A Look at the Interesting Applications of Machine Learning in Pharmaceutical Industry

Amalgamation and integration of 2-3 advanced technologies into a sector to boost its efficiency and productivity has been one of the striking features of the 21^st century. Innovative technologies like artificial intelligence (AI) and machine learning (ML) are being introduced in different sectors to gauge the impact these technologies have on the output of the industries. The pharmaceutical industry, too, has not been able to isolate itself from this phenomenon; introduction of machine learning in pharmaceutical industry has gained pace in the last few years and is producing astonishing results.

Innovative Applications of Machine Learning in Pharmaceutical Industry

Increasingly diverse and ingenious applications of machine learning in pharmaceutical industry have been devised in the past few years which has increased the reach, expanse, and market value of the machine learning in pharmaceutical industry market. As per a report published by Research Dive, the global machine learning in pharmaceutical industry market is predicted to garner a revenue of $26,151.8 million in the 2022-2031 timeframe with a stunning CAGR of 37.9% by 2031.

One major application area of machine learning in pharmaceutical and medical industry is in disease diagnosis and identification. Many a times, the symptoms of a particular disease are not that conclusive, which will make the doctor point to a certain disease. In such cases, machine learning can detect even the minute symptoms at the initial stages which can help in starting the treatment at the earliest. Moreover, another important problem faced during disease identification is that some symptoms of different diseases are similar in nature, and hence can be misinterpreted. Machine learning can help in accurate predictive analysis and can point to the disease correctly by taking cues from several data points simultaneously.

Another way in which machine learning in pharmaceutical industry can create a sizeable impact is in the treatment stage. Consider this scenario- two patients suffer from the exact same disorder; nonetheless, their treatment regimes prescribed by the doctor may not be exactly the same. This is because the two patients may have different medical histories and may react to the same medical treatments differently. Hence, designing and chalking out a tailor-made treatment plan for a patient is a very important part of medical studies. Machine learning, while manufacturing different dosages of pharmaceuticals, considers the various medical conditions of the patient and recommends a treatment plan accordingly.

Clinical trials, one of the preliminary stages of drug or vaccine manufacturing, benefits a lot from introduction of machine learning in pharmaceutical industry. Assessing the exact effect of the drug on the volunteers during the trials is significantly simplified with the help of machine learning. Furthermore, using self-learning techniques, it can derive at the correct composition of the vaccine or the drug quickly, thus saving crucial time required in manufacturing the drug.

Use of machine learning in pharmaceutical industry can also help in designing “smart” electronic record keeping techniques. The importance of accurate record-keeping of medical history can’t be understated. Also, digitization and cloud storage of medical records has become necessary so that they can be accessed at any time and from anywhere. Tackling and treating medical emergencies, thus, becomes easier with the introduction of machine learning in pharmaceutical industry.

The Bottom Line

As the world is slowly getting back on track in the post-pandemic world, there is an added emphasis on building a robust medical and pharmaceutical sector. In this quest, using self-learning and intelligent systems like machine learning has become one of the most popular ways. Adopting machine learning in pharmaceutical industry can truly revolutionize the health and medical care industries in the long run and help in building a healthier planet.

About the Author(s)

Princy A. J

Princy holds a bachelor’s degree in Civil Engineering from the prestigious Tamil Nadu Dr. M.G.R. University at Chennai, India. After a successful academic record, she pursued her passion for writing. A thorough professional and enthusiastic writer, she enjoys writing on various categories and advancements in the global industries. She plays an instrumental role in writing about current updates, news, blogs, and trends.