Jerusalem-based drug discovery start-up Pepticom announced Thursday that it had managed to secure $5 million in Series A funding from the Chartered Group investment firm. The start-up, which was founded in 2011 after it spun out of Yissum, the Hebrew University of Jerusalem's technology transfer company, utilizes advanced AI technology to discover new peptide-based drug candidates and alleviate development risks by searching an enormous set of possible solutions. This streamlined and less risky process has turned them into world leader in the field of peptide drug discovery.

The original scan (left) and the areas where information was extracted (in red and green, right) using the technology developed at the Technion. Researchers at Technion-Israel Institute of Technology have developed a deep learning-based method for mapping critical receptors on cancer cells, which is expected to significantly improve personalized cancer treatment, the Office of the Technion Spokesperson reported on Wednesday. According to the report, the new technology extracts molecular information from images of breast cancer biopsies that underwent hematoxylin and eosin (H&E) staining. The staining, made by a common dye used to test biopsy tissue, allows the pathologist to identify the type of cancer and its severity but does not allow the identification of biological characteristics that are crucial for personalized treatment.

Researchers at Bar-Ilan University have said they have created a new type of ultra-fast artificial intelligence (AI) algorithm based on the dynamics of the human brain. According to a report published Friday in Scientific Reports, the algorithm demonstrates that, despite the human brain computing at a much slower rate than modern computers, it is extremely fast and efficient. As such, the scientists say, "Insights of fundamental principles of our brain have to be once again at the center of future artificial intelligence."

Artificial intelligence and machine-learning algorithms are a useful predictor of schizophrenia with 74% accuracy, according to research at IBM and the University of Alberta in Edmonton, Canada. The retrospective study, which just appeared in Schizophrenia – published by the journal Nature – shows that the technology is capable of predicting the severity of certain symptoms in schizophrenia.