Some of the applications of AI work in
pharma analysis system requires language processing, repetitive tasks, data management, medical consultation, and medication management.
Also, artificial Intelligence in pharmaceutical industry has the following applications.
1.R&D
Pharma companies use advanced ML algorithms and AI-powered tools to streamline drug discovery. These intelligent tools are designed to identify hidden patterns in large datasets. The companies use them to solve challenges with the complicated biological network. It can study the habits of various diseases and recognise which drug composite would suit best for treating a particular disease. Pharma companies can invest accordingly in the R&D of drugs with the highest chances of treating a medical condition to improve immunity.
2. Drug and report
AI can improve the R&D process. AI can do it all quickly to design and identify new molecules for target-based drug validation and discoveries.
According to an MIT study, only 13-14% of drugs successfully pass clinical trials in numbers. A pharma company has to pay anywhere between a million to a billion for a cure to get through the complete process of clinical practice. Also, get FDA approval to let it go in for the next stage. These are the two reasons why pharma companies mainly adopt AI. Firstly, to improve the success rates of new drugs. Secondly, to create affordable drugs and reduce operational charges.
3. Diagnosis
Doctors use advanced Machine Learning systems to collect and analyze large volumes of patient’s healthcare data. People around the world are using ML technology to store sensitive patient data with security in the storage sources or central system. These are known as electronic medical records ears.
Doctors can refer to these records when they need to understand the result of a genetic trait on the patient’s health. Or, how a particular drug can treat a health issue. ML systems can utilize the data stored in EMRs to make real-time predictions for diagnosis and suggest proper treatment to patients.
ML technologies can quickly analyze massive amounts of data to save millions of lives.
4. Disease Prevention
Artificial Intelligence in pharmaceutical companies cures both known diseases as well as rare diseases. ROI is low compared to the time and costs it takes to develop drugs for treating rare conditions.
According to global strategy, nearly 95% of rare diseases don’t have FDA-approved treatments or cures.
5. Epidemic Prediction
Many healthcare providers already use Artificial Intelligence in pharmaceutical sector and ML to monitor and forecast global outbreaks. These technologies feed on the data from disparate sources on the web. To study the connection of various environmental and biological factors to the health of the population of demographics. Also, to link the dots between these factors and previous epidemic outbreaks. Such AI/ML models become especially helpful for underdeveloped economies lacking medical infrastructure and financial framework.
An excellent example of the application of Artificial Intelligence in pharmaceutical industry is the ML-based Malaria Outbreak Prediction Model. A warning tool predicting any possible malaria outbreak and aiding healthcare providers in taking the best course of interaction to combat it.
6. Remote Monitoring
Many pharma companies have developed wearables powered by AI algorithms that can remotely monitor patients suffering from life-threatening problems. Integrating this AI technology with smartphone apps makes it possible to remotely monitor a patient’s opening and closing motions from the location. On detecting movement, the smartphone camera will capture it to determine the symptoms. The frequency of activity will determine the severity score of the patient’s condition. This allows doctors to change the drugs and their doses remotely in an instance.
7. Manufacturing
Artificial Intelligence in pharmaceutical companies helps in manufacturing for higher productivity, improved efficiency, and faster production of life-saving drugs. AI can use AI for quality control.
- Predictive maintenance
- Waste reduction
- Process automation
AI can replace the time-taking or consuming conventional manufacturing techniques. Helping pharma companies launch drugs in the market much faster and cheaper. Apart from increasing their ROI by limiting the manufacturing process, AI would also eliminate any scope for human error.
8. Marketing
The pharmaceutical industry is a sales-driven sector. AI can be a great tool in pharma marketing. With AI, pharma companies can develop unique marketing strategies that promise high revenues and brand awareness. AI can map and help customer journeys. Allowing companies to see which marketing technique leads visitors to their site and ultimately pushes them to purchase. In this way, pharma companies focus more on those marketing strategies to increase revenues.
AI tools can analyze past marketing and compare the results to identify which remained the most profitable. It allows companies to design the present marketing accordingly while reducing time and saving money. Also, AI systems can even accurately predict marketing campaigns’ success or failure rates.
Conclusions
As Artificial Intelligence in pharmaceutical sector is growing wildly, the transformation process is not without challenges. The current IT infrastructure of pharma companies on legacy systems that haven’t been optimized for AI.
The integration & adoption of AI demands industry expertise and skills. However, the process of AI adoption in the pharma sector can be simple by taking these steps:
- Collaborating with institutions specializing in AI R&D to help pharma companies adopt AI.
- Work with companies that specialize in AI-driven medicine and discovery to get the benefits of assistance, and advanced tools.
- Train R&D to implement AI tools and techniques properly for optimal productivity.
