Artificial intelligence is growing steadily and bringing transformative changes in every sphere of our various working sectors. Initially, it started contributing towards the technical sector, but now it has also paved the way for digital transformation in the pharma R&D industry as well. The term that is quite prominent these days is “AI in drug discovery”. Drug discovery, which is a very fundamental part of pharmacy, now, with the help of AI, is transforming itself in a way that wasn’t expected.
It can contribute to candidate identification faster, it can even help in understanding diseases better , and a lot more that you have not heard of. Artificial intelligence in pharma industry is gradually showing the changes not only in discovery and research but beyond that as well. It is transforming strategic sourcing, which is how the pharma industry is buying services, choosing vendors , and managing partnerships.
The scope of AI-powered Drug discovery and strategic sourcing is getting deeper. To help you understand better about how Artificial intelligence in the pharma industry is changing , adapting, and bringing a positive impact. We have provided a detailed description in this blog, scroll on to read ahead.
How AI Is Revolutionizing Drug Discovery
The process of drug discovery involves many steps ,which starts from candidate identification and go till clinical trial. Before the introduction of AI in drug discovery, these procedure usually it take more time, however, after the adoption of AI in pharmacy, it has brought a big revolution. Let’s read ahead to find out the positive influence of artificial intelligence in the pharma industry.
Accelerated Candidate Identification
If you want to understand scientifically, candidate identification is the initial step of drug discovery, in which a candidate or drug is identified that could interact with a disease target like a gene, protein and receptor , and can help in treating that disease. Before the inclusion of AI, it usually takes 2-5 years of lab research for this foundation ,but artificial intelligence has shorten it to a few months. Trial and error and other manual processes are switched over to AI scanning of the genetic and protein database. Hence, it provides edge in accelerating Candidate Identification.
Improves Trial Design
If you start looking at the difference between traditional clinical trials and AI-powered clinical trials, you can find a huge difference not only in cost but also in the number of years invested. Apart from this, the traditional clinical trials could fail at the final stages of trial; however, AI-powered clinical trials can overcome the failures and can provide a reliable trial outcome. Also, when it comes to trial design, Artificial Intelligence provide the one if best design before starting , which eventually help in reducing the risk of trial failure.
Enhances Efficiency
Usage of AI for faster drug development is becoming prominent because of its leading contribution in enhancing work efficiency as well as cost efficiency. Whether drug discovery or clinical trial, the AI efficieny is unbeatable.
Key Factors For Procurement And Vendor Evaluation
Strategic sourcing in pharma also includes procurement and vendor evaluation. The Following are some of the key factors for procurement and vendor evaluation.
Supplier Discovery
Discovering a Supplier is a manual task that requires a lot of time and effort but important part of procurement and vendor evaluation. With AI and pharma partnerships, it has become quite easy. You should not look for more directories and limited option because with the help of AI Scan, you can get a bigger dataset , which help in providing accurate supplier details.
Risk Assessment
It is also one of the key factors for procurement and vendor evaluation. In today’s scenarios, data-driven pharma sourcing reduces the risks of loss. The vendors who have access and hands-on experience with Artificial Analysis are consider because the procurement team with AI can take preventive measure before than the traditional ones.
Cost Analysis
Cost is always an evaluating factor, choosing which gives fair and long term value for the product is important. Therefore, the vendor and procurement team who are switching from traditional to Artificial Intelligence are considered. As with AI, cost analysis becomes quite convenient.
Conclusion
Indeed, AI is revolutionizing drug discovery and Strategic sourcing in pharma. It helps making things easier and quicker along enhancing cost efficiency. However, we should also be proactive in securing data privacy, as the pharma industry still needs regulation in the context of Artificial Intelligence. Apart from this, with the utilization of AI, we should also keep in mind that we should not over-reliant on it. Biology is complex , hence we should still need to priortize experimental validation along with Artificial Intelligence Validation.