For a longer time, the pharmaceutical industry has depended on the pioneering technologies that assist in the deliverance of risk-free, trusted drugs in the market. With the latest pandemic hitting badly, the pharmaceutical companies have proven to be highly valuable to acquire the best quality drugs and vaccines to offer for quick sale in the market.
AI and ML have evolved in the IT industry tremendously, making the tables turn towards new inventions such as surgical bots, virtual assistants, chat-bots, smart homes, etc. Both AI and ML can be effortlessly applied in every facet of the pharmaceutic industry, beginning from exploring new drugs to its manufacturing to processing to sales and marketing. Pharma companies by the implementation of AI/ML systems can make their business run economically and stably.
As per the ‘Smart Pharma’ report from GlobalData, “Twenty-eight percent of the surveyed companies are planning on applying Artificial Intelligence (AI) and Machine Learning (ML) to optimize new drug disclosures and development procedures in the upcoming two years.”
To add to it, more than 32 percent of respondents would be hiring AI and data analytics for contouring marketing and sales efforts. This showcases the flourishing significance of AI and ML in technological as well as operational features of pharmaceutical business enterprises.
How are AI and ML being implemented in the current pharmaceutical industry?
- Digital therapeutics/ Primary treatment: Digital therapeutics can be applied efficiently to help and spot out those individuals to offer a deep awareness and perception into such conditions like skin disorders, gum conditions. Also recommending primary treatment choices like an over-the-counter remedy, or boosting clinical and educational decisions set by the medical doctors/ health professionals/ teachers, or distributing ancillary tools to increase the accuracy of diagnosis of doctors.
- Disease identification and proper diagnosis: This can vary from oncology to Covid outbreak to deterioration in the eyes or any other rare diseases which need to be diagnosed under proper medication and from the best doctors. Here is where the AI/ML pattern-identified proficiency in data as well as in images are enhancing the quick disease identification followed by accurate diagnosis needed for recovery.
- Drug discovery, manufacturing, and production: From the initial screening of drug composites to predicting the success rates based on biological aspects to manufacturing till production, AI and ML are being thoroughly utilized, thus assessing the RNA and DNA swiftly. Not only the right kind of drugs are discovered in the market, but also tailored for patients with personalized medication.
- Predictive forecasting: Be it predicting the spread of pandemic or epidemic, are the key examples where AI and ML are being implemented to monitor from close and allowing the pharmaceutical companies to make the right kinds of drugs in precise quantity and available at the right time, based on the prediction intensity.
- Larger agility and resilience in operations: When it comes to the organizational level, as per McKinsey, the pharma companies are concentrating more on operational resilience and pacing new initiatives that help larger agility and opacity. This gives way to a bigger demand for digitization, automation, and analytic tools. Using AI and ML, they can offer excellent care and medication to the patients with improved efficacy.
- Supply chain, logistics, and automation: With rapid evolution, the pharma industry has acquired better quality digital tools that result in supply chains becoming app-based, and patient-centric. Take, for example, MHRA together with the UK division of Genpact utilizes AI for tracking vaccine distribution location-wise and number-wise across the countries. The pharmacies are also focusing to amend their logistics via the latest technology.
Predicting and Monitoring via AL/ML
AI/ML acts as an advanced warning system where it evaluates great data for assisting researchers and medical practitioners predict the spread of diseases like Covid-19. Take, for example, researchers at Chan Zuckerberg Biohub have utilized AL/ML for predicting many unnoticed Covid-19 sequences for global public health.
Maintaining the quick development in data and insights
AL and ML are offering support to the healthcare researcher and providers to manage a growing amount of data based on Covid-19. This rise in information can turn out to be tough to yield treatment insights. Therefore, the latest launch by AWS on CORD-19 Search, which is an ML-powered search website, can effortlessly extract accurate medical info from unorganized data. This can further look for answers correctly and at a quick pace, also find research papers and documents.
Few Use Cases for AI and ML technology in the pharmaceutical industry
According to the article written in Guardian: Artificial Intelligence group, a scientific problem is cracked by DeepMind which baffled the researchers for years. A company named AlphaFold and research laboratory applied an AI program which exhibited predictions on how proteins bend into 3D shapes that will help them explore the mechanisms driving few diseases and making the way for designer medicines, better nutritious crops, as well as green enzymes which fails the plastic pollution.
Another ideal use case included AI in Sensory Science that allows the GSK consumer R&D team. AI and ML are inclined towards predicting parametric quantities in beverages, foods, medicine, and agriculture. These could direct towards hyper-personalized products customized for distinct demographics, adding the usage of sensory properties like texture, smell, and appearance, putting an impact on your choice of eating or drinking.
Therefore, to summarize, besides healthcare conditions, AL and ML use is also witnessed in digital transformation sectors for many Pharmacy and Healthcare companies such as Sales, Supply Chain, AdTech, Customer Service, and Martech. Hence, pharma companies can grasp the AI and ML initiatives for driving a finer economy along with the valuable efficacy of regulatory functions.
Sanghamitra Roychoudhary
Latest posts by Sanghamitra Roychoudhary (see all)
- 8 Top Challenges of Cyber Security in the Digital Age - April 27, 2024
- 7 Best Practices for an Effective DevSecOps Implementation - April 26, 2024
- Top Impacts of IoT on Businesses - July 21, 2023
