Artificial Intelligence (AI) has been a buzzword in the tech world since its inception. It’s no surprise that the pharmaceutical industry has also become an early adopter of this technology. AI has revolutionized the way drug discovery, development, and manufacturing are approached. The incorporation of AI has accelerated the discovery of new drug molecules and allowed the pharmaceutical industry to deploy novel drugs to treat diseases that haven’t been treatable before.
Drug Discovery
The process of discovering a new drug used to take years and cost upwards of billions of dollars. However, with the aid of AI, this process has been significantly shortened. Currently, drug discovery involves large-scale screening using High-Throughput Screening (HTS) to identify a molecule that can perform a specific function. But, AI algorithms have added a new dimension to this method, allowing for the identification of compounds that can serve as new chemical entities.
AI platforms can scan millions of data points to identify new compounds that can potentially act against the underlying disease or condition. This helps in finding the right molecule to target the specific disease pathway and reduce the risk of failure.
For instance, Insilico Medicine, a biotechnology company, recently used AI to identify six drug molecules that could help cure fibrosis. Fibrosis is a condition caused by the accumulation of extracellular matrix (ECM) proteins in organs. Within four days, AI algorithms had processed more than 30 million possible pairs of molecules to propose six drug molecules that could address this condition. A task that would have otherwise taken years to achieve.
Clinical Trials
The success of a drug molecule in the pre-clinical stage doesn’t guarantee success in clinical trials. Clinical trials involve testing the efficacy and safety of the drug in human subjects. These trials are necessary to ensure the drug is safe and can deliver the desired therapeutic effect.
However, the average cost of a clinical trial ranges from $312 million to $2.6 billion, and the success rate is only 10% to 20%. AI has revolutionized this process by providing the ability to simulate the drug molecule’s effect on the human body. The development of digital patients has enabled researchers to experiment with combining different doses, forms, and frequencies of the drug. This data can be used to optimize the drug’s development, reducing the cost and time spent on clinical trials.
In addition to facilitating the design of better drugs, AI is also used to manage clinical trials’ operational complexities. AI algorithms can identify the right patients for clinical trials through predictive algorithms that can analyze patient data. This approach reduces the time it takes to recruit participants for clinical trials, which is a significant challenge for pharmaceutical companies.
Manufacturing and Supply Chain Management
Another area where AI is making an impact is in manufacturing and supply chain management. The production of drugs involves several processes that require close monitoring to ensure that the final product is of high quality and meets the desired specifications. This requires frequent testing and analysis of the intermediate and final products. Manually monitoring these processes is resource-intensive and time-consuming, but with AI, this process can be automated.
AI sensors can be placed on manufacturing equipment to monitor the process in real-time, detect abnormal fluctuations, and notify employees if corrective action is required. This approach minimizes human error and avoids delays in the production schedule. It also reduces product recalls and ensures that the product meets quality standards.
Furthermore, AI-enabled supply chain optimization is another area where pharmaceutical companies can benefit. Supply chain optimization algorithms can predict future demand and, based on that, develop sourcing, transportation, and distribution plans. This approach reduces the risk of delayed product shipments, which can be disastrous for pharmaceutical companies.
Conclusion
AI is transforming the pharmaceutical industry in unprecedented ways, enhancing the drug discovery, development, and manufacturing processes. It’s making the drug discovery process faster, cheaper, and more efficient. It’s accelerating the clinical trials process, reducing costs and risks associated with drug development. It’s also optimizing manufacturing and supply chain management, reducing errors, and providing actionable insights. With the advent of AI, the hope is that previously incurable diseases may now find a cure, and more people will have access to innovative drugs. The pharmaceutical industry should embrace AI’s potential and be at the forefront of innovations that can improve people’s health and wellbeing.