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We, as humanity, have gone a long road in search of an understanding of AI. From the early beginning of the world’s digitalization, the mainstream media taught us that artificial intelligence is a super complicated mechanism that is supposed to cover human existence hurdles, explain the universe’s secrets, start or prevent a global cataclysm, and other significant events. The reality turned out to be more mundane: modern-day neural networks are somehow different from the AI image we are used to. Still, the impact of this technology is much more significant than most of us can think.
Of course, most people may still think that artificial intelligence is something terrible from Terminator movies rather than their daily social network feed or high art picture generator. What about more complicated cases like the medical and pharmaceutical industries? As niche becomes increasingly digitalized, usages of AI in pharma grow in breadth and depth.
We analyzed the recent market research and are ready to share it with you. This article will cover the most important areas of AI influence on the pharma industry and new drugs development.
To understand the impact of AI technology, let’s talk about what kind of technologies are called “AI” in a nutshell and what they are used for. Mainly, technology specialists define three directions:
Data science algorithms. These human-created automated algorithms are designed to analyze past activities and create alternative decisions. For example, it can provide a more effective treatment plan or drug combination based on the patient’s clinical data and medical history.
Machine learning algorithms are a more complicated way of decision-making analysis based on neural network analytics. It works with given datasets to predict decision consequences and categorize and classify information. This is a quick and reliable way to create marketing strategies or conduct clinical trials.
Deep learning is based on more complicated forms of learning and natural language processing, it is used for more detailed diagnosis. It can analyze sensitive images like skin conditions or radiology scans and combine received data with historical treatment outcomes or other patient-specific information to create the most suitable solution.
AI algorithms and machine learning models have a significant impact on the biotech industry. From life-saving drugs discovery, development, and production to clinical trials, communication, and drug target identification — AI pharmaceutical is a definite game-changer.According to The McKinsey Global Institute’s research,
the influence of AI and machine learning on the pharma market generated around $100B across the US healthcare system in 2021.Here, we are diving deep into the main aspects of AI influence.
Maybe, the first thing that comes to mind, when talking about AI and controlling processes, is manufacturing. AI can help improve processes, which involve many people, from maintenance specialists to quality control and more.
AI tools can optimize production by taking over the most complicated functionality. It ensures that tasks will be performed very precisely. As well as providing high-quality work, it can analyze the processes, find the weak spots, improve decision making or find areas where it can be streamlined.
Drug discovery and development of new drugs is quite an expensive and competitive process for every pharma company. It is highly wired on data science and massive scientific and research datasets. AI helps to apply machine learning to this data and rapidly increases the discovery of new molecules. It can research and cross-reference published scientific materials with alternative resources, including clinical trial results, to develop drugs and discover new effective treatment methods for rare diseases.
As any new particular drug should be approved before becoming a consumable product, pharmaceutical companies must conduct research and drug trials during drug discovery. The use of artificial intelligence allows us to perform and automate the QA process and ensure high standards of the drug development process and value chain. It helps to improve the production process reducing the chance of domestic issues, reducing development spending during the drug discovery process, and increasing drug adherence.
Regarding diagnosis of particular disease, AI becomes an inevitable tool for pharma companies to apply a data-driven approach, process volumes of sensitive patient data, and deliver personalized treatment based on the most accurate analysis and calculations. Especially it is important during rare diseases diagnostics. Thanks to artificial intelligence technologies, doctors have much more opportunities to provide the patient with fast and precise results of such complicated medical examinations as, for example, colonoscopy.
Another good example is the Chinese tech giant Tencent. They teamed up with a British healthcare firm, Medopad, to create AI software that
reduces the diagnosis time for Parkinson’s Disease by ten times — from 30 minutes to 3 minutes.Apart from gathering and processing supersensitive information, modern AI technologies can manage clinical data storage and organization. A specifically tuned neural network can keep data secure and manage electronic medical records (EMR) to store patients’ sensitive information and treatment records.
One of the most vital things that AI influences are clinical trials. Clinical trials are always something related to significant amounts of different information. It becomes harder to process clinical trial data manually since data becomes more complicated yearly, and the risk of human error increases. This is where AI handles big data arrays without breaking a sweat.
Many pharma businesses rely on identifying the right candidate for clinical trials on AI. The technology can collect and process data such as existing diseases of the targeted audience, demographic specifics, rate of infection, and other overlapping factors to represent the right testing group and conduct a successful drug trial. It significantly improves drug adherence and repurposing options.
Our industry is hard-wired to sales-driven factors, and digital marketing aims to develop unique marketing strategies and increase revenue and brand awareness. This is where the use of artificial intelligence changes the perception of the game and helps companies to stay on top.
Artificial intelligence in pharma industry can compare the results of past marketing campaigns to identify the most profitable ones. It helps to analyze any marketing activity and how they affect the audience to create the most efficient strategy for your subsequent customer journeys. Based on different patient outcomes and data, it can predict the success or failure of varying engagement methods within a particular campaign.
Year by year, pharma companies face more complicated challenges each time we reach another level of digitalization. As the amount of information about our daily activities and health only grows, pharma and life science industries are looking for more advanced and decision-making solutions. The opportunity of AI technology leaves no other alternative but to join the digitalization and ensure pharma’s most vital processes are in their “hands”. It will make different aspects of your pharma business more effective and innovative and optimize your resource spending.
The use of AI solutions made a significant impact on decision-making, creating innovations for patient’s health, remote patient monitoring, and conducting medical research. Also, artificial intelligence pharmaceutical automation allows your company performs predictive maintenance and quality control of drug combinations.
There’s no sign of this trend slowing down — on the contrary,
about 50 percent of global healthcare companies plan to implement AI strategies and broadly adopt the technology by 2025.
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