Breaking Barriers How AI is Revolutionizing the Pharma Industry

Technologies based on artificial intelligence are becoming more ingrained in the pharmaceutical industry. From a time and cost perspective, AI is proving to be a game-changer in drug and vaccine discoveries. 94% of the pharmaceutical industry believes that IoT, RPA, machine learning, and AI will all have an impact on the industry in the near future. 19% of pharmaceutical companies claim to be at the beginning of a revolution. There are thousands of diseases that have no cure. AI offers ground-breaking opportunities for researchers to use AI technologies to discover new disease treatments, medications, and vaccines.

Netlink’s enterprise-grade Artificial Intelligence and Machine Learning Solutions help organizations in generating data that delivers the most relevant and pertinent insights

Let’s quickly go over the various ways that artificial intelligence is being used in the pharmaceutical sector:

Identifying patterns in large data sets

Numerous sources, including clinical trials, academic papers, patient files, and patents, provide a vast amount of data. This volume of data cannot be analyzed by human intelligence to identify precise patterns. AI, on the other hand, has the ability to distinguish between various entities and show how they relate to one another.

A San Francisco-based company called Atomwise is using artificial intelligence’s analytic capabilities to identify patterns and develop new multiple sclerosis treatments.

Quicker discovery and development of new drug

Pharmaceutical companies can reduce costs and expedite clinical development by using AI. Pharmaceutical companies invest 2.7 billion dollars into developing each drug that reaches the market, which explains why 90% of drugs fail in clinical trials.

The following are the processes in which AI is being used as we move through the stages of drug development:

The method for identifying drug targets
Identifying methods to enhance various molecular reactions

Arpeggio Biosciences, a Colorado-based startup, is using machine learning to gather and synthesize data in order to find new drugs.

Patient matching and outdated clinical trials can benefit from AI

A significant challenge in bringing medicines to market is finding a suitable candidate for a clinical trial. AI can mine medical records to quickly identify the right patients for clinical trials.

NLP software, a branch of artificial intelligence (AI), is used by Deep6 AI to quickly identify patients who match complex trial requirements.

Repurposing drugs

With the development of AI, drug repurposing has become more alluring and practical. Drug repurposing is the idea of using an already-approved treatment for a different disease, which aids pharmaceutical companies in cutting costs.

With the help of “IBM Watson Health,” IBM uses machine learning algorithms on sizable data sets to test potential drug repurposing candidates.

Future Possibilities

There is a lot of room for drug development and discovery. In the medical field, there is a push towards personalized medicine, which involves determining the best medications for a patient based on their genetic profile. If we take the human genome project as an illustration, it was a significant achievement for biologists.

By using AI, Google’s deep variant has created a model of a patient’s genome from their DNA. We can use that information to identify various druggable regions of the genetic code. Large pharmaceutical companies that are always looking to improve the drug development pipeline now have a new target. In the near future, personalized medicine may be made possible by AI. To improve the quality of life on Earth, we must investigate the vast opportunities that AI has to offer.

With the help of Netlink Artificial Intelligence and Machine Learning Solutions, you can generate accurate insights, develop and implement scalable solutions. Netlink has a team of skilled AI/ML professionals who also perform outstanding research and have in-depth knowledge of various industry domains and use cases.

Conclusion

The majority of businesses are attempting to diversify in the age of disruption by finding the most effective ways to use vast and moving data. It enables them to augment for the future effectively. Enterprise-grade AI and machine learning solutions from Netlink assist businesses in producing data that yields the most pertinent and valuable insights. With excellent research, use case-specific knowledge, and industry domain expertise, Netlink has a team of skilled AI/ML professionals to develop and deploy scalable solutions.