Transformations In The Pharmaceutical Industry In The Era Of Artificial Intelligence

Artificial Intelligence (AI) is making waves across a variety of industries. While its applications are more apparent in some sectors than others, it’s clear that AI is set to change the way people do business.

The pharmaceutical industry refuses to lag behind in the race for AI adoption. Biotech executives feel eager to introduce this technology alongside the Internet of Things and Machine Learning to futureproof their respective companies.

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While AI still appears futuristic for many people, it’s essential to know that AI and machine learning is already here. Tasks that normally require human intervention can now be performed by high-tech computer systems, speeding up the execution and turnover of mundane jobs. This frees up manpower, thus saving the industry millions of dollars in human resources alone.

In the healthcare industry, the influence of AI is already being felt. Human-created algorithms allow researchers or clinicians to perform evidence-based approaches. Integrating data into these algorithms help them extract pertinent information, analyze results, and then apply what they learn to any given issue.

For example, clinicians can diagnose the disease of a patient and offer the best treatment option by simply combining consensus algorithms with the patient’s medical history. They can create profiles based on clinicodemographic data and other medical-based evidence.

A man aged 40, for instance, may show early signs of testosterone decline. The individual medical history of the patient will be compared against that of other people under the profiles generated by AI. Clinicians can then extract information, decide whether traditional treatments are necessary, or offer alternatives like Erogan to help the patient increase testosterone levels.

It’s also worth noting that AI can help pharmaceutical firms reduce research and development costs. Surprisingly, only 1 out of 10 drugs make it to clinical trials. Consequently, a very limited number makes it to the approval stage. This is one of the reasons why research and development of new drugs proves to be extremely costly—and rather slow as well.

According to estimates, the cost of developing new drugs is around $1.2 billion. Those who suffer the most are the patients themselves, as the R&D costs are passed down to them. Thankfully, AI can speed up the drug discovery process.

In drug trials, AI has the potential of reducing the time required for a drug to move from approval to market launch. This brings down the overall cost of drug discovery, which equates to lower drug costs and more treatment options for end consumers. It has been difficult for the pharmaceutical industry to maintain a high standard of care, but AI and machine learning may just hold the key to improve it even further.

By leveraging these technologies to automate repetitive processes, generate data-driven decisions, and forecast the market with the help of predictive analysis tools, pharmaceutical firms put themselves in the best position to enhance R&D success and come up with new, effective, and more affordable drugs. While adoption of AI has been slow compared to other industries, any firm that wishes to stay competition should take the first steps toward full AI integration.

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