The Pharmaceutical industry is leveraging the power of Data Analytics to improve its operations. Machine Learning, Natural Language Processing, Deep Learning, and Computer Vision are being used to make wiser decisions and gain maximum productivity. Soon, all the tasks that have a possibility to be automated will be done using AI, and new, more intelligent jobs would be created for humans.
Undermentioned are some of the applications and uses of AI in the Pharmaceutical Industry that would help in decision making and process automation. Nevertheless, these are flexible and can be modified further.
AI use cases in the pharmaceutical industry?
Using Computer Vision, Video analytics can be integrated with CCTV for workforce monitoring and unsafe or unauthorized access monitoring, and instant alerts can be sent to the concerned administrator. Fire and smoke detection, unauthorized entry, vehicle monitoring, number plate reading, inventory monitoring, equipment monitoring, object detection, and counting, and facial recognition can be done.
Sales team visit system
This is a solution to illustrate all the information of the product and its features and analytics to the doctors and physicians so that they are well informed about the components of the new medicines and drugs produced. The doctors and physicians can interact with the scientists and pharmacists using this solution.
Monitor and manage your machines from a distance. Past data about the machine is used to predict failure beforehand and inform about the problem before it arises to tackle it instantly. Anomalies in operation are detected. It allows you to schedule maintenance when your equipment and machinery actually need it. Preventing machine breakdown will save overhead costs. IoT sensors are used for this.
Chat Bot is a very basic application of AI in pharmacy. Every active website needs a ChatBot. Answer FAQs, unexpected questions, customer queries, and make your website a hub of helpful information. ChatBots can be multilingual, i.e. they can interact in any/all languages desired and can be integrated with WhatsApp or other Web Apps and Sites.
Automated data scraping customer reviews, feedback, and comments from social media and forums can help with sentiment analysis. Market trend analysis and identifying buzzwords used by competitors and what they are saying on social media can help with competitor analysis. Using Automated Targeted Marketing, identify the right target audience to generate more leads and eliminate unnecessary spending.
Using Sentiment Analysis, customer reviews and thoughts can be scraped from the internet to understand their experience and make the necessary changes. AI can also be used to interact with existing clients who are not responding and keep them satisfied.
Customized sales forecasting models can be created by understanding the requirements of pharmaceutical products, the affecting internal and external factors, and predicting its future sales to plan the production accordingly. The business gets an idea about the sales going to take place in the near future. Accurate Sales forecasts enable you to make informed business decisions and predict short-term and long-term performance.
In case of a negative prediction, the necessary preventive measures can be taken or the model to be trained to do this, your previous data would be required, more data would generate more accurate results.
Demand Sensing and Raw Material Consumption Prediction
Using deep learning frameworks, predict upcoming demand, and predict which raw materials and chemicals would be needed in a period of time to prevent shortage or wastage of supplies. AI can interpret a huge amount of relevant data and provide relevant insights. This will help in inventory planning. For this again, previous data would be required, past data about raw material purchases, quantities, and time will help provide more accurate results.
Conversion of handwritten documents to digital format
Using OCR, any hard copies, including those written by hand can be converted to digital softcopies to store online. The hard copies are converted to editable documents. If the documents are lengthy and need to be summarized, the next use case could be used post this.
Automated Summary Generator
Keywords are fed into the ML algorithm and the solution is trained to understand which parts of the content are important. Based on these keywords, the words around them are analyzed. This is how any huge document of thousands of words can be brought down to a hundred, into one short summary.
How has AI changed the pharmaceutical industry?
As technology progresses, digital transformation is helping to speed up the advancements by leveraging the power of Artificial Intelligence to do automatically the tasks that would otherwise be done by humans. Artificial Intelligence supports the pharmaceutical industry that supports doctors and hospitals that support us. Soon, all such industries will understand the impact of Data Science and Analytics, and AI in Pharma will be an obvious inclusion.
This is the right time to integrate AI in pharma and many companies have started doing that as they can see great opportunities after integrating AI in their pharmaceutical industry.
As the covid pandemic started disrupting the healthcare system of India then by applying vast AI systems like disease identification, personalized treatment, drug discovery, and predictive forecasting helps to overcome the disrupting situation of the healthcare system.