A successful pharmaceutical sector is dependent on understanding the effect a disease has on biological systems. It is necessary to identify the molecules most likely to interact with relevant biologic targets and alter the pathophysiology of disease, a timely and expensive process which contributes to the over $1 billion pharma is estimated to spend on every drug it creates. AI can examine vast quantities of unstructured data, at a rate well beyond the ability of humans to understand, significantly speeding up these processes and delivering vital time and cost savings to researchers.
AI software can analyse large volumes of medical data to source appropriate candidates for complex clinical trials in minutes, something that could take researchers using traditional recruitment methods months to achieve. The faster clinical trial participants can be recruited, the faster new cures can be found and drugs bought to market. It is estimated that AI could help create up to $13 billion in benefits by 2026 in terms of clinical trial participant identification alone.