Regeneron Pharmaceuticals Inc. has elected to exercise its right to advance a therapeutic antibody candidate, discovered in partnership with Abcellera Biologics Inc. as part of a multitarget collaboration between the companies, into further preclinical development.

Diwali, the Festival of Light, marks different events depending on where it is celebrated. In some areas of India, it marks the return of Lord Rama to his birthplace of Ayodhya after defeating the demon Ravana.

Mercury Bio LLC has developed a patent-pending technology that will enable highly targeted delivery of both RNA therapeutics and small-molecule drugs to targeted diseased cells.

Diwali, the Festival of Light, marks different events depending on where it is celebrated. In some areas of India, it marks the return of Lord Rama to his birthplace of Ayodhya after defeating the demon Ravana. For Vivek Subbiah, associate professor at the Department of Investigational Cancer Therapeutics, Division of Cancer Medicine of the MD Anderson Cancer Center, the story of how Rama defeated Ravana has parallels in drug discovery. Ravana had 10 heads, and when one was cut off, it grew back. Rama defeated Ravana by means of a magic arrow that entered through the demon’s navel.

Turn Biotechnologies Inc. has presented interim preclinical data that demonstrates treating T cells with its proprietary technologies can significantly increase their ability to kill cancer.

Researchers based at the City University of New York (CUNY) have designed a deep learning artificial intelligence (AI) model that can improve preclinical predictions of drug responses in humans. As outlined in the Oct. 17, 2022, online issue of Nature Machine Intelligence, the researchers believe their model – a context-aware deconfounding autoencoder (CODE-AE) – can help improve the quality of early drug response prediction and help reduce subsequent clinical trial failures.

Researchers based at the City University of New York (CUNY) have designed a deep learning artificial intelligence (AI) model that can improve preclinical predictions of drug responses in humans. As outlined in the Oct. 17, 2022, online issue of Nature Machine Intelligence, the researchers believe their model – a context-aware deconfounding autoencoder (CODE-AE) – can help improve the quality of early drug response prediction and help reduce subsequent clinical trial failures.

Anti-SARS-CoV-2 monoclonal antibody (MAb) pair COV2-2196 (tixagevimab, class I) and COV2-2130 (cilgavimab, class III) are human neutralizing Abs (nAbs) that target nonredundant, complementary epitopes within the receptor binding domain of SARS-CoV-2 spike protein (S-RBD).