A team of researchers from Amity University and Rama University in India have discovered that the one area where AI is making the most significant impact is in drug discovery.
AI algorithms can be used to identify potential drug targets, design new molecules, and predict the efficacy and safety of drug candidates.
This can significantly reduce the time and cost of bringing new drugs to market.
Authors Seema Yadav, Abhishek Singh, Rishika Singhal and Jagat Pal Yadav, however, maintain that there is currently a lack of empirical evidence to support the widespread use of AI in clinical research.
To create novel treatments and treat complex diseases, the pharmaceutical sector is essential. Drug discovery, however, is a time-consuming, pricey, and dangerous endeavor. Artificial intelligence (AI) has become a potent instrument that has transformed several industries, including healthcare, in recent years… The pharmaceutical sector is experiencing a drug discovery revolution because of AI. The drug discovery process is changing at distinct phases because of AI approaches like machine learning and deep learning… To fully realise the potential of AI in pharmaceutical research and development, issues relating to data accessibility, algorithm interpretability, and laws must be resolved
AI is also being used to improve the efficiency and effectiveness of clinical trials. Algorithms can be used to identify potential participants, monitor patient safety, and analyse trial data.
This can help to ensure that clinical trials are conducted more quickly and efficiently, and that the results are more reliable.
AI-powered tools can be used to personalise treatment plans, monitor patient health, and provide decision support to healthcare providers, which helps improve patient outcomes and reduce healthcare costs.
While several companies are exploring AI in drug discovery, the current industry darling is Recursion Pharmaceuticals.
Its AI-driven drug discovery platform combines automation, machine learning, and experimental biology, is being hailed as an accelerator for rapid clinical approvals
Their platform has the potential to identify novel drug targets and develop new therapies for a wide range of diseases, but there is no concrete evidence yet.
More concerning is that Novo Nordisk is chasing it, through its parent organisation, the Novo Nordisk Foundation.
The foundation is helping build an AI supercomputer in Denmark powered by Nvidia technology to accelerate AI research and development in biopharma and other fields.
Another notable company in this space include Exscientia, which focuses on AI-driven drug design.
The company recently announced its new platform partnership with AWS that will leverage the AWS Design-Make-Test-Learn (DMTL) loops, generative AI, active learning, ML, physics-based systems and many other predictive methods and also draws on large language models via Amazon Bedrock.
Although this announcement comes in the wake of job cuts to increase financial efficiency.
BenevolentAI is another company that uses AI to analyse vast amounts of biomedical data to identify new drug targets and repurpose existing drugs.
However, the biotech is doing its second round of job cuts within 12 months and shuttering its US operations to reduce cash burn and extend its life through 2025.
There’s a warning in this research paper that AI-based drug repurposing is still in its pilot stages and needs to overcome challenges in prediction accuracy to reach the level of manual prediction by professionals.
As the technology continues to mature, we can expect to see even more innovative applications of AI in the pharmaceutical industry in the years to come.
However, it's important to acknowledge the current limitations and the need for further research and validation to fully realise the potential of AI in this field.
