Identifying therapeutic gene targets is essential for advancing personalized medicine and addressing the genetic basis of diseases. However, traditional experimental methods for discovering these targets are costly and time-consuming. While deep learning has shown promise in identifying biomarker genes, it has struggled to identify therapeutic genes. To address this challenge, researchers have developed an innovative method, the Hypergraph Interactive Transformer, which accurately and quickly identifies therapeutic gene targets using hypergraphs and attention-based learning.

A pilot study in a rural Florida community tested an intergenerational program to help older adults adopt mobile health technology using smartwatches and assessed daily brain health behaviors. Despite challenges with digital literacy, 91% of participants engaged with health surveys delivered via the devices. Social contact was positively linked to physical activity, mental engagement and cognitive well-being. The participants, aged 53-84, successfully used the smartwatches regardless of their health literacy or technological skills, highlighting the potential of such programs in supporting aging in place.

Cambridge, MA – March 5, 2025 – Today, Insilico Medicine, a clinical-stage biotechnology company pioneering generative AI for drug discovery and development, announced the deployment of the first bipedal humanoid in its AI-powered fully-robotic drug discovery laboratory. The humanoid, called “Supervisor” will be used for data acquisition and data generation for training of the embodied AI systems to learn the skills of human laboratory scientists. The work will be conducted by the Insilico Robotics team at Insilico Medicine. The humanoid will also immediately assist with lab tours, telepresence, tracking and lab supervision.