AIkido Pharma Executes Artificial Intelligence and Machine Learning Research Agreement with Cogia Biotech LTD

AIkido Pharma | May 06, 2020

AIkido Pharma Executes Artificial Intelligence and Machine Learning Research Agreement with Cogia Biotech LTD
AIkido Pharma Inc. (Nasdaq: AIKI) today announced execution of an Artificial Intelligence (AI), and Machine Learning (ML) research agreement with Cogia Biotech LTD ("Cogia") (www.cogia.de) to accelerate the Company's pancreatic cancer genetic marker research.  Cogia is a Big-data, AI, and ML software company committed to using powerful AI engines and algorithms to develop compelling outcomes in drug development.  Cogia provides state-of-the-art digital information and discovery tools to subject-matter experts and scientists working in genetics and cancer research, to advance drug development.  Cogia's existing clients include many international companies, including international pharmaceutical companies. Cogia will augment the Company's efforts of using machine learning to find genetic markers that could lead to pancreatic cancer. As with many cancers, early detection is vital, but in pancreatic cancer, surgical intervention is currently the only effective treatment for the extension of life. Pancreatic cancer is relatively rare; however, it is the third leading cause of cancer deaths in the United States.  The disease is often asymptomatic, making early detection and treatment difficult or even impossible. Only 20% of individuals are diagnosed with pancreatic cancer early enough to be surgical candidates. Reliable markers for early detection will expand the number of patients who are eligible for life-extending surgery. Andreas Typaldos, Executive Chairman of Cogia Biotech, expressed his excitement about the research agreement with AIkido. "Even during the preparatory work leading up to this strategic agreement with AIkido, one could see the promise of compelling outcomes in early and better detection of pancreatic cancer and possibility for novel and more effective therapeutics using state-of-the-art technologies like AI and ML. The very earliest project-design work sessions between Cogia Biotech AI/ML data scientists, bio-informatics engineers, and cancer research scientists, on one hand, and AIkido and University of Texas Southwestern Medical Center research scientists, on the other, clearly pointed to how compelling and appropriate is the vision of Anthony Hayes for having AIkido use of these breakthrough biotech technologies in disease detection and drug development. We are excited and honored to be part of Anthony's plan and effort.

Spotlight

The genomic variation comes in many forms, from single point mutations through too much larger structural variations. To date, the majority of genetic research has focused on single nucleotide polymorphisms (SNPs); however, it is now known that structural variation accounts for a greater number of variable bases than SNPs. Perhaps unsurprisingly then, While advances in sequencing technology over the last 40 years have increased our understanding of the genome considerably, its application to structural variation analysis has been limited by the short read technology commonly used.

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CELL AND GENE THERAPY

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Graphite Bio | November 26, 2021

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Northwest Biotherapeutics Announces the Completion of Financing on a Favorable Terms for Approximately $8 Million

Northwest Biotherapeutics | August 12, 2020

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MEDTECH

Flamingo Therapeutics Expands Alliance with Ionis Pharmaceuticals to Develop RNA-targeted Therapies for Oncology

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Spotlight

The genomic variation comes in many forms, from single point mutations through too much larger structural variations. To date, the majority of genetic research has focused on single nucleotide polymorphisms (SNPs); however, it is now known that structural variation accounts for a greater number of variable bases than SNPs. Perhaps unsurprisingly then, While advances in sequencing technology over the last 40 years have increased our understanding of the genome considerably, its application to structural variation analysis has been limited by the short read technology commonly used.