Causality’s role in drug development and precision medicine

Summary

MBZUAI's Kun Zhang is applying causal machine learning to improve drug development and precision medicine, focusing on answering 'why' questions. Traditional drug development is costly (est. $2B) due to extensive studies needed to determine drug toxicity and efficacy. Zhang is combining causal ML with organs-on-chips technology to improve pre-clinical drug testing, aiming to reduce the failure rate of drugs in human trials. Why it matters: By improving the accuracy of pre-clinical drug testing, this research could significantly reduce the cost and time required to bring new medicines to market in the region and worldwide.