The Weizmann Institute is a powerhouse of biomedical research, with over one hundred research groups developing cutting-edge technology and experimental strategies to understand biology in health and disease. Modern revolutionary techniques such as single-cell genomics, genetic engineering, and profiling of the immune system and of pathogens all rely on massive data collection and sophisticated analysis. However, to transform the excellent science in Weizmann labs into novel medicine, radically new ideas and innovative tools are required.

Human health is shaped by an untold number of factors. AI has the potential to sift through this vast mosaic of influences, zooming in on specific factors involved in pathogenesis, thus opening the door to altering them to prevent or treat disease. Modern biology is completely changing the ways scientists and physicians can interrogate human physiology. This could transform AI into a powerful decision-making tool for researchers and clinicians, enabling faster and more accurate diagnoses, promoting the development of better treatments, and delivering on the promise of precision medicine - the tailoring of treatment to the specific biology of each patient to optimize treatment results.

However, fulfilling this potential requires overcoming significant challenges. Even when approaching relatively simple diagnostic tasks that humans currently perform routinely, the scarcity of datasets for training, the lack of sufficient tagged data, and the large variability in patient health states all make AI-based solutions difficult to deliver. These difficulties may be overcome as more data becomes available and efforts to standardize it continue. But a real AI revolution in medicine will have to aim much higher – looking for truly novel ways to diagnose and treat patients given data and decision-making processes that are currently not even defined. We will have to train computers to search for what we don’t know – and do it in an environment in which mistakes or trial-and-error cycles are unthinkable.

Another significant challenge, not unique to this field but whose gravity increases when human lives are at stake, is demystifying the AI "black box" and understanding how the computer arrived at a particular conclusion to gain physicians' and patients' trust.