research

AI Proteins, a biotechnology company focused on designing therapeutic miniproteins, has entered into a Collaborative Research Agreement with the University of Missouri-Columbia. 

The partnership involves working with Dr. Carolyn Anderson, Simón-Ellebracht Professor in Medicinal Chemistry and Professor of Radiology, to advance the development of targeted radioligand therapy (RLT).

The collaboration aims to explore the potential of de novo designed miniproteins labeled with alpha and beta-emitting radionuclides as cancer theranostics—compounds that combine diagnostic and therapeutic capabilities. The research will evaluate multivalent miniproteins, which can target multiple tumor-associated antigens (TAAs) simultaneously, compared to traditional single-antigen approaches.

Dr. Chris Bahl, founder, President, and CEO of AI Proteins, said:

“AI Proteins recognizes Dr. Carolyn Anderson and her team as leaders in molecular imaging and theranostics research. We are excited to apply our ability to design multivalent miniproteins de novo to create targeted theranostics that are capable of binding to multiple different tumor antigens. By working together, we have the opportunity to take a major step forward for patients who are battling cancer.”

Research goals

The collaboration seeks to address limitations in current theranostic technologies, which often target only one or two tumor antigens. By expanding the targeting capabilities to multiple TAAs, the research could improve cancer specificity and effectiveness while addressing challenges such as tumor heterogeneity and resistance.

Dr. Anderson highlighted the significance of this approach, stating:

“A major limitation of current theranostics is that they have affinity for one, or at most two, tumor antigens. This collaboration proposes a potential breakthrough approach in the ability to target theranostics to as many tumor antigens as possible in furtherance of solving long-standing challenges in cancer specificity, heterogeneity, and potentially resistance, which are major impediments to improving outcomes for patients.”

The research is expected to result in a platform that can be applied to various cancers. Following the completion of this phase, the collaboration plans to advance the technology through preclinical and clinical development and explore additional cancer indications.